Identification of key genes of the ccRCC subtype with poor prognosis

Scientific Reports. 2022. Vol. 12. No. 1. Article 14588.

Grigory Andreevich Puzanov

Clear cell renal carcinoma has been reported in many research studies as a rather heterogeneous disease. Identification of different subtypes and their molecular characteristics can help in choosing a more effective treatment and predicting a response to it. In this study, using multi-omics clustering of RNA-Seq data of patients with clear cell renal carcinoma from TCGA. Specific genes were identified for the most aggressive ccRCC subtype associated with metastasis and a subtype associated with a more favorable course of the disease. Among them were genes associated with blood clotting (FGA, FGG) and genes associated with changes in the immune characteristics of a tumor (ENAM, IGFBP1, IL6). In addition, an association of hub genes of poor survival ccRCC subtype with the levels of infiltration of endothelial cells, hematopoietic stem cells, T cells NK and mast cells was revealed. It was shown that MFI2, CP, FGA, and FGG expression can predict the response to sunitinib, while the APOB, ENAM, IGFBP1, and MFI2 expression predict the response to nivolumab. The results obtained provide insight into the genetic characteristics underlying the aggressive subtype of ccRCC and may help develop new approaches to the treatment of this disease.

Keywords: кластеризация k-means, K-Means clustering, bioinformatics, биоинформатика, экспрессия генов, Cancer biomarkers, Онкобиомаркеры, genes expression