Abstract
The genetic landscape of clear cell renal cell carcinoma (ccRCC) had been investigated extensively but its evolution patterns remained unclear. Here we analyze the clonal architectures of 473 patients from three different populations. We find that the mutational signatures vary substantially across different populations and evolution stages. The evolution patterns of ccRCC have great inter-patient heterogeneities, with del(3p) being regarded as the common earliest event followed by three early departure points: VHL and PBRM1 mutations, del(14q) and other somatic copy number alterations (SCNAs) including amp(7), del(1p) and del(6q). We identify three prognostic subtypes of ccRCC with distinct clonal architectures and immune infiltrates: long-lived patients, enriched with VHL but depleted of BAP1 mutations, have high levels of Th17 and CD8+ T cells while short-lived patients with high burden of SCNAs have high levels of Tregs and Th2 cells, highlighting the importance of evaluating evolution patterns in the clinical management of ccRCC.
Highlights
The genetic landscape of clear cell renal cell carcinoma had been investigated extensively but its evolution patterns remained unclear
After several preprocessing and filtering steps, a total of 40,697 somatic single-nucleotide variants (SNVs) and 9,451 somatic copy number alterations (SCNAs) segments were kept for downstream analysis in the clear cell renal cell carcinoma (ccRCC)-473 cohort
We identified 12,458 and 4,143 subclonal SNVs and SCNA segments, respectively
Summary
The genetic landscape of clear cell renal cell carcinoma (ccRCC) had been investigated extensively but its evolution patterns remained unclear. Multi-region exome sequencing of several ccRCC patients showed that different sections of the same tumor masses harbored somatic events co-existing in distinct subclones which evolved following a branched pattern[14,15] These studies found that del(3p) and inactivation of VHL were trunk events while most of the other driver aberrations were subclonal. It is necessary to evaluate the inter-patient differences in ITH and evolution patterns systematically and to further analyze their influence on clinical outcomes in large cohorts of ccRCCs. Previous studies had demonstrated the possibility of reconstructing the clonal architecture of single tumor biopsy by estimating the fraction of tumor cells carrying either SCNAs or single-nucleotide variants (SNVs)[16,17,18,19]. We further perform molecular subtyping of ccRCC based on the CCFs of all potential prognostic events and characterize the expression and immune features of the different prognostic genomic subtypes
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