Evidence map›Paper›PMID 39848687›Full record

ReviewJournal for immunotherapy of cancer2025

Leveraging mRNA technology for antigen based immuno-oncology therapies.

Charalampos S Floudas, Siranush Sarkizova, Michele Ceccarelli, Wei Zheng

Abstract readReview
In one paragraph

Review in Journal for immunotherapy of cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Charalampos S FloudasCenter for Immuno-Oncology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA charalampos.floudas@nih.gov.ORCID http://orcid.org/0000-0002-0020-237X
Siranush SarkizovaModerna, Inc, Cambridge, Massachusetts, USA.ORCID http://orcid.org/0000-0003-2530-8610
Michele CeccarelliSylvester Comprehensive Cancer Center, Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, Florida, USA.ORCID http://orcid.org/0000-0002-4702-6617
Wei ZhengModerna, Inc, Cambridge, Massachusetts, USA.ORCID http://orcid.org/0000-0002-9196-2795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The application of messenger RNA (mRNA) technology in antigen-based immuno-oncology therapies represents a significant advancement in cancer treatment. Cancer vaccines are an effective combinatorial partner to sensitize the host immune system to the tumor and boost the efficacy of immune therapies. Selecting suitable tumor antigens is the key step to devising effective vaccinations and amplifying the immune response. Tumor neoantigens are de novo epitopes derived from somatic mutations, avoiding T-cell central tolerance of self-epitopes and inducing immune responses to tumors. The identification and prioritization of patient-specific tumor neoantigens are based on advanced computational algorithms taking advantage of the profiling with next-generation sequencing considering factors involved in human leukocyte antigen (HLA)-peptide-T-cell receptor (TCR) complex formation, including peptide presentation, HLA-peptide affinity, and TCR recognition. This review discusses the development and clinical application of mRNA vaccines in oncology, with a particular focus on recent clinical trials and the computational workflows and methodologies for identifying both shared and individual antigens. While this review centers on therapeutic mRNA vaccines targeting existing tumors, it does not cover preventative vaccines. Preclinical experimental validations are crucial in cancer vaccine development, but we emphasize the computational approaches that facilitate neoantigen selection and design, highlighting their role in advancing mRNA vaccine development. The versatility and rapid development potential of mRNA make it an ideal platform for personalized neoantigen immunotherapy. We explore various strategies for antigen target identification, including tumor-associated and tumor-specific antigens and the computational tools used to predict epitopes capable of eliciting strong immune responses. We address key design considerations for enhancing the immunogenicity and stability of mRNA vaccines, as well as emerging trends and challenges in the field. This comprehensive overview highlights the therapeutic potential of mRNA-based cancer vaccines and underscores ongoing research efforts aimed at optimizing these therapies for improved clinical outcomes.

Indexed as

Antigens, NeoplasmCancer VaccinesImmunotherapyNeoplasmsRNA, MessengerHumansAntigens, NeoplasmCancer VaccinesRNA, MessengerGenomeImmunotherapyMajor histocompatibility complex - MHCT cell Receptor - TCRVaccine

Identifiers

PMID39848687
PMCPMC11784169

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.