Evidence map›Paper›PMID 41744786›Full record

ReviewCells2026

mRNA and Peptide Vaccines in Melanoma-Current Landscape and Future Direction.

Jiaxing Jason Qin, Yang Wang, Shahneen Sandhu

Abstract readReview
In one paragraph

Review in Cells, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. Review
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

3 authors.

Jiaxing Jason QinDepartment of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.ORCID 0000-0002-8428-6311
Yang WangDepartment of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.ORCID 0000-0002-9365-3611
Shahneen SandhuDepartment of Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.ORCID 0000-0002-8660-4475

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors have transformed the treatment landscape for advanced melanoma in the past 15 years, delivering unprecedented and durable survival benefits. This success has propelled the development of complementary immune-directed therapies, including cancer vaccines. Among these, synthetic long peptide (SLP) and mRNA vaccine platforms have emerged as highly promising. Advances in next-generation sequencing technology, alongside computational neoantigen algorithm predictions, have enabled patient-specific neoantigen identification to improve vaccine immunogenicity and enhance therapeutic efficacy. Off-the-shelf and personalised SLP and mRNA vaccines have demonstrated the ability to induce robust antigen-specific T-cell responses and modulate the tumour microenvironment. Mechanistically, cancer vaccines synergise with immune checkpoint inhibition. This review outlines the current clinical development of mRNA and peptide vaccines in melanoma, highlighting the significant promise to synergise with immune checkpoint inhibition to enhance efficacy without adding to the systemic toxicity profile. The neoadjuvant setting, characterised by intact tumour antigens and draining lymphatic architecture, offers a compelling biological context for leveraging cancer vaccines for enhanced immune priming and response assessment. Collectively, the rapid advances in technology and emerging clinical data position cancer vaccines as a promising therapy capable of improving immunotherapy in Stage III and IV melanoma.

Indexed as

melanomamRNA vaccinesneoadjuvant therapypeptide vaccinestumour immunology

Identifiers

PMID41744786
PMCPMC12939437

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.