Modified vs. Unmodified mRNA: Navigating Immunogenicity for Next-Generation Therapeutics

Abstract

This article provides a comprehensive analysis of the immunogenicity profiles of modified and unmodified mRNA platforms, a central consideration for therapeutic development. Tailored for researchers and drug development professionals, it explores the foundational mechanisms through which nucleoside modifications, such as N1-methylpseudouridine (m1Ψ), alter innate immune sensing. It delves into methodological strategies for application-specific design, troubleshooting challenges like dose-limiting reactogenicity and translational repression, and validates choices through comparative pre-clinical and clinical data. The synthesis offers a strategic framework for selecting and optimizing mRNA platforms based on therapeutic intent, from prophylactic vaccines to protein replacement therapies.

The Innate Immune Blueprint: How mRNA Modifications Redefine Self vs. Non-Self Recognition

The immunogenicity of messenger RNA (mRNA) vaccines is fundamentally governed by the innate immune system's ability to detect foreign genetic material through pattern recognition receptors (PRRs). The core distinction between modified and unmodified mRNA platforms lies in their interaction with these receptors. While nucleoside-modified mRNA incorporates substitutions like N1-methylpseudouridine (m1Ψ) to evade robust immune detection, unmodified mRNA retains its inherent capacity to potently activate specific PRR pathways [1] [2]. This interaction is not merely a byproduct but a critical determinant of the vaccine's reactogenicity, adaptive immune profile, and potential therapeutic application. Framed within the broader thesis of immunogenicity research, this guide provides a detailed, data-driven comparison of how unmodified mRNA engages Toll-like Receptors (TLRs) and Retinoic Acid-Inducible Gene I (RIG-I)-like Receptors (RLRs), offering a scientific basis for platform selection for different medical applications, from prophylactic vaccines to cancer immunotherapies.

PRR Signaling Pathways for Unmodified mRNA

Unmodified mRNA is recognized as a "non-self" molecule by several classes of PRRs, primarily located in the endosomal compartments and the cytoplasm. This recognition triggers a coordinated signaling cascade that culminates in the production of type I interferons (IFNs) and pro-inflammatory cytokines, establishing an antiviral state and shaping the subsequent adaptive immune response [3] [4].

Key Receptors and Signaling Cascades

The diagram below illustrates the primary PRR pathways activated by unmodified mRNA.

Diagram 1: PRR signaling pathways for unmodified mRNA. Unmodified mRNA is sensed by endosomal TLR7/8 and cytosolic RIG-I/MDA5, leading to nuclear translocation of transcription factors and production of immune effectors.

Detailed Pathway Mechanisms

• Endosomal TLR Activation: Following cellular uptake via endocytosis, unmodified mRNA is sensed by Toll-like Receptor 7 (TLR7) and TLR8 within endosomal compartments. TLR7 is highly expressed in plasmacytoid dendritic cells (pDCs) and B cells, while TLR8 is prevalent in monocytes and conventional DCs [1] [5]. Engagement of these receptors recruits the adaptor protein MyD88, initiating a signaling cascade that activates the transcription factors IRF7 and NF-κB. This results in the robust production of Type I Interferons (IFN-α/β) and pro-inflammatory cytokines such as IL-6 and TNF [1] [4].

• Cytosolic RLR Activation: Cytosolic delivery of unmodified mRNA leads to its recognition by RIG-I and MDA5. RIG-I is particularly adept at sensing short double-stranded RNA (dsRNA) structures and 5'-triphosphorylated RNA, which are common byproducts of the in vitro transcription (IVT) process used to produce mRNA vaccines [4]. Upon ligand binding, RIG-I/MDA5 undergoes a conformational change and interacts with the mitochondrial antiviral-signaling protein (MAVS). This interaction triggers the activation of TBK1 and IKK kinases, which phosphorylate the transcription factors IRF3 and NF-κB, respectively. Their translocation to the nucleus induces the expression of Type I and III IFNs and inflammatory cytokines [3] [4].

Direct Comparison: Unmodified vs. Modified mRNA

Recent head-to-head studies in non-human primates (NHPs) and clinical observations have quantified the differential immune activation profiles of unmodified and nucleoside-modified (m1Ψ) mRNA vaccines.

Innate Immune Cytokine Profiles

The table below summarizes key differences in innate cytokine and adaptive immune responses based on a direct NHP study [1] [6] [7].

Table 1: Comparative Immune Responses to High-Dose mRNA Vaccination in Non-Human Primates

Parameter	Unmodified mRNA (160 μg)	N1-methylpseudouridine-modified mRNA (400/800 μg)	Experimental Context & Measurement
IFN-α Induction	Higher levels [1] [7]	Lower levels	NHP model; 24h post-immunization, plasma cytokine levels [1] [7]
IL-7 Induction	Higher levels [1] [7]	Lower levels	NHP model; 24h post-immunization, plasma cytokine levels [1] [7]
IL-6 & TNF Induction	Lower levels	Higher levels (dose-dependent) [1] [7]	NHP model; 24h post-immunization; linked to higher LNP content in high-dose groups [1]
Antigen-Specific Antibodies	Comparable kinetics and titers [1] [7]	Comparable kinetics and titers [1] [7]	Gag-specific IgG; measured after 2nd dose, peaked after 5th dose [7]
T cell Responses	Comparable, weak CD4+ & CD8+ responses; trend for more IFNγ+ CD8+ T cells [1]	Comparable, weak CD4+ & CD8+ responses; trend for better CD4+ memory [1]	Measured by ICS/AIM after 3 immunizations; sample size too small for definitive conclusions [1]
Innate Immune Tolerance	Tolerizing effect upon repetitive dosing (5th dose induced fewer DEGs than 1st) [1]	No tolerance in high-dose group; DEGs increased after 5th dose [1]	Transcriptomic profiling of blood; Number of Differentially Expressed Genes (DEGs) [1] [7]

Transcriptional and Clinical Outcomes

• Transcriptomic Profiling: Studies show that unmodified mRNA induces a strong but self-limiting innate immune activation. With repetitive administration, a tolerizing effect is observed, where the fifth immunization results in fewer differentially expressed genes (DEGs) compared to the first [1] [7]. In contrast, high-dose modified mRNA shows no such tolerance, with the number of DEGs increasing after the fifth dose, indicating a more sustained capacity to provoke innate immunity at high concentrations [1].

• Clinical Vaccine Efficacy: The differential PRR activation has direct clinical consequences. The BNT162b2 (BioNTech/Pfizer) and mRNA-1273 (Moderna) vaccines, which use m1Ψ-modified mRNA, demonstrated over 90% efficacy in preventing COVID-19 infection [1] [2]. In contrast, CureVac's CVnCoV vaccine, which used unmodified mRNA, demonstrated only 47% efficacy despite using a similar LNP formulation, highlighting the potential impact of unmodified mRNA's heightened reactogenicity and potential degradation on clinical performance [1] [2].

Detailed Experimental Protocols for PRR Research

To generate the comparative data cited in this guide, specific, rigorous methodologies are employed. The following section details key experimental protocols for profiling the innate immune response to mRNA vaccines in vivo and in vitro.

In Vivo NHP Study Design and Immune Monitoring

The referenced NHP study [1] [6] [7] provides a robust template for comparative mRNA vaccine assessment.

Diagram 2: NHP study design for mRNA vaccine comparison. Rhesus macaques immunized under different regimens undergo longitudinal sampling for comprehensive immune profiling.

Key Methodological Steps:

• Vaccine Formulations: Construct unmodified and m1Ψ-modified mRNA encoding a model antigen (e.g., HIV-1 Gag), formulated in standardized lipid nanoparticles (LNPs) [7].
• Immunization Schedule: Administer vaccines to groups of rhesus macaques (n=5 per group) following a intensive schedule: five doses at two-week intervals, with a final booster at week 20. This models the high-frequency dosing potential required for cancer immunotherapy [7].
• Blood Collection & Processing: Collect blood samples pre-vaccination and at specified time points post-vaccination (e.g., 24 hours for innate response; 2 weeks for adaptive response). Process to isolate Peripheral Blood Mononuclear Cells (PBMCs) and plasma [7].
• Innate Immune Readouts (24h post-dose):
  • Flow Cytometry: Quantify fluctuations in innate immune cells (plasmacytoid DCs, CD14+CD16+ monocytes, neutrophils) [7].
  • Multiplex Cytokine Assay: Quantify levels of IFN-α, IL-6, IL-7, TNF, and others in plasma [1] [7].
  • RNA Sequencing (RNA-seq): Perform transcriptomic profiling on PBMCs to identify Differentially Expressed Genes (DEGs) and conduct Gene Set Enrichment Analysis (GSEA) for pathways like type I IFN signaling and antigen presentation [1] [7].
• Adaptive Immune Readouts:
  • ELISA: Measure antigen-specific antibody titers in serum over time [7].
  • Intracellular Cytokine Staining (ICS) & Activation-Induced Marker (AIM) Assay: Stimulate PBMCs with antigen peptides and quantify antigen-specific CD4+ and CD8+ T cell responses via flow cytometry [7].

In Vitro Assays for Specific PRR Signaling

• TLR7/8 Reporter Assays: Utilize human cell lines (e.g., HEK293) stably transfected with human TLR7 or TLR8 and a reporter construct (e.g., luciferase) under the control of an NF-κB or IRF promoter. Transfect cells with unmodified or modified mRNA and measure reporter activity to quantify receptor activation [5] [4].
• RIG-I Signaling Assays: Transfert unmodified mRNA into murine or human fibroblast cells wild-type or deficient in RIG-I. Measure downstream IFN-β production via ELISA to confirm the specific role of the RIG-I pathway [4].

The Scientist's Toolkit: Key Research Reagents

Table 2: Essential Reagents for Investigating PRR Responses to mRNA

Reagent / Tool	Function in Research	Specific Example / Application
N1-methylpseudouridine (m1Ψ)	Critical nucleotide modification to compare against unmodified mRNA; dampens TLR7/RLR activation [1] [2].	Positive control for "immune-silent" mRNA design in PRR pathway studies.
Lipid Nanoparticles (LNPs)	Standardized delivery vehicle for in vivo and in vitro mRNA delivery; component can contribute to inflammatory responses (e.g., IL-6) [1] [7].	Formulate both modified and unmodified mRNA to ensure comparable delivery and isolate mRNA-specific effects.
Pattern Recognition Receptor Agonists/Antagonists	Pharmacological tools to dissect specific PRR contributions.	CL097 (TLR7/8 agonist), R837 (Imiquimod, TLR7 agonist), R848 (Resiquimod, TLR7/8 agonist), 5'ppp-dsRNA (RIG-I agonist) [5].
ELISA & Multiplex Cytokine Kits	Quantify protein-level secretion of cytokines and interferons.	Measure IFN-α, IFN-β, IL-6, TNF, IL-7 in cell culture supernatant or plasma [1] [7].
RNA-seq & Bioinformatics Pipelines	Unbiased profiling of the transcriptomic response, including DEG and pathway analysis (GSEA).	Identify upregulated gene modules (e.g., type I IFN, antigen presentation) post-mRNA stimulation [1] [7].
PRR-Deficient Cell Lines	Genetically engineered tools to confirm the role of specific receptors.	RIG-I knockout or MAVS knockout cell lines to isolate TLR-specific signaling [4].

The fundamental mechanisms of PRR recognition firmly establish unmodified mRNA as a potent agonist for TLR7/8 and RIG-I pathways, leading to a distinct innate immune profile characterized by robust IFN-α and IL-7 production. This stands in contrast to the modified mRNA platform, which is engineered for stealth but can still elicit inflammation, partly through LNPs and at high doses. The choice between these platforms is therefore not a matter of superiority but of strategic application. The strong immunostimulatory nature of unmodified mRNA may be a liability for widespread prophylactic vaccines but could be a critical asset in the context of therapeutic cancer vaccination, where reprogramming a suppressive tumor microenvironment requires potent innate immune activation [1]. Future research, employing the detailed protocols and tools outlined herein, should focus on refining sequence engineering and delivery systems for unmodified mRNA to better harness its immunostimulatory potential while managing reactogenicity for specific clinical indications.

The development of therapeutic messenger RNA (mRNA) represents a transformative advance in vaccinology and protein-replacement therapy. A fundamental challenge, however, lies in the intrinsic immunogenicity of in vitro transcribed (IVT) mRNA. Unmodified mRNA is recognized by the innate immune system as foreign material, triggering inflammatory pathways that can lead to unwanted side effects and reduce translational output [8]. The incorporation of nucleoside modifications, specifically pseudouridine (Ψ) and its derivative N1-methylpseudouridine (m1Ψ), has been a pivotal strategy to circumvent this problem. This review objectively compares the performance of Ψ and m1Ψ against unmodified mRNA, framing the discussion within the broader thesis of immunogenicity research. We summarize key experimental findings, detail the methodologies used to obtain them, and elucidate the recently uncovered molecular mechanisms that explain how these modifications enable mRNA to evade immune detection, a principle that has been critical for the success of mRNA vaccines [9].

Molecular Mechanisms of Immune Evasion

For years, the superior performance of modified mRNA was an observed phenomenon without a complete mechanistic understanding. Groundbreaking recent research has illuminated a two-pronged mechanism through which Ψ and m1Ψ avoid triggering Toll-like receptors (TLR) 7 and 8 in the endolysosome [10] [9] [11].

The Established Two-Pronged Evasion Mechanism

The innate immune detection of single-stranded RNA (ssRNA) by TLR7/8 is not a simple process of direct binding. It requires a prerequisite processing step by endolysosomal nucleases. The current model establishes that the enzymes RNase T2 and Phospholipase D (PLD3/4) work cooperatively to cleave ssRNA into specific fragments that are potent agonists for TLR7 [9]. Pseudouridine modifications disrupt this process at two levels:

• Impaired Enzymatic Processing: RNA containing Ψ or m1Ψ is a poor substrate for both RNase T2 and PLD3/4. These enzymes show reduced efficiency in cleaving and processing modified RNA, thereby failing to generate the key TLR-agonistic ligands [10] [9].
• Neglected TLR Engagement: Even if fragments were generated, the receptors themselves show a diminished ability to recognize them. TLR8 neglects pseudouridine as a ligand for its first binding pocket, and TLR7 neglects pseudouridine-containing RNA as a ligand for its second pocket [10].

This two-pronged failure—in processing and in recognition—provides a robust molecular basis for the lack of immunostimulation by Ψ-modified RNA, allowing the host immune system to distinguish self-like RNA from non-self RNA without launching an inflammatory response [9].

The following diagram illustrates this two-pronged immune evasion mechanism.

Structural and Biophysical Basis

The remarkable ability of Ψ to evade immune receptors is rooted in its distinct chemical structure. Pseudouridine is an isomer of uridine where the uracil base is linked to the ribose sugar via a carbon-carbon (C5-C1') bond instead of a nitrogen-carbon (N1-C1') bond.

• Additional Hydrogen Bond Donor: This C-C bond frees the N1 position, creating an additional imino group (H1N1) that can act as a hydrogen bond donor. This is absent in uridine [12] [13].
• Impact on RNA Structure: The additional hydrogen bond donor allows Ψ to create highly occupied hydration sites and stabilize local RNA structure by enhancing base stacking and increasing the rigidity of the sugar-phosphate backbone [12]. These biophysical changes are believed to underpin its resistance to enzymatic cleavage by RNase T2 and its poor fit into the ligand-binding pockets of TLR7/8 [10] [12].

Comparative Experimental Data: Ψ, m1Ψ vs. Unmodified mRNA

The mechanistic insights are corroborated by extensive experimental data comparing the immunogenicity and efficacy of unmodified, Ψ-modified, and m1Ψ-modified mRNAs. The table below summarizes key quantitative findings from pivotal studies.

Table 1: Comparative Experimental Data on mRNA Immunogenicity and Efficacy

Experimental Parameter	Unmodified mRNA	Ψ-Modified mRNA	m1Ψ-Modified mRNA	Experimental Context
Cytokine Induction	Significant TNF-α, IL-6, IFN-α response [8] [9]	Greatly reduced cytokine response [8] [9]	Greatly reduced cytokine response [9] [14]	Human monocytes, pDCs, and mouse models
RNase T2 Processing	Efficiently cleaved [9]	Resistant to cleavage [10] [9]	Resistant to cleavage [10] [9]	In vitro enzymatic assays
Translation Efficiency (In Vitro)	Higher protein expression in HeLa cells [8]	~50% lower than unmodified in HeLa cells [8]	Variable, can be comparable or superior [14]	LNP or lipoplex transfection in cell culture
Translation Efficiency (In Vivo)	Equivalent to Ψ-mRNA in liver [8]	Equivalent to unmodified mRNA in liver [8]	High, used in effective vaccines [14]	Systemic LNP delivery in mice
Vaccine Neutralizing Antibody Titer	High titer [14]	Not tested in comparison	High titer, similar to U-mRNA [14]	Andes virus vaccine in hamsters
Impact on Translation Fidelity	Baseline miscoding [15]	Can subtly modulate miscoding in a context-dependent manner [15]	Can subtly modulate miscoding in a context-dependent manner [15]	Reconstituted E. coli translation system and HEK293 cells

Key Experimental Protocols

The data in Table 1 were derived from rigorous experimental methodologies. Below are detailed protocols for the key assays cited.

• In Vitro Immunogenicity Assessment (Cytokine Measurement): Primary human monocytes or plasmacytoid dendritic cells (pDCs) are transfected with unmodified or nucleoside-modified IVT mRNA. After a defined incubation period (e.g., 6-24 hours), the cell culture supernatant is collected. The levels of cytokines (e.g., TNF-α, IL-6, IFN-α) are quantified using techniques such as Enzyme-Linked Immunosorbent Assay (ELISA) or multiplex bead-based immunoassays [8] [9]. For in vivo validation, mice are injected with mRNA formulations, and serum cytokine levels are measured post-injection.
• Enzymatic Processing Assays: Radiolabeled or fluorescently labeled unmodified and Ψ-modified RNA substrates are incubated with recombinant RNase T2 or PLD3/4 enzymes in a controlled buffer system. The reactions are stopped at specific time points, and the products are analyzed via gel electrophoresis or mass spectrometry to quantify cleavage efficiency and identify fragments [10] [9].
• In Vivo Efficacy and Expression Analysis: mRNAs encoding reporter proteins (e.g., luciferase, erythropoietin) are encapsulated in lipid nanoparticles (LNPs). Mice are injected intravenously with these LNP formulations. Protein expression is tracked longitudinally using bioluminescence imaging (for luciferase) or measured in serum via ELISA (for EPO). Organs are harvested post-mortem to assess biodistribution and organ-specific expression [8].

The Scientist's Toolkit: Essential Research Reagents

Research into mRNA immunogenicity and modification relies on a suite of specialized reagents and tools. The following table catalogues key solutions essential for experiments in this field.

Table 2: Key Research Reagent Solutions for mRNA Immunogenicity Studies

Research Reagent / Solution	Function and Application	Specific Examples / Notes
Nucleoside-Modified IVT Kits	For laboratory-scale synthesis of mRNA transcripts with defined modifications.	Kits incorporating N1-methylpseudouridine-5'-triphosphate are widely used to recapitulate vaccine technology [14].
Lipid Nanoparticles (LNPs)	In vivo delivery vehicle that protects mRNA and facilitates cellular uptake.	C12-200-based LNPs are a well-studied formulation for systemic mRNA delivery to the liver [8].
Pattern Recognition Receptor Assays	To dissect the contribution of specific innate immune pathways.	HEK293 reporter cell lines engineered to express human TLR7 or TLR8 are used to test RNA immunogenicity [9].
RNase T2 & PLD Enzymes	Key reagents for studying the mechanistic step of RNA processing in immune activation.	Recombinant human enzymes are used in in vitro cleavage assays [10] [9].
Cytokine Detection Kits	Quantifying the downstream immune response to mRNA transfection.	Multiplex ELISA panels allow simultaneous measurement of dozens of cytokines from small sample volumes [8].
BID-seq Methodology	For transcriptome-wide, quantitative mapping of Ψ modifications at single-base resolution.	An optimized protocol for bacterial RNA (baBID-seq) has been developed, leveraging bisulfite-induced deletion signatures [16].

The following diagram outlines a typical experimental workflow for comparing modified and unmodified mRNA, integrating many of these key reagents.

The incorporation of pseudouridine and N1-methylpseudouridine represents a cornerstone of modern mRNA therapeutic design, directly addressing the central challenge of unmodified mRNA immunogenicity. While early studies reported seemingly contradictory results on their efficacy—often traceable to differences in delivery vehicles, mRNA sequences, and administration routes [8]—a consensus has solidified around their critical role in dampening the innate immune response. The recent elucidation of the molecular mechanism, involving impaired processing by endolysosomal nucleases and failed TLR engagement, provides a satisfying explanation for years of observational data [10] [9]. This fundamental understanding, coupled with experimental evidence showing that these modifications can yield mRNAs with high translational capacity and reduced immunogenicity in vivo, validates their use. Future research will continue to refine our understanding of how subtle changes in the mRNA code dictate immune recognition and protein expression, paving the way for ever-more sophisticated and effective RNA therapeutics.

This guide compares the performance of nucleoside-modified and sequence-codon-optimized unmodified mRNA platforms in alleviating immune-mediated translational repression. The innate immune system can recognize exogenous mRNA and trigger pathways that suppress translation, ultimately impacting vaccine efficacy and therapeutic protein expression. Drawing from a controlled non-human primate study, we analyze how these two mRNA technologies differ in their inherent immunogenicity and subsequent translational output, providing critical data for therapeutic development.

The efficacy of mRNA-based vaccines and therapies is fundamentally tied to the efficiency with which the delivered mRNA is translated into the encoded protein. A significant challenge is that mammalian cells have evolved sophisticated mechanisms to detect foreign RNA, triggering an innate immune response that can severely repress translation [17]. This immune-mediated translational repression presents a major hurdle, potentially reducing the yield of the desired immunogen or therapeutic protein.

Two primary strategies have emerged to circumvent this problem: nucleoside modification and sequence codon optimization. Nucleoside modification involves incorporating naturally modified nucleosides (e.g., pseudouridine) into the mRNA to evade detection by innate immune sensors [18]. In contrast, codon optimization redesigns the coding sequence using synonymous codons to enhance translational efficiency without altering the amino acid sequence, though it typically retains unmodified nucleosides [6]. This guide objectively compares these two approaches, framing the analysis within the broader thesis that the chemical nature of the mRNA backbone is a critical determinant of immunogenicity and translational success.

Comparative Analysis of mRNA Platforms

Core Experimental Findings

A head-to-head comparison in rhesus macaques provides the foundational data for this analysis. Researchers immunized subjects with either a nucleoside-modified mRNA or a sequence-codon-optimized unmodified mRNA, both encoding the same model antigen (HIV-1 gag) [18] [6]. The study employed high doses and multiple immunizations to rigorously stress the systems.

Table 1: Summary of Key Experimental Findings

Parameter	Nucleoside-Modified mRNA	Unmodified mRNA
Construct Description	Incorporation of modified nucleosides (e.g., pseudouridine)	Redesigned CDS with synonymous codons for optimal translation; standard nucleosides
Innate Immune Activation	Clear but transient increase in innate immune cells and cytokines	Stronger induction of IFN-α and IL-7
Cytokine Profile	Higher IL-6 levels	Higher IFN-α and IL-7 levels
Transcriptomic Impact	Higher number of differentially expressed genes at prime, increasing after the 5th immunization	Significant upregulation of IFN and innate immune genes
Antigen-Specific Immunity	Robust gag-specific antibody and T cell responses	Similar levels and kinetics of gag-specific antibody and T cell responses

The data revealed that both mRNA constructs successfully elicited robust and comparable adaptive immune responses, namely gag-specific antibody and T-cell levels, despite underlying differences in innate immune activation [18]. This indicates that both platforms can ultimately overcome or function adequately despite immune-mediated repression. The critical distinction lies in the nature and intensity of the innate immune response, which directly influences the translation environment.

Mechanisms of Immune-Mediated Repression and Alleviation

Innate immune sensing of exogenous mRNA occurs primarily through pattern recognition receptors (PRRs) like Toll-like receptors (TLRs). Upon recognition, these receptors trigger signaling cascades that lead to the production of type I interferons (IFNs) and pro-inflammatory cytokines [17]. A key effect of this response is a global downregulation of translation efficiency. This occurs through several mechanisms, including the phosphorylation of the translation initiation factor eIF2α, which halts the initiation step of protein synthesis, and the induction of proteins that can broadly suppress the translation machinery.

Nucleoside-Modified mRNA functions by stealth. The incorporation of modified nucleosides, such as pseudouridine, fundamentally changes the structure of the mRNA, making it less recognizable to PRRs like TLRs [18]. By evading detection, this platform preemptively short-circuits the signaling cascade that leads to translational repression. Consequently, cells experience a lower level of IFN-triggered suppression, allowing for more efficient translation of the encoded antigen.

Unmodified, Codon-Optimized mRNA operates through a different principle. This mRNA is still recognized by the innate immune system, as evidenced by the higher levels of IFN-α it induces [18]. However, codon optimization enhances the intrinsic translational efficiency of the mRNA. Messages with higher translation efficiency are inherently more robust and can better withstand cellular stresses, including some forms of repression [19]. By using codons that are optimally matched to the host cell's tRNA pool, the ribosome can translate the message more rapidly and accurately, potentially outcompeting the mechanisms of repression that are activated by the immune response.

Figure 1: mRNA Immune Sensing and Platform Mechanisms. Nucleoside-modified mRNA evades immune detection, while codon-optimized unmodified mRNA relies on enhanced intrinsic efficiency to overcome repression.

Detailed Experimental Protocols

To ensure reproducibility and provide a clear framework for the data presented, this section outlines the key methodologies from the foundational non-human primate study [18] [6].

mRNA Construct Preparation

• Nucleoside-Modified mRNA: The mRNA was transcribed in vitro using a nucleotide mixture containing modified nucleosides (specifically, pseudouridine or N1-methylpseudouridine). The encoded antigen was HIV-1 gag. The mRNA was purified and formulated in lipid nanoparticles (LNPs).
• Unmodified Codon-Optimized mRNA: The HIV-1 gag antigen sequence was analyzed, and synonymous codon substitutions were made to create a coding sequence (CDS) with enhanced codon adaptation index (CAI), optimizing it for translation in the target organism. This sequence was then transcribed in vitro using standard, unmodified nucleotides, followed by LNP formulation.

Immunization and Sampling Schedule

• Animal Model: Rhesus macaques.
• Dosing: Unmodified mRNA (160 μg), Modified mRNA (400 μg and 800 μg).
• Schedule: Five immunizations administered at two-week intervals, with a final boost 20 weeks after the initial series.
• Sample Collection: Blood and other relevant biological samples were collected at predefined time points, including 24 hours post-vaccination for innate immune analysis and subsequent time points for monitoring adaptive immunity.

Key Analytical Methods

• Innate Immune Profiling:
  • Flow Cytometry: To quantify transient changes in innate immune cell populations (plasmacytoid dendritic cells, monocytes, neutrophils).
  • Cytokine Multiplex Assays: To measure concentrations of type I IFNs and inflammatory cytokines (e.g., IL-6, IL-7) in serum.
• Transcriptomic Analysis:
  • RNA Sequencing (RNA-Seq): Performed on peripheral blood mononuclear cells (PBMCs) to identify differentially expressed genes and pathway activation related to IFN signaling and innate immunity.
• Adaptive Immune Monitoring:
  • ELISA: To quantify antigen-specific antibody (gag) titers.
  • Intracellular Cytokine Staining & ELISpot: To measure the magnitude and functionality of gag-specific T-cell responses.

The Scientist's Toolkit

Table 2: Essential Research Reagents and Materials

Item	Function in Research
Nucleoside-Modified mRNA	The experimental construct designed to reduce immunogenicity by incorporating modified nucleosides (e.g., pseudouridine), thereby evading innate immune sensors and alleviating translational repression [18].
Codon-Optimized Unmodified mRNA	The alternative construct designed to enhance translational output by using a coding sequence with synonymous codons that match the host's tRNA pool, making translation more efficient even in the presence of immune activation [6].
Lipid Nanoparticles (LNPs)	A delivery vehicle formulation that protects the mRNA from degradation and facilitates its cellular uptake in vivo, which is critical for both vaccine and therapeutic applications [18].
Pattern Recognition Receptor (PRR) Assays	In vitro systems (e.g., reporter assays) used to characterize and quantify the intrinsic immunostimulatory capacity of different mRNA constructs by measuring their activation of TLRs and other sensors.
Ribosome Profiling	A specialized sequencing technique that provides a genome-wide snapshot of translation (ribosome positions) by deep sequencing of ribosome-protected mRNA fragments. This allows for direct measurement of translation efficiency [19] [20].

The choice between nucleoside-modified and unmodified codon-optimized mRNA platforms involves a strategic trade-off. Nucleoside modification directly dampens the innate immune response, creating a more permissive environment for translation. Unmodified codon-optimized mRNA accepts a degree of immune activation but is engineered for superior translational robustness to power through it. The experimental data demonstrate that both strategies can achieve the ultimate goal of potent antigen expression and robust adaptive immunity. The optimal choice is context-dependent, influenced by the specific application, desired immune profile, and therapeutic goals. This comparison underscores that managing immune-mediated translational repression is not a matter of complete suppression but of strategic control and compensation.

The remarkable success of mRNA vaccines has catalyzed a paradigm shift in therapeutic development, drawing significant attention to the nuanced immunogenicity of their components. While scientific discourse has often centered on the role of nucleoside modifications (e.g., N1-methylpseudouridine, m1Ψ) in modulating immune responses, a growing body of evidence highlights the lipid nanoparticle (LNP) delivery system as a critical determinant of vaccine efficacy. The LNP is no longer viewed as a mere passive vehicle but is now recognized as an active participant with intrinsic adjuvant properties that can profoundly shape both innate and adaptive immunity [21] [22]. This review examines the immunostimulatory capacity of LNPs within the broader context of ongoing research comparing the immunogenicity of modified versus unmodified mRNA, providing a comparative analysis for researchers and drug development professionals.

The core of this discourse lies in balancing desired immune activation against excessive reactogenicity. Modified nucleosides like m1Ψ were foundational to the first-generation COVID-19 vaccines, primarily by suppressing innate immune recognition via Toll-like receptors (TLRs) and RIG-I-like receptors (RLRs), thereby enhancing protein expression [1] [23]. In contrast, unmodified mRNA is a potent activator of these pathways, triggering robust type I interferon (IFN-α/β) and inflammatory cytokine secretion [1] [6]. However, the LNP itself contributes a significant, and sometimes dominant, layer of immunogenicity. This review will dissect this complex interplay, presenting direct experimental comparisons and quantitative data to guide the rational selection of mRNA and LNP components for specific therapeutic applications.

Comparative Immunogenicity of mRNA Constructs: The Nucleoside Modification Perspective

The choice between modified and unmodified mRNA is not merely a binary selection but a strategic decision that influences translational efficiency, innate immune sensing, and the quality of the adaptive response. The following table synthesizes key immunological differences observed in head-to-head comparisons, particularly from studies in non-human primates (NHPs) [1] [6] [18].

Table 1: Comparative Immunogenicity of Modified vs. Unmodified mRNA Vaccines

Parameter	Unmodified mRNA	N1-methylpseudouridine (m1Ψ) Modified mRNA
Innate Immune Sensing	Robust activation of TLR7/8 and RLR pathways [1]	Attenuated TLR7/8 and RLR activation; evades immune detection [1] [23]
Key Cytokine Signature	Higher levels of IFN-α and IL-7 [1] [6] [18]	Higher levels of IL-6 and TNF (often LNP-driven) [1] [6]
Type I Interferon Response	Strong induction [6]	Weaker induction [1]
Translational Efficiency	Subject to immune-mediated translational inhibition [23]	Enhanced, due to alleviation of immune restriction [1] [23]
Impact of Repetitive Dosing	Can induce a tolerizing effect (reduced cytokines/DEGs after 5th dose) [1]	High-dose regimens show no tolerance; DEGs increase post-5th dose [1]
T Cell Response Quality	Trend towards more IFNγ+ CD8+ T cells [1]	Trend towards better CD4+ memory induction [1]
Humoral Response	Comparable Gag-specific antibody levels and kinetics to modified mRNA [1] [6]	Comparable Gag-specific antibody levels and kinetics to unmodified mRNA [1] [6]

A critical study by Engstrand et al. directly compared these platforms in rhesus macaques using an HIV-1 Gag model antigen. Despite using a lower dose (160 μg) of unmodified mRNA versus high-dose modified mRNA (400/800 μg), the unmodified construct induced significantly higher levels of IFN-α and the T-cell supportive cytokine IL-7 [6] [18]. Conversely, the modified mRNA induced higher levels of IL-6 and TNF, which the authors attributed not to the nucleoside modification itself, but to the larger amount of LNP required to deliver the higher mRNA dose, highlighting the difficulty in disentangling RNA from LNP effects [1]. Notably, despite these divergent innate immune pathways, the ultimate adaptive immune outcomes—Gag-specific antibody levels and T cell responses—were remarkably similar across platforms in this NHP model [1] [6].

LNP as an Intrinsic Adjuvant: Mechanisms and Experimental Evidence

The immunostimulatory role of LNPs extends far beyond their function as a delivery vehicle. Specific LNP components, particularly the ionizable lipid, are now understood to be potent triggers of innate immune pathways, effectively acting as built-in adjuvants [21] [22]. This intrinsic activity is a key factor in the success of mRNA-LNP vaccines.

The adjuvant effect of LNPs is mechanistically distinct from that of mRNA. While unmodified mRNA activates intracellular TLRs (e.g., TLR7/8 in endosomes) and cytosolic RLRs, LNP components can trigger inflammatory pathways independently of these receptors. One study noted that LNP-induced TNF and IL-6 production was independent of Myd88, a central adaptor protein for most TLR signaling [1]. This suggests LNPs may activate alternative pathways, such as the NLRP3 inflammasome or other cytosolic sensors, to initiate a pro-inflammatory cascade that crucially supports the T follicular helper (Tfh) cell and antibody response [1] [21].

The following diagram illustrates the synergistic immune activation pathways triggered by the combined mRNA-LNP system.

Strategic Enhancement of LNP Adjuvanticity

Recognizing the intrinsic adjuvant capacity of LNPs has spurred the development of strategies to rationally engineer this property. A prominent approach involves the incorporation of known immune potentiators, such as Toll-like receptor (TLR) agonists, directly into the LNP structure.

A 2025 study demonstrated this by incorporating a novel TLR7/8 agonist (AD7/8) into SM-102-based LNPs by partially replacing cholesterol [23]. This optimized formulation, termed AD03-LNP, was evaluated with m1Ψ-modified mRNA encoding various antigens (HPV, SARS-CoV-2, influenza). The results were striking, showing a consistent boost in immune responses compared to conventional LNP:

• Cellular Immunity: In the HPV mRNA model, AD03-LNP enhanced antigen-specific CD8⁺ T cell and cytokine responses by 1.5-2.1-fold [23].
• Humoral Immunity: In the SARS-CoV-2 model, it markedly elevated IgG2a levels (indicative of a Th1-skewed response) by 8-fold, and in the influenza model, it increased total IgG by 3.6-fold [23].

This innovative strategy successfully counteracts the blunted innate immunity associated with m1Ψ-modified mRNA, proving that the LNP component can be engineered to fine-tune the quality and magnitude of the adaptive immune response.

Direct Comparative Analysis: Experimental Data and Protocols

To facilitate a direct comparison of the experimental evidence supporting the immunostimulatory roles of mRNA formats and LNP adjuvanticity, the following table summarizes key findings and the methodologies used to obtain them.

Table 2: Summary of Key Experimental Comparisons and Methodologies

Study Focus	Experimental Model / Protocol	Key Comparative Findings
High-dose mod. vs. unmod. mRNA [1] [6]	NHP Model: Rhesus macaques (n=small group).Immunization: 5 doses (160 μg unmod.; 400/800 μg mod.) at 2-wk intervals + booster at wk 20.Readouts: Cytokine (IFN-α, IL-7, IL-6), transcriptomics, flow cytometry (T cells), Ab titers.	- Unmod. mRNA: Higher IFN-α & IL-7.- Mod. mRNA: Higher IL-6 (LNP-linked).- Tolerance: Observed with unmod. mRNA upon repetition.- Adaptive Immunity: Similar Ab and T cell levels.
LNP with integrated TLR7/8 agonist [23]	Mouse Model: C57BL/6, ICR, BALB/c.LNP Formulation: SM-102, DSPC, Cholesterol, DMG-PEG, TLR7/8 agonist AD7/8 (partial chol. replacement).Readouts: Antigen-specific CD8⁺ T cells (flow cytometry), IgG/IgG2a titers (ELISA).	- AD03-LNP (0.5% agonist): Enhanced CD8⁺ T cells (1.5-2.6x), total IgG (3.6x), IgG2a (8x).- Confirmed enhanced Th1-skewed immunity for m1Ψ-mRNA.
Circular RNA vs. Self-Amplifying RNA [24]	Mouse Model: SARS-CoV-2 RBD antigen.Vaccine Construct: Circ-RNA (CVB3 IRES, Anabaena intron) vs. SAM (SFV replicon).Readouts: Neutralizing Ab, memory T cells, stability at 4°C.	- Circ-RNA: Higher memory T cell response, stable for 4 weeks at 4°C.- SAM & Circ-RNA: Comparable neutralizing Ab titers.

The Scientist's Toolkit: Essential Reagents for LNP and mRNA Immunology Research

For researchers aiming to investigate these phenomena, the following table catalogs key reagents and their functions as derived from the cited experimental protocols.

Table 3: Essential Research Reagents for Investigating LNP and mRNA Immunogenicity

Reagent / Material	Function in Experimental Design
Ionizable Lipids (e.g., SM-102)	The key functional lipid in LNP formulation for mRNA encapsulation and endosomal escape; a major contributor to inherent adjuvant effects [23] [21].
TLR7/8 Agonists (e.g., AD7/8, R848)	Potent immune potentiators; used to be incorporated into LNPs to enhance innate immune activation and drive Th1-skewed adaptive responses [23].
N1-methylpseudouridine (m1Ψ)	Modified nucleoside used in IVT mRNA to reduce innate immunogenicity and enhance translational efficiency [1] [23].
HEK-Blue hTLR7/8 Reporter Cells	Cell lines engineered to express human TLR7 or TLR8; used with assays like QUANTI-Blue to quantify TLR-specific activation by mRNA or agonists [23].
pNF-κB-Luciferase Reporter Plasmid	Reporter construct transfected into cells (e.g., RAW264.7) to measure NF-κB pathway activation, a key downstream signaling event of TLR and inflammatory pathways [23].
RNase R	Enzyme used to digest linear RNA; critical for confirming the successful circularization of Circ-RNA constructs by assessing resistance to digestion [24].

The paradigm of mRNA vaccinology is evolving from a simplistic view of the LNP as a delivery vehicle to a sophisticated understanding of it as an integral immunomodulatory component. The direct comparisons between modified and unmodified mRNA reveal a complex landscape: while they engage the innate immune system through distinct pathways and cytokine profiles, they can ultimately converge on similar adaptive immune outcomes [1] [6]. The LNP's intrinsic adjuvant effect, and our newfound ability to engineer it—for instance, by incorporating TLR7/8 agonists—provides a powerful lever to skew responses towards desired phenotypes, such as strong Th1 immunity or potent CD8⁺ T cell activation [23] [21].

Future research must focus on deconvoluting the precise mechanisms of LNP-induced immunogenicity, identifying which lipid components and physical properties are most responsible for adjuvant effects. Furthermore, as the field expands into therapeutic areas like cancer and protein replacement, the choice between a highly immunogenic unmodified mRNA/LNP system versus a "stealth" modified mRNA/LNP system will be critical. The former may be ideal for cancer vaccines, where robust innate activation is needed to break tolerance in a "cold" tumor microenvironment [1]. The latter is essential for protein replacement therapies, where minimizing immune recognition is paramount for safety and sustained protein expression [25]. Ultimately, the future of mRNA therapeutics lies in the rational, context-dependent combination of mRNA chemistry and LNP engineering to achieve precise immunological control.

Strategic Platform Selection: Tailoring mRNA Chemistry to Therapeutic Intent

The emergence of mRNA vaccine technology represents a transformative advancement in immunology, with distinct applications across infectious diseases and oncology. While both fields utilize the same fundamental platform, they exhibit divergent requirements for immunogenicity—a balancing act between achieving protective immunity against pathogens and generating robust antitumor responses without excessive reactogenicity. Recent research has shed light on how different mRNA modifications, particularly nucleoside-modified versus unmodified constructs, influence this immunogenicity balance. Understanding these nuances is critical for researchers and drug development professionals optimizing mRNA platforms for specific therapeutic contexts. This review systematically compares the performance characteristics of various mRNA vaccine modalities, examining how their immunogenic properties can be harnessed for infectious disease prevention versus cancer immunotherapy.

mRNA Vaccine Platforms: Modified vs. Unmodified

Fundamental Structural Differences

mRNA vaccines comprise synthetic mRNA molecules that direct the production of antigens that generate immune responses. These in vitro-transcribed (IVT) mRNAs mimic endogenous mRNA structure with five key components: 5' cap, 5' untranslated region (UTR), open reading frame encoding the antigen, 3' UTR, and a poly(A) tail [26]. The strategic modifications to these components significantly influence both the immunogenicity and efficacy of the resulting vaccine.

Two primary mRNA platforms have emerged: nucleoside-modified mRNA (used in licensed COVID-19 vaccines) and sequence-codon-optimized unmodified mRNA. The critical distinction lies in their nucleoside composition and how they interact with the innate immune system [7] [26] [25].

Table 1: Key Characteristics of mRNA Vaccine Platforms

Feature	Nucleoside-Modified mRNA	Unmodified mRNA
Nucleoside composition	Incorporates modified nucleosides (e.g., N1-methylpseudouridine)	Uses natural, unmodified nucleosides
Recognition by pattern recognition receptors	Reduced recognition of TLRs, RIG-I	Readily recognized by TLR3, TLR7, TLR8, RIG-I
Innate immune activation	Attenuated, leading to lower reactogenicity	Potent, often resulting in higher reactogenicity
Translation efficiency	Enhanced due to evasion of immune detection	Can be limited by interferon responses
Dosing considerations	Higher doses typically well-tolerated	Lower doses often necessary due to reactogenicity
Current applications	Prophylactic vaccines (COVID-19)	Investigational cancer vaccines

Immunogenicity Mechanisms

The immunogenicity of mRNA vaccines stems from their intrinsic ability to activate pattern recognition receptors (PRRs). Unmodified mRNA is recognized by Toll-like receptors (TLR3, TLR7, TLR8) and retinoic acid-inducible gene I (RIGI) receptors, which trigger type I interferon production and innate immune activation [26] [25]. This response creates a potentially favorable environment for immune recognition but can also inhibit mRNA translation and increase reactogenicity.

Nucleoside-modified mRNA incorporates substitutions such as pseudouridine or N1-methylpseudouridine for uridine, which prevents recognition by these PRRs [25] [27]. This evasion reduces innate immune activation while enhancing antigen translation—a crucial advantage for prophylactic vaccines where high antigen expression correlates with protective immunity.

Diagram 1: mRNA immune recognition pathways. Unmodified mRNA activates PRRs triggering interferon responses and innate immunity, while modified mRNA evades detection enabling enhanced translation.

Comparative Immunogenicity Profiles: Experimental Evidence

Recent Non-Human Primate Study Design

A seminal 2025 study directly compared the immunogenicity of modified versus unmodified mRNA platforms in rhesus macaques, providing crucial insights into their differential effects [7] [18] [6]. The experimental design methodology was as follows:

• Antigen: Both platforms encoded identical HIV-1 gag as a model antigen
• Vaccine constructs: Nucleoside-modified mRNA (400μg and 800μg doses) versus sequence-codon-optimized unmodified mRNA (160μg dose)
• Immunization schedule: Five immunizations at 2-week intervals, with a final boost 20 weeks later
• Sample collection: Blood samples at 24h post-vaccination for innate immunity assessment and at multiple timepoints for adaptive immunity monitoring
• Analysis methods: Cytokine profiling, immune cell phenotyping, transcriptomic analysis, and antigen-specific T cell and antibody measurements

This comprehensive approach enabled direct comparison of both innate and adaptive immune responses generated by each platform.

Innate Immune Responses

At 24 hours post-vaccination, both mRNA constructs elicited clear but transient innate immune activation, though with distinct characteristics [7]:

• Cellular changes: Both platforms increased plasmacytoid dendritic cells, intermediate CD14+CD16+ monocytes, and neutrophils, with a concomitant decrease in T cells suggesting redistribution to tissues
• Cytokine profiles: Unmodified mRNA induced higher interleukin-7 (IL-7) and IFN-α levels, whereas modified mRNA induced higher IL-6 levels
• Dose dependency: High-dose modified mRNA (800μg) showed the strongest inflammatory cytokine induction (IL-6, TNF) and the highest number of differentially expressed genes (DEGs), which increased further after the fifth immunization

Table 2: Comparative Innate Immune Responses to mRNA Vaccine Platforms

Parameter	Unmodified mRNA (160μg)	Modified mRNA (400μg)	Modified mRNA (800μg)
IFN-α levels	++++	++	+
IL-7 levels	++++	++	+
IL-6 levels	+	++	++++
Monocyte activation	++	++	+++
DEGs after prime	Moderate	Moderate	High
DEGs after 5th dose	Decreased	Decreased	Increased

Transcriptomic profiling revealed significant upregulation of genes related to type I interferon signaling, antigen presentation, and innate immune activation induced by both mRNA constructs [7]. Gene set enrichment analysis confirmed similar enrichment patterns across groups, with IL-6 signaling pathway significantly enriched in all conditions.

Adaptive Immune Responses

Despite differences in innate immune activation, all groups developed similar gag-specific adaptive immune responses [7] [6]:

• Antibody responses: All regimens induced well-detectable gag-specific antibodies 2 weeks after the second immunization, with increasing titers up until the fifth dose, followed by waning. The final boost restored titers to peak levels with similar kinetics and magnitude across platforms.
• T cell responses: Gag-specific memory T cell responses were readily detected after three immunizations in all groups at similar frequencies. Both CD4+ and CD8+ T cell responses were induced, with CD4+ responses dominating over CD8+ responses.
• Kinetics: Response kinetics were comparable across platforms, with rapid induction and similar durability profiles.

This dissociation between innate immune activation and adaptive outcomes highlights the complexity of mRNA vaccine immunogenicity and suggests that pronounced innate activation is not necessarily required for robust adaptive immunity.

Application-Specific Considerations

Infectious Disease Vaccines

For prophylactic vaccines against infectious diseases, the primary goal is generating neutralizing antibodies and memory responses while minimizing reactogenicity to ensure good vaccine acceptability [26] [28]. The success of nucleoside-modified mRNA vaccines in COVID-19 demonstrates the effectiveness of this approach:

• Reduced reactogenicity: Modified mRNA enables higher dosing with better tolerability profiles
• Enhanced antigen expression: Evasion of innate immune detection allows for more efficient protein translation and higher antigen yields
• Robust neutralizing antibodies: Clinical data show modified mRNA vaccines (e.g., BNT162b2, mRNA-1273) induce potent neutralizing antibodies at >94% efficacy rates [26]
• Durability considerations: While generating strong initial protection, ongoing research addresses durability of immune responses against evolving pathogens

Recent phase 3 data for adapted COVID-19 vaccines demonstrate the continued effectiveness of this platform, with LP.8.1-adapted vaccines showing at least 4-fold increases in neutralizing antibody titers in high-risk populations [29].

Cancer Immunotherapy

The requirements for mRNA vaccines in oncology differ significantly from infectious disease applications [25] [27]:

• Immunogenicity as advantage: Potent innate immune activation can provide beneficial adjuvant effects for breaking tolerance against tumor antigens
• Targets: Cancer vaccines typically target tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs), including neoantigens derived from tumor mutations
• Dosing schedule: Therapeutic cancer vaccines often require higher mRNA doses and more frequent administrations compared to prophylactic vaccines
• Combination strategies: mRNA cancer vaccines frequently combine with immune checkpoint inhibitors to overcome tumor immunosuppression

Ongoing clinical trials are exploring both unmodified and modified mRNA platforms for various malignancies including melanoma, non-small cell lung cancer, prostate cancer, and pancreatic ductal adenocarcinoma [27]. Some have advanced to phase 3 with promising results in both safety and efficacy.

Diagram 2: Application-specific considerations for mRNA vaccines. Infectious disease and oncology applications have distinct immunological requirements influencing platform selection.

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagent Solutions for mRNA Vaccine Studies

Reagent/Category	Function/Application	Examples/Specifications
Nucleoside-modified mRNAs	Reduce innate immune activation; enhance translation	N1-methylpseudouridine, pseudouridine, 5-methylcytosine
Unmodified mRNAs	Study innate immune activation; potential adjuvant effects	Sequence-codon-optimized natural mRNA
Lipid Nanoparticles (LNPs)	mRNA delivery and protection	Ionizable lipids, cholesterol, helper phospholipids, PEGylated lipids
In vitro transcription kits	mRNA production	T7, T3, or SP6 RNA polymerase-based systems
Capping systems	Enhance mRNA stability and translation	CleanCap (co-transcriptional), vaccinia virus-derived enzymes (post-transcriptional)
Immune profiling panels	Characterize innate and adaptive responses	Cytokine arrays, multicolor flow cytometry panels, ELISpot assays
Transcriptomic tools	Analyze global gene expression responses	RNA-seq, gene set enrichment analysis (GSEA)

The strategic balancing of immunogenicity in mRNA vaccine design requires platform selection aligned with application-specific needs. For infectious disease prevention, nucleoside-modified mRNA offers favorable profiles with reduced reactogenicity and enhanced antigen expression. For oncology applications, the inherent immunostimulatory properties of unmodified mRNA may provide beneficial adjuvant effects for breaking immune tolerance against tumor antigens.

Future research directions include optimizing modified nucleoside combinations to fine-tune immunogenicity, developing personalized mRNA vaccines targeting patient-specific neoantigens, and exploring combination strategies with other immunomodulators. The continued refinement of both platforms will expand the therapeutic potential of mRNA technology across diverse medical applications, ultimately enabling more precise control over vaccine-induced immune responses for specific clinical contexts.

The discovery that in vitro transcribed (IVT) messenger RNA (mRNA) can be used to direct the production of therapeutic proteins in vivo represents a breakthrough in modern medicine. However, a significant challenge persists: the inherent immunogenicity of exogenous mRNA triggers innate immune responses that can severely limit its therapeutic efficacy for non-immunotherapy applications. When synthetic mRNA is introduced into the body, the immune system recognizes it as foreign material through various pattern recognition receptors (PRRs), leading to the production of type I interferons and inflammatory cytokines. This immune activation not only reduces translation efficiency but can also cause unwanted side effects, creating a substantial barrier for protein replacement therapies and gene editing applications where high, sustained target protein expression is desired without immune activation [30] [25].

The immunogenicity of mRNA presents a "double-edged sword" in therapeutic development. While this property is advantageous for vaccine applications where immune activation enhances efficacy, it is counterproductive for non-immunotherapy applications such as protein replacement therapy, regenerative medicine, and gene editing [25]. In these contexts, immune activation leads to diminished protein expression and potential adverse reactions, making the minimization of immunogenicity a critical priority. This comparison guide examines the key strategies being employed to overcome this challenge, focusing specifically on the central role of mRNA modification technologies and their performance in reducing immune activation while maintaining therapeutic protein expression.

Comparative Analysis of mRNA Modification Strategies

Table 1: Comparison of Nucleoside Modification Strategies for Reducing mRNA Immunogenicity

Modification Type	Recognition by PRRs	Translation Efficiency	Stability	Reported Frameshifting	Key Research Findings
Unmodified mRNA	High	Low to Moderate	Low	Not reported	Strong activation of TLRs and RLRs; rapid degradation; higher IFN-α levels [18]
Pseudouridine (Ψ)	Significantly reduced	Enhanced	Improved	Not reported	First major modification shown to reduce immunogenicity; enhances translation [30]
N1-methylpseudouridine (m1Ψ)	Significantly reduced	Greatly enhanced	Improved	Observed in studies	Gold standard used in COVID-19 vaccines; may cause +1 ribosomal frameshifting [30]
5-methylcytidine (m5C)	Reduced	Moderate improvement	Moderate improvement	Not reported	One of several modifications identified to evade immune detection [25]
5-methyluridine (m5U)	Reduced	Moderate improvement	Moderate improvement	Not reported	Effective alternative to uridine modifications [25]
N6-methyladenosine (m6A)	Reduced	Moderate improvement	Moderate improvement	Not reported	Naturally occurring modification; reduces immune recognition [25]

Table 2: Non-Nucleoside Modification Approaches for Optimizing Therapeutic mRNA

Modification Approach	Mechanism of Action	Impact on Immunogenicity	Expression Duration	Key Advantages
Nucleotide sequence optimization	Codon optimization; UTR engineering	Moderate reduction	Moderate	No chemical alterations; algorithm-driven design [30]
5' cap analogs	Mimics eukaryotic cap structure; reduces RIG-I recognition	Significant reduction	Extended	Enhances translation initiation; reduces decapping [30]
Poly(A) tail engineering	Optimal length stabilization; prevents degradation	Indirect reduction	Significantly extended	Critical for mRNA stability; no nucleoside modification needed [30]
Circular RNA (circRNA)	Covalently closed structure resistant to exonucleases	Innately lower	Greatly extended	No cap or poly(A) tail needed; highly stable [25]
Self-amplifying RNA (saRNA)	Viral replicon enables intracellular amplification	Varies with design	Extended	Lower dose required; sustained expression [25]

Experimental Approaches for Evaluating mRNA Immunogenicity

In Vitro Transcription and Template Design

The production of mRNA for therapeutic applications primarily relies on in vitro transcription (IVT), a cell-free process that utilizes phage RNA polymerases (T7, T3, or SP6) to synthesize RNA from a linear DNA template. The DNA template must contain a promoter sequence recognized by the polymerase, followed by the elements of the mature mRNA: the 5' untranslated region (UTR), the open reading frame (ORF) encoding the target protein, the 3' UTR, and a poly(A) tail sequence. The first nucleotide of the transcript is typically guanosine to ensure high transcription efficiency. Following transcription, a 5' cap structure is added either co-transcriptionally using cap analogs or post-transcriptionally using capping enzymes [30].

Critical to minimizing immunogenicity is the purification of IVT mRNA to remove double-stranded RNA (dsRNA) contaminants, which are potent inducers of innate immune responses. High-performance liquid chromatography (HPLC) or cellulose-based purification methods are commonly employed to achieve this. The quality of the final mRNA product is assessed through various analytical methods, including electrophoresis for size confirmation, spectrophotometry for concentration and purity measurement, and encapsulation efficiency testing when lipid nanoparticles (LNPs) are used as delivery vehicles [30].

Innate Immune Response Profiling Assays

Comprehensive evaluation of mRNA immunogenicity requires multiple complementary assays. Transcriptomic analysis through RNA sequencing or microarray-based approaches can identify differentially expressed genes in response to mRNA administration, particularly those involved in type I interferon signaling pathways and inflammatory responses. In a comparative study of modified versus unmodified mRNA, researchers observed significant upregulation of type I interferon-stimulated genes following administration of both mRNA types, though with distinct kinetics and magnitude [18].

Cytokine profiling via ELISA or multiplex bead-based arrays provides quantitative data on protein-level immune activation. Key cytokines to monitor include IFN-α, IFN-β, IL-6, TNF-α, and various chemokines. Research has demonstrated that unmodified mRNA tends to induce higher levels of IFN-α, while modified mRNA (e.g., m1Ψ) may induce higher IL-6, suggesting that different modification strategies may activate distinct aspects of the immune response [18].

Flow cytometry enables immunophenotyping of cells exposed to mRNA, assessing changes in the frequency and activation state of various immune cell populations. Studies have shown that both modified and unmodified mRNA can elicit transient increases in plasmacytoid dendritic cells, intermediate CD14+CD16+ monocytes, and neutrophils at 24 hours post-administration [18].

In Vivo Modeling and Expression Analysis

Animal models, particularly non-human primates and mice, provide critical insights into the performance of modified mRNA platforms in complex biological systems. Experimental protocols typically involve administering mRNA via relevant routes (intramuscular, intravenous, or subcutaneous) at various doses, with subsequent monitoring of both immune activation and therapeutic protein expression.

For protein expression quantification, ELISA assays specific to the encoded protein are commonly used to measure serum or tissue concentrations over time. Luciferase-encoding mRNA provides a highly sensitive alternative for tracking expression kinetics through bioluminescence imaging. Research comparing high-dose modified mRNA (400μg and 800μg) against lower-dose unmodified mRNA (160μg) demonstrated that despite differences in innate immune activation, similar levels and kinetics of antigen-specific antibody and T-cell responses can be achieved with proper optimization [18].

Table 3: Essential Research Reagents for mRNA Immunogenicity Studies

Reagent/Category	Specific Examples	Research Function	Technical Considerations
Nucleotide Analogs	N1-methylpseudouridine, Pseudouridine, 5-methylcytidine	Replaces natural nucleotides in IVT to reduce PRR recognition	Varying effects on translation efficiency and ribosomal frameshifting observed [30]
In Vitro Transcription System	T7, T3, SP6 RNA polymerases; cap analogs (CleanCap)	mRNA synthesis with reduced immunogenicity	Co-transcriptional capping improves yield and capping efficiency [30]
Purification Kits	HPLC systems; cellulose-based purification	Remove immunogenic dsRNA contaminants	Critical step regardless of modification strategy [30]
Delivery Vehicles	Lipid nanoparticles (LNPs); polymeric nanoparticles	Protect mRNA and enhance cellular uptake	Composition affects immunogenicity; can be tuned for specific applications [25]
Immune Assays	IFN-α/β ELISA; multiplex cytokine panels; RNA sequencing	Quantify innate immune activation	Multiple timepoints needed to capture kinetic response [18]

Key Signaling Pathways in mRNA Immune Recognition

Diagram 1: mRNA Immune Recognition Pathways and Modification Effects. Modified nucleotides (green) reduce detection by pattern recognition receptors, minimizing immune activation and enabling therapeutic protein expression.

The innate immune system employs multiple pattern recognition receptors (PRRs) to detect exogenous RNA, initiating signaling cascades that ultimately suppress translation and trigger inflammatory responses. Understanding these pathways is essential for developing effective strategies to minimize immune activation. The primary sensors for exogenous mRNA include endosomal Toll-like receptors (TLR7 and TLR8) and cytosolic RIG-I-like receptors (RLRs), which detect distinct molecular patterns in RNA molecules [30].

When unmodified mRNA enters cells through endocytosis, it can engage TLR7 and TLR8 in endosomal compartments, particularly when complexed with delivery vehicles. Activation of these receptors initiates a signaling cascade through the adaptor protein MYD88, leading to the production of proinflammatory cytokines and type I interferons. Simultaneously, if mRNA reaches the cytosol, it can be recognized by RIG-I and MDA5, which signal through the mitochondrial antiviral-signaling protein (MAVS) pathway to induce interferon-stimulated genes that create an antiviral state incompatible with efficient translation of therapeutic mRNA [30].

Chemical modifications, particularly nucleoside substitutions such as replacement of uridine with pseudouridine or N1-methylpseudouridine, alter the molecular structure of mRNA in ways that reduce its affinity for these pattern recognition receptors. This strategy effectively "fools" the immune system into perceiving the exogenous mRNA as less foreign, thereby dampening the activation of both the MYD88 and MAVS pathways and allowing for enhanced translation of the encoded therapeutic protein [30].

Advanced mRNA Platforms Beyond Nucleoside Modification

Circular RNA and Self-Amplifying mRNA

Beyond nucleoside modifications, innovative RNA structures offer promising alternatives for minimizing immunogenicity while extending therapeutic protein expression. Circular RNA (circRNA) represents a covalently closed-loop structure that lacks the 5' cap and 3' poly(A) tail of traditional linear mRNA. This unique architecture confers exceptional stability against exonuclease-mediated degradation, significantly extending the half-life of the molecule and consequently the duration of protein expression. The translation of circRNA occurs through cap-independent mechanisms, often mediated by internal ribosome entry site (IRES) elements, which bypass the conventional translation initiation pathway [25].

Self-amplifying RNA (saRNA) incorporates genes from positive-strand RNA viruses that encode RNA-dependent RNA polymerase and other non-structural proteins enabling intracellular RNA amplification. This technology allows for substantially lower doses compared to conventional mRNA, as each delivered molecule can generate numerous copies, ultimately reducing the overall immune stimulus while maintaining therapeutic protein levels. However, the larger size of saRNA constructs presents delivery challenges, and the prolonged expression may raise safety concerns regarding potential chronic immune activation in some applications [25].

Sequence Optimization and Delivery System Engineering

Nucleotide sequence optimization through codon usage adjustment and secondary structure minimization represents a non-chemical approach to reducing mRNA immunogenicity. By maximizing the translation efficiency of each mRNA molecule, lower doses can be administered, indirectly reducing immune stimulation. Advances in computational tools, including machine learning algorithms, now enable more sophisticated mRNA sequence design that accounts for multiple parameters simultaneously, including translation efficiency, stability, and immunogenicity [30].

The delivery system plays a crucial role in modulating mRNA immunogenicity. Lipid nanoparticles (LNPs) can be formulated with ionizable lipids that promote endosomal escape while minimizing inflammatory responses. Similarly, polymeric carriers can be engineered with specific charge densities and biodegradation profiles to reduce immune recognition. Recent innovations include the development of LNPs that preferentially target specific tissues or cell types, further enhancing the therapeutic index of mRNA medicines for non-immunotherapy applications [25].

The development of mRNA platforms for non-immunotherapy applications requires careful balancing of reduced immunogenicity with maintained translation efficiency and stability. While nucleoside modifications like N1-methylpseudouridine have revolutionized the field, emerging challenges such as ribosomal frameshifting indicate that further optimization is needed. The future of therapeutic mRNA lies in combining multiple strategies—nucleoside modifications, sequence optimization, advanced structures like circRNA, and tailored delivery systems—to create precisely tuned molecules that escape immune detection while achieving therapeutic protein expression levels sufficient for clinical efficacy.

As the field progresses, standardized experimental protocols for comprehensive immunogenicity assessment will be essential for meaningful comparisons between platforms. Similarly, understanding how patient-specific factors such as age, gender, and pathological conditions affect mRNA immunogenicity and performance will be crucial for developing personalized mRNA therapeutics for protein replacement and gene editing applications.

The rapid development of messenger RNA (mRNA) therapeutics has revolutionized vaccinology and therapeutic protein delivery. Central to this revolution is the sophisticated chemical engineering of mRNA molecules to enhance their stability, translational efficiency, and immunogenic properties. The immunogenicity profile of mRNA—whether activating or evading innate immune recognition—represents a critical determinant in therapeutic applications, creating a fundamental dichotomy between immune-activating unmodified mRNA for cancer immunotherapy and immune-silenced modified mRNA for prophylactic vaccines and protein replacement therapy.

This guide provides a comprehensive comparison of major mRNA chemical modifications and sequence optimization technologies, focusing on their distinct mechanisms, immunological consequences, and experimental performance data. We examine three predominant RNA modifications—N1-methylpseudouridine (m1Ψ), 5-methylcytosine (m5C), and N6-methyladenosine (m6A)—alongside advanced codon optimization strategies, providing researchers with objective data to inform therapeutic design decisions.

Modified vs. Unmodified mRNA: Immunological Paradigms

The choice between modified and unmodified mRNA hinges on the desired immune activation profile, which varies dramatically between application contexts.

Innate Immune Recognition Mechanisms

Unmodified mRNA is recognized by multiple pattern recognition receptors, including Toll-like receptor (TLR)7, TLR8, and RIG-I-like receptors (RLR), leading to robust type I interferon (IFN-α/β) production and innate immune activation [1]. This immunostimulatory property is desirable for cancer vaccines but problematic for protein replacement therapies.

Modified nucleosides, particularly m1Ψ, fundamentally alter this recognition profile. Pseudouridine (Ψ) and its derivative m1Ψ suppress unwanted immunogenicity through a two-pronged mechanism: they directly impair RNA processing into TLR-agonistic ligands and hinder TLR activation itself [31]. This immune evasion enables repeated administration without diminished efficacy—a crucial advantage for therapeutic regimens requiring multiple doses.

Comparative Performance in Vaccine Applications

Head-to-head comparisons in non-human primates (NHPs) reveal distinct immunological profiles for modified versus unmodified mRNA formats. A high-dose vaccination study using HIV-1 Gag as a model antigen demonstrated that unmodified mRNA induced significantly higher IFN-α and interleukin (IL)-7 levels, whereas m1Ψ-modified mRNA produced elevated IL-6 and tumor necrosis factor (TNF) release [1] [18] [6]. These differential cytokine profiles persisted through multiple immunizations, with unmodified mRNA showing a tolerizing effect upon repetitive application [1].

Despite these divergent innate immune signatures, both platforms ultimately generated comparable levels and kinetics of antigen-specific antibodies and T-cell responses in NHPs [18] [6]. This dissociation between innate immune activation and adaptive immunogenicity underscores the complexity of predicting vaccine efficacy based solely on early innate immune markers.

Table 1: Direct Comparison of Unmodified vs. m1Ψ-Modified mRNA Vaccine Performance

Parameter	Unmodified mRNA	m1Ψ-Modified mRNA	Experimental Context
Innate Immune Activation	High IFN-α and IL-7	Elevated IL-6 and TNF	NHP study, 160μg unmodified vs. 400-800μg modified [1] [18]
TLR7/TLR8 Activation	Strong activation	Significantly reduced	In vitro receptor activation assays [1] [31]
Protein Expression	Variable, context-dependent	Generally enhanced	Primary human myoblasts and dendritic cells [32]
Therapeutic Context	Cancer vaccines (CVGBM)	Prophylactic vaccines (COVID-19)	Clinical applications [1]
Clinical Efficacy	47% (CureVac CVnCoV)	>90% (Moderna, BioNTech)	SARS-CoV-2 vaccine efficacy [1]

mRNA Modification Systems

N1-Methylpseudouridine (m1Ψ) Modification

Mechanisms and Functional Properties

m1Ψ demonstrates dual functionality in mRNA therapeutics: it simultaneously attenuates innate immune recognition and enhances protein translation. The immunomodulatory effect stems from both direct interference with TLR7/8 activation and reduced production of immunogenic double-stranded RNA byproducts during in vitro transcription [1]. The enhancement of translational capacity is believed to result from both the alleviation of immune-mediated translational restriction and direct effects on the translational machinery, though the precise mechanisms remain under investigation [1].

The performance of m1Ψ-modified mRNA is significantly influenced by delivery vehicle composition. Studies demonstrate a synergistic effect between nucleoside modification and ionizable lipid composition in lipid nanoparticles (LNPs) [32]. For instance, m1Ψ modification enhanced protein expression in primary human myoblasts and dendritic cells when delivered with cKK-E10 or OF-02 LNPs, but this advantage was cell-type-dependent and less consistent with SM-102 LNPs [32]. This highlights the critical importance of considering both mRNA chemistry and delivery system as integrated components.

Experimental Evidence

Global translational analyses reveal that transfection with both unmodified and m1Ψ-modified mRNA causes translational repression, though m1Ψ-modified mRNA consistently shows ~40-46% higher global translation levels compared to unmodified mRNA across multiple LNP formulations [32]. This preservation of cellular translation capacity represents a significant advantage for therapeutic applications requiring sustained protein production.

Transcriptomic profiling further differentiates these platforms: unmodified mRNA produces stronger early antiviral signatures, while m1Ψ-modified mRNA exhibits distinct kinetics in innate immune activation that vary with LNP composition [32]. These findings underscore that mRNA modification and delivery systems jointly determine the translational efficiency and immunogenicity profile.

m5C RNA Methylation System

Regulatory Machinery

The m5C methylation system operates through a coordinated network of writers, erasers, and readers that dynamically regulate RNA function:

• Writers (Methyltransferases): The NSUN family (NSUN1-7) and DNMT2/TRDMT1 catalyze m5C formation using S-adenosyl-L-methionine (SAM) as methyl donor [33] [34]. These enzymes target diverse RNA species including mRNA, tRNA, rRNA, and mitochondrial RNA, with NSUN2 being the most extensively characterized for its roles in epitranscriptomic regulation.
• Erasers (Demethylases): The TET enzyme family (TET1-3) catalyzes the oxidation of m5C to 5hmC, 5fC, and 5caC, enabling reversible methylation [33].
• Readers (Recognition Proteins): ALYREF facilitates nuclear export of m5C-modified mRNA, while YBX1 and SRSF2 recognize m5C sites to regulate mRNA stability, splicing, and translation [33] [34].

Functional Roles and Experimental Applications

m5C modifications regulate multiple aspects of RNA metabolism, including nuclear export, transcript stability, and translation efficiency [33] [34]. In cancer biology, dysregulated m5C patterning contributes to oncogenesis through various mechanisms. For example, in gallbladder cancer, NSUN2 silencing inhibits cancer cell proliferation and tumor formation [33], while in liver cancer, m5C-modified lncRNA H19 recruits G3BP1 to promote cancer progression [33].

The experimental toolkit for studying m5C includes:

• Methylated RNA immunoprecipitation sequencing for genome-wide mapping
• Bisulfite sequencing for single-base resolution
• Liquid chromatography-mass spectrometry for quantitative analysis
• RNA immunoprecipitation quantitative PCR for target validation

m6A RNA Methylation System

Regulatory Components and Functions

m6A represents the most abundant internal mRNA modification in eukaryotes, with its deposition, recognition, and removal mediated by a sophisticated regulatory network:

• Writers: The core methyltransferase complex consists of METTL3, METTL14, and WTAP, with additional regulators including VIRMA, RBM15, and METTL16 fine-tuning specificity and activity [35].
• Erasers: FTO and ALKBH5 catalyze m6A removal through oxidative demethylation, enabling dynamic regulation [35].
• Readers: YTHDF1-3, YTHDC1-2, hnRNPs, and IGF2BP1-3 recognize m6A marks to direct downstream consequences including altered splicing, translation, stability, and subcellular localization [35].

m6A predominantly localizes to stop codons, 3' untranslated regions, and long internal exons, with consensus recognition sequence RRACH (R = G/A; H = A/C/U) [35].

Immunological Significance and Experimental Targeting

m6A methylation serves as a pivotal regulator of antitumor immunity, influencing immune cell differentiation, activation, and effector functions within the tumor microenvironment [35]. In therapeutic contexts, targeting m6A modifiers presents innovative strategies for enhancing cancer immunotherapy:

• Small-molecule inhibitors of dysregulated m6A regulatory factors
• m6A modifier engineering in combination with intracellular checkpoint genes like CISH
• Dual therapeutic approaches combining m6A modulation with anti-PD1 antibodies

Table 2: Comparative Overview of RNA Modification Systems

Modification	Key Regulatory Proteins	Primary Functions	Therapeutic Context	Experimental Evidence
m1Ψ	N/A (Synthetic incorporation)	Immune evasion, Enhanced translation	Prophylactic vaccines, Protein replacement	>90% clinical efficacy in COVID-19 vaccines [1]
m5C	Writers: NSUN1-7, DNMT2; Erasers: TET1-3; Readers: ALYREF, YBX1	Nuclear export, RNA stability, Translation control	Cancer (e.g., gallbladder, liver), Neurological disorders	NSUN2 silencing inhibits gallbladder cancer proliferation [33]
m6A	Writers: METTL3/14, WTAP; Erasers: FTO, ALKBH5; Readers: YTHDF, IGF2BP	mRNA splicing, decay, translation, immune cell function	Cancer immunotherapy, Immune modulation	YTHDF1 promotes mRNA translation via eIF3 recruitment [35]

mRNA Sequence Optimization Strategies

Evolution of Codon Optimization Approaches

Traditional codon optimization strategies relied on rule-based approaches such as Codon Adaptation Index (CAI) maximization and GC content adjustment to mimic highly expressed endogenous genes [36]. However, these methods often failed to correlate with experimental protein expression levels due to oversimplification of the complex factors governing mRNA translation and stability.

Recent advances have introduced deep learning frameworks that directly learn from large-scale experimental data, enabling more sophisticated and predictive optimization. RiboDecode represents one such approach that integrates translation prediction with exploration of vast sequence spaces beyond heuristic constraints [36].

RiboDecode: A Deep Learning Framework

RiboDecode incorporates three key components:

• Translation prediction model: Trained on 320 paired ribosome profiling and RNA sequencing datasets from 24 human tissues and cell lines
• Minimum free energy (MFE) prediction model: Uses deep neural networks to predict mRNA secondary structure stability
• Codon optimizer: Employs gradient ascent optimization to generate sequences with enhanced properties [36]

This framework demonstrated robust predictive accuracy with R² values of 0.81-0.89 across cross-validation datasets representing unseen genes and cellular environments [36]. Ablation analysis revealed that mRNA abundances constituted the most important input for translation prediction, highlighting the critical role of cellular context in optimization efficacy.

Experimental Validation and Therapeutic Efficacy

In vitro experiments demonstrated that RiboDecode-optimized sequences produced substantial improvements in protein expression, significantly outperforming previous methods including LinearDesign [36]. The platform maintained robust performance across different mRNA formats, including unmodified, m1Ψ-modified, and circular mRNAs—an essential feature for therapeutic applications requiring format flexibility.

In vivo validation in mouse models confirmed the therapeutic superiority of optimized sequences:

• Influenza hemagglutinin mRNAs induced approximately ten times stronger neutralizing antibody responses compared to unoptimized sequences
• Nerve growth factor mRNAs achieved equivalent neuroprotection at one-fifth the dose in an optic nerve crush model [36]

These results demonstrate that deep learning-guided codon optimization can significantly enhance both the immunogenicity and therapeutic potency of mRNA pharmaceuticals while potentially reducing dosage requirements and associated side effects.

Experimental Protocols and Research Toolkit

Key Methodologies for Comparative Evaluation

Innate Immune Profiling

Comprehensive assessment of mRNA immunogenicity requires multi-parameter approaches:

• Plasmacytoid dendritic cell and monocyte quantification by flow cytometry at 24 hours post-vaccination
• Cytokine profiling for IFN-α, IL-7, IL-6, and TNF via ELISA or multiplex assays
• Transcriptomic analysis through RNA sequencing to identify differentially expressed genes in pathways related to type I interferon signaling, antigen presentation, and innate immune activation [18] [6]

These analyses should be conducted at multiple timepoints (e.g., 1, 4, and 24 hours post-transfection) to capture kinetic differences in immune activation.

Translation Efficiency Assessment

• Puromycin incorporation assays to measure global translational activity after mRNA transfection
• Immunofluorescence imaging and flow cytometry for target protein quantification in relevant cell types
• Ribosome profiling sequencing to obtain nucleotide-resolution maps of translating ribosomes
• Dual-luciferase reporter systems for high-throughput screening of optimized sequences

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagents for mRNA Modification Studies

Reagent/Category	Specific Examples	Function/Application	Experimental Context
mRNA Modifications	m1Ψ, Ψ, m5C, m6A	Modulate immunogenicity and translation	In vitro transcription [1] [33]
LNP Formulations	OF-02, cKK-E10, SM-102	mRNA delivery and adjuvant effects	In vitro and in vivo delivery [32]
Immune Assays	IFN-α/β ELISA, Multiplex cytokine panels	Quantify innate immune activation	NHP and murine studies [1] [18]
Translation Assays	Puromycin incorporation, Ribo-seq	Measure protein synthesis and ribosome occupancy	Global translation assessment [32]
Sequencing Methods	Ribo-seq, RNA-seq, MeRIP-seq	Profile translatome, transcriptome, epitranscriptome	Molecular mechanism studies [36] [35]
Prediction Tools	RiboDecode, LinearDesign	mRNA sequence optimization	Computational design [36]

The expanding chemical toolbox for mRNA engineering provides researchers with sophisticated means to tailor therapeutic properties for specific applications. The comparative data presented in this guide demonstrates that modification strategies involve significant trade-offs between immunogenicity, translational efficiency, and therapeutic context.

m1Ψ modification remains the gold standard for prophylactic vaccines where minimized reactogenicity and enhanced protein expression are paramount. For cancer immunotherapy, unsilenced innate immune activation through unmodified mRNA may provide adjuvant effects beneficial in cold tumor microenvironments. The m5C and m6A methylation systems offer complex regulatory networks for fine-tuning gene expression, with growing implications for cancer biology and immunology. Finally, deep learning-guided codon optimization represents a paradigm shift from heuristic to data-driven sequence design, enabling substantial improvements in protein expression and therapeutic efficacy across multiple mRNA formats.

As the field advances, the integration of multiple modification strategies with optimized delivery systems and sequence designs will likely yield next-generation mRNA therapeutics with enhanced potency, specificity, and safety profiles tailored to diverse clinical applications.

The rapid development of messenger RNA (mRNA) vaccines during the COVID-19 pandemic demonstrated the transformative potential of RNA-based therapeutics. However, conventional linear mRNA platforms face inherent challenges related to the transient nature of gene expression and the balancing of immunogenicity. Within this context, two innovative RNA structures have emerged as promising solutions for achieving sustained protein production: self-amplifying RNA (saRNA) and circular RNA (circRNA). Both platforms extend the duration of antigen expression, yet they achieve this through fundamentally distinct biological mechanisms, with important implications for their immunogenicity profiles, dosing requirements, and therapeutic applications. Framed within the broader thesis of immunogenicity research for modified versus unmodified mRNA, this guide provides an objective comparison of these platforms, supported by experimental data directly relevant to researchers, scientists, and drug development professionals.

Fundamental Mechanisms and Structural Biology

Self-Amplifying RNA (saRNA) Mechanism

saRNA derives its functionality from the replication machinery of positive-strand RNA viruses, such as alphaviruses. The saRNA construct contains genes encoding viral non-structural proteins (nsP1-4) that form an RNA replicase complex, in addition to the gene of interest (transgene) which is typically subgenomic and under the control of a subgenomic promoter [37] [25]. Upon delivery into the cytoplasm, the saRNA is initially translated to produce the replicase complex. This complex then recognizes specific secondary structures on the saRNA, synthesizes a complementary negative-strand RNA, and uses this negative strand as a template to produce both new positive-strand genomic RNAs and subgenomic mRNAs encoding the transgene [37]. This intracellular amplification enables a single saRNA molecule to generate numerous copies of both itself and the transgene mRNA, resulting in prolonged and elevated protein expression at significantly lower doses compared to conventional mRNA [38] [39].

Circular RNA (circRNA) Mechanism

circRNAs are covalently closed, single-stranded RNA molecules produced through a back-splicing process where the 3' terminus of an upstream exon ligates to the 5' terminus of a downstream exon, forming a stable closed-loop structure [40] [41]. This structure lacks the 5' caps and 3' poly(A) tails characteristic of linear mRNAs. The absence of free ends confers exceptional resistance to exonucleases, dramatically increasing the molecule's intracellular half-life and enabling sustained protein production from a single transcript [40] [42]. Translation of circRNAs occurs through internal ribosomal entry site (IRES)-mediated initiation, bypassing the requirement for a 5' cap [24] [25]. The inherent stability of the closed-loop structure, combined with its reduced activation of innate immune sensors due to the absence of dsRNA byproducts, positions circRNA as a powerful platform for prolonged therapeutic protein expression [40] [24].

Quantitative Comparison of Platform Performance

The following tables summarize key performance characteristics of saRNA and circRNA platforms based on recent preclinical and clinical studies, with a focus on expression kinetics, immunogenicity, and stability parameters.

Table 1: Head-to-Head Comparison of saRNA versus circRNA Vaccine Performance Against SARS-CoV-2 RBD Antigen [24]

Performance Parameter	saRNA Vaccine	circRNA Vaccine	Experimental Context
Anti-RBD IgG Titer	Comparable high titer	Comparable high titer	Mouse model, SARS-CoV-2 RBD antigen
Virus-Neutralizing Antibody Titer	Comparable neutralization	Comparable neutralization	Microneutralization assay
Memory T Cell Response	Standard response	Higher response	IFN-γ ELISpot, T cell proliferation
Stability at 4°C	Less stable	Stable for 4 weeks	In vitro stability testing
Thermal Stability	Requires cold chain	Reduced cold-chain dependency	Logistical characteristic

Table 2: In Vivo Expression Kinetics and Immunogenicity Profiles [40] [24] [37]

Characteristic	Self-Amplifying RNA (saRNA)	Circular RNA (circRNA)
Mechanism for Sustained Expression	Intracellular RNA amplification	Nuclease-resistant structure
Expression Onset	Rapid, high peak	Gradual onset
Expression Duration	Up to 60 days (preclinical)	Significantly extended (preclinical)
Typical Relative Dose	0.1-5 µg (clinical: 5 µg for ARCT-154)	Under investigation
Innate Immune Sensing	High (dsRNA intermediates, TLR7/8, RLRs)	Low (reduced immunogenicity)
Key Immunogenicity Concern	Reactogenicity, cytopathic effects	Minimal innate immune activation
Nucleoside Modification	Possible (m5C, 5OHmC enhance performance)	Not required for stability

Table 3: Summary of Clinical-Stage saRNA Vaccine Candidates (as of 2025) [39]

Vaccine Candidate	Developer	Antigen Target	Dose	Clinical Status & Key Findings
ARCT-154	Arcturus/CSL	SARS-CoV-2 full-length Spike	5 µg	Approved in Japan (2023); 56% efficacy against COVID-19; higher neutralizing antibodies vs. 30 µg BNT162b2
VLPCOV-01	Undisclosed	SARS-CoV-2 Spike	0.3-3.0 µg	Phase 1; robust IgG titers maintained 26 weeks; >10-fold higher potency vs. BNT162b2
VLPCOV-02	Undisclosed	SARS-CoV-2 Spike (m5C-modified)	1.0-15 μg	Phase 1; reduced reactogenicity (fever: 4% vs 30% with VLPCOV-01 at 3μg)

Experimental Protocols and Methodologies

Protocol: Direct Comparison of saRNA and circRNA Vaccines

This protocol outlines the methodology used for the head-to-head comparison of saRNA and circRNA vaccines encoding the SARS-CoV-2 receptor-binding domain (RBD) antigen, as detailed in Section 3 [24].

1. RNA Construct Engineering:

• saRNA Backbone: Engineer a Semliki Forest virus (SFV) replicon. Replace viral structural protein genes with the SARS-CoV-2 RBD sequence fused at its 5'-end to a CD5 signal sequence and at its 3'-end to the T4 fibritin foldon trimerization motif.
• circRNA Backbone: Utilize the self-splicing Anabaena group I intron system. Place the RBD sequence (similarly fused to CD5 and foldon) downstream of a Coxsackievirus B3 (CVB3) internal ribosome entry site (IRES). A T7 promoter precedes the intron sequence for in vitro transcription.

2. In Vitro Transcription and Circularization:

• Transcribe saRNA using SP6 RNA polymerase.
• Transcribe circRNA precursor using T7 RNA polymerase under optimized conditions that maximize back-splicing and circularization.
• Confirm Circularization: Treat RNA products with RNase R (a 3'→5' exonuclease that degrades linear RNA but not circRNA) and analyze by gel electrophoresis. Successful circularization is confirmed by RNase R resistance.

3. Formulation and Immunization:

• Encapsulate both saRNA and circRNA in lipid nanoparticles (LNPs) using standardized microfluidic mixing techniques.
• Animal Model: Use 6-8 week old female C57BL/6 mice (n=6-8 per group).
• Immunization Regimen: Administer two intramuscular injections of 1 µg of each vaccine candidate (saRNA-RBD, circRNA-RBD) at a 3-week interval. Include control groups receiving empty LNPs or buffer.

4. Immunogenicity and Efficacy Assessment:

• Humoral Response: Collect serum samples bi-weekly. Measure antigen-specific IgG titers and isotypes (IgG1, IgG2a/c) by ELISA. Perform virus microneutralization assays using live SARS-CoV-2.
• Cellular Response: Isolate splenocytes post-boost. Quantify antigen-specific T cells by interferon-gamma (IFN-γ) ELISpot and intracellular cytokine staining. Measure memory T cell populations by flow cytometry.
• Challenge Study: Challenge immunized mice with a mouse-adapted SARS-CoV-2 strain. Monitor body weight, survival, and viral load in lungs for 10-14 days.

5. Stability Assessment:

• Store formulated vaccines at 4°C for up to 4 weeks. Periodically sample and test integrity by gel electrophoresis and in vitro translation assays to measure functional half-life.

Protocol: Evaluating the Impact of Nucleoside Modifications on saRNA

This protocol is based on studies that systematically evaluated how modified nucleosides affect saRNA potency and immunogenicity [39].

1. Synthesis of Modified saRNA:

• Generate a library of saRNAs encoding a reporter gene (e.g., mCherry, firefly luciferase) where a single type of modified nucleoside (e.g., 5-methylcytidine, m5C; 5-hydroxymethylcytidine, 5OHmC; 5-methyluridine, m5U) completely replaces its natural counterpart during in vitro transcription. Use CleanCap AU for capping.

2. In Vitro Screening:

• Transfect a human T-cell line with LNP-formulated, modified saRNAs using a standardized transfection reagent.
• Primary Readout: Quantify reporter protein expression 24-48 hours post-transfection using flow cytometry (for mCherry) or luminometry (for luciferase).
• Immunogenicity Assessment: Transfect human peripheral blood mononuclear cells (PBMCs) from multiple donors. Harvest RNA 6 hours post-transfection and analyze expression of early interferon-response genes (e.g., IFIT1, ISG15) by RT-qPCR.

3. In Vivo Validation:

• Model: Use BALB/c mice.
• Dosing: Inject mice intramuscularly with a low dose (e.g., 2.5 µg) of LNP-formulated saRNA (modified or unmodified) encoding luciferase.
• Kinetics: Monitor bioluminescence longitudinally using an in vivo imaging system over 28 days to assess the duration and level of protein expression.
• Efficacy Challenge: Immunize mice with a very low dose (e.g., 10 ng) of modified (m5C) or unmodified saRNA encoding SARS-CoV-2 Spike. Challenge with live virus and monitor weight loss and survival.

Innate Immune Sensing and Immunogenicity Pathways

The immunogenicity profile of an RNA therapeutic is a critical determinant of its safety, efficacy, and application. saRNA and circRNA engage with the host's innate immune system in fundamentally different ways, which is a central consideration in the choice of platform.

The diagram above illustrates the distinct immunogenicity pathways. saRNA's replication cycle generates double-stranded RNA (dsRNA) intermediates, which are potent pathogen-associated molecular patterns (PAMPs). These are sensed by cytosolic receptors like RIG-I and MDA5, and the saRNA itself can activate endosomal Toll-like receptors (TLR7 and TLR8) [37]. This triggers a robust type I interferon (IFN) response and production of pro-inflammatory cytokines (e.g., IL-6, TNF). While this self-adjuvanting effect can be beneficial for vaccines, it can also lead to reactogenicity, translational inhibition, and potential cytopathic effects at high doses [37]. Incorporating modified nucleosides like m5C into saRNA has been shown to suppress this early IFN response, reducing reactogenicity and increasing potency in vivo [39].

In contrast, circRNAs are characterized by their low immunogenicity. Their covalently closed structure lacks free ends, making them inherently resistant to exonuclease recognition. Furthermore, the in vitro production of circRNA does not typically generate significant amounts of immunostimulatory dsRNA byproducts [40]. This allows circRNA to avoid detection by innate immune sensors, resulting in minimal type I IFN induction. This stealth property is advantageous for applications requiring prolonged protein expression without immune-mediated clearance of transfected cells, such as in protein replacement therapies [40] [24]. The need for nucleoside modifications to dampen immunogenicity is therefore obviated in the circRNA platform.

The Scientist's Toolkit: Essential Research Reagents

Table 4: Key Reagents for saRNA and circRNA Research and Development

Reagent / Solution	Function	Example Use Case	Technical Notes
Alphavirus Replicon Backbone	Provides nsP genes for RNA amplification	Engineering saRNA constructs	VEEV, SFV, and SINV backbones are common [37]
Group I Intron System (PIE)	Catalyzes RNA circularization in vitro	Generating circRNA transcripts	Anabaena pre-tRNA intron is widely used [40] [24]
Modified NTPs (m5C, 5OHmC)	Reduces innate immune activation; enhances stability	Producing low-reactogenicity saRNA	Complete substitution requires optimized NTP ratios [39]
CleanCap AU Analog	Co-transcriptional capping for IVT RNA	Producing high-quality saRNA or linear mRNA	Critical for translation initiation efficiency [39]
RNase R	Degrades linear RNA; validates circularization	Confirming successful circRNA production	Resistance confirms closed-loop structure [24]
Lipid Nanoparticles (LNPs)	In vivo RNA delivery and cellular uptake	Formulating vaccines/therapeutics for IM injection	Composition affects potency and reactogenicity [37]
CVB3 IRES	Drives cap-independent translation initiation	Enabling protein expression from circRNA	Inserted upstream of the transgene ORF [24]

Overcoming Hurdles: Mitigating Reactogenicity, Dosing Challenges, and Unintended Effects

The rapid deployment of mRNA vaccines during the COVID-19 pandemic highlighted their transformative potential while simultaneously drawing attention to the phenomenon of innate immune reactogenicity. This inflammatory response, characterized by local and systemic symptoms such as pain, fever, and fatigue, represents a physical manifestation of the body's early immune activation following vaccination. For researchers and drug development professionals, understanding the precise cytokine profiles and underlying mechanisms of this reactogenicity is crucial for designing next-generation mRNA platforms that balance immunogenicity with favorable tolerability profiles. This guide objectively compares the reactogenicity of different mRNA vaccine constructs by examining experimental data on innate immune activation, with particular focus on the distinct responses elicited by modified versus unmodified mRNA platforms.

Innate Immune Mechanisms of mRNA Vaccine Reactogenicity

Vaccine reactogenicity represents the physical manifestation of the inflammatory response to vaccination, comprising a subset of reactions that occur soon after immunization [43]. These responses primarily arise from innate inflammatory pathways that are activated following vaccine administration. When mRNA vaccines enter the body, vaccine components are recognized as potential pathogens by pattern-recognition receptors (PRRs) expressed on immune cells and resident stromal cells [43]. This recognition triggers a complex signaling cascade that results in the synthesis and release of pyrogenic cytokines including interleukin (IL)-1, IL-6, tumor necrosis factor-alpha (TNF-α), and prostaglandin-E2 into the bloodstream [43].

The inflammatory events following vaccination are crucial for triggering strong antigen-specific acquired immune responses necessary for protection, yet these same events also lead to the development of clinical signs and symptoms [43]. Injection-site symptoms like pain, redness, and swelling occur through a coordinated process involving vasodilators and chemokine gradients that promote immune cell recruitment. Blood-borne neutrophils, monocytes, and lymphocytes adhere to vessel walls and accumulate at the injection site, where they may contribute to peripheral nociceptive sensitization by releasing soluble factors including cytokines, prostaglandins, or ATP, directly interacting with sensory neurons to cause pain [43]. Systemic symptoms emerge when inflammatory mediators enter the circulation and affect other body systems, leading to fever, fatigue, headache, and myalgia.

Table 1: Key Cytokines and Immune Mediators in mRNA Vaccine Reactogenicity

Mediator	Primary Source	Biological Function	Role in Reactogenicity
IL-6	Monocytes, macrophages	Pro-inflammatory cytokine; induces acute phase proteins	Fever, fatigue, systemic symptoms
TNF-α	Macrophages, T cells	Pro-inflammatory cytokine; regulates immune cells	Inflammation amplification, pain sensitization
IFN-γ	T cells, NK cells	Antiviral response; macrophage activation	Correlates with systemic reactogenicity
CXCL10	Multiple cell types	Chemokine for immune cell recruitment	Associated with post-vaccination symptoms
CRP	Liver (IL-6 induced)	Acute phase inflammatory protein	Systemic inflammation marker
MCP-2	Monocytes, fibroblasts	Chemotaxis for monocytes and eosinophils	Positively associated with antibody response

Comparative Innate Immune Profiles of mRNA Vaccine Platforms

Modified versus Unmodified mRNA Platforms

Fundamental differences in innate immune activation exist between nucleoside-modified and unmodified mRNA vaccine constructs. A 2025 comparative study in rhesus macaques directly evaluated these platforms by immunizing animals with either nucleoside-modified mRNA or sequence-codon-optimized unmodified mRNA encoding an identical model antigen (HIV-1 gag) [18]. Both platforms elicited clear but transient innate immune activation 24 hours post-vaccination, characterized by increased plasmacytoid dendritic cells, intermediate CD14+ CD16+ monocytes, and neutrophils, along with secretion of type I interferon-related and inflammatory cytokines [18]. However, distinct cytokine profiles emerged between the platforms: unmodified mRNA induced higher interleukin-7 (IL-7) and IFN-α levels, whereas modified mRNA induced higher IL-6 levels [18]. Transcriptomic profiling revealed significant upregulation of genes related to type I interferon signaling, antigen presentation, and innate immune activation induced by both mRNA constructs, with high-dose modified mRNA inducing a higher number of differentially expressed genes at prime immunization [18].

Lipid Nanoparticles and Innate Immune Activation

The lipid nanoparticle (LNP) delivery system itself contributes significantly to innate immune activation. Empty LNPs without mRNA cargo can stimulate innate immune responses, though the presence of mRNA amplifies this effect [44] [45]. Research demonstrates that pre-vaccination peripheral blood mononuclear cells (PBMCs) stimulated with mRNA-LNP show distinct activation profiles compared to those stimulated with empty LNP or Toll-like receptor (TLR) agonists [44] [45]. Specifically, heightened conventional dendritic cell (cDC) and weaker plasmacytoid DC (pDC) responses to RNA stimuli correlated with the magnitude of acute IgG responses following vaccination [45]. These findings highlight the complex interplay between mRNA modification status, LNP components, and the resulting innate immune profile that collectively influence both reactogenicity and immunogenicity.

Table 2: Comparative Innate Immune Profiles of mRNA Vaccine Constructs

Parameter	Unmodified mRNA	Nucleoside-Modified mRNA	Experimental Model
IFN-α Induction	Higher levels	Lower levels	Rhesus macaques [18]
IL-6 Induction	Lower levels	Higher levels	Rhesus macaques [18]
IL-7 Induction	Higher levels	Lower levels	Rhesus macaques [18]
Differentially Expressed Genes	Moderate increase	Higher number, especially at high dose	Rhesus macaques [18]
Type I IFN Signaling	Significant upregulation	Significant upregulation	Rhesus macaques [18]
Antigen Presentation Pathways	Significant upregulation	Significant upregulation	Rhesus macaques [18]
Humoral Immunogenicity	Similar levels and kinetics	Similar levels and kinetics	Rhesus macaques [18]

Experimental Models and Methodologies for Assessing Reactogenicity

In Vitro Human PBMC Stimulation Models

To systematically evaluate innate immune correlates of reactogenicity prior to vaccination, researchers have developed sophisticated in vitro models using pre-vaccination PBMCs collected from vaccine recipients [44] [45]. The methodology involves isolating PBMCs from participants prior to vaccination, then stimulating these cells with various innate immune stimuli including empty LNP, mRNA-LNP, or specific TLR agonists [45]. Following stimulation, researchers perform multiparameter spectral flow cytometry to analyze baseline immune states, innate responsiveness to stimuli, and cytokine profiles [45]. These pre-vaccination in vitro results are then analyzed for correlations with post-vaccination symptoms and spike-specific IgG responses, creating predictive models of reactogenicity and immunogenicity [45].

This approach has revealed that baseline dendritic cell states inversely correlate with the magnitude of symptoms following BNT162b2 vaccination, while heightened conventional DC and weaker plasmacytoid DC responses to RNA stimuli correlate with acute IgG response magnitude [45]. Furthermore, IgG durability has been shown to modestly correlate with lower pDC state but higher cDC2 and monocyte baseline states, and inversely correlate with TLR3 agonist responsiveness [45]. These findings demonstrate the predictive potential of pre-vaccination immune assessment.

Chronic Inflammation Murine Models

To evaluate mRNA vaccine safety in vulnerable populations with pre-existing inflammatory conditions, researchers have developed a chronic inflammation mouse model using subcutaneously implanted LPS pumps that release bacterial lipopolysaccharide at a constant rate (0.11 μg/h) over 4 weeks [46]. This model successfully induces mild, persistent inflammation primarily observed in the heart, characterized by significantly elevated mRNA levels of inflammatory cytokines including IL-1β, IL-6, IL-18, and TNF-α, along with increased monocyte chemoattractant protein-1 (a macrophage infiltration marker) and natriuretic peptide A (a cardiovascular damage marker) [46].

When mRNA vaccines are administered to these chronically inflamed mice (on days 14 and 28 after LPS pump implantation), researchers observe exacerbated cardiac damage, with significant increases in cardiac hypertrophy markers and inflammatory cytokines compared to non-vaccinated controls [46]. Histopathological analyses reveal that mRNA vaccine immunization induces myocarditis under chronic inflammatory conditions, with significant inflammatory cell infiltration in heart tissue [46]. This model provides crucial insights into potential risks of mRNA vaccination in individuals with chronic inflammatory diseases.

Wearable Sensor Technology for Real-Time Inflammation Monitoring

Innovative digital approaches are emerging to objectively quantify inflammatory responses following vaccination. Recent research utilizes a torso-worn sensor patch (VitalPatch) that continuously collects physiological data including electrocardiogram, tri-axial accelerometry, skin temperature, and posture information [47]. Using machine learning methodologies within a similarity-based modeling framework, researchers derive an individualized digital inflammatory biomarker - the inflammatory multivariate change index (iMCI) - which creates personalized baseline models of each participant's physiological dynamics [47].

This digital biomarker demonstrates moderate to strong positive correlation with traditional serum inflammatory markers, showing Spearman correlations of 0.59 with C-reactive protein and 0.56 with interferon gamma across vaccine types and doses [47]. Importantly, the association between this objective digital measure and self-reported systemic reactogenicity is only moderate (0.48), suggesting that wearable sensors can provide complementary objective data to subjective symptom reporting [47].

Diagram 1: Dual-Nature of mRNA Vaccine-Induced Innate Immunity. The same innate immune activation mechanisms that drive protective adaptive immunity also mediate adverse reactogenicity symptoms.

Correlation Between Reactogenicity and Immunogenicity

A comprehensive review of the relationship between vaccine immunogenicity and reactogenicity reveals that the bulk of evidence suggests a positive association between these two phenomena, particularly for systemic adverse events and antibody titers [48]. The most consistent signal has been observed in studies of either antigen-naïve individuals receiving live-attenuated vaccines or antigen-experienced individuals receiving non-live vaccines, especially mRNA-based platforms [48]. However, the effect size is generally small to moderate, resulting in only a modest boost in antibody levels post-vaccination among those experiencing stronger reactogenicity [48].

Research specifically on COVID-19 mRNA vaccines demonstrates that the pre-vaccination assessment of innate immune function and resting states can be used to fit models predictive of both immunogenicity and reactogenicity to BNT162b2 vaccination [45]. Pre-vaccination dendritic cell states appear to influence reactogenicity, while the response to RNA stimuli may impact antibody responses [45]. Additionally, studies tracking inflammatory biomarkers in healthcare workers vaccinated with BNT162b2 found that higher baseline levels of T-cell surface glycoprotein CD6 and hepatocyte growth factor were associated with lower mean antibody titers at follow-up, while monocyte chemotactic protein 2 levels had a positive association with antibody levels [49].

These findings collectively suggest that while reactogenicity and immunogenicity are linked, the relationship is complex and influenced by multiple host factors and vaccine components. This underscores the importance of considering individual immune variations rather than assuming a simple direct correlation between side effects and protection.

Diagram 2: In Vitro Predictive Model Workflow. Experimental approach for predicting reactogenicity and immunogenicity from pre-vaccination immune profiling.

The Scientist's Toolkit: Essential Research Reagents and Methodologies

Table 3: Essential Research Tools for Investigating mRNA Vaccine Reactogenicity

Tool/Reagent	Application	Key Features	Representative Use
PBMC Isolation	Pre-vaccination immune cell collection	Cryopreservation with >70% viability post-thaw	Pre-vaccination immune profiling [44]
mRNA-LNP Stimuli	In vitro innate immune activation	Empty LNP and mRNA-LNP formulations	Assessing innate immune responsiveness [45]
TLR Agonists	Control innate immune stimuli	Specific pathway activation (e.g., TLR3, TLR7/8)	Comparative innate response profiling [45]
Multiparameter Spectral Flow Cytometry	Immune cell phenotyping	High-dimensional single-cell analysis	Dendritic cell and monocyte subset characterization [45]
Multiplex Cytokine Assays	Inflammatory mediator quantification	Simultaneous measurement of multiple cytokines	Serum biomarker profiling (e.g., CRP, IFN-γ, CXCL10) [49] [47]
Digital Wearable Sensors	Real-time physiological monitoring	Continuous ECG, temperature, activity tracking	Objective inflammatory biomarker derivation (iMCI) [47]
Olink Proteomics	Comprehensive biomarker analysis	Proximity Extension Assay technology	Broad-scale inflammatory protein profiling [49]

The systematic investigation of innate immune reactogenicity reveals complex relationships between mRNA vaccine platforms, host immune factors, and resulting inflammatory profiles. Modified and unmodified mRNA constructs elicit distinct cytokine signatures despite similar overall immunogenicity, with unmodified mRNA inducing higher IFN-α and IL-7, while modified mRNA produces greater IL-6 responses. Critical to advancing the field are sophisticated experimental approaches including pre-vaccination immune profiling, chronic inflammation models, and digital monitoring technologies that collectively provide insights into the mechanistic basis of reactogenicity. As the mRNA vaccine platform continues to evolve, these research tools and methodologies will enable the development of next-generation vaccines with optimized safety and efficacy profiles, particularly for vulnerable populations with pre-existing inflammatory conditions. The ongoing challenge remains balancing sufficient innate immune activation to drive robust adaptive immunity while minimizing excessive inflammation that manifests as adverse symptoms.

In the development of mRNA-based therapeutics and protein biologics, achieving precise dosing is fundamentally linked to controlling the amount, timing, and location of protein production. The relationship between the administered dose of a genetic construct and the resulting protein output is not linear but is governed by a complex amplification effect: a single dose of mRNA or DNA can template the production of many thousands of protein molecules. This amplification is both a tremendous opportunity and a significant challenge for therapeutic developers. When poorly controlled, it can lead to subtherapeutic outcomes or toxic side effects. Furthermore, this protein output is critically influenced by the inherent immunogenicity of the platform technology itself, particularly when comparing modified versus unmodified mRNA constructs. Unmodified mRNA is more readily recognized by the innate immune system, leading to higher type I interferon (IFN)-α levels, which can simultaneously inhibit translation and enhance immune activation, creating a complex feedback loop that directly impacts protein yield and dosing precision [18] [6]. This article will objectively compare the performance of leading mRNA and therapeutic protein platforms, analyze the experimental data governing their output, and provide a toolkit for researchers navigating this challenging landscape.

Comparative Analysis of mRNA and Therapeutic Protein Platforms

Table 1: Comparison of Key mRNA and Therapeutic Protein Platform Characteristics

Platform / Characteristic	Protein Output Control & Amplification	Key Immunogenicity Profile	Primary Dosing Challenges	Reported Efficacy/Output Data
Nucleoside-modified mRNA	Sustained, high-level expression; reduced innate sensing	Lower IFN-α; higher IL-6 induction [18] [6]	Fine-tuning for minimal reactogenicity; potential for high dose requirements (e.g., 400-800 μg in primates) [18]	Similar antigen-specific T-cell & antibody levels as unmodified, despite different innate activation [18]
Unmodified mRNA	Transient expression; translation can be inhibited by innate immune response	Higher IFN-α and IL-7 levels [18] [6]	Balancing immune activation with protein yield; shorter protein half-life	Effective immunity induction but with greater innate immune signature [18]
siRNA (e.g., Patisiran)	Not applicable (gene silencing)	Minimal with GalNAc/LNP delivery	Targeted delivery to hepatocytes; sustained effect enabling infrequent dosing [50]	Improved neuropathy scores in hATTR amyloidosis (Phase III) [50]
Therapeutic Proteins (e.g., Monoclonal Antibodies)	Direct administration; no cellular amplification	Anti-drug antibodies; potential anaphylaxis	Stability during storage and delivery; aggregation leading to immunogenicity and efficacy loss [51] [52]	Market value ~$800B; >170 recombinant proteins in clinical use [52]

Table 2: Impact of Optimization Strategies on mRNA Protein Output and Dosing

Optimization Strategy	Mechanism of Action on Protein Output	Effect on Dosing Precision & Amplification	Experimental Evidence
Codon Optimization (RiboDecode)	Enhances translation efficiency and mRNA stability via AI-driven sequence design [36]	Enables dose reduction (e.g., 5-fold lower dose for equivalent effect); increases neutralizing antibodies 10-fold [36]	In vivo mouse study: Optimized NGF mRNA achieved equivalent neuroprotection at 1/5th the dose [36]
Nucleoside Modification (e.g., pseudouridine)	Reduces innate immune recognition via TLR suppression; increases translational fidelity [50]	Allows for higher protein yield per μg of mRNA; reduces inhibitory IFN responses	Critical for clinical success of COVID-19 vaccines; improves stability and reduces immune activation [50]
Lipid Nanoparticles (LNPs)	Protects mRNA integrity; facilitates cellular uptake and endosomal escape [53] [50]	Enables systemic delivery and redosing (unlike viral vectors); liver-tropic	First personalized in vivo CRISPR therapy safely delivered via LNP with multiple doses [53]
mRNA Translation Boosters	Small molecules that block pattern recognition receptors or aid endosomal escape [54]	Increases protein yield per dose; modulates kinetics of expression	Co-delivered adjuvants improve translational fidelity and protein expression in COVID-19 vaccines [54]

Detailed Experimental Protocols and Methodologies

Protocol 1: Comparative Immunogenicity and Protein Output of Modified vs. Unmodified mRNA

Objective: To quantitatively compare the innate immune activation, protein expression kinetics, and subsequent adaptive immune responses induced by nucleoside-modified mRNA versus unmodified, sequence-codon-optimized mRNA encoding the same antigen.

Key Materials & Reagents:

• mRNA Constructs: Nucleoside-modified mRNA and unmodified, codon-optimized mRNA, both encoding HIV-1 gag as a model antigen [18].
• Animal Model: Rhesus macaques (non-human primates).
• Delivery Vehicle: Lipid nanoparticles (LNPs) for in vivo delivery.
• Assay Kits: ELISA for cytokines (IFN-α, IL-6, IL-7) and antigen-specific antibodies; flow cytometry for immune cell phenotyping (plasmacytoid dendritic cells, CD14+ CD16+ monocytes); transcriptomic profiling (RNA-seq) [18] [6].

Methodology Details:

• Immunization Schedule: Administer five immunizations at 2-week intervals, with a final boost 20 weeks later. Utilize different dose levels (e.g., unmodified: 160 μg; modified: 400 μg and 800 μg) to assess dose-response [18].
• Innate Immune Monitoring: At 24 hours post-vaccination, collect blood samples to quantify changes in innate immune cell populations and serum cytokine levels via flow cytometry and ELISA [18] [6].
• Transcriptomic Analysis: Perform RNA sequencing on peripheral blood mononuclear cells (PBMCs) to assess genome-wide differential gene expression, focusing on pathways like type I IFN signaling and antigen presentation [18].
• Protein Output & Efficacy Assessment: Monitor and titrate gag-specific antibody responses (humoral immunity) and T-cell responses (cellular immunity) over time to correlate innate immune profiles with the resulting adaptive immune output [18].

Protocol 2: In Vivo Validation of AI-Optimized mRNA for Dose Efficiency

Objective: To evaluate the therapeutic efficacy and dose-sparing potential of mRNA sequences optimized by the RiboDecode deep learning framework in disease models.

Key Materials & Reagents:

• Optimized mRNAs: RiboDecode-optimized mRNA sequences for target antigens (e.g., Influenza Hemagglutinin (HA) and Nerve Growth Factor (NGF)) [36].
• Control: Unoptimized mRNA sequences encoding the same proteins.
• Animal Models:
  • Wild-type mice for influenza virus challenge model.
  • Mouse model of optic nerve crush for neuroprotection study.
• Delivery Vehicle: Lipid nanoparticles (LNPs) for systemic delivery.

Methodology Details:

• Vaccination & Challenge (Influenza Model):
  • Immunize mice with optimized or unoptimized HA mRNA.
  • Measure neutralizing antibody titers against influenza virus post-vaccination.
  • Challenge immunized mice with live influenza virus and monitor survival and disease severity [36].
• Neuroprotection Study (Optic Nerve Model):
  • Administer a single, low dose (e.g., 1/5th of standard dose) of optimized NGF mRNA or a full dose of unoptimized NGF mRNA via LNP after inducing optic nerve injury.
  • Quantify the survival and health of retinal ganglion cells over time using histological analysis to assess equivalent neuroprotective efficacy [36].
• Protein Expression Analysis: In parallel groups, use in vivo imaging or serum protein analysis to quantify and compare the magnitude and duration of target protein expression from optimized vs. unoptimized mRNAs.

Visualizing Signaling Pathways and Experimental Workflows

Innate Immune Signaling in Modified vs. Unmodified mRNA

The following diagram illustrates the distinct innate immune signaling pathways activated by unmodified and nucleoside-modified mRNA, which directly impact protein translation and output.

RiboDecode AI-Driven mRNA Optimization Workflow

The following diagram outlines the sequential data-driven workflow of the RiboDecode deep learning framework for optimizing mRNA codon sequences to enhance protein output.

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Research Reagent Solutions for mRNA and Protein Output Studies

Reagent / Solution	Primary Function	Application in Dosing & Output Studies
Ribo-seq & RNA-seq Datasets	Provides genome-wide snapshot of translating mRNAs and transcript abundance [36].	Training data for AI models (e.g., RiboDecode) to predict and optimize translation efficiency.
Lipid Nanoparticles (LNPs)	In vivo delivery vehicle protecting mRNA and facilitating cellular uptake [53] [50].	Critical for systemic administration and enabling redosing in vivo; organ tropism (e.g., liver) affects protein output location.
Nucleoside-Modified mRNA	mRNA incorporating modified bases (e.g., pseudouridine) to evade innate immune sensing [50].	Key reagent for comparing immunogenicity and protein yield against unmodified mRNA controls.
Pattern Recognition Receptor (PRR) Assays	In vitro systems (e.g., TLR reporter cells) to quantify innate immune activation by mRNA [54].	Screening tool for identifying mRNA constructs with lower immunogenicity and higher translational capacity.
Codon Optimization Algorithms (e.g., RiboDecode)	AI-driven design of mRNA sequences for enhanced translation and stability [36].	Core tool for engineering sequences that maximize protein output per dose, enabling dose-sparing regimens.

The pursuit of precise dosing in protein-based therapeutics hinges on our ability to understand and control the amplification effect from genetic template to functional protein. The comparative data reveals that no single platform is superior in all aspects; rather, each offers distinct advantages. Nucleoside-modified mRNA provides a path to higher protein yield with lower reactogenicity, which is vital for non-vaccine applications like protein replacement therapy. In contrast, the inherent immunogenicity of unmodified mRNA can be harnessed as a built-in adjuvant in vaccine contexts, without necessarily compromising the ultimate adaptive immune response [18] [6]. The emergence of AI-driven codon optimization tools like RiboDecode represents a paradigm shift, moving beyond simple rule-based sequence design to a holistic, data-driven approach that can significantly amplify protein output and achieve dramatic dose reductions, as evidenced by the 5-fold dose sparing in a neuroprotection model [36]. The future of dosing precision lies in the intelligent integration of these platforms—selecting the right mRNA construct, delivery vehicle, and potential boosters based on the therapeutic goal, whether it is to maximize a vaccine-induced immune response or to provide steady, regulated protein replacement with minimal off-target expression.

The development of therapeutic mRNA platforms necessitates a delicate balance between minimizing unwanted innate immune activation and ensuring accurate, robust protein expression. This comparison guide examines two significant challenges in the field: ribosomal frameshifting associated with the widely adopted N1-methylpseudouridine (m1Ψ) modification, and the development of tolerogenicity observed with repeated administration of unmodified mRNA. The m1Ψ modification was a critical advancement, reducing innate immune recognition and enhancing translation, which contributed significantly to the success of COVID-19 mRNA vaccines [30] [55]. However, emerging data reveal that this modification can impair translational fidelity, leading to off-target protein products [56] [57]. In parallel, while unmodified mRNA is inherently more immunogenic, studies show that this strong activation can become tolerogenic with repeated dosing, potentially limiting its therapeutic window [1] [6]. This guide objectively compares the experimental data underlying these phenomena, providing researchers with a detailed analysis of their mechanisms and implications for drug development.

Ribosomal Frameshifting with m1Ψ-Modified mRNA

Experimental Evidence and Quantification

Recent investigations have demonstrated that incorporation of m1Ψ into IVT mRNA can cause ribosomal +1 frameshifting during translation. A seminal 2024 study systematically evaluated this phenomenon using a dual luciferase frameshift reporter construct (Fluc+1FS) where the carboxy-terminal Fluc segment was placed in the +1 reading frame [57]. Translation of unmodified Fluc+1FS mRNA produced only the expected, catalytically inactive truncated protein. In contrast, m1Ψ-modified Fluc+1FS mRNA produced significant +1 frameshifted products, observed both in vitro and in HeLa cells [57].

Table 1: Quantitative Analysis of +1 Ribosomal Frameshifting with m1Ψ-mRNA

mRNA Type	Modification	Frameshifting Efficiency (% of in-frame protein)	Experimental System	Key Findings
Fluc+1FS Reporter	Unmodified	Minimal	In vitro translation	Baseline frameshifting
Fluc+1FS Reporter	m1Ψ	~8%	In vitro translation	Significant increase in +1 frameshifting
Fluc+1FS Reporter	m1Ψ + 5-methylC	~8%	In vitro translation	Frameshifting maintained with combined modifications
Fluc+1FS Reporter	5-methoxyU	Not significant	In vitro translation	No increased frameshifting
BNT162b2 Vaccine	m1Ψ	Detected (T cell responses)	Human recipients	Off-target cellular immunity to frameshifted products

The immunogenic consequences of this frameshifting were confirmed in studies of the BNT162b2 COVID-19 vaccine. Researchers detected T cell responses against +1 frameshifted spike peptides in both vaccinated mice and humans, which were not observed in recipients of the ChAdOx1 nCoV-19 adenoviral vector vaccine [57]. This indicates that frameshifted products are translated, processed, and presented to the immune system in vivo.

Proposed Mechanism and Contributing Factors

The underlying mechanism for m1Ψ-induced frameshifting appears to be ribosome stalling at specific "slippery" sequences. The current model suggests that the modification alters ribosome kinetics during decoding, increasing the probability of tRNA misalignment on mRNA sequences prone to slippage [57]. This stalling provides a window for tRNA to realign into an alternative reading frame before translation continues.

Diagram: Mechanism of m1Ψ-Induced Ribosomal Frameshifting

Not all sequences are equally susceptible. The frameshifting occurs predominantly at "slippery" heptamer sequences (XXXYYYZ, spaces indicate zero-frame codons) where the ribosome pauses, allowing re-pairing of tRNAs to -1 frame codons [58]. Synonymous codon editing to target these slippery sequences has been shown to be an effective strategy to reduce frameshifted products [57].

Tolerogenicity with Repeated Unmodified mRNA Dosing

Innate Immune Tolerance from High-Dose Regimens

In contrast to the frameshifting issue with modified mRNA, unmodified mRNA faces challenges related to its inherent immunogenicity. A 2025 study by Engstrand et al. directly compared responses to high-dose, repetitive immunization with unmodified versus m1Ψ-modified mRNA in non-human primates [1] [6]. The researchers immunized rhesus macaques five times at two-week intervals with a final boost 20 weeks later, using a Gag antigen model.

Table 2: Comparative Innate Immune Responses to Repeated mRNA Dosing

Immune Parameter	Unmodified mRNA (160 μg)	m1Ψ-Modified mRNA (400/800 μg)	Biological Significance
IFNα Induction	Higher	Lower	Stronger innate immune activation via TLR7/8 and RLRs
IL-7 Induction	Higher	Lower	T cell supportive, benefits cytotoxic response
IL-6/TNF Induction	Lower	Higher	Driven by higher LNP dose; supports Tfh and antibody response
Transcriptomic Changes	Reduced DEGs after 5th dose	Sustained or increased DEGs (high-dose)	Indicates tolerance development with unmodified mRNA
Adaptive Immunity	Similar Gag-specific antibodies	Similar Gag-specific antibodies	Comparable final immunogenicity despite different pathways

The study revealed that while the first dose of unmodified mRNA induced robust innate immune activation, a tolerizing effect was observed upon repetitive application. After the fifth immunization, unmodified mRNA resulted in fewer differentially expressed genes (DEGs) and reduced expression of IFNα, IL-7, and IL-7 downstream targets compared to initial responses [1]. This pattern suggests the development of innate immune tolerance, a phenomenon not observed with high-dose m1Ψ-mRNA regimens [1].

Mechanisms of Tolerance and Differential Signaling

The tolerogenicity observed with repeated unmodified mRNA administration stems from its potent activation of multiple innate immune pathways. Unmodified mRNA robustly activates Toll-like receptor (TLR)7/8 in plasmacytoid dendritic cells and monocytes, as well as RIG-I-like receptors (RLRs) in various cell types [1]. These pathways collectively induce type-I interferon release. The higher IL-7 production with unmodified mRNA may originate from TLR activation in lymphoid organs or potentially the liver [1].

Diagram: Immune Signaling and Tolerance with Repeated Unmodified mRNA Dosing

In contrast, the increased IL-6 and TNF response to m1Ψ-mRNA is likely attributable to the higher LNP dose required for its delivery rather than the RNA modification itself, as LNPs can induce these cytokines independently of TLR signaling [1]. The differential propensity for tolerance induction may result from diverse TLR activity, as TLR3, 7, and 8 activation has been reported to induce innate immune tolerance, while RLR activation has not [1].

Comparative Experimental Approaches and Methodologies

Key Experimental Protocols

Frameshifting Detection Protocol (Mulroney et al., 2024) [57]:

• Construct Design: Dual luciferase reporter with C-terminal Fluc segment in +1 reading frame
• mRNA Synthesis: In vitro transcription with unmodified, m1Ψ, 5-methylC, or 5-methoxyU nucleotides
• In Vitro Translation: Rabbit reticulocyte lysate system, quantification of frameshifted products
• Cell Culture: HeLa cell transfection with modified mRNAs
• Immunogenicity Assessment: IFNγ ELISpot assays with peptides corresponding to predicted +1 frameshifted products
• Human Validation: PBMCs from BNT162b2 vaccine recipients tested against frameshifted peptides

Tolerogenicity Study Protocol (Engstrand et al., 2025) [1] [6]:

• Animal Model: Rhesus macaques (non-human primates)
• mRNA Constructs: Identical HIV-1 Gag antigen encoded in either unmodified or m1Ψ-modified mRNA
• Dosing Regimen: Five immunizations at 2-week intervals with sixth booster after 20 weeks
• Dosages: Unmodified mRNA (160 μg) vs. m1Ψ-mRNA (400 μg low-dose, 800 μg high-dose)
• Immune Monitoring: Flow cytometry, cytokine measurements (IFNα, IL-7, IL-6), transcriptomic profiling
• Timeline: Blood collection at multiple time points post-immunization for innate and adaptive responses

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Reagents for mRNA Immunogenicity and Translation Fidelity Research

Reagent/Category	Specific Examples	Research Function	Considerations
Nucleotide Modifications	N1-methylpseudouridine (m1Ψ), Pseudouridine (Ψ), 5-methylcytidine (m5C)	Reduce innate immunogenicity, enhance translation	m1Ψ increases frameshifting; purity critical for consistent results
Delivery Systems	Lipid Nanoparticles (LNPs)	Protect mRNA, enhance cellular uptake, enable in vivo delivery	LNPs themselves can contribute to cytokine responses (e.g., IL-6)
Reporter Systems	Dual luciferase frameshift constructs (e.g., Fluc+1FS)	Quantify ribosomal frameshifting efficiency	Must validate with appropriate controls
Immune Assays	IFNγ ELISpot, Cytokine Luminex, Multiplex transcriptomics	Profile innate and adaptive immune responses	Essential for detecting responses to frameshifted products
mRNA Purification	FPLC, HPLC purification systems	Remove dsRNA contaminants that activate innate immunity	Critical for reducing unintended immune activation
Animal Models	Non-human primates, Humanized mice, Inbred mouse strains	Preclinical evaluation of immunogenicity and tolerance	Species-specific immune differences must be considered

The comparative analysis of m1Ψ-modified and unmodified mRNA reveals a complex landscape where solutions to one challenge may inadvertently create another. The m1Ψ modification successfully reduces innate immunogenicity but introduces translational fidelity issues through ribosomal frameshifting, potentially leading to off-target immune responses [56] [57]. Conversely, unmodified mRNA maintains accurate translation but triggers strong innate immune activation that can evolve into tolerogenicity with repeated dosing [1] [6].

For therapeutic development, these findings highlight critical considerations. Protein replacement therapies and applications requiring precise translation may benefit from approaches that minimize frameshifting, such as slippery sequence optimization or alternative modifications [57]. For vaccine applications and cancer immunotherapy, where strong immune activation may be desirable, unmodified mRNA platforms continue to show promise, particularly in platforms like CureVac's CVGBM and BioNTech's iNest [1]. The emerging understanding of these unintended consequences enables more informed platform selection and underscores the continued need for innovation in mRNA engineering to optimize both safety and efficacy across diverse therapeutic applications.

The advent of lipid nanoparticle (LNP)-based mRNA vaccines has heralded a transformative era in vaccinology and therapeutics, demonstrated by the successful clinical deployment of COVID-19 vaccines. However, a significant challenge persists in optimizing LNP formulations to balance efficient mRNA delivery with controlled immunogenicity profiles. The immunological response to mRNA therapeutics is profoundly influenced by both the nucleotide sequence design (particularly the use of modified versus unmodified nucleosides) and the physicochemical properties of the encapsulating LNP delivery system [59] [60]. Traditional formulation development approaches rely heavily on empirical, labor-intensive screening processes that struggle to navigate the complex multivariate parameter space encompassing lipid structures, component ratios, and nucleic acid sequences [61] [62].

The integration of artificial intelligence and machine learning (AI/ML) presents a paradigm shift, enabling systematic exploration of this complex design space through in silico prediction and optimization [61]. This review comprehensively examines the synergistic interplay between LNP formulation parameters and mRNA sequence design, with particular emphasis on their collective impact on immunogenicity. By synthesizing experimental data from recent studies and comparing advanced ML-driven approaches against traditional methods, we provide a framework for rational design of next-generation mRNA-LNP therapeutics with enhanced efficacy and safety profiles.

LNP Formulation Components and Their Impact on Immunogenicity

Critical LNP Components and Functions

LNPs are sophisticated multi-component systems where each lipid constituent plays a distinct functional role in nucleic acid encapsulation, delivery, and ultimately, immunogenic response [60] [63]. The core LNP structure typically consists of four key lipid classes:

Table 1: Core Components of Lipid Nanoparticles and Their Functional Roles

Component	Key Function	Impact on Immunogenicity	Common Examples
Ionizable Lipid	mRNA encapsulation, endosomal escape	Activates innate immune via PRRs; chemical structure influences cytokine production	DLin-MC3-DMA, ALC-0315, SM-102, novel AA lipids
Phospholipid	Structural integrity of LNP bilayer	Can contribute to complement activation; surface properties affect APC uptake	DSPC, DOPE, DSPE
Cholesterol	Membrane stability and fluidity	Modulates lipid packing and LNP rigidity, affecting immune recognition	Cholesterol derivatives
PEG-lipid	Particle stability, reduces opsonization	Can influence complement activation and antibody responses; impacts pharmacokinetics	DMG-PEG2000, DSG-PEG2000

The ionizable lipid constitutes the most critical component, with its chemical structure dictating both delivery efficiency and immunogenic potential. Ionizable lipids containing tertiary amines facilitate mRNA complexation at acidic pH during formulation while remaining neutral at physiological pH, reducing nonspecific interactions and toxicity [60]. Recent research has identified that lipid nanoparticles activate the innate immune system through pattern recognition receptors (PRRs), including Toll-like receptors (TLRs) and retinoic acid-inducible gene (RIG)-I-like receptors (RLRs) [59]. This recognition triggers inflammatory pathways and cytokine production that shape subsequent adaptive immune responses.

LNP Physicochemical Properties and Immune Recognition

Beyond lipid composition, the physicochemical characteristics of LNPs significantly influence their interactions with the immune system [63]. Particle size, surface charge, and internal structure collectively determine biodistribution, cellular uptake, and intracellular processing.

• Size and Surface Charge: LNPs typically range from 20-200 nm, with smaller particles (<100 nm) demonstrating enhanced tissue penetration and drainage to lymph nodes where they directly interact with immune cells. Surface charge, characterized by zeta potential, affects opsonization and phagocytosis; slightly positive charges may enhance dendritic cell uptake while highly positive surfaces increase cytotoxicity and nonspecific interactions with serum proteins [63].

• Internal Structure: Advanced analytical techniques reveal that LNP internal architecture evolves with environmental pH. At pH 4.0, empty LNPs exhibit lamellar organization, while transition to physiological pH prompts formation of electron-dense amorphous cores. siRNA-loaded LNPs demonstrate concentric bilayer rings at specific nitrogen-to-phosphorus (N/P) ratios, with higher ratios producing amorphous cores surrounded by siRNA-lipid bilayers [63]. These structural arrangements impact mRNA release kinetics and accessibility to immune sensors.

• Protein Corona Formation: Upon administration, LNPs rapidly adsorb serum proteins forming a "protein corona" that dictates subsequent immune interactions and cellular targeting. Corona composition depends on LNP surface properties, with specific protein patterns potentially triggering complement activation or recognition by scavenger receptors on antigen-presenting cells [63].

Machine Learning Approaches for LNP Optimization

ML Workflows for Ionizable Lipid Design

The development of high-throughput synthesis methodologies has enabled generation of extensive lipid libraries, providing the foundational datasets for machine learning applications [62]. The typical ML workflow for ionizable lipid optimization encompasses four key stages:

• Data Acquisition: High-throughput combinatorial chemistry approaches, such as Ugi three-component reactions (3-CR) and Passerini reactions, facilitate rapid synthesis of diverse ionizable lipid libraries with systematic structural variations [62]. Microfluidic LNP production ensures consistent nanoparticle characteristics with minimal batch-to-batch variation.

• Feature Representation: Lipid structures are encoded as machine-readable features using molecular descriptors (e.g., from RDKit) or simplified molecular-input line-entry system (SMILES) strings, capturing critical structural attributes including chain length, branching patterns, and headgroup characteristics [62].

• Model Training and Prediction: Both traditional machine learning (Random Forest, Support Vector Machines) and deep learning architectures (Graph Neural Networks, Convolutional Neural Networks) are trained to predict LNP performance metrics such as transfection efficiency, organ targeting specificity, and immunogenicity profiles from structural features [61] [62].

• Validation and Refinement: Model predictions guide synthesis of promising candidate lipids, with experimental results fed back to iteratively refine predictive algorithms in an active learning cycle [62].

This data-driven approach has demonstrated significant acceleration in identifying optimal ionizable lipids, with ML models capable of predicting in vivo delivery efficacy based on chemical structure alone [62].

Immunogenicity Prediction through Deep Learning

Specialized deep learning frameworks have emerged to address the particular challenge of immunogenicity prediction. The DeepImmuno platform employs a convolutional neural network (CNN) architecture with several innovative features [64]:

• Beta-Binomial Immunogenic Scoring: Unlike binary classification approaches, DeepImmuno utilizes a beta-binomial probabilistic model to derive continuous immunogenic scores, weighting each peptide-MHC complex based on experimental evidence confidence [64].

• Amino Acid Physicochemical Encoding: Instead of standard one-hot encoding, sequences are represented using a reduced principal component analysis (PCA) feature space derived from 566 curated amino acid physicochemical properties from the AAindex1 database [64].

• Generative Adversarial Networks: DeepImmuno incorporates GANs to simulate novel immunogenic peptides with physicochemical properties mirroring validated antigens, addressing data scarcity limitations [64].

In systematic benchmarking, DeepImmuno-CNN significantly outperformed existing immunogenicity prediction algorithms (DeepHLApan and IEDB) across diverse testing datasets including dengue virus, cancer neoantigens, and SARS-CoV-2 epitopes [64].

Comparative Analysis of LNP Formulation Strategies

Ionizable Lipid Design and Performance Metrics

Recent advances in LNP formulation have yielded novel ionizable lipids with improved delivery efficiency and tailored immunogenicity profiles. The following table compares representative ionizable lipids from recent studies:

Table 2: Comparative Performance of Ionizable Lipids in mRNA Delivery

Ionizable Lipid	Formulation Context	mRNA Delivery Efficiency	Immunogenicity Profile	Key Findings
AA2 (Amino alcohol-derived)	LNP-spike mRNA vaccine [65]	5.4-fold higher luminescence vs. ALC-0315; 2.4-fold vs. SM-102 [65]	Enhanced T-cell immunity against spike epitopes	Hydroxyl group enables hydrogen bonding with mRNA; branched ester tail improves endosomal escape
AA15V (Amino acid-derived)	saRNA encoding spike epitope-loaded SCT [65]	Potent RNA delivery to tumor cells	Enables tumor-specific antigen presentation	Effective for intratumoral delivery and presentation of viral epitopes on MHC-I
DODMA	Dengue and Leishmania infantum antigen mRNA [66]	Luciferase activity detected in liver/spleen within 6h; >85% encapsulation	Strong antigen-specific IgG and IFN-γ production	Similar immunogenicity to recombinant protein or plasmid DNA vaccines
DLin-MC3-DMA	siRNA delivery (Onpattro) [60]	Efficient hepatic delivery	Established safety profile in humans	First FDA-approved ionizable lipid for nucleic acid delivery
C12-200	Erythropoietin-encoding mRNA [67]	Effective intravenous mRNA delivery	Well-tolerated in preclinical models	Early ionizable lipid optimized for mRNA delivery

The data reveal that novel amino alcohol-derived lipids (AA series) demonstrate superior mRNA delivery efficiency compared to clinically established lipids, attributed to their hydrogen bond-donating capabilities and optimized hydrophobic tail architectures that promote cone-shaped molecular geometry for enhanced endosomal disruption [65].

Experimental Models for Evaluating LNP Immunogenicity

Standardized experimental protocols are essential for rigorous comparison of LNP formulation immunogenicity. Key methodological approaches include:

In Vitro Transfection and Immunogenicity Assays

• Cell Line Models: C2C12 myoblasts and JAWSII dendritic cells serve as representative models for intramuscular vaccination targets [65]. Cells are typically treated with LNPs at mRNA concentrations of 0.1-1 μg/well for 24-48 hours.
• Readout Methods: Transfection efficiency quantified via luciferase activity or fluorescent reporter expression; cytokine production (IFN-α, IFN-β, IL-6, TNF-α) measured by ELISA; cellular uptake tracked with fluorescently labeled LNPs [65] [63].
• Dendritic Cell Activation: Flow cytometric analysis of surface activation markers (CD80, CD86, MHC-II) following LNP treatment [63].

In Vivo Immunogenicity Assessment

• Vaccination Regimen: BALB/c or C57BL/6 mice (6-8 weeks) immunized intramuscularly with 1-10 μg mRNA-LNP in prime-boost schedules (2-4 week intervals) [65] [66].
• Humoral Immunity: Antigen-specific IgG titers measured by ELISA at serial timepoints post-immunization; neutralizing antibodies assessed in virus inhibition assays [66].
• Cellular Immunity: IFN-γ ELISpot or intracellular cytokine staining of splenocytes following antigen restimulation; tetramer staining for antigen-specific CD8+ T cells [65] [66].
• Biodistribution: Luciferase-encoding mRNA-LNPs tracked via in vivo imaging systems (IVIS) at 6h, 24h, and 7 days post-administration [66].

Integrated Analysis: LNP Formulation and mRNA Sequence Interplay

Modified Nucleosides and LNP-Mediated Immune Activation

The immunogenicity of mRNA therapeutics is significantly modulated through the incorporation of modified nucleosides, which dampen innate immune recognition without compromising protein expression. Kariko et al.'s seminal work demonstrated that nucleoside modifications (e.g., N1-methylpseudouridine) reduce TLR activation and minimize interferon responses [66]. This approach synergizes with LNP formulation parameters to fine-tune immunogenicity:

• Modified mRNA in LNPs: LNP formulations incorporating N1-methylpseudouridine-modified mRNAs encoding dengue virus E protein or Leishmania infantum antigen induced robust antigen-specific IgG and IFN-γ production comparable to recombinant protein or DNA vaccines, while minimizing excessive inflammatory responses [66].

• Unmodified mRNA in LNPs: Unmodified mRNAs typically trigger stronger RIG-I and MDA5 activation, potentially beneficial for vaccine applications but problematic for protein replacement therapies [59]. LNP composition can either amplify or mitigate these effects through selective engagement of endosomal TLRs (TLR3, TLR7/8) versus cytosolic sensors.

The following diagram illustrates the integrated signaling pathways through which LNPs and mRNA sequences collectively modulate immune responses:

Immune Signaling Pathways in LNP-mRNA Therapeutics

This integrated signaling network demonstrates how LNP formulation (particularly ionizable lipid structure) primarily influences endosomal TLR pathways, while mRNA modification status predominantly affects cytosolic sensor engagement. The convergence of these pathways determines the balance between desirable immunogenicity for vaccination versus excessive inflammation that compromises safety and efficacy.

Machine Learning-Enabled Optimization of LNP-mRNA Systems

The combination of LNP formulation parameters and mRNA sequence features creates a multidimensional optimization challenge ideally suited for machine learning approaches. Emerging strategies include:

• Multi-Objective Optimization: ML models simultaneously optimize for multiple criteria including transfection efficiency, organ specificity, immunogenicity, and safety profiles [61] [62]. Pareto front analysis identifies candidate formulations balancing these potentially competing objectives.

• Transfer Learning Across Applications: Models trained on siRNA-LNP datasets are fine-tuned for mRNA delivery prediction, leveraging shared structural determinants of delivery efficiency while accounting for differences in nucleic acid properties and immunological profiles [61].

• Generative Design: Variational autoencoders (VAEs) and generative adversarial networks (GANs) create novel ionizable lipid structures with desired properties, expanding beyond traditional chemical space [68] [62]. These approaches have generated candidate lipids with improved in vivo performance compared to existing benchmarks.

Experimental validation of ML-predicted formulations demonstrates the power of these approaches. In one representative study, ML-guided LNP designs achieved approximately 60% reduction in development time and 50% cost savings compared to traditional sequential optimization, while maintaining or improving key performance metrics [68].

The Scientist's Toolkit: Essential Research Reagents and Methodologies

Table 3: Essential Research Reagents for LNP-mRNA Studies

Category	Specific Reagents/Materials	Research Function	Key Considerations
Ionizable Lipids	DLin-MC3-DMA, ALC-0315, SM-102, DODMA, AA lipids [65] [60] [66]	mRNA complexation and delivery	Purity critical for reproducibility; storage at -20°C under inert gas
Structural Lipids	DSPC, DOPE, Cholesterol [60] [66]	LNP bilayer formation and stability	Source variability can affect LNP characteristics; use high-purity grades
PEG-Lipids	DMG-PEG2000, DSG-PEG2000 [60] [66]	Particle stability, pharmacokinetics	Percentage in formulation affects immunogenicity and clearance
mRNA Synthesis	CleanCap cap analog, N1-methylpseudouridine, MEGAscript T7 Kit [66]	Production of modified mRNAs	Cap structure and nucleoside purity crucial for translation efficiency
Formulation Equipment	Microfluidic devices (e.g., NanoAssemblr, Particle Works) [62] [66]	Reproducible LNP production	Flow rate ratios determine size and PDI; precision pumps essential
Analytical Instruments	DLS/Zetasizer, NTA, HPLC, cryo-TEM [63] [66]	LNP characterization	Multi-method approach needed for comprehensive characterization

The synergistic integration of LNP formulation optimization with machine learning approaches represents a transformative advancement in mRNA therapeutic development. Experimental evidence consistently demonstrates that rational design of ionizable lipid structures, coupled with strategic mRNA sequence modifications, enables fine control over immunogenicity profiles while maintaining potent delivery efficiency. The multivariate nature of these interactions makes them particularly amenable to ML-driven exploration, with demonstrated improvements in development timelines and predictive accuracy.

Future developments will likely focus on several key areas: (1) expansion of high-quality experimental datasets encompassing diverse lipid chemistries and in vivo outcomes; (2) development of explainable AI models that provide mechanistic insights alongside predictive outputs; and (3) integration of multi-omics data to capture system-level responses to LNP-mRNA therapeutics. As these technologies mature, the design paradigm for nucleic acid therapeutics will shift from empirical screening to rational in silico prediction, accelerating the development of next-generation vaccines and therapeutics with optimized efficacy and safety profiles.

Head-to-Head: Comparative Immunogenicity and Efficacy in Pre-Clinical and Clinical Models

The deployment of messenger RNA (mRNA) vaccines represented a pivotal turning point in the COVID-19 pandemic response. While these vaccines share a common fundamental mechanism—delivering genetic instructions for the SARS-CoV-2 spike protein to host cells—critical distinctions in their molecular design profoundly impact their immunogenicity and clinical performance. This analysis examines the clinical evidence comparing the performance of modified mRNA vaccines (BNT162b2 and mRNA-1273) against the unmodified mRNA vaccine candidate from CureVac (CVnCoV), framing the comparison within the broader thesis that nucleoside modification significantly enhances the efficacy and safety profile of mRNA-based vaccines.

The core technological distinction lies in the uridine modification: BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) incorporate modified nucleosides (1-methylpseudouridine) in place of uridine, while CureVac's first-generation candidate, CVnCoV, utilizes unmodified, natural nucleotides [69]. This molecular difference, though seemingly minor, has profound implications for how the immune system recognizes the synthetic mRNA and, consequently, the magnitude and quality of the vaccine-induced immune response. Understanding this relationship is crucial for researchers and drug development professionals working to optimize mRNA platforms for current and future applications.

Comparative Vaccine Performance: Immunogenicity and Efficacy Data

Direct comparisons and individual trial outcomes demonstrate clear efficacy differences between the vaccine platforms, which can be attributed to the distinct mRNA technologies.

Vaccine Candidate	mRNA Technology	Dose (Primary Series)	Reported Efficacy	Neutralizing Antibody Titers (Relative to Convalescent)	Key Limitations & Trial Context
BNT162b2 (Pfizer-BioNTech)	Nucleoside-modified (1-methylpseudouridine)	30 μg	~95% (Phase 3) [69]	High, significantly exceeding convalescent levels [70]	Declining effectiveness against Delta variant infection; waning immunity after 6 months [71]
mRNA-1273 (Moderna)	Nucleoside-modified (1-methylpseudouridine)	100 μg	~94% (Phase 3) [69]	Highest among approved vaccines; robust T-cell responses [70] [72]	Higher reactogenicity; lower effectiveness against Delta infection compared to original strain [70] [71]
CVnCoV (CureVac)	Unmodified nucleotide	12 μg	47% (Interim Phase 2b/3) [69]	Comparable to convalescent patients in early phases [73]	Lower antigen expression and protein translation; high innate immunogenicity interfering with efficacy [69]

Analysis of Comparative Immunogenicity

• Humoral Immunity Hierarchy: A 2021 comparative immunogenicity study found a distinct hierarchy in humoral responses. mRNA-1273 induced the strongest antibody and neutralization titers, followed by BNT162b2, with both yielding comparable or superior antibody concentrations to convalescent individuals after a single dose. This robust response is linked to the enhanced protein expression enabled by nucleoside modification [70].
• T-Cell Responses: Cellular immunity followed a similar pattern. Both mRNA-1273 and BNT162b2 elicited higher bulk and cytotoxic T-cell responses than adenovirus-vectored vaccines like Ad26.COV2.S. However, it is notable that fewer than 50% of recipients of any vaccine demonstrated detectable CD8+ T-cell responses to spike peptides, highlighting a potential limitation of current mRNA platforms [70] [74].
• Impact on Vulnerable Populations: The immunogenicity advantage of higher-dose, modified mRNA vaccines is particularly pronounced in immunocompromised (IC) patients. A 2024 meta-analysis demonstrated that mRNA-1273 (100 μg) was associated with a significantly higher likelihood of seroconversion and 50% higher total antibody titers compared to BNT162b2 (30 μg) in IC individuals. This suggests that the dose and the platform collectively influence outcomes in populations with blunted immune responses [72].

Underlying Experimental Evidence and Protocols

The differential performance of these vaccines is not an artifact of clinical trials but is rooted in measurable differences in biological behavior, elucidated through standardized experimental protocols.

Key Methodologies for Comparative Immunogenicity Assessment

Researchers employed consistent laboratory methods to enable direct comparisons between vaccine immune responses. The following table details the core assays used in the studies referenced.

Research Reagent / Assay	Specific Function & Measurement	Experimental Context & Application
SARS-CoV-2 Pseudovirus Neutralization Assay	Measures functional, neutralizing antibodies by quantifying inhibition of pseudovirus entry into host cells [70].	Used to compare neutralization titers against original and variant viruses (e.g., Beta, Gamma, Delta) post-vaccination with different platforms [70].
ELISA (Enzyme-linked Immunosorbent Assay)	Quantifies total IgG/M/A binding antibodies against specific viral antigens like Spike protein or RBD [70].	Employed to measure the concentration and avidity of binding antibodies induced by vaccination [70] [75].
IFN-γ ELISpot Assay	Detects and enumerates antigen-specific T-cells by measuring cytokine (IFN-γ) release upon peptide stimulation [70].	Critical for quantifying SARS-CoV-2 spike-specific CD4+ and CD8+ T-cell responses in vaccinated individuals [70].
Flow Cytometry with MHC Multimers	Identifies and characterizes antigen-specific T-cell populations (e.g., memory phenotypes, cytotoxic potential) [75].	Used in in-depth analysis of T-cell responses, as seen in trials of fractional dose mRNA-1273 [75].

Molecular and Preclinical Insights

• The Innate Immune Sensing Problem: Unmodified mRNA is recognized by pattern recognition receptors (e.g., TLRs, RIG-I) as a potential pathogen-associated molecular pattern (PAMP). This triggers a potent type I interferon (IFN) response, which can inhibit the translation of the encoded antigen, thereby reducing the amount of protein available to stimulate adaptive immunity [69]. This is a primary mechanism for the lower immunogenicity of CVnCoV.
• The Role of Nucleoside Modification: The incorporation of modified nucleosides like 1-methylpseudouridine allows the mRNA to evade or attenuate this innate immune recognition. This "stealth" effect reduces IFN signaling and markedly increases antigen production by facilitating efficient and sustained translation in the host cell's cytoplasm [69]. The increased antigen load directly correlates with stronger B- and T-cell activation.
• Preclinical Validation of Second-Generation Designs: CureVac's own research following the setback of CVnCoV confirmed this principle. Their second-generation candidate, CV2CoV, developed with GSK, features a completely optimized mRNA backbone. Preclinical data showed this new design provided "high levels of antigen production" and a "fast onset of strong neutralizing antibody titers after first vaccination," including cross-neutralization against variants of concern, even at low doses [73]. This evolution in their platform validates the critical importance of the modifications pioneered by BioNTech and Moderna.

The logical pathway below summarizes the core mechanism by which mRNA modification dictates immunogenicity and clinical performance.

The clinical evidence presents a clear verdict: the incorporation of nucleoside-modified mRNA is a superior strategy for vaccine development. The stark contrast between the high efficacy (~94-95%) of BNT162b2 and mRNA-1273 and the sub-50% efficacy of the unmodified CVnCoV underscores a fundamental principle in mRNA biology. Modified mRNA achieves a favorable balance by minimizing undesirable innate immune activation while maximizing the desired adaptive immune response through high-level antigen production.

For researchers and drug developers, these findings are transformative. The success of modified mRNA platforms validates a design principle that extends far beyond SARS-CoV-2. This technology offers a versatile and rapidly adaptable framework for targeting a wide range of infectious diseases, cancers, and other therapeutic areas. Future work should focus on further refining nucleotide chemistry and delivery systems (LNPs) to enhance stability, reduce reactogenicity, and extend the duration of protection. The evolution of CureVac's own platform from CVnCoV to its second-generation candidates in collaboration with GSK serves as a powerful case study, confirming that the future of mRNA medicines is built on a foundation of strategic molecular modification.

The emergence of mRNA vaccine platforms has revolutionized prophylactic and therapeutic medicine, yet fundamental questions remain regarding how specific mRNA modifications influence immunogenicity. At the core of this scientific discourse is whether nucleoside-modified mRNA constructs offer distinct advantages over sequence-optimized unmodified mRNA platforms, particularly in the context of therapeutic applications requiring high-dose, repetitive administration. While the successful COVID-19 vaccines from Moderna and Pfizer/BioNTech employ N1-methylpseudouridine (m1Ψ)-modified mRNA [1], earlier candidates like CureVac's CVnCoV utilized unmodified mRNA with notably lower efficacy (47% versus >90%) despite using identical lipid nanoparticles in some cases [1]. This efficacy gap suggests inherent immunological differences between platforms that warrant rigorous preclinical investigation.

Non-human primates (NHPs), particularly rhesus macaques, serve as critical model organisms for bridging rodent studies and human clinical trials due to their shared immune system properties with humans [76]. Recent NHP studies have specifically aimed to dissect how modified versus unmodified mRNA vaccines activate innate immunity and how this initial activation shapes subsequent adaptive responses. Understanding these dynamics is particularly crucial for therapeutic cancer vaccines and other applications requiring repeated administration, where both potent immunogenicity and acceptable reactogenicity profiles must be carefully balanced [7] [1]. This review synthesizes recent preclinical insights from NHP studies to objectively compare the innate immune activation and adaptive response kinetics induced by these distinct mRNA platforms.

Experimental Designs: Head-to-Head NHP Comparison Studies

Vaccination Regimens and Antigen Selection

Recent NHP studies have adopted systematic approaches to compare mRNA vaccine platforms under conditions mimicking therapeutic applications. A 2025 investigation by Engstrand et al. employed a rigorous model in rhesus macaques using HIV-1 gag as a well-characterized model antigen [7] [6]. The study design incorporated five immunizations at two-week intervals with a final boost 20 weeks later, specifically chosen to explore the limits of reactogenicity and immune activation under high-stress conditions [7]. This intensive regimen mirrors proposed therapeutic cancer vaccine protocols (NCT03897881, NCT04534205) where frequent, high-dose administration is necessary to overcome immunosuppressive microenvironments [7].

The study compared three distinct vaccine conditions: unmodified mRNA (160 μg) versus two dose levels of m1Ψ-modified mRNA (400 μg and 800 μg) [7] [6]. The deliberate dose differential reflects clinical reality, where unmodified mRNA typically requires lower dosing due to stronger innate immune activation and associated adverse reactions [7]. All constructs encoded the identical HIV-1 gag antigen and were formulated in lipid nanoparticles to ensure comparable delivery efficiency, with the gag antigen selected specifically for its well-characterized immunogenicity in NHPs [7].

Sample Collection and Analytical Methods

Comprehensive immunological profiling was performed through serial blood collection at multiple time points, with intensive analysis at 24 hours post-vaccination to capture peak innate immune responses [7]. Researchers employed multi-parameter flow cytometry to characterize immune cell fluctuations, including plasmacytoid dendritic cells (pDCs), intermediate CD14+CD16+ monocytes, neutrophils, and T-cell subsets [7]. Cytokine and chemokine secretion was quantified using multiplex assays, with particular focus on type I interferon-related proteins (CXCL11, IFN-α) and inflammatory cytokines (IL-1RA, IL-6, IL-7, TNF) [7].

Bulk transcriptomic profiling provided complementary data on gene expression changes, with differential expression analysis and gene set enrichment analysis (GSEA) revealing pathway-level activation [7]. Antigen-specific adaptive immunity was assessed through gag-specific antibody titers measured by ELISA and memory T-cell responses quantified via intracellular cytokine staining and activation-induced marker (AIM) expression following antigen recall [7]. This comprehensive methodological approach enabled direct comparison of both innate sensing mechanisms and functional adaptive outcomes between platforms.

Table 1: Key Experimental Parameters in NHP mRNA Vaccine Studies

Parameter	Unmodified mRNA	Modified mRNA (Low Dose)	Modified mRNA (High Dose)
mRNA Type	Sequence-codon optimized	N1-methylpseudouridine-modified	N1-methylpseudouridine-modified
Dose	160 μg	400 μg	800 μg
Immunization Schedule	5 doses at 2-week intervals, final boost at week 20	Same	Same
Antigen	HIV-1 gag	HIV-1 gag	HIV-1 gag
Formulation	Lipid nanoparticles	Lipid nanoparticles	Lipid nanoparticles
Animals per Group	5 rhesus macaques	5 rhesus macaques	5 rhesus macaques

Innate Immune Activation: Distinct Patterns by mRNA Platform

Cellular and Cytokine Responses

Both modified and unmodified mRNA vaccines elicited rapid, transient innate immune activation detectable within 24 hours post-immunization [7]. Characteristic patterns included significant increases in plasmacytoid dendritic cells, intermediate CD14+CD16+ monocytes, and neutrophils, alongside a temporary decrease in T-cell counts suggesting lymphocyte redistribution to tissues [7]. These cellular fluctuations occurred alongside secretion of type I interferon-related cytokines and inflammatory mediators, with distinct patterns emerging between platforms.

Unmodified mRNA induced significantly higher levels of interleukin-7 (IL-7) and interferon-alpha (IFN-α), whereas modified mRNA produced greater interleukin-6 (IL-6) responses, particularly at higher doses [7] [6]. The elevated IFN-α response to unmodified mRNA aligns with its known capacity for stronger activation of Toll-like receptors (TLR7, TLR8) and RIG-I-like receptors [1]. The mechanistic basis for differential IL-7 induction remains less clear, though potential involvement of TLR-mediated activation in lymphoid tissues has been proposed [1]. Importantly, these cytokine patterns persisted through multiple immunizations, though unmodified mRNA showed evidence of tolerization with repeated administration [1].

Diagram 1: Innate immune sensing pathways for modified versus unmodified mRNA vaccines. Unmodified mRNA strongly activates TLR7/TLR8 and RIG-I-like receptors, driving type I IFN and IL-7 responses. Modified mRNA has reduced TLR activation but can still signal through RIG-I pathways; its higher LNP content contributes to IL-6/TNF production via inflammasome activation.

Transcriptomic Profiles and Dose Dependencies

Transcriptomic analyses revealed both shared and distinct gene expression patterns between platforms. Both mRNA constructs significantly upregulated genes related to type I interferon signaling, antigen presentation, and innate immune activation [7]. However, the magnitude and durability of these responses differed substantially. The high-dose modified mRNA group exhibited the highest number of differentially expressed genes (DEGs) after initial immunization, with this response further increasing after the fifth dose [7] [6]. In contrast, both unmodified mRNA and lower-dose modified mRNA showed reduced DEGs after the fifth immunization compared to prime immunization, suggesting platform- and dose-dependent tolerance effects [1].

Gene set enrichment analysis confirmed upregulation of type I IFN signaling pathways across all groups, with additional enrichment detected in IL-6 signaling pathways, particularly for modified mRNA recipients [7]. Notably, detection of gag expression from the vaccines in transcriptomic data confirmed successful vaccine uptake and translation, though levels were lower after boost immunizations, potentially reflecting clearance of antigen-expressing cells by vaccine-induced immunity [7].

Table 2: Comparative Innate Immune Profiles by mRNA Platform

Immune Parameter	Unmodified mRNA (160 μg)	Modified mRNA (400 μg)	Modified mRNA (800 μg)
IFN-α Induction	+++ (Highest)	+	++
IL-7 Induction	+++ (Highest)	+	++
IL-6 Induction	+	++	+++ (Highest)
TNF Induction	+	++	+++ (Highest)
pDC Activation	+++	+++	+++
Monocyte Fluctuation	+++	+++	+++
DEGs After Prime	Moderate	Moderate	High
DEGs After 5th Dose	Reduced	Reduced	Further Increased
Tolerance Development	Yes	Yes	No

Adaptive Immune Responses: Surprisingly Similar Outcomes

Antibody and T-Cell Kinetics

Despite pronounced differences in innate immune activation, all vaccine platforms ultimately generated comparable adaptive immune responses [7] [6]. Gag-specific antibodies emerged two weeks after the second immunization, with titers progressively increasing through the fifth dose before expected waning [7]. The final boost at week 20 successfully restored antibody titers to peak levels across all groups [7]. Notably, both the kinetics and magnitude of antibody responses were remarkably consistent between platforms, suggesting that the qualitatively different inflammatory environments similarly supported humoral immunity [7].

Similarly, gag-specific memory T-cell responses emerged after three immunizations at comparable frequencies across groups [7]. Both CD4+ and CD8+ T-cell responses were detectable by intracellular cytokine staining and activation-induced marker assays [7]. The CD4+ T-cell responses predominated over CD8+ responses across all platforms, consistent with previous mRNA vaccine studies [7]. Subtle potential differences in T-cell quality, including slightly enhanced IFN-γ production from CD8+ T cells following unmodified mRNA vaccination, were noted but require confirmation in larger studies [1].

Impact of Repeated Administration

The intensive vaccination schedule provided critical insights into how repeated administration affects immune responses to different mRNA platforms. While unmodified mRNA showed evidence of innate tolerance development with repeated dosing (diminished cytokine responses and DEGs), this tolerization did not materially impact adaptive immunity [1]. Similarly, the absence of tolerance development with high-dose modified mRNA did not confer adaptive advantages [1].

These observations suggest redundant pathways supporting adaptive immunity or compensatory mechanisms that ensure robust antigen-specific responses despite oscillating innate activation. The similar antibody and T-cell kinetics across platforms indicate that the adaptive immune system can generate robust responses across a spectrum of inflammatory contexts, provided adequate antigen expression is achieved [7] [1].

Research Reagent Solutions for mRNA Vaccine Immunology

Table 3: Essential Research Tools for NHP mRNA Vaccine Studies

Research Tool	Specific Application	Function in Experimental Design
N1-methylpseudouridine-modified mRNA	Modified mRNA vaccine platform	Reduces innate immune activation via TLR7/8; enhances translational capacity
Sequence-codon optimized unmodified mRNA	Unmodified mRNA vaccine platform	Provides stronger innate immune activation; potential adjuvant effect
Ionizable lipid nanoparticles (LNPs)	mRNA delivery vehicle	Protects mRNA; facilitates cellular uptake and endosomal escape; contributes to immunogenicity
HIV-1 gag antigen	Model antigen in NHP studies	Well-characterized immunogenicity; enables comparison with historical data
Multi-parameter flow cytometry	Immune cell phenotyping	Quantifies fluctuations in pDCs, monocytes, neutrophils, T-cell subsets
Bulk RNA sequencing	Transcriptomic profiling	Identifies differentially expressed genes and enriched pathways
Activation-induced marker (AIM) assay	Antigen-specific T-cell detection	Measures rare antigen-responsive T cells without requiring cytokine secretion
Luminex/multiplex cytokine assays	Cytokine and chemokine quantification	Profiles inflammatory and IFN-related soluble mediators

The NHP studies reviewed herein demonstrate that while modified and unmodified mRNA platforms engage distinctly different innate immune pathways, they ultimately converge on similar adaptive immune outcomes under the experimental conditions tested. The more robust innate sensing of unmodified mRNA—characterized by elevated type I IFN and IL-7—appears counterbalanced by modified mRNA's enhanced translational capacity and reduced intrinsic immunogenicity, resulting in comparable antigen-specific antibody and T-cell responses [7] [1] [6].

These findings have significant implications for therapeutic vaccine development. For cancer immunotherapy applications, where robust T-cell priming against tumor antigens is paramount, the stronger innate immune activation by unmodified mRNA might provide superior adjuvant effects, particularly in immunosuppressive tumor microenvironments [1]. This potential advantage may explain why several ongoing clinical trials for cancer vaccines continue to explore unmodified mRNA platforms (NCT05938387, NCT03289962) [1]. Conversely, for prophylactic vaccines against infectious diseases or scenarios requiring repeated administration, modified mRNA's superior tolerability profile may be preferable [7].

Future research should prioritize direct comparison of these platforms using tumor antigen models and in tumor-bearing hosts to better understand how these immunological differences translate to therapeutic efficacy. Additionally, exploration of hybrid approaches—such as prime-boost strategies combining both platforms or further optimization of non-coding regions—may harness the distinctive advantages of each technology [1]. As the mRNA therapeutic field continues to expand, these NHP studies provide a critical foundation for rational platform selection based on intended application, desired immune polarization, and acceptable reactogenicity profile.

Within immunogenicity research for mRNA therapeutics, the comparative profile of T-cell and antibody responses is a central focus. The choice between modified and unmodified mRNA platforms profoundly influences the magnitude, durability, and breadth of the adaptive immune response. This guide provides an objective comparison of these responses, framing the data within the ongoing scientific investigation of mRNA design. The subsequent analysis, supported by experimental data and standardized protocols, offers a reference for researchers and drug development professionals evaluating vaccine and therapeutic candidates.

Quantitative Comparison of Immune Responses

The adaptive immune response comprises two key arms: antibody-mediated (humoral) immunity and cell-mediated immunity, primarily driven by T-cells. The following tables summarize their characteristic profiles based on data from natural infection and vaccination studies.

Table 1: Comparative Profile of T-cell and Antibody Responses to SARS-CoV-2

Parameter	T-cell Responses	Antibody Responses
Magnitude & Severity Correlation	Broader responses correlated with less severe disease [77]. Higher CD8+ T-cell counts associated with survival in severe COVID-19 [77].	Stronger antibody responses correlate with more severe clinical disease [77]. Higher IgG levels against spike protein were observed in patients who died from SARS [77].
Durability	Long-lived. Virus-specific T-cells remain detectable for years to over a decade after SARS-CoV-1 infection [77] [78]. Memory T-cells are maintained for at least several months post-SARS-CoV-2 infection [79].	Shorter-lived. Antibodies to common cold coronaviruses wane within a year [77]. SARS-CoV-1 survivors had no detectable antibodies at 6 years [77]. A decreasing trend is observed ~7 months post-vaccination [80].
Breadth of Antigen Recognition	Broad. CD4+ and CD8+ T-cells target multiple structural (S, N, M) and non-structural proteins [79] [77]. In one study, convalescent individuals targeted a median of 13 regions in the S protein and 4 in the N protein [79].	Narrow. Predominantly target surface proteins, primarily the Spike (S) protein and its Receptor Binding Domain (RBD), which are the focus of most vaccines [77] [81].
Impact of Variants	Largely preserved. Most CD8+ T-cell epitopes maintain HLA binding (94-96%) for Omicron subvariants, suggesting amino acid changes have a limited impact [79].	Significantly reduced. SARS-CoV-2 variants frequently possess escape mutations that reduce the efficacy of neutralizing antibodies [79] [77].

Table 2: Impact of mRNA Modification on Immune Parameters

Parameter	Unmodified mRNA	N1-methylpseudouridine (m1Ψ) Modified mRNA
Innate Immune Sensing	High. Robustly activates TLR7/8 and RIG-I-like receptors, leading to high levels of IFNα and IL-7 [1].	Attenuated. Modified nucleosides help mRNA evade innate sensors, reducing inflammation [81] [1].
Pro-inflammatory Cytokines	Lower induction of IL-6 and TNF [1].	Induces higher levels of IL-6 and TNF, largely attributed to the greater amount of LNP required for delivery [1].
Antigen Expression & Translation	Lower due to immune-mediated translational restriction [1].	Enhanced translation due to reduced innate immune activation and direct effects on the translational machinery [1].
Durability of Innate Activation	Shows a tolerizing effect upon repetitive dosing, with reduced innate activation after the 5th dose [1].	No tolerance measured for high-dose regimens, with IL-6 levels remaining unaltered over multiple doses [1].
Adaptive Immunogenicity	Induces Gag-specific antibody titers virtually identical to modified mRNA and can induce a CD8+ T-cell response with more IFNγ release [1].	Induces a better CD4+ memory T-cell response. Antibody and T-cell responses are highly effective, as demonstrated by COVID-19 vaccines [1].

Experimental Protocols for Immune Monitoring

Enzyme-Linked Immunosorbent Spot (ELISpot) Assay

The IFN-γ ELISpot is a widely used, high-throughput method for quantifying antigen-specific T-cell responses [82].

• Principle: Captures cytokine (e.g., IFN-γ) secreted by individual T-cells upon antigen stimulation, creating a visible "spot" that corresponds to a single reactive cell.
• Workflow:
  • Plate Coating: Coat a nitrocellulose plate with an antibody against IFN-γ.
  • Cell Seeding & Stimulation: Seed peripheral blood mononuclear cells (PBMCs) into wells and stimulate with overlapping peptide pools covering viral proteins (e.g., S, N, M). Include positive (e.g., phytohemagglutinin) and negative (media alone) control wells.
  • Incubation: Incubate plates for 24-48 hours to allow cytokine secretion and capture.
  • Detection: Remove cells and add a biotinylated detection antibody against IFN-γ, followed by enzyme-conjugated streptavidin.
  • Spot Development: Add a precipitating substrate to form insoluble spots where cytokine was secreted.
  • Analysis: Enumerate spots using an automated ELISpot reader. Results are expressed as spot-forming cells (SFC) per million input cells [79].

Intracellular Cytokine Staining (ICS) and Flow Cytometry

ICS provides a multiparameter analysis of T-cell functionality and phenotype at a single-cell level.

• Principle: T-cells are stimulated in the presence of a protein transport inhibitor, then stained intracellularly for cytokines and surface markers to identify specific T-helper subsets (e.g., Th1, Tfh) [80].
• Workflow:
  • Cell Stimulation: Incubate PBMCs with peptide pools in the presence of a protein transport inhibitor (e.g., Brefeldin A) for 4-16 hours.
  • Surface Staining: Stain cells with fluorescently-labeled antibodies against surface markers (e.g., CD3, CD4, CD8, CD45RA, CCR7).
  • Fixation and Permeabilization: Treat cells with fixation and permeabilization buffers to make intracellular proteins accessible.
  • Intracellular Staining: Stain cells with antibodies against cytokines (e.g., IFN-γ, IL-2, TNF-α) and functional markers (e.g., CD40L for Tfh cells).
  • Data Acquisition & Analysis: Acquire data on a flow cytometer. Analyze to determine the frequency and phenotype of cytokine-producing antigen-specific T-cells [80].

T-cell Receptor Immunosequencing

This molecular assay identifies and tracks clonal expansions of T-cells without the need for functional assays.

• Principle: Uses high-throughput sequencing of the TCRβ chain to quantitatively profile the T-cell repertoire. SARS-CoV-2-specific TCRs can be identified and used to measure the breadth and depth of the response [78].
• Workflow:
  • DNA Extraction: Isolate genomic DNA from PBMCs or whole blood.
  • Multiplex PCR: Amplify rearranged TCRβ genes using a multiplex PCR system.
  • High-Throughput Sequencing: Sequence the amplified products.
  • Bioinformatic Analysis: Identify clonally expanded TCR sequences. Public TCRs shared across individuals can serve as biomarkers of infection or vaccination [78].

Diagram 1: T-cell Activation Pathway

Diagram 2: T-cell-Dependent Antibody Response

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Reagents for Evaluating T-cell and Antibody Responses

Reagent / Assay	Function / Application	Experimental Context
Overlapping Peptide Pools	Synthetic peptides (15-20 aa) spanning viral proteins (S, N, M) used to stimulate T-cells and map epitopes in ELISpot/ICS [79].	Comprehensive screening of T-cell responses at the peptide level [79].
ELISpot Kit (e.g., IFN-γ)	High-throughput, robust, and economical kit for quantifying antigen-specific T-cell frequencies from PBMCs [82].	Primary endpoint in immunogenicity trials; used to detect memory T-cells in convalescent individuals [79] [82].
MHC Multimers (Tetramers)	Fluorescently labeled complexes of MHC molecules and peptide used to identify and phenotype antigen-specific T-cells via flow cytometry [82].	Precise identification and isolation of T-cell clones specific for a known epitope/HLA combination.
Electrochemiluminescence (ECL) Bridging Assay	Highly sensitive immunoassay for detecting anti-drug antibodies (ADA) or in this context, anti-Spike/RBD antibodies [83].	Quantifying humoral immunogenicity; preferred for its broad dynamic range and sensitivity [80] [83].
LNP Formulation Components	Ionizable lipid (e.g., SM-102, ALC-0315), PEG-lipid, cholesterol, and phospholipid. Critical for mRNA delivery and adjuvant activity [81].	Core component of mRNA vaccines; the iLNP itself acts as a powerful adjuvant, inducing cytokines like IL-6 [81] [1].

The development of messenger RNA (mRNA) cancer vaccines represents a paradigm shift in oncology, leveraging the body's own cellular machinery to generate targeted immune responses against tumors. A central debate in this field revolves around the use of nucleoside-modified mRNA versus unmodified mRNA, each offering distinct immunological profiles and therapeutic implications. Nucleoside-modified mRNA typically incorporates N1-methylpseudouridine (m1Ψ), which dampens innate immune recognition and enhances protein translation, while unmodified mRNA retains its inherent immunostimulatory properties that may be advantageous in certain oncological contexts [1] [84].

The strategic selection between these platforms involves balancing translation efficiency, immunogenicity, and activation of innate immunity—all critical factors that influence vaccine performance. This comparison guide examines the technical specifications, experimental data, and clinical applications of both platforms to inform researchers and drug development professionals working at the intersection of mRNA technology and cancer immunotherapy.

Technical Comparison: Modified vs. Unmodified mRNA Platforms

Table 1: Core Characteristics of Modified and Unmodified mRNA Vaccine Platforms

Parameter	Unmodified mRNA	Nucleoside-Modified mRNA (m1Ψ)
Innate Immune Recognition	Strong activation of TLR7/8 and RIG-I pathways [1]	Attenuated immune recognition; reduced TLR7/8 activation [1]
Type I Interferon Response	Robust IFNα and IL-7 production [1]	Significantly reduced IFNα response [1]
Translational Efficiency	Limited by immune-mediated translational restriction [1]	Enhanced; alleviates translational repression [1]
Cytokine Profile	Higher IL-7; supports T-cell responses [1]	Increased IL-6 and TNF; enhances antibody responses [1]
Dosing Considerations	Effective at lower doses due to high immunogenicity [1]	Often requires higher doses and more LNP [1]
Repetitive Dosing Effect	Tolerization effect observed with repeated administration [1]	Sustained response with multiple doses [1]

Table 2: Preclinical and Clinical Performance in Oncology Applications

Application Context	Unmodified mRNA Performance	Modified mRNA Performance
HPV-Related Cancers (Mouse Models)	Single dose eradicated established tumors; strong CD8+ T cell response [84]	Single dose eradicated established tumors; strong CD8+ T cell response [84]
Therapeutic Antibody Response	Moderate antibody titers in NHP models [1]	Robust antibody titers; enhanced by LNP-mediated cytokine release [1]
T Cell Immunogenicity	Potent IFNγ+ CD8+ T cells [1]	Enhanced CD4+ memory cell induction [1]
Clinical Vaccine Efficacy (Infectious Disease)	CVnCoV (CureVac): 47% efficacy against COVID-19 [1]	BNT162b2 (Pfizer) & mRNA-1273 (Moderna): >90% efficacy [1]
Ongoing Cancer Clinical Trials	CVGBM (CureVac) in phase 1; BioNTech's iNest platform [1]	Personalized vaccines (e.g., mRNA-4157) in multiple trials [1]

Experimental Protocols: Head-to-Head Comparisons

Non-Human Primate Study of High-Dose mRNA Vaccination

A rigorous comparative study evaluated both mRNA platforms in non-human primates using a Gag-antigen model designed to simulate therapeutic cancer vaccination parameters [1].

Methodology:

• Vaccine Formulations: Three formulations tested: (1) 160 μg unmodified mRNA, (2) 400 μg m1Ψ-modified mRNA (low-dose), and (3) 800 μg m1Ψ-modified mRNA (high-dose)
• Immunization Schedule: Five administrations at 2-week intervals with a sixth booster at 20 weeks
• Delivery System: Lipid nanoparticles (LNPs) for all formulations
• Immune Monitoring: Comprehensive analysis of innate cytokine responses, antigen-specific antibody titers, and T cell responses including CD4+ memory and CD8+ IFNγ production

Key Findings: The investigation revealed that unmodified mRNA induced significantly higher levels of IFNα and IL-7 despite the lower dose administered, indicating potent activation of innate immunity. In contrast, m1Ψ-modified mRNA resulted in increased IL-6 and TNF release, partly attributable to the higher LNP content required for delivery. Notably, antibody responses across all platforms were remarkably similar, while T cell responses showed nuanced differences: unmodified mRNA generated more IFNγ-producing CD8+ T cells, whereas modified mRNA favored CD4+ memory cell development [1].

Comparative Study of HPV-Specific mRNA Vaccines

A direct comparison of three mRNA vaccine platforms for treating HPV-related cancers provided critical insights into their relative efficacies [84].

Methodology:

• Vaccine Designs: (1) Unmodified nonreplicating mRNA, (2) m1Ψ-modified nonreplicating mRNA, and (3) self-amplifying mRNA
• Antigen Target: All vaccines encoded an engineered gDE7 fusion protein combining HPV-16 E7 oncoprotein with herpes simplex virus glycoprotein D
• Tumor Models: Mice implanted with E7-expressing cancer cells to establish early- and late-stage tumors
• Dosing Regimen: Single-dose administration to assess therapeutic efficacy
• Immune Analysis: Depth of CD8+ T cell response and protection against tumor rechallenge

Key Findings: All three mRNA platforms demonstrated equivalent capability to eradicate established HPV-related tumors in mouse models following a single dose, with protection against tumor rechallenge in most animals. While slight differences in immune activation were noted, all formats stimulated sufficient antigen-specific CD8+ T cells to mediate complete tumor regression, outperforming both DNA-based and protein-based vaccines targeting the same antigen [84].

Mechanisms of Action: Signaling Pathways and Immune Activation

The differential immune activation by modified and unmodified mRNA vaccines involves distinct signaling pathways that shape the resultant adaptive immunity. The diagram below illustrates these key mechanistic differences.

Diagram 1: Differential signaling pathways and immune activation mechanisms of unmodified versus modified mRNA vaccines. Unmodified mRNA (red pathway) strongly activates pattern recognition receptors, triggering robust type I interferon responses that enhance cytotoxic T lymphocyte (CTL) activation. Modified mRNA (blue pathway) evades immune recognition, enabling enhanced translation and promoting different immune effectors through LNP-mediated cytokine release.

The immunological mechanisms underlying these platforms extend beyond simple antigen expression. Unmodified mRNA activates multiple pattern recognition receptors (PRRs), including TLR7/8 in endosomes and RIG-I in the cytoplasm, creating a robust inflammatory milieu characterized by high levels of type I interferons [1]. This environment promotes dendritic cell maturation and enhances cross-priming of CD8+ T cells, critical for antitumor immunity. The observed IL-7 elevation further supports T-cell survival and expansion [1].

In contrast, nucleoside-modified mRNA minimizes PRR activation through its altered molecular structure, reducing interferon responses but permitting unhindered translation of the encoded antigen. The cytokine profile shifts toward LNP-driven IL-6 and TNF production, which supports T follicular helper cell development and antibody responses [1]. This fundamental difference in innate immune engagement dictates the quality and balance of subsequent adaptive immunity, with implications for cancer vaccine efficacy.

Essential Research Reagents and Methodologies

Table 3: Key Research Reagent Solutions for mRNA Cancer Vaccine Development

Research Reagent	Function & Application	Experimental Considerations
Lipid Nanoparticles (LNPs)	Protect mRNA and facilitate cellular uptake [85] [27]	Composition affects cytokine induction; dose-dependent with mRNA [1]
Poly-ICLC	TLR3 agonist; enhances vaccine immunogenicity as adjuvant [86]	Used in NeoVax platform to stimulate dendritic cells [86]
Montanide ISA 51	Water-in-oilemulsion; enhances antigen presentation [86]	Added to NeoVaxMI to create depot effect and improve immune responses [86]
Immune Checkpoint Inhibitors	Block inhibitory receptors on T cells (e.g., anti-PD-1) [87] [88]	Synergizes with mRNA vaccines by reversing tumor-mediated suppression [87] [88]
Single-Cell RNA Sequencing	High-resolution immune profiling of vaccine responses [86]	Identifies vaccine-induced T cell clones and tumor infiltration [86]

The comparative analysis of modified and unmodified mRNA platforms reveals a complex trade-off between translation efficiency and immune activation. While unmodified mRNA creates a more favorable microenvironment for cytotoxic T-cell responses through potent type I interferon signaling, modified mRNA offers advantages in antigen production and antibody induction. The optimal choice depends on the specific cancer context, desired immune response, and combination therapy strategy.

Future research should focus on structure-activity relationships of different nucleoside modifications, LNP composition optimization, and rational combination with immunomodulatory agents. The emerging concept of non-specific mRNA vaccines that reset the tumor microenvironment without targeting tumor antigens represents a promising new direction [89] [90]. As the field advances, personalized cancer vaccines will likely incorporate both platforms based on individual tumor immunogenicity and host factors, moving toward increasingly precise cancer immunotherapy strategies.

Conclusion

The choice between modified and unmodified mRNA is not a binary one but a strategic decision dictated by the therapeutic objective. Modified mRNA, with its reduced innate immunogenicity and enhanced translation, is the established platform for applications requiring high, transient protein expression, such as prophylactic vaccines. In contrast, unmodified mRNA may offer advantages in oncology by providing a more robust innate immune activation to counteract immunosuppressive tumor microenvironments. Future directions must focus on decoding the nuanced synergies between mRNA chemistry and LNP composition, developing novel modifications that further decouple translation efficiency from immune recognition, and advancing targeted delivery systems to minimize systemic reactogenicity. The continued refinement of these platforms, guided by robust comparative data, will unlock the full potential of mRNA therapeutics across a wider spectrum of human diseases.

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