Zhang Enchong, Shiori Fujisawa, Zhang Mo, Wang Peng, He Jieqian, Ge Yuntian, Song Yongsheng, Shan Liping
Department of Urology, Shengjing Hospital of China Medical University, Shenyang, China.
Department of Breast Endocrine Surgery, Tohoku University Hospital, Sendai, Japan.
Front Mol Biosci. 2021 May 28;8:676138. doi: 10.3389/fmolb.2021.676138. eCollection 2021.
Prostate cancer (PCa) is the most common malignancy among men worldwide. However, its complex heterogeneity makes treatment challenging. In this study, we aimed to identify PCa subtypes and a gene signature associated with PCa prognosis. In particular, nine PCa-related pathways were evaluated in patients with PCa by a single-sample gene set enrichment analysis (ssGSEA) and an unsupervised clustering analysis (i.e., consensus clustering). We identified three subtypes with differences in prognosis (Risk_H, Risk_M, and Risk_L). Differences in the proliferation status, frequencies of known subtypes, tumor purity, immune cell composition, and genomic and transcriptomic profiles among the three subtypes were explored based on The Cancer Genome Atlas database. Our results clearly revealed that the Risk_H subtype was associated with the worst prognosis. By a weighted correlation network analysis of genes related to the Risk_H subtype and least absolute shrinkage and selection operator, we developed a 12-gene risk-predicting model. We further validated its accuracy using three public datasets. Effective drugs for high-risk patients identified using the model were predicted. The novel PCa subtypes and prognostic model developed in this study may improve clinical decision-making.
前列腺癌（PCa）是全球男性中最常见的恶性肿瘤。然而，其复杂的异质性使得治疗具有挑战性。在本研究中，我们旨在识别前列腺癌亚型以及与前列腺癌预后相关的基因特征。具体而言，通过单样本基因集富集分析（ssGSEA）和无监督聚类分析（即一致性聚类）对前列腺癌患者的九条与前列腺癌相关的通路进行了评估。我们识别出了三种预后不同的亚型（Risk_H、Risk_M和Risk_L）。基于癌症基因组图谱数据库，探究了这三种亚型在增殖状态、已知亚型频率、肿瘤纯度、免疫细胞组成以及基因组和转录组图谱方面的差异。我们的结果清楚地表明，Risk_H亚型与最差的预后相关。通过对与Risk_H亚型相关的基因进行加权相关网络分析以及最小绝对收缩和选择算子分析，我们构建了一个12基因风险预测模型。我们使用三个公共数据集进一步验证了其准确性。预测了使用该模型识别出的高危患者的有效药物。本研究中开发的新型前列腺癌亚型和预后模型可能会改善临床决策。
