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PMID: 41127022 Published · epublish English

Unraveling the role of coagulation-related genes in esophageal squamous cell carcinoma: development of a prognostic model and exploration of potential clinical significance.

Frontiers in oncology ·Vol. 15 ·2025-00-00

Deng L, Fang C, Zhang W, Zhu Z, Gu Y, Gu P, Tan X, Yuan J, Feng Y, Ma H

Abstract

Esophageal squamous cell carcinoma (ESCC), the most common form of esophageal cancer, is associated with high incidence and mortality rates, representing a major public health challenge. Although previous research has suggested a link between coagulation dysfunction and cancer progression, the precise role of coagulation-related genes in ESCC remains poorly understood. To investigate this, we integrated various multi-omics datasets, including mRNA expression data from TCGA and GEO, single-cell RNA sequencing data, as well as DNA mutation and methylation profiles. By applying machine learning algorithms, we identified coagulation-related genes in ESCC and developed a predictive model with clinical relevance. Further analyses were performed to assess the biological functions, prognostic significance, clinical implications, immune interactions, and drug sensitivity associated with these genes. In this study, we identified seven coagulation feature genes-RAP1B, SRC, CFHR4, PLA2G4A, ORAI1, RINT1, and SPTB-in ESCC. A prognostic model based on these genes effectively stratified patients and demonstrated robust predictive value for clinical outcomes. Further analysis revealed distinct differences in immune function, drug sensitivity, and disease-related pathways between high- and low-risk groups. Among these genes, RINT1 emerged as a key factor, with pan-cancer analysis highlighting its potential relevance across multiple tumor types. We used immunohistochemistry, qRT-PCR, and Western blot to validate its differential expression in ESCC, highlighting its potential as a therapeutic target. Our findings emphasize the significance of coagulation-related genes in ESCC progression and their involvement in critical biological and immune processes. The proposed prognostic model provides a valuable tool for risk assessment. Additionally, the identification of RINT1 provides new insights as a potential prognostic biomarker and candidate for future therapeutic investigation in ESCC patients.

Keywords
RINT1 coagulation esophageal squamous cell carcinoma genomic instability machine learning prognosis
Article Info
Journal
Frontiers in oncology
Abbr.
Front Oncol
ISSN
2234-943X
Published
2025-00-00
Language
English
Country/Region
Switzerland
NLM ID
101568867
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