Evidence map›Paper›PMID 41530714›Full record

ArticleBMC cancer2026

T-cell exhaustion indicator characterizes the tumor microenvironment landscape and predicts colon adenocarcinoma prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.

Haifeng Sun, Ning Hu, Shaowei Ma, Yu Zheng, Ren Niu, Wenya Zhu, Shaofan Qiu

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Article in BMC cancer, 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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5 · Who and what money

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7 authors.

Haifeng Sun *Department of Colorectal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Ning Hu *Department of Surgical Oncology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Shaowei Ma *Department of Gastrointestinal Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yu Zheng *Department of Gastrointestinal Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Ren NiuSecond Department of Oncology, The Second Hospital of Hebei Medical University, Shijiazhuang, China. niurenhb2h@163.com.
Wenya ZhuDepartment of Geriatric, The Sixth Medical Center, Chinese PLA General Hospital, Beijing, China. zhuwenya_1985@163.com.
Shaofan QiuDepartment of Gastrointestinal Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang, China. qiushaofanHB2H@126.com.

Funding

Innovation Cultivation Fund PLA General Hospital Sixth Medical Center CXPY202205Medical Science Research Project of Hebei 20220104
6 · The paper itself

Abstract

backgroundColon adenocarcinoma (COAD) is the most common type of colon cancer, posing a significant threat to public health. In the tumor microenvironment (TME), T cells differentiate into terminally exhausted T cells (TEX), but the relationship between TEX and COAD has not been fully elucidated.

methodsTo identify TEX-related signatures, we integrated transcriptomic data from TCGA and GEO databases (GSE103479, GSE17536). A prognostic model was constructed using GSVA, univariate Cox, LASSO, and random forest algorithms. The tumor immune microenvironment was characterized using CIBERSORTx and GSEA. The functional role of FAT4 was validated in vitro using FAT4-knockdown COAD cell lines assessed by flow cytometry and RT-qPCR.

resultsWe developed a prognostic signature based on five TEX-related genes (IL21R, FCRL3, TIFAB, TNFSF14, SLAMF1). Patients in the high-risk group showed significantly poorer overall survival and distinct immune cell infiltration patterns, characterized by decreased CD8 + T cells and M1 macrophages. At single-cell resolution, CD8 + TEX cells exhibited high expression of immune checkpoints like LAG3. Furthermore, in vitro experiments demonstrated that knockdown of FAT4, a frequently mutated gene in COAD, promoted apoptosis and induced G0/G1 cell cycle arrest in COAD cells.

conclusionWe proposed a non-invasive prediction method based on TEX-related genes, which effectively predicts survival outcomes and therapeutic responses in COAD patients. Additionally, FAT4 was found to regulate proliferative and apoptotic phenotypes in COAD.

Indexed as

AdenocarcinomaColonic NeoplasmsTumor MicroenvironmentBiomarkers, TumorCell Line, TumorGene Expression Regulation, NeoplasticHumansPrognosisRNA-SeqSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisT-Cell ExhaustionBiomarkers, TumorCD8 + T cellsColon adenocarcinomaFAT4T cell exhaustionTumor microenvironment

Identifiers

PMID41530714
PMCPMC12888615

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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.