Single-cell deconvolution of a specific malignant cell population as a poor prognostic biomarker in low-risk clear cell renal cell carcinoma patients

BACKGROUND: Intra-tumor heterogeneity (ITH) is a key feature in clear-cell renal cell carcinomas (ccRCCs) which impacts outcomes such as aggressiveness, response to treatments or recurrence. In particular, it may explain tumor relapse after surgery in clinically low-risk patients who did not benefit from adjuvant therapy. Recently, single-cell RNA-seq (scRNA-seq) has emerged as a powerful tool to unravel expression intra-tumor heterogeneity (eITH) and might enable better assessment of clinical outcomes in ccRCC. OBJECTIVE: To explore eITH in ccRCC with a focus on malignant cells (MCs), and assess its relevance to improve prognosis for low-risk patients. RESULTS AND LIMITATIONS: We analyzed 54,812 cells and identified 35 cell subpopulations. The eITH analysis revealed that each tumor contained various degrees of clonal diversity. The transcriptomic signatures of MCs in one particularly heterogeneous sample were used to design a deconvolution-based strategy which allowed to risk-stratify 310 low-risk ccRCC patients. We performed scRNA-seq on tumor samples from five untreated ccRCC patients ranging from pT1a to pT3b. Data was complemented with a published dataset composed of pairs of matched normal and ccRCC samples. Submitter states that the raw data files (fastq files) have been submitted to the EGA repository