Identification of a Novel Signature and Construction of a Nomogram Predicting Overall Survival in Clear Cell Renal Cell Carcinoma

Abstract

Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC), which accounts for majority of RCC-related deaths. It is clearly essential to further identify more novel prognostic signatures and therapeutic targets. Material and Methods: We identified differentially expressed genes (DEGs) between ccRCC and adjacent normal tissues in GEO database using a Robust Rank Aggregation (RRA) method. An mRNA signature (mRNASig) based on DEGs was developed using Cox and LASSO analysis in the TCGA database and validated in the ICGC database. Afterward, the influence of mRNASig mRNAs on the immune microenvironment in ccRCC was explored using comprehensive bioinformatics analysis. Results: A total of 957 robust DEGs were identified using the RRA method. mRNASig comprised CEP55, IFI44, NCF4, and TCIRG1 and was developed and validated to identify high-risk patients who had poorer prognosis than low-risk patients. A nomogram was also constructed based on mRNASig, AJCC stage, and tumor grade. The mRNASig were closely related to a variety of tumor-infiltrating lymphocytes, especially including CD8+ T cells, activated CD4+ memory T cells, regulatory T cells, activated NK cells, and resting NK cells. The mRNASig were also correlated positively with the expression of CTLA4, LAG3, PDCD1, TIGIT, and HAVCR2. Conclusion: We developed and validated mRNASig to assist clinicians in making personalized treatment decisions. Furthermore, CEP55, IFI44, NCF4, and TCIRG1 may be novel potential targets for future treatment of ccRCC.