Abstract
Purpose: Sarcomatoid renal cell carcinoma (SRCC) ranks among the most aggressive clinicopathologic phenotypes of RCC. However, the paucity of high-quality, genome-wide molecular examinations of SRCC has hindered our understanding of this entity. Experimental Design: We interrogated the mutational, copy number, and transcriptional characteristics of SRCC and compared these data with those of nonsarcomatoid RCC (RCC). We evaluated whole-exome sequencing, single-nucleotide polymorphism, and RNA sequencing data from patients with SRCC (n = 65) and RCC (n = 598) across different parent RCC subtypes, including clear-cell RCC, papillary RCC, and chromophobe RCC subtypes. Results: SRCC was molecularly discrete from RCC and clustered according to its parent RCC subtype, though with upregulation of TGFβ signaling across all subtypes. The epithelioid (E-) and spindled (S-) histologic components of SRCC did not show differences in mutational load among cancer-related genes despite a higher mutational burden in S-. Notably, sarcomatoid clear-cell RCC (SccRCC) showed significantly fewer deletions at 3p21-25, a lower rate of two-hit loss for VHL and PBRM1, and more mutations in PTEN, TP53, and RELN compared with ccRCC. A two-hit loss involving VHL predicted for ccRCC and a better prognosis, whereas mutations in PTEN, TP53, or RELN predicted for SccRCC and worse prognosis. Conclusions: SRCC segregates by parent subtype, and SccRCC has a fundamentally different early molecular pathogenesis, usually lacking the classic 3p21-25 deletion and showing distinctive mutational and transcriptional profiles. These features prompt a more precise molecular classification of RCC, with diagnostic, prognostic, and therapeutic implications.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 6686-6696 |
| Number of pages | 11 |
| Journal | Clinical Cancer Research |
| Volume | 23 |
| Issue number | 21 |
| DOIs | |
| State | Published - Nov 1 2017 |
ASJC Scopus subject areas
- Oncology
- Cancer Research
MD Anderson CCSG core facilities
- Bioinformatics Shared Resource
- Biostatistics Resource Group
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