A single-cell transcriptome analysis and prognostic model construction of stromal cells for renal cell carcinoma

Abstract

Renal cell carcinoma (RCC) is among the top three cancers of the urinary system and its incidence keeps increasing worldwide in recent decades. However, methods for accurate prognosis evaluation and effective treatment are still lacking nowadays. Here, to explore the molecular expression features of RCC and establish a new RCC clinical prognosis evaluation model, a cell landscape of 187,263 renal cells obtained from eight patients with RCC was analyzed in this study. And by extracting and focusing on the main stromal cells from RCC tissues, innovative molecular characteristics and pathways of tumors were identified, like the well-known hypoxia pathway. By analyzing cell-cell communication, fibroblasts were found to promote tumor development by repressing natural killer cells. Based on Cox and least absolute shrinkage and selection operator regression analysis, four risk factors were screened and used to construct a reliable RCC clinical risk estimation model. In conclusion, our work provides new insights into the tumor microenvironment of RCC, as well as potential therapeutic targets and a clinical risk model for RCC invasiveness. Hopefully, these findings will be useful for cancer research and clinical treatment in future.