Identification of neutrophil‐related genes and development of a prognostic model for cholangiocarcinoma

鉴定(生物学) 基因 生物 计算生物学 医学 生态学 遗传学
作者
Jianfeng Li,Jianhui Xiong,Wei Lin,Mengyang Zhang,Jian Yi,Longzi Liu
出处
期刊:Journal of Gene Medicine [Wiley]
卷期号:26 (1) 被引量:2
标识
DOI:10.1002/jgm.3569
摘要

Cholangiocarcinoma is a prevalent gastrointestinal tumor with limited effective early diagnostic methods. The role of neutrophils in the context of cholangiocarcinoma remains largely unexplored. A comprehensive analysis was performed on a cohort of cholangiocarcinoma samples (TCGA-CHOL) from the TCGA database to investigate the relationship between cholangiocarcinoma and neutrophils. Methodologies included single-sample gene set enrichment analysis (ssGSEA), differential expression analysis, weighted gene co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA). The study identified a significant decrease of neutrophils in cholangiocarcinoma via ssGSEA. WGCNA and differential expression analysis led to the identification of a neutrophil-related gene module comprised of 1059 genes. Cluster 1, showing a higher proportion of neutrophils, was linked to better survival outcomes. GSEA disclosed downregulation of complement, inflammatory response and interferon response pathways in Cluster 2, hinting at possible cholangiocarcinoma development triggers. A notable upregulation of PD1, PD-L1 and CTLA4 was observed in Cluster 1, suggesting potential benefits from immunotherapy. A prognostic model was developed based on clinical data and expression levels of three prognostic genes (SOWAHD, TNFAIP8 and EBF3) showing satisfactory discrimination, calibration and clinical benefits. An overexpression of TNFAIP8 in cholangiocarcinoma cells was found, with its knockdown significantly inhibiting cell proliferation and migration. This study elucidates a neutrophil-related gene module and prognostic genes, offering insights into the role of neutrophils in cholangiocarcinoma development and progression. It also introduces a clinical prediction model for enhanced prognosis assessment. These findings may lay the groundwork for the development of innovative therapeutic strategies in cholangiocarcinoma treatment.
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