Evidence map›Paper›PMID 41646182›Full record

ArticleSports medicine and health science2026

An exerkine-based prognostic index reveals immune heterogeneity and predicts outcomes across 33 cancers.

Jiawei Du, Jinghua Hou

Abstract readLetter
In one paragraph

Article in Sports medicine and health science, 2026. 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

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Jiawei DuKey Laboratory of Sports and Physical Fitness of the Ministry of Education, Beijing Sport University, Beijing, China.
Jinghua HouKey Laboratory of Sports and Physical Fitness of the Ministry of Education, Beijing Sport University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Exercise exerts tumor-suppressive effects across multiple malignancies, partly through exerkines-exercise-induced secreted factors with immunomodulatory and metabolic functions. However, the prognostic relevance of exerkines across cancer types remains unclear, and the molecular determinants of exercise responsiveness are poorly defined. Methods: We systematically profiled 183 curated exerkine-related genes across 33 cancer types from The Cancer Genome Atlas (TCGA) using non-negative matrix factorization (NMF) to define molecular subtypes. Prognostic significance was evaluated via Kaplan-Meier analysis. For five cancers with consistent survival divergence (LGG, KIRC, LUAD, PAAD, ACC), we developed an Exerkine Prognostic Index (EPI) using LASSO Cox regression and validated its predictive performance through time-dependent ROC analysis. Immune cell infiltration (CIBERSORT), stromal/immune scores (ESTIMATE), and immune checkpoint expression were assessed to characterize immune landscape differences between EPI subgroups. Results: Exerkine-based NMF clustering identified prognostically distinct subtypes in 25 cancers. The EPI robustly stratified patients into high- and low-risk groups with significant differences in overall survival ( Discussion: Our findings reveal that exerkine expression patterns capture biologically and clinically relevant heterogeneity across cancers. The EPI provides a robust molecular tool to stratify patients by prognosis and immune contexture, offering insights into differential exercise responsiveness. Conclusions: Exerkines represent promising biomarkers for risk stratification and precision-guided exercise interventions in oncology.

Indexed as

Cancer prognosisExercise oncologyExerkinesImmune checkpointMachine learningTumor microenvironment

Identifiers

PMID41646182
PMCPMC12869029

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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.