Evidence map›Paper›PMID 41601019›Full record

ReviewVaccines2026

Hidden Targets in Cancer Immunotherapy: The Potential of "Dark Matter" Neoantigens.

Francois Xavier Rwandamuriye, Alec J Redwood, Jenette Creaney, Bruce W S Robinson

Abstract readReview
In one paragraph

Review in Vaccines, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

4 authors.

Francois Xavier RwandamuriyeNational Centre for Asbestos Related Diseases, Institute for Respiratory Health, Nedlands, WA 6009, Australia.ORCID 0000-0002-3456-3931
Alec J RedwoodNational Centre for Asbestos Related Diseases, Institute for Respiratory Health, Nedlands, WA 6009, Australia.ORCID 0000-0001-8601-8292
Jenette CreaneyNational Centre for Asbestos Related Diseases, Institute for Respiratory Health, Nedlands, WA 6009, Australia.ORCID 0000-0002-9391-9395
Bruce W S RobinsonNational Centre for Asbestos Related Diseases, Institute for Respiratory Health, Nedlands, WA 6009, Australia.ORCID 0000-0002-5281-7923

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of cancer immunotherapies has transformed cancer treatment paradigms, yet durable and tumour-specific responses remain elusive for many patients. Neoantigens, immunogenic peptides arising from tumour-specific genomic alterations, have emerged as promising cancer vaccine targets. Early-phase clinical trials using different vaccine platforms, including mRNA, peptide, DNA, and viral vector-based personalised cancer vaccines, have demonstrated the feasibility of targeting neoantigens, with early signals of prolonged survival in some patients. Most current vaccine strategies focus on canonical neoantigens, typically derived from exonic single-nucleotide variants (SNVs) and small insertions/deletions (INDELs), yet this represents only a fraction of the potential neoantigen repertoire. Evidence now shows that non-canonical neoantigens, arising mostly from alternative splicing, intron retention, translation of non-coding RNAs, gene fusions, and retroelement activation, broaden the antigenic landscape, with the potential for increasing tumour specificity and immunogenicity. In this review, we explore the biology of non-canonical neoantigens, the technological advances that now enable their systematic detection, and their potential to inform next-generation personalised cancer vaccines.

Indexed as

crypticdark mattermRNAneoantigennon-canonicalpeptidevaccine

Identifiers

PMID41601019
PMCPMC12846397

What OpenQuestion holds

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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 OpenQuestion graph.