Evidence map›Paper›PMID 42038030›Full record

ArticleJournal of Cancer2026

A squamous epithelial gene interaction perturbation network index for risk stratification in esophageal squamous cell carcinoma.

Chen Zhang, Huimin Wang, Huaping Wang, Xuexin Wang, Shan Tang, Feng Li, Li-Dong Wang, Jianqiu Sheng

Abstract read
In one paragraph

Article in Journal of 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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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Chen ZhangMedical School of Chinese PLA, Beijing, 100853, China.
Huimin WangDepartment of Oncology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Huaping WangDepartment of Gastroenterology, the Seventh Medical Center, Chinese PLA General Hospital, Beijing, 100700, China.
Xuexin WangMedical School of Chinese PLA, Beijing, 100853, China.
Shan TangDepartment of Gastroenterology, the Seventh Medical Center, Chinese PLA General Hospital, Beijing, 100700, China.
Feng LiDepartment of Thoracic Surgery, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Li-Dong WangHenan Key Laboratory for Esophageal Cancer Research and State Key Laboratory of Metabolic Dysregulation & Prevention and Treatment of Esophageal Cancer of the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Jianqiu ShengMedical School of Chinese PLA, Beijing, 100853, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal squamous cell carcinoma (ESCC) exhibits substantial molecular heterogeneity and unfavorable clinical outcomes. Current transcriptomic advances are shifting the focus from static gene expression profiles to the dynamic architecture of gene interaction networks. However, gene interaction perturbation signatures specific to ESCC remain poorly understood. This study aimed to develop a network-informed prognostic index derived from malignant epithelial cell signatures. In-house single-cell RNA sequencing data from 15 ESCC samples from the First Affiliated Hospital of Zhengzhou University were analyzed to identify dysregulated genes in malignant squamous epithelial cells. Then, a gene interaction perturbation network index (GIPNI) was constructed by systematically evaluating 75 combinations of machine-learning methods and validated across 3 independent cohorts. Associations between the GIPNI and genomic alterations, immune-related characteristics, and therapeutic response were also evaluated. Results showed ESCCs with high-GIPNI scores were associated with advanced clinicopathological features and overactivated mitotic cell cycle and epithelial cell differentiation pathways. Immune profiling suggested that low-GIPNI tumors had a more immune-infiltrated microenvironment. Notably, high-GIPNI ESCCs were associated with higher sensitivity to some common chemotherapeutic agents. Overall, the GIPNI provides a network-informed and malignant squamous cell-oriented framework for prognostic assessment in ESCC. This integrative approach may facilitate risk stratification and provide insights into individualized therapeutic strategies.

Indexed as

esophageal squamous cell carcinomagene interaction perturbationsmachine learningrisk stratificationsingle-cell RNA sequencing

Identifiers

PMID42038030
PMCPMC13105158

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