scholarly journals Comprehensive analysis of pyroptosis regulators and tumor immune microenvironment in clear cell renal cell carcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yan Zhang ◽  
Xianwu Chen ◽  
Qinghe Fu ◽  
Feifan Wang ◽  
Xuejian Zhou ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Immune Microenvironment ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Immune Microenvironment ◽  
Cluster 2

Abstract Background Increasing evidence has indicated that pyroptosis could regulate the tumor immune microenvironment (TIME) to affect the tumor development. As a highly immunogenic tumor, clear cell renal cell carcinoma (ccRCC) can benefit from immunotherapy, but related research on pyroptosis in the TIME of ccRCC is still deficient. Methods Available data derived from TCGA and GEO databases were analyzed to identify the different expression profiles of pyroptosis in ccRCC and normal tissues, and the correlation of pyroptosis regulators with TIME was evaluated in ccRCC. Results According to consensus clustering analysis, two differential expression levels of subtypes were identified to affect patient prognosis, and were related to histological tumor stage and grade. Immune cells were calculated by the CIBERSORT algorithm. Higher infiltrated levels of B cells naive, T cells CD4 memory resting, NK cells resting, monocytes, macrophages were observed in Cluster 1, while higher infiltrated levels of CD8+ T cells, T follicular helper cells, and Tregs were observed in Cluster 2. Gene set enrichment analysis indicated that Cluster 2 was enriched in multiple immune-related pathways, including the JAK-STAT signaling pathway. Moreover, overexpression of eight immune checkpoints was related to ccRCC development, especially in Cluster 2. As four potentially key pyroptosis regulators, AIM2, CASP5, NOD2, and GZMB were confirmed to be upregulated in ccRCC by RT-qPCR analysis and further verified by the HPA database. Further pan-cancer analysis suggested that these four pyroptosis regulators were differentially expressed and related to the TIME in multiple cancers. Conclusion The present study provided a comprehensive view of pyroptosis regulators in the TIME of ccRCC, which may provide potential value for immunotherapy.

Characterization of the tumor immune microenvironment in clear cell renal cell carcinoma (ccRCC): Prognostic value and therapeutic implications of an M0-macrophage enriched subtype.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 4572-4572
Author(s):  
Mark Farha ◽  
Randy Vince ◽  
Srinivas Nallandhighal ◽  
Judith Stangl-Kremser ◽  
Steven Goldenthal ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
Enrichment Score ◽  
Immune Microenvironment ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Immune Microenvironment

4572 Background: Metastatic clear cell renal cell carcinoma (ccRCC) has a 5-year survival of 12%, but the number of approved immune checkpoint blockade (ICB) agents is growing, necessitating the need to better identify responders. The composition and role of the tumor immune microenvironment (TIME) has yet to be comprehensively characterized in ccRCC. Here, we leveraged a genomic data driven approach to characterize TIME subtypes in ccRCC. Methods: Whole transcriptome data from patients with local and metastatic disease in the Cancer Genome Atlas KIRC (TCGA-KIRC) project was utilized (n = 537). CIBERSORT was used for immune cell deconvolution, and unsupervised hierarchical clustering divided the cohort based on similar immune profiles. Progression free (PFS) and overall (OS) survival of each cluster was analyzed, and Gene Set Enrichment analysis was performed among clusters. The tumor immune dysfunction and exclusion (TIDE) tool, which uses a genomic signature validated on immunotherapy treated melanoma patients to model tumor immune evasion, was then used to predict response to ICB in the TCGA-KIRC clusters. Results: There was a distinct M0hi cluster identified which demonstrated a higher proportion of patients with stage III/IV disease, decreased PFS and OS (Table). Additionally, the M0hi cluster was characterized by lower PD-L1 expression (ANOVA, p = 0.0045) and an enrichment of epithelial to mesenchymal transition (EMT) hallmark genes [Enrichment Score = 0.64, p = 0.001]. The M0hi cluster also showed a higher degree of T-Cell Exclusion (ANOVA, p = 2.2x10-16), predominance of Cancer Associated Fibroblasts (CAFs; ANOVA, p = 2.2x10-16) and Myeloid Derived Suppressor Cells (MDSCs; ANOVA, p = 4.1x10-10). The M0hi cluster had the lowest predicted response to immunotherapy using the TIDE tool (Table). Conclusions: Comprehensive characterization of the TCGA-KIRC cohort led to identification of a distinct cluster of ccRCC defined molecularly by decreased PD-L1 and increased EMT gene expression and cellularly by enrichment of M0 macrophages, CAFs, MDSCs, and an exclusion of T Cells. Patients within this cluster exhibited aggressive disease and poor predicted response to ICB. These findings warrant further validation to identify appropriate therapeutic approaches for this ccRCC subgroup.[Table: see text]

scholarly journals The analysis of N6-methyladenosine regulators impacting the immune infiltration in clear cell renal cell carcinoma

2021 ◽  
Author(s):  
Jianpeng Li ◽  
Jinlong Cao ◽  
Ran Deng ◽  
Pan Li ◽  
Junqiang Tian
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Essential Role ◽  
Clear Cell ◽  
Immune Microenvironment ◽  
Cell Renal Cell Carcinoma ◽  
Tumor Immune Microenvironment ◽  
Cluster 2

Abstract Background: The tumor immune microenvironment (TIME) and N6-methyladenosine (m6A) are related to the progression of several types of cancer. Nevertheless, the impact of m6A on the tumor immune microenvironment of clear cell renal cell carcinoma (ccRCC) remains unclear. Methods: This study used an unsupervised clustering algorithm to divide the samples into distinct subgroups. The single sample gene set enrichment analysis (ssGSEA) algorithm to estimate the tumor immune microenvironment. The correlation between m6A regulators and immune cells in different subgroups was calculated using Spearman analysis. At last, the relationship between IGF2BP2 and HMGA2 was validated in several datasets, including TCGA-KIRC, GEO, and HPA datasets.Results: We found that m6A regulators were differently expressed in several clinical groups, such as grade and stage. Based on the expression of m6A regulators, we divided the samples into three subgroups. Then, the survival analysis for these three subgroups showed that the cluster 2 subgroup had poor overall survival (OS). Further, we found that IGF2BP2 and IGF2BP3 were essential components in the cluster 2 subgroup using the principal component analysis (PCA) algorithm. In addition, the expression of these two genes was significantly correlated with overall survival (OS), disease-specific survival (DSS), progression-free interval (PFI). At last, we found that HMGA2 was significantly correlated with IGF2BP2 in several datasets, which indicated that HMGA2 is an essential role in affecting IGF2BP2 regulating the TIME.Conclusion: There is a close correlation between m6A regulators and TIME. Moreover, IGF2BP2 is related to the progression of ccRCC and plays an essential role in affecting the tumor immune microenvironment.

scholarly journals Comprehensive Analysis of Ferroptosis Regulators With Regard to PD-L1 and Immune Infiltration in Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Song Wang ◽  
Shiming Chen ◽  
Yufan Ying ◽  
Xueyou Ma ◽  
Haixiang Shen ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Gene Set Enrichment Analysis ◽  
M2 Macrophage ◽  
Cell Renal Cell Carcinoma ◽  
Immune Infiltration ◽  
M1 Macrophage ◽  
Cluster 2

Clear cell renal cell carcinoma (ccRCC) is one of the tumor types with sensitivity to ferroptosis, and immunotherapy has emerged as a standard pillar for metastatic ccRCC treatment, while it remains largely obscure whether ferroptosis influences the tumor immune microenvironment in ccRCC. Based on available data in The Cancer Genome Atlas, divergent expression profiles of ferroptosis regulators were noted in ccRCC and normal tissues, and we also found that the ferroptosis regulators correlated with the PD-L1 expression. Two independent subtypes were determined by consensus clustering analysis according to the expression level of ferroptosis regulators in ccRCC. Cluster 1 showed lower histological tumor stage and grade, more favorable prognosis, and higher PD-L1 expression compared to cluster 2. CIBERSORT analysis revealed that cluster 2 harbored higher infiltrated levels of CD8+ T cell, Tregs, and T follicular helper cell, while cluster 1 more correlated with the monocyte, M1 macrophage, and M2 macrophage. Gene set enrichment analysis indicated that the ERBB signaling and JAK_STAT signaling pathways were significantly enriched in cluster 1. We subsequently identified CARS as the potentially key immune infiltration-related ferroptosis regulator, whose high expression showed dismal prognosis and was positively correlated with PD-L1 expression in ccRCC. We also verified the upregulation of CARS in ccRCC tissues and cell lines via qRT-PCR method. Additionally, a pan-cancer analysis demonstrated that CARS closely related to the expression of immune checkpoint-related genes (especially PD-L1) and an unfavorable prognosis in diverse cancer types. In summary, our study suggested the crucial role of ferroptosis in immune infiltration of ccRCC, and CARS is a potentially novel prognostic biomarker and potential target for cancer immunotherapy.

scholarly journals Roles of the Dynamic Tumor Immune Microenvironment in the Individualized Treatment of Advanced Clear Cell Renal Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Enyu Lin ◽  
Xuechao Liu ◽  
Yanjun Liu ◽  
Zedan Zhang ◽  
Lu Xie ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Targeted Therapy ◽  
Combination Therapy ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Immune Microenvironment ◽  
Cell Renal Cell Carcinoma ◽  
Durable Response ◽  
Tumor Immune Microenvironment

Immune checkpoint inhibitors (ICIs) are currently a first-line treatment option for clear cell renal cell carcinoma (ccRCC). However, recent clinical studies have shown that a large number of patients do not respond to ICIs. Moreover, only a few patients achieve a stable and durable response even with combination therapy based on ICIs. Available studies have concluded that the response to immunotherapy and targeted therapy in patients with ccRCC is affected by the tumor immune microenvironment (TIME), which can be manipulated by targeted therapy and tumor genomic characteristics. Therefore, an in-depth understanding of the dynamic nature of the TIME is important for improving the efficacy of immunotherapy or combination therapy in patients with advanced ccRCC. Here, we explore the possible mechanisms by which the TIME affects the efficacy of immunotherapy and targeted therapy, as well as the factors that drive dynamic changes in the TIME in ccRCC, including the immunomodulatory effect of targeted therapy and genomic changes. We also describe the progress on novel therapeutic modalities for advanced ccRCC based on the TIME. Overall, this review provides valuable information on the optimization of combination therapy and development of individualized therapy for advanced ccRCC.

scholarly journals Identification for prognostic value of differentially expressed genes in immune microenvironment of clear cell renal cell carcinoma

2019 ◽  
Author(s):  
Xingming Zhang ◽  
Xiaoxue Yin ◽  
Zhenhua Liu ◽  
Guangxi Sun ◽  
Xudong Zhu ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
T Cells ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Clear Cell ◽  
Functional Enrichment ◽  
Clinicopathological Parameters ◽  
Resting Cells ◽  
Immune Microenvironment ◽  
Cell Renal Cell Carcinoma

Abstract Background: Genes related to Anchorimmune microenvironment of clear cell renal cell carcinoma (ccRCC) remains unclear. We aimed to identify related to immune microenvironment and to screen the most significant genes to predict outcomes of ccRCC. Methods: Gene expression and clinicopathological data from TCGA data portal were obtained (KIRC). Immune and stromal scores were calculated based on ESTIMATE algorithm. DEGs between low and high groups of immune scores were identified. Subsequent functional enrichment analysis and protein-protein interaction of DEGs were conducted by DAVID database. Results: Patients were divided into low and high groups by medians according to immune (median: 1038.45) and stromal scores (median: 667.945), respectively. Immune scores were significantly correlated with clinicopathological parameters and overall survival (OS). Based on immune scores, 1433 genes were up-regulated, and among them, 890 DEGs were significantly associated with OS. Based on top 10 DEGs, cases with number of up-regulated genes ≥5 were associated poor OS (P = 0.002). In addition, the mean differences of percentages of CD8 T cells (11.32%), CD4 memory resting T cells (-4.52%) and mast resting cells (-3.55%) between low and high immune scores were the most significant. Conclusions: A list of immune microenvironment-related genes in ccRCC was initially identified, and high immune score was an independent poor prognostic factor of OS. Furthermore, the combination of these genes might use to predict the efficacy of immunotherapy. Further analyses of these genes were warrant to explore their potential association with the prognosis of ccRCC.

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