Dataset Information

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm.

ABSTRACT: Emerging evidence has highlighted that the immune and stromal cells formed the majority of tumor microenvironment (TME) which are served as important roles in tumor progression. In our study, we aimed to screen vital prognostic signature associated with TME in clear cell renal cell carcinoma (ccRCC). We obtained total 611 samples from TCGA database consisting of transcriptome profiles and clinical data. ESTIMATE algorithm was applied to estimate the infiltrating fractions of immune/stromal cells. We found that the immune scores revealed more prognostic significance in overall survival and positive associations with risk clinical factors than stromal scores. We carried out differential expression analysis between Immunescore and stromalscore groups to obtain the 72 intersect genes. Protein to protein interaction (PPI) network and functional analysis was performed to indicate potential altered pathways. Additionally, we further conducted multivariate Cox analysis to identify 12 hub genes associated highly with TME of ccRCC using a stepwise regression procedure. Accordingly, risk score was constructed from the multivariate Cox results and Receiver Operating Characteristic (ROC) curve was used to assess the predictive value (AUC = 0.781). The ccRCC patients with high risk scores suffered poor survival outcomes than that with low risk scores. In the validation cohort from GSE53757, TNFSF13B, CASP5, and GJB6 correlated positively with tumor stages, while FREM1 negatively correlated with tumor stages. Importantly, we further observed that TNFSF13B, CASP5 and XCR1 showed the remarkable correlations with tumor-infiltrating immune cells. Taken together, our research identified specific signatures that related to the infiltration of stromal and immune cells in TME of ccRCC using the transciptome profiles, which reached a comprehensive understanding of tumor microenvironment in ccRCC.

SUBMITTER: Luo J

PROVIDER: S-EPMC7300420 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm.

Luo Jun J Xie Yi Y Zheng Yuxiao Y Wang Chenji C Qi Feng F Hu Jiateng J Xu Yaoting Y

Cancer medicine 20200420 12

Emerging evidence has highlighted that the immune and stromal cells formed the majority of tumor microenvironment (TME) which are served as important roles in tumor progression. In our study, we aimed to screen vital prognostic signature associated with TME in clear cell renal cell carcinoma (ccRCC). We obtained total 611 samples from TCGA database consisting of transcriptome profiles and clinical data. ESTIMATE algorithm was applied to estimate the infiltrating fractions of immune/stromal cells ...[more]

PMID: 32311223

Similar Datasets

Project description:BackgroundRNA N6-methyladenosine (m6A) has been found to have a critical impact on clear cell renal cell carcinoma (ccRCC) by affecting the tumor microenvironment (TME) and immune cell (IC) infiltration and is related to the treatment and survival rate of patients with ccRCC. However, the mechanism of m6A in TME and IC infiltration remained unclear.MethodsNonnegative Matrix Factorization (NMF) clustering was performed on 650 ccRCC cases from the Cancer Genome Atlas (TCGA) and the Gene-Expression Omnibus (GEO) datasets. The immune infiltration was generated by the single-sample gene-set enrichment analysis (ssGSEA) algorithm. Survival analyses were performed using the Kaplan-Meier method, and the significance of the differences was determined using the log-rank test. The m6A score was constructed based on the expression of m6A regulators to quantify m6A modification. The package "survminer R" was employed to layer patients' low and high scores groups and predict the immunotherapy response.ResultsThree different patterns of m6A modification were established, and significant differences in TME and IC infiltration features were found in these three patterns. Survival analysis demonstrated that m6A cluster A and m6A gene cluster A experienced a longer survival time. Evaluation of m6A modification patterns in individual tumors was initiated by the m6A score. The low m6A score subtype was characterized by increased tumor mutation burden (TMB) and immune infiltration, whereas a high m6A score with a lack of immune cell infiltration showed significantly better overall survival. m6A score was also associated with the expression of programmed cell death protein 1 (PD-L1) and cytotoxic T lymphocyte antigen 4 (CTLA-4). Patients in the high m6A score group had high PD-L1 expression and low CTLA-4 expression. Significant differences in prognosis were identified among types of different TMB and m6A scores, where low TMB and high m6A score had longer survival time.ConclusionsThis research indicated that m6A modification greatly affected TME and IC infiltration. Physicians can develop practical immunotherapy strategies for patients with ccRCC by evaluating m6A-associated genes.

Dataset Information

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm.

Publications

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets