关键词: Gleason score bioinformatics gene networks gene signature prostate cancer

Mesh : Male Humans Gene Regulatory Networks Prostatic Neoplasms / genetics Cell Cycle Cell Division Adenoviridae

来  源:   DOI:10.3390/ijms25073626   PDF(Pubmed)

Abstract:
Prostate cancer (PCa) is the most prevalent non-cutaneous cancer in men. Early PCa detection has been made possible by the adoption of screening methods based on the serum prostate-specific antigen and Gleason score (GS). The aim of this study was to correlate gene expression with the differentiation level of prostate adenocarcinomas, as indicated by GS. We used data from The Cancer Genome Atlas (TCGA) and included 497 prostate cancer patients, 52 of which also had normal tissue sample sequencing data. Gene ontology analysis revealed that higher GSs were associated with greater responses to DNA damage, telomere lengthening, and cell division. Positive correlation was found with transcription factor activator of the adenovirus gene E2 (E2F) and avian myelocytomatosis viral homolog (MYC) targets, G2M checkpoints, DNA repair, and mitotic spindles. Immune cell deconvolution revealed high M0 macrophage counts and an increase in M2 macrophages dependent on the GS. The molecular pathways most correlated with GSs were cell cycle, RNA transport, and calcium signaling (depleted). A combinatorial approach identified a set of eight genes able to differentiate by k-Nearest Neighbors (kNN) between normal tissues, low-Gleason tissues, and high-Gleason tissues with high accuracy. In conclusion, our study could be a step forward to better understanding the link between gene expression and PCa progression and aggressiveness.
摘要:
前列腺癌(PCa)是男性中最常见的非皮肤癌。通过采用基于血清前列腺特异性抗原和Gleason评分(GS)的筛选方法,早期PCa检测已成为可能。这项研究的目的是将基因表达与前列腺腺癌的分化水平相关联。如GS所示。我们使用来自癌症基因组图谱(TCGA)的数据,包括497名前列腺癌患者,其中52个也具有正常组织样品测序数据。基因本体论分析显示,较高的GSs与对DNA损伤的更大反应相关,端粒延长,和细胞分裂。发现与腺病毒基因E2的转录因子激活因子(E2F)和禽粒细胞瘤病毒同源物(MYC)靶标呈正相关,G2M检查站,DNA修复,和有丝分裂纺锤体。免疫细胞去卷积显示高M0巨噬细胞计数和依赖于GS的M2巨噬细胞增加。与GSs最相关的分子途径是细胞周期,RNA转运,和钙信号(耗尽)。一种组合方法确定了一组八个基因,能够通过k-最近邻居(kNN)在正常组织之间进行区分,低格里森组织,和高精度的高格里森组织。总之,我们的研究可能为更好地理解基因表达与PCa进展和侵袭性之间的联系迈出了一步.
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