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S Turajlic, H Xu, K Litchfield, A Rowan, S Horswell, T Chambers, T O'Brien, JI Lopez, TBK Watkins, D Nicol, M Stares, B Challacombe, S Hazell, A Chandra, TJ Mitchell, L Au, C Eichler-Jonsson, F Jabbar, A Soultati, S Chowdhury, S Rudman, J Lynch, A Fernando, G Stamp, E Nye, A Stewart, W Xing, JC Smith, M Escudero, A Huffman, N Matthews, G Elgar, B Phillimore, M Costa, S Begum, S Ward, M Salm, S Boeing, R Fisher, L Spain, C Navas, E Grönroos, S Hobor, S Sharma, I Aurangzeb, S Lall, A Polson, M Varia, C Horsfield, N Fotiadis, L Pickering, RF Schwarz, B Silva, J Herrero, NM Luscombe, M Jamal-Hanjani, R Rosenthal, NJ Birkbak, GA Wilson, O Pipek, D Ribli, M Krzystanek, I Csabai, Z Szallasi, M Gore, N McGranahan, P Van Loo, P Campbell, J Larkin and C Swanton
Abstract
The evolutionary features of clear-cell renal cell carcinoma (ccRCC) have not been systematically studied to date. We analyzed 1,206 primary tumor regions from 101 patients recruited into the multi-center prospective study, TRACERx Renal. We observe up to 30 driver events per tumor and show that subclonal diversification is associated with known prognostic parameters. By resolving the patterns of driver event ordering, co-occurrence, and mutual exclusivity at clone level, we show the deterministic nature of clonal evolution. ccRCC can be grouped into seven evolutionary subtypes, ranging from tumors characterized by early fixation of multiple mutational and copy number drivers and rapid metastases to highly branched tumors with >10 subclonal drivers and extensive parallel evolution associated with attenuated progression. We identify genetic diversity and chromosomal complexity as determinants of patient outcome. Our insights reconcile the variable clinical behavior of ccRCC and suggest evolutionary potential as a biomarker for both intervention and surveillance.
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Concepts
Biodiversity, Randomness, Bacteria, Population genetics, DNA, Genetics, Cancer, Gene
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