Evidence map›Paper›PMID 42469881›Full record

ArticleBiology direct2026

A senescence-associated gene signature predicts radiotherapy prognosis in non-small cell lung cancer and identifies CSF1 as a target to potentiate radioimmunotherapy.

Shaochuan Liu, Yuhan Zhang, Liuze Li, Huanhuan Wang, Hao Yuan, Deyi Zhang, Donghe Zhao, Yong Guan, Zhiyong Yuan

Abstract read
In one paragraph

Article in Biology direct, 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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1 · What the graph read from it

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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

9 authors.

Shaochuan Liu *Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Yuhan Zhang *Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Liuze Li *Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Huanhuan WangTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Hao YuanTianjin Foreign Languages School Affiliated to Tianjin Foreign Studies University, Tianjin, 300060, China.
Deyi ZhangTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Donghe ZhaoTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China.
Yong GuanTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China. ALAN099015@163.com.
Zhiyong YuanTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, 300060, China. zyuan@tmu.edu.cn.

Funding

China Postdoctoral Science Foundation 2024M752391National Natural Science Foundation of China 82473240National Natural Science Foundation of China 82503645
6 · The paper itself

Abstract

The role of cellular senescence as a tumor-associated hallmark and therapeutic target in influencing radiotherapy or radioimmunotherapy outcomes remains incompletely understood. To address this, we developed a senescence-associated gene signature to predict prognosis in non‑small cell lung cancer (NSCLC) patients treated with radiotherapy. A risk model based on nine genes-including COL4A1 and CSF1-effectively stratified patients into high‑ and low‑risk groups. High‑risk patients exhibited significantly poorer overall survival and a tumor microenvironment characterized by reduced immune infiltration and an immune‑excluded phenotype. CSF1 was identified as a pivotal gene within this signature. Mechanistically, radiotherapy induces the expansion of a CSF1‑high‑expressing exhausted T‑cell population, which exhibits characteristics of both exhausted and senescent T cells and forms a positive feedback loop with M2‑like macrophages, thereby reinforcing the immunosuppressive microenvironment. Preclinical studies demonstrated that combining a CSF1‑neutralizing antibody with radiotherapy and anti‑PD‑1 therapy effectively reduced exhausted T cells and M2 macrophages, leading to a significant enhancement in therapeutic efficacy. Taken together, our work establishes a nine‑gene signature for risk stratification in NSCLC and provides proof‑of‑concept that targeting CSF1 can potentiate radioimmunotherapy, offering a novel translational strategy for improving patient survival.

Indexed as

Carcinoma, Non-Small-Cell LungCellular SenescenceLung NeoplasmsRadioimmunotherapyAnimalsCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansPrognosisT-Cell ExhaustionTumor MicroenvironmentCSF1ImmunotherapyNon-small cell lung cancerRadiotherapySenescence-associated gene signature

Identifiers

PMID42469881
PMCPMC13663099

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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.