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雄激素相关前列腺癌亚型的免疫微环境与治疗靶点的研究进展。

Insights into immune microenvironment and therapeutic targeting in androgen-associated prostate cancer subtypes.

机构信息

Department of Urology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Hunan Cancer Hospital, Changsha, Hunan, China.

Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, Hunan, China.

出版信息

Sci Rep. 2024 Aug 4;14(1):18036. doi: 10.1038/s41598-024-68863-0.

Abstract

Prostate cancer, one of the most prevalent malignancies among men worldwide, is intricately linked with androgen signaling, a key driver of its pathogenesis and progression. Understanding the diverse expression patterns of androgen-responsive genes holds paramount importance in unraveling the biological intricacies of this disease and prognosticating patient outcomes. In this study, utilizing consensus clustering analysis based on the expression profiles of androgen-responsive genes, prostate cancer patients from the TCGA database were stratified into two distinct subtypes, denoted as C1 and C2. Notably, the C1 subtype demonstrates a significant upregulation of certain genes, such as CGA and HSD17B12, along with a shorter progression-free survival duration, indicating a potentially unfavorable prognosis. Further analyses elucidated the immune infiltration disparities, mutation landscapes, and gene functional pathways characteristic of each subtype. Through integrated bioinformatics approaches and machine learning techniques, key genes such as BIRC5, CENPA, and MMP11 were identified as potential therapeutic targets, providing novel insights into tailored treatment strategies. Additionally, single-cell transcriptome analysis shed light on the heterogeneous expression patterns of these genes across different cell types within the tumor microenvironment. Furthermore, virtual screening identified candidate drugs targeting the BIRC5 receptor, offering promising avenues for drug development. Collectively, these findings deepen our understanding of prostate cancer biology, paving the way for personalized therapeutic interventions and advancing the quest for more effective treatments in prostate cancer management.

摘要

前列腺癌是全球男性最常见的恶性肿瘤之一,与雄激素信号密切相关,是其发病机制和进展的关键驱动因素。了解雄激素反应基因的不同表达模式对于揭示这种疾病的生物学复杂性和预测患者预后至关重要。在这项研究中,我们利用基于雄激素反应基因表达谱的共识聚类分析,将 TCGA 数据库中的前列腺癌患者分为两个不同的亚型,分别表示为 C1 和 C2。值得注意的是,C1 亚型表现出某些基因的显著上调,如 CGA 和 HSD17B12,同时无进展生存期较短,提示预后可能不利。进一步的分析阐明了每个亚型的免疫浸润差异、突变景观和基因功能途径。通过整合生物信息学方法和机器学习技术,确定了 BIRC5、CENPA 和 MMP11 等关键基因作为潜在的治疗靶点,为制定个体化治疗策略提供了新的思路。此外,单细胞转录组分析揭示了这些基因在肿瘤微环境中不同细胞类型中的异质表达模式。此外,虚拟筛选确定了针对 BIRC5 受体的候选药物,为药物开发提供了有前途的途径。综上所述,这些发现加深了我们对前列腺癌生物学的理解,为个性化治疗干预铺平了道路,并推进了寻找更有效的前列腺癌治疗方法的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a5c/11298543/22fd15cbf6cd/41598_2024_68863_Fig1_HTML.jpg

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