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通过综合生物信息学分析鉴定与前列腺癌进展相关的新型生物标志物。

Identification of novel biomarkers correlated with prostate cancer progression by an integrated bioinformatic analysis.

作者信息

Ma Zhifang, Wang Jianming, Ding Lingyan, Chen Yujun

机构信息

Department of Urology, Binzhou Central Hospital.

Department of Urology, Yangxin Country People Hospital.

出版信息

Medicine (Baltimore). 2020 Jul 10;99(28):e21158. doi: 10.1097/MD.0000000000021158.

DOI:10.1097/MD.0000000000021158
PMID:32664150
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7360283/
Abstract

Prostate cancer (PCa) is a highly aggressive malignant tumor and the biological mechanisms underlying its progression remain unclear.We performed weighted gene co-expression network analysis in PCa dataset from the Cancer Genome Atlas database to identify the key module and key genes related to the progression of PCa. Furthermore, another independent datasets were used to validate our findings.A total of 744 differentially expressed genes were screened out and 5 modules were identified for PCa samples from the Cancer Genome Atlas database. We found the brown module was the key module and related to tumor grade (R2 = 0.52) and tumor invasion depth (R2 = 0.39). Besides, 24 candidate hub genes were screened out and 2 genes (BIRC5 and DEPDC1B) were identified and validated as real hub genes that associated with the progression and prognosis of PCa. Moreover, the biological roles of BIRC5 were related to G-protein coupled receptor signal pathway, and the functions of DEPDC1B were related to the G-protein coupled receptor signal pathway and retinol metabolism in PCa.Taken together, we identified 1 module, 24 candidate hub genes and 2 real hub genes, which were prominently associated with PCa progression. With more experiments and clinical trials, these genes may provide a promising future for PCa treatment.

摘要

前列腺癌(PCa)是一种侵袭性很强的恶性肿瘤,其进展的生物学机制尚不清楚。我们对来自癌症基因组图谱数据库的PCa数据集进行了加权基因共表达网络分析,以识别与PCa进展相关的关键模块和关键基因。此外,使用另一个独立数据集来验证我们的发现。从癌症基因组图谱数据库中筛选出总共744个差异表达基因,并为PCa样本识别出5个模块。我们发现棕色模块是关键模块,与肿瘤分级(R2 = 0.52)和肿瘤浸润深度(R2 = 0.39)相关。此外,筛选出24个候选枢纽基因,并鉴定和验证了2个基因(BIRC5和DEPDC1B)为与PCa进展和预后相关的真正枢纽基因。此外,BIRC5的生物学作用与G蛋白偶联受体信号通路相关,DEPDC1B的功能与PCa中的G蛋白偶联受体信号通路和视黄醇代谢相关。综上所述,我们鉴定出1个模块、24个候选枢纽基因和2个真正的枢纽基因,它们与PCa进展显著相关。通过更多的实验和临床试验,这些基因可能为PCa治疗带来光明的前景。

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