The Second Affiliated Hospital of Soochow University, Suzhou 215000, China.
Lishui City People's Hospital, Lishui 323000, China.
Genes (Basel). 2022 Nov 7;13(11):2059. doi: 10.3390/genes13112059.
Renal cell carcinoma (RCC) is the largest category of kidney tumors and usually does not have a good prognosis. N6-methyladenosine(m6A) and immune infiltration have received increased attention because of their great influence on the clinical outcome and prognosis of cancer patients.
We identified hub genes through multi-dimensional screening, including DEGs, PPI analysis, LASSO regression, and random forest. Meanwhile, GO/KEGG enrichment, cMAP analysis, prognostic analysis, m6A prediction, and immune infiltration analysis were performed to understand the potential mechanism and screen therapeutic drugs.
We screened 275 downregulated and 185 upregulated genes using three GEO datasets and the TCGA dataset. In total, 82 candidate hub genes were selected using STRING and Cytoscape. Enrichment analysis illustrated that the top 3 biological process terms and top 1 KEGG term were related to immunity. cMAP analysis showed some antagonistic molecules can be candidate drugs for the treatment of RCC. Then, six hub genes (ERBB2, CASR, P2RY8, CAT, PLAUR, and TIMP1) with strong predictive values for prognosis and clinicopathological features were selected. Meanwhile, P2RY8, ERBB2, CAT, and TIMP1 may obtain m6A modification by binding METTL3 or METTL14. On the other hand, differential expression of CAT, ERBB2, P2RY8, PLAUR, and TIMP1 affects the infiltration of the majority of immune cells.
We identified six hub genes through multi-dimensional screening. They all possess strong predictive value for prognosis and clinicopathological features. Meanwhile, hub genes may regulate the progression of RCC via an m6A- and immunity-dependent mechanism.
肾细胞癌(RCC)是最大的肾脏肿瘤类别,通常预后不佳。由于 N6-甲基腺苷(m6A)和免疫浸润对癌症患者的临床结局和预后有很大影响,因此受到了越来越多的关注。
我们通过多维筛选,包括 DEGs、PPI 分析、LASSO 回归和随机森林,确定了枢纽基因。同时,进行了 GO/KEGG 富集、cMAP 分析、预后分析、m6A 预测和免疫浸润分析,以了解潜在的机制并筛选治疗药物。
我们使用三个 GEO 数据集和 TCGA 数据集筛选出 275 个下调和 185 个上调基因。总共使用 STRING 和 Cytoscape 选择了 82 个候选枢纽基因。富集分析表明,前 3 个生物学过程术语和前 1 个 KEGG 术语与免疫有关。cMAP 分析表明,一些拮抗分子可能是治疗 RCC 的候选药物。然后,选择了 6 个具有较强预后和临床病理特征预测值的枢纽基因(ERBB2、CASR、P2RY8、CAT、PLAUR 和 TIMP1)。同时,P2RY8、ERBB2、CAT 和 TIMP1 可能通过与 METTL3 或 METTL14 结合获得 m6A 修饰。另一方面,CAT、ERBB2、P2RY8、PLAUR 和 TIMP1 的差异表达会影响大多数免疫细胞的浸润。
我们通过多维筛选确定了 6 个枢纽基因。它们都具有较强的预后和临床病理特征预测值。同时,枢纽基因可能通过 m6A 和免疫依赖的机制调节 RCC 的进展。