Evidence map›Paper›PMID 41463470›Full record

ArticleBiology2025

Multi-Omics Tumor Immunogenicity Score Predicts Immunotherapy Outcome and Survival.

Axel Gschwind, Nadja Ballin, Alexander Ott, Andrea Forschner, Amelie Knapp, Öznur Öner, Michael Bitzer, Ghazaleh Tabatabai, Andreas Hartkopf, Thorben Groß and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Axel GschwindInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.ORCID 0000-0003-1181-0335
Nadja BallinInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.
Alexander OttInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.ORCID 0009-0003-5088-2216
Andrea ForschnerCenter for Dermatooncology, Department of Dermatology, University of Tübingen, 72076 Tübingen, Germany.ORCID 0000-0002-6185-4945
Amelie KnappInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.ORCID 0009-0005-9224-3214
Öznur ÖnerCenter for Personalized Medicine Tübingen, University of Tübingen, 72076 Tübingen, Germany.
Michael BitzerCenter for Personalized Medicine Tübingen, University of Tübingen, 72076 Tübingen, Germany.
Ghazaleh TabatabaiCenter for Neurooncology, University of Tübingen, 72076 Tübingen, Germany.
Andreas HartkopfDepartment of Women's Health, University of Tübingen, 72076 Tübingen, Germany.ORCID 0000-0003-1227-1118
Thorben GroßDepartment of Medical Oncology and Pneumology, University of Tübingen, 72076 Tübingen, Germany.
Markus ReitmajerCenter for Dermatooncology, Department of Dermatology, University of Tübingen, 72076 Tübingen, Germany.ORCID 0000-0002-7134-1043
Christopher SchroederInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.
Stephan OssowskiInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.ORCID 0000-0002-7416-9568
Sorin Armeanu-EbingerInstitute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTumor immunogenicity is a concept for modeling the susceptibility of tumors to immune checkpoint inhibitors (ICIs) and other immunotherapies. Single biomarkers, such as tumor mutation burden (TMB) or

methodsSeveral immunogenicity biomarkers, including TMB, neoantigen burden, T-cell receptor repertoire,

resultsMOTIscore achieved results similar to those of the ML model in predicting ICI in melanoma and gastric cancer, with both outperforming TMB. Gastric cancer and melanoma patients with high MOTIscores had a significantly extended overall and progression-free survival. Gene set enrichment analysis revealed the enrichment of immune-related pathways in patients with high MOTIscores. Differential expression analysis between patients with high and low immunogenicity identified highly expressed C-X-C motif chemokine ligands as important characteristics associated with successful ICI therapy and significantly improved PFS. MOTIscores varied widely across cancers treated in the molecular tumor board at our hospital and showed distinct distributions between non-immunogenic and immunogenic cancer types.

conclusionsMOTIscore demonstrated improved ICI outcome predictions compared to single-omics biomarkers. Patients with higher tumor immunogenicity also show significantly improved OS and PFS in melanoma and gastric cancer. The results demonstrate the potential use of the MOTIscore to prioritize ICI in personalized cancer treatment. However, ICI outcomes and survival should be investigated in prospective studies, and additional cancer types and larger patient cohorts are needed.

Indexed as

anti-PD1bulk RNA sequencingimmune checkpoint inhibitorsimmunotherapymulti-omicsnext-generation sequencingtumor immunogenicitywhole exome sequencing

Identifiers

PMID41463470
PMCPMC12730895

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