Table_3_Identification of Metabolism-Related Gene-Based Subgroup in Prostate Cancer.xlsx

Prostate cancer is still the main male health problem in the world. The role of metabolism in the occurrence and development of prostate cancer is becoming more and more obvious, but it is not clear. Here we firstly identified a metabolism-related gene-based subgroup in prostate cancer. We used metabolism-related genes to divide prostate cancer patients from The Cancer Genome Atlas into different clinical benefit populations, which was verified in the International Cancer Genome Consortium. After that, we analyzed the metabolic and immunological mechanisms of clinical beneficiaries from the aspects of functional analysis of differentially expressed genes, gene set variation analysis, tumor purity, tumor microenvironment, copy number variations, single-nucleotide polymorphism, and tumor-specific neoantigens. We identified 56 significant genes for non-negative matrix factorization after survival-related univariate regression analysis and identified three subgroups. Patients in subgroup 2 had better overall survival, disease-free interval, progression-free interval, and disease-specific survival. Functional analysis indicated that differentially expressed genes in subgroup 2 were enriched in the xenobiotic metabolic process and regulation of cell development. Moreover, the metabolism and tumor purity of subgroup 2 were higher than those of subgroup 1 and subgroup 3, whereas the composition of immune cells of subgroup 2 was lower than that of subgroup 1 and subgroup 3. The expression of major immune genes, such as CCL2, CD274, CD276, CD4, CTLA4, CXCR4, IL1A, IL6, LAG3, TGFB1, TNFRSF4, TNFRSF9, and PDCD1LG2, in subgroup 2 was almost significantly lower than that in subgroup 1 and subgroup 3, which is consistent with the results of tumor purity analysis. Finally, we identified that subgroup 2 had lower copy number variations, single-nucleotide polymorphism, and neoantigen mutation. Our systematic study established a metabolism-related gene-based subgroup to predict outcomes of prostate cancer patients, which may contribute to individual prevention and treatment.

前列腺癌依旧是全球范围内主要的男性健康问题。代谢在前列腺癌的发生与发展过程中的作用日益凸显，但其具体机制尚不明确。本研究首先在前列腺癌中识别出一种与代谢相关的基因亚组。我们运用与代谢相关的基因将《癌症基因组图谱》中的前列腺癌患者划分为不同的临床获益人群，并在国际癌症基因组联盟中得到验证。随后，我们从功能分析、差异表达基因集变异数据分析、肿瘤纯度、肿瘤微环境、拷贝数变异、单核苷酸多态性和肿瘤特异性新抗原等多个方面，对临床获益者的代谢和免疫机制进行了深入剖析。通过生存相关单变量回归分析后，我们识别出56个具有显著意义的基因，并据此将患者分为三个亚组。其中，第二亚组的患者展现出更优的总生存期、无病生存期、无进展生存期以及疾病特异性生存期。功能分析表明，第二亚组中差异表达基因富集于异生物代谢过程及细胞发育调节。此外，第二亚组的代谢和肿瘤纯度高于第一和第三亚组，而免疫细胞组成则低于第一和第三亚组。在第二亚组中，主要免疫基因（如CCL2、CD274、CD276、CD4、CTLA4、CXCR4、IL1A、IL6、LAG3、TGFB1、TNFRSF4、TNFRSF9和PDCD1LG2）的表达几乎显著低于第一和第三亚组，这与肿瘤纯度分析结果相一致。最终，我们发现第二亚组的拷贝数变异、单核苷酸多态性和新抗原突变均较低。本系统性研究基于代谢相关基因构建的亚组，有望预测前列腺癌患者的预后，并为个体化预防和治疗提供参考。