Table_1_Macrophage M2 Co-expression Factors Correlate With the Immune Microenvironment and Predict Outcome of Renal Clear Cell Carcinoma.docx

Purpose: In the tumor microenvironment, the functional differences among various tumor-associated macrophages (TAM) are not completely clear. Tumor-associated macrophages are thought to promote the progression of cancer. This article focuses on exploring M2 macrophage-related factors and behaviors of renal clear cell carcinoma.
Method: We obtained renal clear cell carcinoma data from TCGA-KIRC-FPKM, GSE8050, GSE12606, GSE14762, and GSE3689. We used the “Cibersort” algorithm to calculate type M2 macrophage proportions among 22 types of immune cells. M2 macrophage-related co-expression module genes were selected using weighted gene co-expression network analysis (WGCNA). A renal clear cell carcinoma prognosis risk score was built based on M2 macrophage-related factors. The ROC curve and Kaplan–Meier analysis were performed to evacuate the risk score in various subgroups. The Pearson test was used to calculate correlations among M2 macrophage-related genes, clinical phenotype, immune phenotype, and tumor mutation burden (TMB). We measured differences in co-expression of genes at the protein level in clear renal cell carcinoma tissues.
Results: There were six M2 macrophage co-expressed genes (F13A1, FUCA1, SDCBP, VSIG4, HLA-E, TAP2) related to infiltration of M2 macrophages; these were enriched in neutrophil activation and involved in immune responses, antigen processing, and presentation of exogenous peptide antigen via MHC class I. M2-related factor frequencies were robust biomarkers for predicting the renal clear cell carcinoma patient clinical phenotype and immune microenvironment. The Cox regression model, built based on M2 macrophage-related factors, showed a close prognostic correlation (AUC = 0.78). The M2 macrophage-related prognosis model also performed well in various subgroups. Using western blotting, we found that VSIG4 protein expression levels were higher in clear renal cell carcinoma tissues than in normal tissues.
Conclusion: These co-expressed genes were most related to the M2 macrophage phenotype. They correlated with the immune microenvironment and predicted outcomes of renal clear cell carcinoma. These co-expressed genes and the biological processes associated with them might provide the basis for new strategies to intervene via chemotaxis of M2 macrophages.

研究目的：在肿瘤微环境（tumor microenvironment）中，不同肿瘤相关巨噬细胞（tumor-associated macrophages, TAM）之间的功能差异尚未完全阐明。现有研究认为肿瘤相关巨噬细胞可促进癌症进展，本研究旨在探索肾透明细胞癌（renal clear cell carcinoma）中与M2巨噬细胞相关的调控因子及生物学行为。
研究方法：我们从TCGA-KIRC-FPKM、GSE8050、GSE12606、GSE14762及GSE3689数据集获取肾透明细胞癌转录组数据；采用Cibersort算法计算22种免疫细胞中M2巨噬细胞的浸润比例。通过加权基因共表达网络分析（weighted gene co-expression network analysis, WGCNA）筛选与M2巨噬细胞相关的共表达模块基因。基于M2巨噬细胞相关因子构建肾透明细胞癌预后风险评分模型；通过ROC曲线（ROC curve）及Kaplan–Meier分析在各亚组中评估该风险评分的效能。采用Pearson检验分析M2巨噬细胞相关基因与临床表型、免疫表型及肿瘤突变负荷（tumor mutation burden, TMB）之间的相关性。我们还通过实验检测了肾透明细胞癌组织中基因共表达的蛋白水平差异。
研究结果：本研究筛选得到6个与M2巨噬细胞浸润相关的共表达基因（F13A1、FUCA1、SDCBP、VSIG4、HLA-E、TAP2）；这些基因显著富集于中性粒细胞活化通路，并参与免疫应答、抗原加工及经MHC I类分子呈递外源性肽抗原的生物学过程。M2巨噬细胞相关因子的表达特征可作为预测肾透明细胞癌患者临床表型与免疫微环境的可靠生物标志物。基于M2巨噬细胞相关因子构建的Cox回归预后模型展现出良好的预后预测效能（曲线下面积AUC=0.78）；该预后模型在各亚组中均表现出稳定的预测性能。通过蛋白质印迹（western blotting）实验发现，VSIG4蛋白在肾透明细胞癌组织中的表达水平显著高于正常组织。
研究结论：上述共表达基因与M2巨噬细胞表型密切相关，它们与肾透明细胞癌的免疫微环境及患者预后显著相关。这些共表达基因及其参与的生物学过程，可为通过调控M2巨噬细胞趋化干预肾透明细胞癌的新型治疗策略提供理论依据。