Evidence map›Paper›PMID 41031372›Full record

ArticleiScience2025

NovumRNA: Accurate prediction of non-canonical tumor antigens from RNA sequencing data.

Markus Ausserhofer, Dietmar Rieder, Manuel Facciolla, Raphael Gronauer, Giorgia Lamberti, Rebecca Lisandrelli, Serena Pellegatta, Zlatko Trajanoski, Francesca Finotello

Abstract read
In one paragraph

Article in iScience, 2025. 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. Article
  2. Article
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

9 authors.

Markus AusserhoferDepartment of Molecular Biology, Digital Science Center (DiSC), University of Innsbruck, 6020 Innsbruck, Tyrol, Austria.
Dietmar RiederInstitute of Bioinformatics, Medical University of Innsbruck, Tyrol, Innsbruck, Austria.
Manuel FacciollaUnit of Immunotherapy of Brain Tumors, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
Raphael GronauerInstitute of Bioinformatics, Medical University of Innsbruck, Tyrol, Innsbruck, Austria.
Giorgia LambertiInstitute of Bioinformatics, Medical University of Innsbruck, Tyrol, Innsbruck, Austria.
Rebecca LisandrelliInstitute of Bioinformatics, Medical University of Innsbruck, Tyrol, Innsbruck, Austria.
Serena PellegattaUnit of Immunotherapy of Brain Tumors, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
Zlatko TrajanoskiInstitute of Bioinformatics, Medical University of Innsbruck, Tyrol, Innsbruck, Austria.
Francesca FinotelloDepartment of Molecular Biology, Digital Science Center (DiSC), University of Innsbruck, 6020 Innsbruck, Tyrol, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-canonical tumor-specific antigens (ncTSAs) can expand the pool of targets for cancer immunotherapy, but require robust and comprehensive computational pipelines for their prediction. Here, we present NovumRNA, a fully automated Nextflow pipeline for predicting different classes of ncTSAs from patients' RNA sequencing data. We extensively benchmarked NovumRNA using publicly available and newly generated datasets, demonstrating the robustness of its analytical modules and predictions. NovumRNA analysis of RNA-seq data from colorectal cancer organoids and patients' tumor samples revealed comparable ncTSA potential for microsatellite stable and unstable tumors and candidate therapeutic targets for patients with low tumor mutational burden. Finally, our investigation of glioblastoma cell lines demonstrated increased ncTSAs burden upon indisulam treatment, and detection by NovumRNA of therapy-induced ncTSAs, which we could validate experimentally. These findings underscore the potential of NovumRNA for identifying synergistic drugs and novel therapeutic targets for immunotherapy, which could ultimately extend its benefit to a broader patient population.

Indexed as

cancergenomics

Identifiers

PMID41031372
PMCPMC12478123

What OpenQuestion holds

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Registered trials

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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.