Evidence map›Paper›PMID 41583482›Full record

ArticleFrontiers in immunology2025

Tumor mutational burden predicts neoantigen profiles and immunotherapy response in microsatellite stable tumors across different cancer types.

Olesia Kondrateva, Tugce Bilgin Sonay, Inti Zlobec, Maria Anisimova

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Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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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.

Olesia KondratevaInstitute of Computational Life Sciences, School of Life Sciences and Facility Management, Zürich University of Applied Sciences (ZHAW), Waedenswil, Switzerland.
Tugce Bilgin SonayInstitute of Computational Life Sciences, School of Life Sciences and Facility Management, Zürich University of Applied Sciences (ZHAW), Waedenswil, Switzerland.
Inti ZlobecInstitute of Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.
Maria AnisimovaInstitute of Computational Life Sciences, School of Life Sciences and Facility Management, Zürich University of Applied Sciences (ZHAW), Waedenswil, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Immunotherapy has shown positive response in many patients with microsatellite instable (MSI-H) tumors, but its effectiveness in microsatellite stable (MSS) tumors remains limited. We hypothesize that tumor mutational burden (TMB) can help identify a biologically distinct subset of MSS tumors that can benefit from immunotherapy. Methods: We analyzed the molecular characteristics, including mutational landscape, mutational signatures, immune cell profiles and neoantigen load of MSS tumors with high TMB using data from colorectal cancer datasets (TCGA-COAD and TCGA-READ). After that, we extended these findings across other cancer types with MSI classification, further supporting the potential of using TMB as a biomarker for predicting immunotherapy response in MSS tumors. Results: Our results show that MSS tumors with TMB greater than 50 mutations per megabase have POLE gene mutations, which lead to hypermutation. These hypermutated tumors show immune cell signatures that are more similar to MSI-H tumors, rather than MSS tumors with low TMB. We also found that MSS tumors with high TMB have a substantially higher number of neoantigens compared to low-TMB MSS tumors, suggesting they may respond better to immunotherapy, including a high proportion of predicted high-affinity neoantigens. Discussion: These findings support the clinical relevance of TMB as a biomarker for neoantigen prediction and immunotherapy-relevant features in MSS tumors.

Indexed as

Antigens, NeoplasmBiomarkers, TumorImmunotherapyMicrosatellite InstabilityMutationNeoplasmsHumansMicrosatellite RepeatsTreatment OutcomeAntigens, NeoplasmBiomarkers, Tumorcancer biomarkersimmunotherapymicrosatellite stabilityMSSneoantigensPOLETMBtumor mutational burden

Identifiers

PMID41583482
PMCPMC12824007

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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.