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膀胱癌的分子特征:关键基因、转录因子和药物相互作用。

Molecular Landscape of Bladder Cancer: Key Genes, Transcription Factors, and Drug Interactions.

机构信息

Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea.

National Center for Cancer Immune Therapy (CCIT-DK), Department of Oncology, Copenhagen University Hospital, 2730 Herlev, Denmark.

出版信息

Int J Mol Sci. 2024 Oct 12;25(20):10997. doi: 10.3390/ijms252010997.

Abstract

Bladder cancer is among the most prevalent tumors in the urinary system and is known for its high malignancy. Although traditional diagnostic and treatment methods are established, recent research has focused on understanding the molecular mechanisms underlying bladder cancer. The primary objective of this study is to identify novel diagnostic markers and discover more effective targeted therapies for bladder cancer. This study identified differentially expressed genes (DEGs) between bladder cancer tissues and adjacent normal tissues using data from The Cancer Genome Atlas (TCGA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of these genes. A protein-protein interaction (PPI) network was also constructed to identify and analyze hub genes within this network. Gene set variation analysis (GSVA) was conducted to investigate the involvement of these genes in various biological processes and pathways. Ten key genes were found to be significantly associated with bladder cancer: , , , , , , , , , and . GSVA analyses revealed that these genes are involved in a variety of biological processes and signaling pathways, including coagulation, UV-response-down, apoptosis, Notch signaling, and Wnt/beta-catenin signaling. The diagnostic relevance of these genes was validated through ROC curve analysis. Additionally, potential therapeutic drug interactions with these key genes were identified. This study provides valuable insights into key genes and their roles in bladder cancer. The identified genes and their interactions with therapeutic drugs could serve as potential biomarkers, presenting new opportunities for enhancing the diagnosis and prognosis of bladder cancer.

摘要

膀胱癌是泌尿系统中最常见的肿瘤之一,其恶性程度较高。虽然传统的诊断和治疗方法已经确立,但最近的研究集中在了解膀胱癌的分子机制上。本研究的主要目的是鉴定膀胱癌的新型诊断标志物,并发现更有效的针对膀胱癌的靶向治疗方法。

本研究使用来自癌症基因组图谱(TCGA)的数据,鉴定了膀胱癌组织与相邻正常组织之间的差异表达基因(DEGs)。进行了基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集分析,以探索这些基因的功能作用。还构建了蛋白质-蛋白质相互作用(PPI)网络,以识别和分析该网络中的枢纽基因。进行了基因集变异分析(GSVA),以研究这些基因在各种生物学过程和途径中的参与情况。

发现了 10 个与膀胱癌显著相关的关键基因:、、、、、、、、和。GSVA 分析表明,这些基因参与了多种生物学过程和信号通路,包括凝血、UV 反应下调、细胞凋亡、Notch 信号通路和 Wnt/β-catenin 信号通路。通过 ROC 曲线分析验证了这些基因的诊断相关性。此外,还确定了与这些关键基因的潜在治疗药物相互作用。

本研究为膀胱癌的关键基因及其作用提供了有价值的见解。鉴定的基因及其与治疗药物的相互作用可能成为潜在的生物标志物,为增强膀胱癌的诊断和预后提供了新的机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ebad/11507096/ee05be14a654/ijms-25-10997-g001.jpg

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