The impact of TNFSF14 on prognosis and immune microenvironment in clear cell renal cell carcinoma

414 Background: While mutations in PBRM1 (~40%) and BAP1(~10%) are associated with clinical outcomes and pathologic features in clear cell renal cell carcinoma (ccRCC), the impact of protein expression of these genes remains unknown. Herein, we quantify PBRM1/BAP1 protein expression in a large cohort of patients with localized ccRCC and associate expression with cancer-specific survival (CSS) and pathologic features. Methods: We utilized the Mayo Clinic Renal Registry and identified 1,416 patients who underwent nephrectomy to treat clinically localized ccRCC between 1/3/1990 and 4/14/2009. We used immunohistochemistry (IHC) to detect PBRM1/BAP1 expression, and a central pathologist blinded to the outcomes scored tumors as either positive or negative. Tumors with heterogeneous or equivocal staining were excluded from this analysis. We generated Cox proportional hazard regression models for associations with ccRCC-SS, and we employed Mann-Whitney U tests for associations with pathologic features. Results: Of the 1,416 samples, 1,232 (87%) were PBRM1/BAP1 positive or negative, 163 (11%) had heterogeneous staining, and 21 (1%) could not be assessed. The distribution and association of PBRM1/BAP1 phenotypes with clinical outcomes are listed in the table below. PBRM1+/BAP1+ tumors have the best CSS, and PBRM1-/BAP1- have the worst. In addition, PBRM1/BAP1 expression strongly associated with the tumor size, stage, grade, and tumor necrosis (p<0.0001). Conclusions: This study is the first and largest to quantify PRBM1/BAP1 protein expression in ccRCC tumors. We were able to quantify PBRM1/BAP1 through IHC in the vast majority of tumors (87%), and PRBM1/BAP1 expression strongly associates with both CSS and pathologic tumor characteristics. Our data confirms our previous findings of the importance of PRBM1/BAP1 in the molecular pathogenesis of ccRCC. [Table: see text]

Download Full-text

The impact of three-dimensional tumor volume on cancer-specific survival for patients with pT1 clear-cell renal cell carcinoma

World Journal of Urology ◽

10.1007/s00345-015-1592-6 ◽

2015 ◽

Vol 34 (1) ◽

pp. 83-88 ◽

Cited By ~ 3

Author(s):

Wan Song ◽

Byong Chang Jeong ◽

Seong Il Seo ◽

Seong Soo Jeon ◽

Hyun Moo Lee ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Tumor Volume ◽

Clear Cell ◽

Three Dimensional ◽

Cell Renal Cell Carcinoma ◽

Cancer Specific Survival ◽

The Impact

Download Full-text

Genomic Instability Promotes the Progression of Clear Cell Renal Cell Carcinoma Through Influencing the Immune Microenvironment

Frontiers in Genetics ◽

10.3389/fgene.2021.706661 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiyi Wei ◽

Yichun Wang ◽

Chengjian Ji ◽

Jiaocheng Luan ◽

Liangyu Yao ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Tumor Progression ◽

Cell Carcinoma ◽

Genomic Instability ◽

Renal Cell ◽

Clear Cell ◽

Immune Microenvironment ◽

Cell Renal Cell Carcinoma ◽

Low Expression

Background: Long non-coding RNAs (lncRNAs) are now under discussion as novel promising biomarkers for clear cell renal cell carcinoma (ccRCC). However, the role of genomic instability-associated lncRNA signatures in tumors has not been thoroughly uncovered. The purpose of our study is to probe the role of genomic instability-derived lncRNA signature (GILncSig) and to further investigate the mechanism of genomic instability-mediated ccRCC progression.Methods: The transcriptome data and somatic mutation profiles of ccRCC as well as clinical characteristics used in this study were obtained from The Cancer Genome Atlas database and Gene Expression Omnibus database. Lasso regression analysis was performed to construct the GILncSig. Gene set enrichment analysis (GSEA) was performed to elucidate the biological functions and relative pathways. CIBERSORT and EPIC algorithm were applied to calculate the proportion of immune cells in ccRCC. ESTIMATE algorithm was utilized to compute the immune microenvironment scores.Results: In total, 148 novel genomic instability-derived lncRNAs in ccRCC were identified. Immediately, on the basis of univariate cox analysis and lasso analysis, a GILncSig was appraised, through which the patients were allocated into High-Risk and Low-Risk groups with significantly different characteristics and prognoses. In addition, we confirmed that the somatic mutation count, tumor mutation burden, and the expression of UBQLN4, which were ascertainably associated with genomic instability, were significantly correlated with the GILncSig, indicating its reliability as a measurement of the genomic instability. Furthermore, the efficiency of GILncSig in prognostic aspects was better than the single mutation gene in ccRCC. In addition, MNX1-AS1 was defined to be a potential biomarker characterized by strong correlation with clinical features. Moreover, GSEA results indicated that the IL6/JAK/STAT3/SIGNALING pathway could be considered as a potential mechanism of genomic instability to influence tumor progression. Besides, the immune microenvironment showed significant differences between the GS-like group and the GU-like group, which was specifically manifested as high expression of CTLA4, GITR, TNFSF14, and regulatory T cells (Tregs) as well as low expression of endothelial cells (ECs) in the GU-like group. Finally, the prognostic value and clinical relevance of GILncSig were verified in GEO datasets and other urinary tumors in TCGA dataset.Conclusion: In conclusion, our study provided a new perspective for the role of lncRNAs in genomic instability and revealed that genomic instability may mediate tumor progression by affecting immunity. Besides, MNX1-AS1 played critical roles in promoting the progression of ccRCC, which may be a potential therapeutic target. What is more, the immune atlas of genomic instability was characterized by high expression of CTLA4, GITR, TNFSF14, and Tregs, and low expression of ECs.

Download Full-text

Systematic exploration of prognostic alternative splicing events related to immune microenvironment of Clear Cell Renal Cell Carcinoma

10.21203/rs.3.rs-1138551/v1 ◽

2021 ◽

Author(s):

Youyuan Deng ◽

Jianguo Wang ◽

Yanrui Pang ◽

Jingyong Li ◽

Huaixiao Zhang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Alternative Splicing ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Functional Enrichment ◽

Immune Microenvironment ◽

Cell Renal Cell Carcinoma ◽

Systematic Exploration ◽

Immune Score

Abstract Background Clear cell renal cell carcinoma (ccRCC) accounts for almost 75% of all renal cancers, with high heterogeneity and poor prognosis. There is increasing evidence that alternative splicing (AS) is associated with tumorigenesis and immune microenvironment. However, studies on the relationship between AS events and immunity in ccRCC are still few but needed. Methods The transcriptional data and clinicopathological information of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. We grouped patients according to the ESTIMATE algorithm and identified for differentially expressed AS events (DEASs). The functional enrichment analysis and unsupervised consensus analysis were performed to investigate the association between AS events and immune features. The regulatory network of survival-related AS events and intersection SFs was used to explore potential mechanisms. Results In total, 515 ccRCC patients were included in the present study. The low immune-score group had longer overall survival (OS) than the high low immune-score group. 861 AS events were identified as DEASs, and they were enriched in immune-related pathways. Unsupervised clustering analysis revealed that AS-based clusters significantly corelated with prognosis and immune features of ccRCC. Finally, MBNL1 was identified as a hub SF, and it was shown to inhibit proliferation and metastasis, promote apoptosis, and block cells in G2/M phase in 786O and A498 cells. Conclusion The present systematic exploration elaborated that not only some critical AS events were related to prognosis and immune microenvironment of ccRCC, but also the hub SF, such as MBNL1, could affect the development and progression of ccRCC.

Download Full-text

Typical prognostic immune subtypes of clear cell renal cell carcinoma defined by the unique tumor immune microenvironment

European Urology ◽

10.1016/s0302-2838(21)00937-4 ◽

2021 ◽

Vol 79 ◽

pp. S759

Author(s):

W-H. Xu ◽

Z. Hailiang ◽

A. Aihetaimujiang ◽

Y. Dingwei

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Immune Microenvironment ◽

Cell Renal Cell Carcinoma ◽

Tumor Immune Microenvironment

Download Full-text

The impact of peptidase activity on clear cell renal cell carcinoma survival

AJP Renal Physiology ◽

10.1152/ajprenal.00477.2012 ◽

2012 ◽

Vol 303 (12) ◽

pp. F1584-F1591 ◽

Cited By ~ 24

Author(s):

Gorka Larrinaga ◽

Lorena Blanco ◽

Begoña Sanz ◽

Itxaro Perez ◽

Javier Gil ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Cell Carcinoma ◽

Renal Cell ◽

Clear Cell ◽

Rank Test ◽

Activity Levels ◽

Peptidase Activity ◽

Cell Renal Cell Carcinoma ◽

Dpp Iv ◽

The Impact

Several studies have proposed that protease expression and activity may have a predictive value in the survival of clear cell renal cell carcinoma (CCRCC). Most efforts on this issue have been focused on the analysis of matrix metalloproteinases (MMP) and very little on the role of other proteases, such as peptidases. The catalytic activity of 9 peptidases (APN, APB, ASP, CAP, DPP-IV, NEP/CD10, PEP, PGI, and PSA) was quantified by fluorometric methods in a series of 79 CCRCC patients, and the results obtained were analyzed for survival (Kaplan-Meier curves, log-rank test, and Cox multivariate analysis). CCRCC patients with higher activity levels of membrane-bound APN and soluble APN, DPP-IV, and CAP had significantly shorter 5-yr survival rates than those with lower levels. By contrast, higher soluble APB activity significantly correlated with longer survival. Our data suggest the involvement of peptidases in the biological aggressiveness of CCRCC and support the usefulness of measuring these proteases to assess the prognosis of patients with CCRCC.

Download Full-text

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

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.4572 ◽

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]

Download Full-text