Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Wang Y

PROVIDER: S-EPMC7938896 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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

Wang Yutao Y Yan Kexin K Lin Jiaxing J Li Jun J Bi Jianbin J

Frontiers in genetics 20210222

<b>Purpose:</b> 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. <b>Method:</b> We obtained renal clear cell carcinoma data from TCGA-KIRC-FPKM, GSE8050, GSE12606, GSE14762, and GSE3689. We used the "Cibersort" algorithm to calc ...[more]

PMID: 33692827

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Project description:Background Cell–cell communications of various cell populations within tumor microenvironment play an essential role in primary tumor growth, metastasis evolution, and immune escape. Nevertheless, comprehensive investigation of cell–cell communications in the ccRCC (Clear cell renal carcinoma) microenvironment and how this interplay affects prognosis still remains limited. Methods Intercellular communications were characterized by single-cell data. Firstly, we employed “CellChat” package to characterize intercellular communications across all types of cells in microenvironment in VHL mutated and non-mutated samples from 8 patients, respectively. And pseudotime trajectory analyses were performed with monocle analyses. Finally clinical prognosis and immunotherapy efficacy with different landscapes of intercellular interplay are evaluated by TCGA-KIRC and immunotherapy cohort. Results Firstly, the VHL phenotype may be related to the intercellular communication landscape. And trajectory analysis reveals the potential relationship of cell–cell communication molecules with T cells and Myeloid cells differentiation. Furthermore, those molecules also correlate with the infiltration of T cells and Myeloid cells. A tumor cluster with highly expressed ligands was defined by quantitative analysis and transcription factor enrichment analysis, which was identified to be pivotal for intercellular communications in tumor microenvironment. Finally, bulk data indicates bulk that different clusters with different intercellular communications have significant predictive value for prognosis and distinguished immunotherapy efficiency. Conclusions The intercellular communication landscapes of VHL wild and VHL mutant ccRCC vary. Intercellular communications within the tumor microenvironment also influence T cell and myeloid cell development and infiltration, as well as predict clinical prognosis and immunotherapy efficacy in ccRCC. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03858-x.

Project description:Background:To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. Methods:We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)|?>?1, P value <0.05 by using package "limma" in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan-Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. Results:A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. Conclusions:Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.

Dataset Information

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

Publications

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

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