Weighted gene co-expression network analysis for hub genes in colorectal cancer.

IF 3.6 3区医学 Q2 PHARMACOLOGY & PHARMACY

Pharmacological Reports Pub Date : 2024-02-01 Epub Date: 2023-12-27 DOI:10.1007/s43440-023-00561-6

Zheng Xu, Jianing Wang, Guosheng Wang

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引用次数: 0

Abstract

Background: This study is designed to explore hub genes participating in colorectal cancer (CRC) development through weighted gene co-expression network analysis (WGCNA).

Methods: Expression profiles of CRC and normal samples were retrieved from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA), and were subjected to WGCNA to filter differentially expressed genes with significant association with CRC. Functional enrichment analysis and protein-protein interaction (PPI) analysis were carried out to filter the candidate genes, further and survival analysis was performed for the candidate genes to obtain potential regulatory hub genes in CRC. Expression analysis was conducted for the candidate genes and a multifactor model was established.

Results: After differential analysis and WGCNA, 289 candidate genes were filtered from the GEO and TCGA. Further functional enrichment analysis demonstrated possible regulatory pathways and functions. PPI analysis filtered 15 hub genes and survival analysis indicated a significant correlation of CLCA1, CLCA4, and CPT1A with prognosis of patients with CRC. The multifactor Cox risk model established based on the three genes revealed that if the three genes were a gene set, they had well predictive capacity for the prognosis of patients with CRC.

Conclusions: CLCA1, CLCA4, and CPT1A express at low levels in CRC and function as core anti-tumor genes. As a gene set, they can predict prognosis well.

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大肠癌中枢基因的加权基因共表达网络分析

背景：本研究旨在通过加权基因共表达网络分析（WGCNA）探索参与结直肠癌（CRC）发病的枢纽基因：本研究旨在通过加权基因共表达网络分析（WGCNA）探索参与结直肠癌（CRC）发生的枢纽基因：从基因表达总库（Gene Expression Omnibus，GEO）和癌症基因组图谱（Cancer Genome Atlas，TCGA）中获取 CRC 和正常样本的表达谱，并对其进行 WGCNA 分析，筛选出与 CRC 有显著关联的差异表达基因。对候选基因进行功能富集分析和蛋白相互作用分析，筛选出候选基因，并对候选基因进行生存分析，以获得 CRC 潜在的调控枢纽基因。对候选基因进行了表达分析，并建立了多因素模型：结果：经过差异分析和 WGCNA，从 GEO 和 TCGA 中筛选出 289 个候选基因。进一步的功能富集分析表明了可能的调控途径和功能。PPI分析筛选出15个枢纽基因，生存分析表明CLCA1、CLCA4和CPT1A与CRC患者的预后有显著相关性。基于这三个基因建立的多因素Cox风险模型显示，如果这三个基因是一个基因组，它们对CRC患者的预后具有很好的预测能力：结论：CLCA1、CLCA4 和 CPT1A 在 CRC 中低水平表达，是抗肿瘤的核心基因。作为一组基因，它们能很好地预测预后。

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来源期刊

Pharmacological Reports 医学-药学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

6 months

期刊介绍： Pharmacological Reports publishes articles concerning all aspects of pharmacology, dealing with the action of drugs at a cellular and molecular level, and papers on the relationship between molecular structure and biological activity as well as reports on compounds with well-defined chemical structures. Pharmacological Reports is an open forum to disseminate recent developments in: pharmacology, behavioural brain research, evidence-based complementary biochemical pharmacology, medicinal chemistry and biochemistry, drug discovery, neuro-psychopharmacology and biological psychiatry, neuroscience and neuropharmacology, cellular and molecular neuroscience, molecular biology, cell biology, toxicology. Studies of plant extracts are not suitable for Pharmacological Reports.