Evidence map›Paper›PMID 40544380›Full record

ArticleDiscover oncology2025

Identification and characterization of survival-dependent genes in esophageal cancer via the DepMap database: unraveling their association with immune infiltration.

Xiangrong Yao, Junyan He, Wentao Xiao, Limou Chen, Fangzhu Xiao

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Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiangrong Yao *School of Public Health, University of South China, Hengyang City, Hunan Province, China.
Junyan He *Department of Oncology Radiotherapy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang City, Hunan Province, China.
Wentao XiaoDepartment of Radiation Oncology, Medical School of Nantong university, Affiliated Hospital of Nantong University, Nantong university, Nantong city, Jiangsu Province, China.
Limou ChenSchool of Public Health, Xiangnan University, ChenZhou City, Hunan Province, China.
Fangzhu XiaoSchool of Public Health, University of South China, Hengyang City, Hunan Province, China. xfzhunh@163.com.

Funding

Ecology and Environment Department of Hunan HBKYXM-2023021
6 · The paper itself

Abstract

backgroundEsophageal cancer ranks as the 11th most diagnosed cancer worldwide and the 7th leading cause of cancer-related deaths, mainly due to late-stage diagnosis. Identifying novel biomarkers is essential for enhancing prognostic evaluations and targeting patients for immunotherapy.

methodsWe used the DepMap database to identify survival-dependent genes in esophageal carcinoma cells. A prognostic model was developed using univariate and multivariate Cox regression and LASSO, validated with the GEO dataset. WGCNA and GSEA analyses were conducted to explore mechanisms, alongside ESTIMATE and ssGSEA for prognosis.

resultsWe constructed a novel four-gene prognostic signature (CPSF6, IGBP1, MTG2, TCP1) based on SDG expression and survival data. This signature stratified esophageal cancer patients into high- and low-risk groups with significantly different survival, with the high-risk group showing shorter survival. WGCNA and GSEA analyses linked prognosis to immune pathways, including interferon-γ response and IL6-JAK-STAT3 signaling. ssGSEA revealed reduced infiltration of 19 immune cell types in high-risk patients, and ESTIMATE analysis confirmed the association between immune infiltration and poor prognosis.

conclusionThis study establishes a four-gene survival signature for esophageal cancer that distinguishes high-risk from low-risk populations, providing novel prognostic indicators. Immune response pathways were downregulated in high-risk patients, offering potential targets for understanding esophageal cancer mechanisms and developing immunotherapeutic strategies.

Indexed as

BiomarkersEsophageal CancerImmune infiltrationPrognostic model

Identifiers

PMID40544380
PMCPMC12183143

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