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前列腺癌高通量数据集中的差异基因表达与加权相关网络动态

Differential Gene Expression and Weighted Correlation Network Dynamics in High-Throughput Datasets of Prostate Cancer.

作者信息

Mohammad Taj, Singh Prithvi, Jairajpuri Deeba Shamim, Al-Keridis Lamya Ahmed, Alshammari Nawaf, Adnan Mohd, Dohare Ravins, Hassan Md Imtaiyaz

机构信息

Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi, India.

Department of Medical Biochemistry, College of Medicine and Medical Sciences, Arabian Gulf University, Manama, Bahrain.

出版信息

Front Oncol. 2022 Jun 1;12:881246. doi: 10.3389/fonc.2022.881246. eCollection 2022.

DOI:10.3389/fonc.2022.881246
PMID:35719950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9198298/
Abstract

Precision oncology is an absolute need today due to the emergence of treatment resistance and heterogeneity among cancerous profiles. Target-propelled cancer therapy is one of the treasures of precision oncology which has come together with substantial medical accomplishment. Prostate cancer is one of the most common cancers in males, with tremendous biological heterogeneity in molecular and clinical behavior. The spectrum of molecular abnormalities and varying clinical patterns in prostate cancer suggest substantial heterogeneity among different profiles. To identify novel therapeutic targets and precise biomarkers implicated with prostate cancer, we performed a state-of-the-art bioinformatics study, beginning with analyzing high-throughput genomic datasets from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) suggests a set of five dysregulated hub genes (MAF, STAT6, SOX2, FOXO1, and WNT3A) that played crucial roles in biological pathways associated with prostate cancer progression. We found overexpressed STAT6 and SOX2 and proposed them as candidate biomarkers and potential targets in prostate cancer. Furthermore, the alteration frequencies in STAT6 and SOX2 and their impact on the patients' survival were explored through the cBioPortal platform. The Kaplan-Meier survival analysis suggested that the alterations in the candidate genes were linked to the decreased overall survival of the patients. Altogether, the results signify that STAT6 and SOX2 and their genomic alterations can be explored in therapeutic interventions of prostate cancer for precision oncology, utilizing early diagnosis and target-propelled therapy.

摘要

由于癌症治疗耐药性的出现以及癌性特征的异质性,精准肿瘤学在当今是绝对必要的。靶向驱动的癌症治疗是精准肿瘤学的瑰宝之一,已经取得了重大医学成就。前列腺癌是男性中最常见的癌症之一,在分子和临床行为方面具有巨大的生物学异质性。前列腺癌中分子异常的范围和不同的临床模式表明不同特征之间存在显著异质性。为了确定与前列腺癌相关的新型治疗靶点和精确生物标志物,我们开展了一项前沿的生物信息学研究,首先分析了来自癌症基因组图谱(TCGA)的高通量基因组数据集。加权基因共表达网络分析(WGCNA)表明一组五个失调的枢纽基因(MAF、STAT6、SOX2、FOXO1和WNT3A)在与前列腺癌进展相关的生物学途径中起关键作用。我们发现STAT6和SOX2过表达,并将它们提议为前列腺癌的候选生物标志物和潜在靶点。此外,通过cBioPortal平台探索了STAT6和SOX2的改变频率及其对患者生存的影响。Kaplan-Meier生存分析表明候选基因的改变与患者总生存期的降低有关。总之,结果表明在前列腺癌的治疗干预中,可以利用早期诊断和靶向驱动治疗来探索STAT6和SOX2及其基因组改变,以实现精准肿瘤学。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1059/9198298/4b2f2a0dba20/fonc-12-881246-g008.jpg
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