Li Hanwen, Mo Zengnan
Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China.
Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China.
Int J Gen Med. 2021 Oct 18;14:6885-6898. doi: 10.2147/IJGM.S328109. eCollection 2021.
Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers. Thus, it is warranted to detect the status of metabolism-related genes (MRGs) and infiltrating immune cells in ccRCC progression for the prognosis of ccRCC. This research was designed to establish and verify the prognostic signature of ccRCC using MRGs. In addition, we investigated the potential link between the relative proportion of tumor infiltrated immune cells (TIICs) and ccRCC prognosis.
Sequencing data of metabolism-related gene sets in ccRCC cases were obtained from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus Database (GEO). The R Programming Language software packages were applied for differential analysis of MRGs. First, a univariate Cox regression model was applied to determine the MRGs linked with overall survival (OS). Then, the multivariate Cox regression model was applied to establish the prognostic signature. Finally, the CIBERSORT algorithm was used to determine the proportion of TIICs.
Overall, 286 differentially expressed MRGs were identified in the TCGA dataset. Univariate and multivariate Cox regression models were applied to develop a prognostic signature with six MRGs. The predictive capability of the prognostic signature was further verified by TCGA and GEO database. In addition, positively correlated with memory B cells, plasma cells, activated memory CD4+ T cells, follicular helper T cells, regulatory T cells, CD8+ T cells, and M0 macrophages, and were negatively associated with resting memory CD4+ T cells, resting dendritic cells, activated dendritic cells, M2 macrophages, monocytes, resting mast cells, and eosinophils.
Herein, a prognostic signature was developed using MRGs for ccRCC prognosis. The proportion of 22 TIICs in ccRCC and the association between TIICs and clinical outcomes were also determined. The identified genes and cells could guide future targeted therapy and immunotherapy.
透明细胞肾细胞癌（ccRCC）是最常见的癌症之一。因此，在ccRCC进展过程中检测代谢相关基因（MRGs）和浸润性免疫细胞的状态对于ccRCC的预后具有重要意义。本研究旨在利用MRGs建立并验证ccRCC的预后特征。此外，我们还研究了肿瘤浸润免疫细胞（TIICs）的相对比例与ccRCC预后之间的潜在联系。
从癌症基因组图谱数据库（TCGA）和基因表达综合数据库（GEO）中获取ccRCC病例中代谢相关基因集的测序数据。使用R编程语言软件包对MRGs进行差异分析。首先，应用单变量Cox回归模型确定与总生存期（OS）相关的MRGs。然后，应用多变量Cox回归模型建立预后特征。最后，使用CIBERSORT算法确定TIICs的比例。
总体而言，在TCGA数据集中鉴定出286个差异表达的MRGs。应用单变量和多变量Cox回归模型开发了一个包含六个MRGs的预后特征。TCGA和GEO数据库进一步验证了该预后特征的预测能力。此外，与记忆B细胞、浆细胞、活化记忆CD4 + T细胞、滤泡辅助性T细胞、调节性T细胞、CD8 + T细胞和M0巨噬细胞呈正相关，与静息记忆CD4 + T细胞、静息树突状细胞、活化树突状细胞、M2巨噬细胞、单核细胞、静息肥大细胞和嗜酸性粒细胞呈负相关。
在此，利用MRGs开发了一种用于ccRCC预后的预后特征。还确定了ccRCC中22种TIICs的比例以及TIICs与临床结果之间的关联。所鉴定的基因和细胞可为未来的靶向治疗和免疫治疗提供指导。
