Identification of Selected Genes Associated With the Prediction of Prognosis in Bladder Cancer.

IF 1.6 4区医学 Q4 BIOCHEMICAL RESEARCH METHODS

Combinatorial chemistry & high throughput screening Pub Date : 2025-05-13 DOI:10.2174/0113862073352389250407104347

Xiao-Dong Li, Jun-Ming Zhu, Qi You, Xiao-Hui Wu, Qi Huang, Hai Cai, Yong Wei, Yun-Zhi Lin, Xiong-Lin Sun, Ning Xu, Xue-Yi Xue, Qing-Shui Zheng

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引用次数: 0

Abstract

Background: Bladder cancer (BC) is one of the most common urological malignancies, ranking as the eleventh most common cause of cancer-related deaths worldwide. The lack of specific and sensitive prognostic biomarkers presents a significant challenge in the early diagnosis and treatment of BC.

Methods: We used the Gene Expression Omnibus (GEO) dataset GSE13507 and the Cancer Genome Atlas (TCGA) database to screen differentially expressed genes related to BC. By using Weighted Gene Co-expression Network Analysis (WGCNA), two modules associated with BC were investigated in GSE13507 and TCGA. Hub genes were identified through Protein-Protein Interaction (PPI) network analysis and their functions were validated through multiple approaches, including Gene Expression Profiling Interactive Analysis (GEPIA), Western Blotting (WB) assay, Human Protein Atlas (HPA), Oncomine analysis, and quantitative Real-Time PCR (qRTPCR) analysis. Additionally, miRNAs associated with hub gene expression were identified using various databases to predict the progression and prognosis of BC.

Results: WCGNA and differential gene expression analysis identified 171 common genes as target genes. Ten genes (MYH11, ACTA2, TPM2, ACTG2, CALD1, MYL9, TPM1, MYLK, SORBS1, and LMOD1) were identified using the PPI tool and the CytoHubba plugin of Cytoscape. The CALD1 and MYLK genes showed a significant prognostic value for overall survival and diseasefree survival in patients with BC. According to the HPA and Oncomine databases, CALD1 and MYLK expression levels were significantly lower in BC tissues than in normal tissues. Additionally, qRT-PCR analysis, WB assay, and immunohistochemical analysis confirmed CALD1 and MYLK as tumor suppressor genes in BC. Furthermore, miR-155 showed a significant positive correlation with MYLK.

Conclusion: This study established MYLK as a direct target gene of miR-155, functioning as an actionable survival-related gene correlated with BC development.

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膀胱癌预后预测相关基因的鉴定。

背景：膀胱癌（BC）是泌尿系统最常见的恶性肿瘤之一，在全球癌症相关死亡原因中排名第11位。缺乏特异性和敏感性的预后生物标志物对BC的早期诊断和治疗提出了重大挑战。方法：利用GEO数据集GSE13507和Cancer Genome Atlas （TCGA）数据库筛选BC相关差异表达基因。采用加权基因共表达网络分析（Weighted Gene Co-expression Network Analysis， WGCNA）对GSE13507和TCGA中与BC相关的两个模块进行了研究。通过蛋白-蛋白相互作用（PPI）网络分析鉴定枢纽基因，并通过基因表达谱相互作用分析（GEPIA）、Western Blotting （WB）、Human Protein Atlas （HPA）、Oncomine分析和实时荧光定量PCR （qRTPCR）等多种方法验证枢纽基因的功能。此外，通过各种数据库鉴定与hub基因表达相关的mirna，以预测BC的进展和预后。结果：WCGNA和差异基因表达分析鉴定出171个常见基因作为靶基因。使用PPI工具和Cytoscape的CytoHubba插件鉴定了10个基因（MYH11、ACTA2、TPM2、ACTG2、CALD1、MYL9、TPM1、MYLK、SORBS1和LMOD1）。CALD1和MYLK基因对BC患者的总生存期和无病生存期具有重要的预后价值。根据HPA和Oncomine数据库，CALD1和MYLK在BC组织中的表达水平明显低于正常组织。此外，qRT-PCR分析、WB分析和免疫组织化学分析证实CALD1和MYLK是BC的肿瘤抑制基因。此外，miR-155与MYLK呈显著正相关。结论：本研究确定MYLK是miR-155的直接靶基因，是与BC发生相关的可操作的生存相关基因。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Combinatorial chemistry & high throughput screening 化学-生化研究方法

CiteScore

3.10

自引率

5.60%

发文量

327

审稿时长

7.5 months

期刊介绍： Combinatorial Chemistry & High Throughput Screening (CCHTS) publishes full length original research articles and reviews/mini-reviews dealing with various topics related to chemical biology (High Throughput Screening, Combinatorial Chemistry, Chemoinformatics, Laboratory Automation and Compound management) in advancing drug discovery research. Original research articles and reviews in the following areas are of special interest to the readers of this journal: Target identification and validation Assay design, development, miniaturization and comparison High throughput/high content/in silico screening and associated technologies Label-free detection technologies and applications Stem cell technologies Biomarkers ADMET/PK/PD methodologies and screening Probe discovery and development, hit to lead optimization Combinatorial chemistry (e.g. small molecules, peptide, nucleic acid or phage display libraries) Chemical library design and chemical diversity Chemo/bio-informatics, data mining Compound management Pharmacognosy Natural Products Research (Chemistry, Biology and Pharmacology of Natural Products) Natural Product Analytical Studies Bipharmaceutical studies of Natural products Drug repurposing Data management and statistical analysis Laboratory automation, robotics, microfluidics, signal detection technologies Current & Future Institutional Research Profile Technology transfer, legal and licensing issues Patents.