Integrated bulk and single-cell transcriptome data identify clinically relevant cell populations in clear cell renal cell carcinoma.

Renal cell carcinoma,which consists of three main histo-logical subtypes,namely,clear cell renal cell carcinoma(ccRCC),papillary RCC(pRCC),and chromophobe RCC(chRCC),accounts for most kidney cancer cases.ccRCC accounts for approximately 85％ of all RCC cases,1 and it is a malignant tumor with multiple molecular features and a poor prognosis.Studies have shown that ccRCC is one of the most immune and vaso-invasive cancer types.2 Considering that ccRCC is not sensitive to either radiotherapy or chemotherapy,targeted therapies,such as vascular endo-thelial growth factor inhibitors/tyrosine kinase inhibitors and immunotherapy,are now the mainstay first-line ther-apies that are used in the clinic.However,a significant proportion of patients do not respond to the two treat-ments mentioned above or have high recurrence rates,which are related to the high degree of tumor heteroge-neity and the tumor microenvironment(TME)2 of ccRCC.Single-cell transcriptome sequencing provides accurate gene expression data at the single-cell level.Integrated single-cell and large transcriptome data from ccRCC sam-ples provide comprehensive information,such as informa-tion about prognosis,metastasis,and response to sorafenib and anti-PD-1 treatment.In the present study,we aimed to integrate bulk and single-cell transcriptome data to reveal the clinically relevant cell types in renal cell carcinoma,aiming to reveal the underlying molecular mechanism.