Affiliation:
1. Peking University First Hospital, Peking University, National Urological Cancer Centre
2. Chinese Academy of Sciences
Abstract
Abstract
Both lncRNAs and N6-Methylandenosine (m6A) modification have been reported as key regulators in tumorigenesis and innate immunity. This study is aimed to develop a prognostic signature based on m6A-related lncRNAs in kidney renal clear cell carcinoma (KIRC). Differential expression analysis and Pearson correlation analysis were used to identify m6A-related lncRNAs in The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied for further selection and the selected genes were inputted into stepwise regression to develop m6A-related lncRNA risk score (MRLrisk). According to our results, MRLrisk was established based on 6 m6A-related lncRNAs, NFE4, AL008729.2, AL139123.1, LINC02154, AC124854.1 and ARHGAP31-AS1. Higher MRLrisk was identified as a risk factor for patients' prognosis in TCGA dataset as well as in subgroup analysis with different clinicopathological characteristics. Furthermore, a MRLrisk-based nomogram was developed and demonstrated as a reliable tool for prognosis prediction in KIRC. MRLrisk-related biological phenotypes were analyzed in enrichment analysis and tumor mutation signature, providing us with novel insights for further functional studies. Additionally, patients' response to immunotherapy was inferred by the tumor immune dysfunction and exclusion (TIDE) score. Results showed that higher MRLrisk may indicate worse response to immunotherapy. pRRophetic R package was used to predict patient's response to certain chemodrugs and targeted drugs. In conclusion, we developed a MRLrisk model with robust prognostic value and ability to predict immunotherapy and targeted therapy response in KIRC, which may contribute to clinical patient stratification and treatment selection for KIRC.
Publisher
Research Square Platform LLC