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

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.

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Journal
Biology Direct
Published
2026-07-17
DOI
https://doi.org/10.1186/s13062-026-00901-5
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00

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article

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, D C Zhang, Y Zhang, Huanhuan Wang et al.
Biology Direct
Cancer Immunotherapy and Biomarkers
article

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, D C Zhang, Y Zhang, Huanhuan Wang, Li Li, Donghe Zhao, Zhiyong Yuan, Yong Guan, Hao Yuan
article en

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.

Biology Direct
Tianjin Foreign Studies University (CN), Tianjin Medical University Cancer Institute and Hospital (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
No poverty
Openalex Percentile: Top 11%
Cancer Immunotherapy and Biomarkers
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