Identification of Mast Cell-Based Molecular Subtypes and a Predictive Signature in Clear Cell Renal Cell Carcinoma

Abstract

Background: Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. Surgery is the preferred treatment option; however, the rate of distant metastasis is high. Mast cells in the tumor microenvironment promote or inhibit tumorigenesis depending on the cancer type; however, their role in KIRC is not well-established. Here, we used a bioinformatics approach to evaluate the roles of mast cells in KIRC.Methods: To quantify mast cell abundance based on gene sets, a single-sample gene set enrichment analysis (ssGSEA) was utilized to analyze three datasets. Weighted correlation network analysis (WGCNA) was used to identify the genes most closely related to mast cells. To identify new molecular subtypes, the nonnegative matrix factorization algorithm was used. GSEA and least absolute shrinkage and selection operator (LASSO) Cox regression were used to identify genes with high prognostic value. A multivariate Cox regression analysis was performed to establish a prognostic model based on mast cell-related genes. Promoter methylation levels of mast cell-related genes and relationships between gene expression and survival were evaluated using the UALCAN and GEPIA databases.Results: A prolonged survival in KIRC was associated with a high mast cell abundance. KIRC was divided into two molecular subtypes (cluster 1 and cluster 2) based on mast cell-related genes. Genes in Cluster 1 were enriched for various functions related to cancer development, such as the TGFβ signaling pathway, renal cell carcinoma, and mTOR signaling pathway. Based on drug sensitivity predictions, sensitivity to doxorubicin was higher for cluster 2 than for cluster 1. By a multivariate Cox analysis, we established a clinical prognostic model based on eight mast cell-related genes.Conclusion: We identified eight mast cell-related genes and constructed a clinical prognostic model. These results improve our understanding of the roles of mast cells in KIRC and may contribute to personalized medicine.

Low Tumor Infiltrating Mast Cell Density Reveals Prognostic Benefit in Cervical Carcinoma

“…However, studies on MCs and the prognosis of different cancers have reached different conclusions. [23][24][25] Similarly, previous studies also observed the anti-and pro-tumor effects of MCs in CC. [13][14][15][16][17] Our study aimed to explore and clarify this question.…”

The clinical significance, immune infiltration, and tumor mutational burden of angiogenesis-associated lncRNAs in kidney renal clear cell carcinoma

“…As one of the most prevalent primary malignant tumors of the urinary system, KIRC has the characteristics of high heterogeneity, poor prognosis, and distant metastasis ( 4 , 31 , 32 ). It is critical to explore the potential predictor for KIRC treatment and prognosis.…”

Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses

“…Using R software's “survival”, “survminer”, and “timeROC' packages, our TRPP was compared to seven other prognostic signatures (a mast cell-based signature developed by Liu et al [ 14 ], an m5C-related risk signature developed by Wu et al [ 15 ], and a four hypoxia-associated long non-coding RNA signature developed by Chen et al [ 16 ], an m6A-lncRNAs prognostic index developed by Lin et al [ 17 ], an autophagy-associated gene prognostic model developed by Wang et al [ 18 ], a nine-RNA binding protein signature developed by Zhong et al [ 19 ], and an inflammasome-related signature developed by Zheng et al [ 20 ]) on the basis of each gene combination in each signature.…”