Prediction of overall survival based upon a new ferroptosis-related gene signature in patients with clear cell renal cell carcinoma

Abstract

Background Clear cell renal cell carcinoma (ccRCC) is the most common and lethal renal cell carcinoma (RCC) histological subtype. Ferroptosis is a newly discovered programmed cell death and serves an essential role in tumor occurrence and development. The purpose of this study is to analyze ferroptosis-related gene (FRG) expression profiles and to construct a multi-gene signature for predicting the prognosis of ccRCC patients. Methods RNA-sequencing data and clinicopathological data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA). Differentially expressed FRGs between ccRCC and normal tissues were identified using ‘limma’ package in R. GO and KEGG enrichment analyses were conducted to elucidate the biological functions and pathways of differentially expressed FRGs. Consensus clustering was used to investigate the relationship between the expression of FRGs and clinical phenotypes. Univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis were used to screen genes related to prognosis and construct the optimal signature. Then, a nomogram was established to predict individual survival probability by combining clinical features and prognostic signature. Results A total of 19 differentially expressed FRGs were identified. Consensus clustering identified two clusters of ccRCC patients with distinguished prognostic. Functional analysis revealed that metabolism-related pathways were enriched, especially lipid metabolism. A 7-gene ferroptosis-related prognostic signature was constructed to stratify the TCGA training cohort into high- and low-risk groups where the prognosis was significantly worse in the high-risk group. The signature was identified as an independent prognostic indicator for ccRCC. These findings were validated in the testing cohort, the entire cohort, and the International Cancer Genome Consortium (ICGC) cohort. We further demonstrated that the signature-based risk score was highly associated with the ccRCC progression. Further stratified survival analysis showed that the high-risk group had a significantly lower overall survival (OS) rate than those in the low-risk group. Moreover, we constructed a nomogram that had a strong ability to forecast the OS of the ccRCC patients. Conclusions We constructed a ferroptosis-related prognostic signature, which might provide a reliable prognosis assessment tool for the clinician to guide clinical decision-making and outcomes research.

Comprehensive analysis of the prognostic signature and tumor microenvironment infiltration characteristics of cuproptosis-related lncRNAs for patients with colon adenocarcinoma

“…When paired with other clinical factors, univariate and multivariate Cox regression analysis were performed to determine whether risk score was an independent predictive factor in COAD patients (32).…”

Construction and Validation of Protein Expression-related Prognostic Models in Clear Cell Renal Cell Carcinoma

“…), or did not thoroughly established potentially significant treatments that could be used to treat the different risk groups of patients their model could stratify. For instance, Tang et al established a prognostic model on 9 autophagy-related long non-coding RNA 42 , Xu et al constructed a panel of 10 cuproptosis-associated lncRNAs 43 , Ming et al designed a panel comprising 12 N7-Methylguanosine (m7G)-related long non-coding RNAs (lncRNAs) 44 , Sun et al constructed a ferroptosis-related prognostic signature based on 19 ferroptosis-related genes 45 , Liu et al identified a 13-gene risk signature related to ccRCC patients' metabolism 46 , Zhao et al described their finding on 3 metabolic genes that were used to build a risk score model 47 , and Peng et al proposed a 3-gene methylation signature that could be used as a risk stratification tool to predict patient's outcomes and treatment response 48 . Compared these previous literature, to our existing knowledge, this is the first study to thoroughly investigate a panel of 13 proteins in ccRCC based on which we established an algorithm able to differentiate high-risk from low-risk patients, predict their 1-, 3- and 5-year OS, perform immune-related functional analysis to investigate the potential effect of immunotherapeutics in these 2 groups of patients and screen for potential drugs that could have be effective in the high and low-risk groups.…”

Cuproptosis-Related Ferroptosis genes for Predicting Prognosis in kidney renal clear cell carcinoma

“…Emerging research suggested that cuproptosis and ferroptosis were key factors of KIRC development. To date, based on cuproptosis and ferroptosis, multiple biomarkers with fair prediction performance for predicting prognostic mRNA or lncRNA value in KIRC have been established [ 26 , 31 – 33 ]. However, the association of CRFGs and prognosis of KIRC needs to be investigated, as developing a CRFGs signature for predicting KIRC prognosis and optimizing therapeutic methods is speculated to be helpful.…”