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Deterministic evolutionary trajectories influence primary tumor growth: TRACERx Renal

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posted on 14.09.2020 by Samra Turajlic, Hang Xu, Kevin Litchfield, Andrew Rowan, Stuart Horswell, Tim Chambers, Tim O’Brien, Jose I Lopez, Thomas BK Watkins, David Nicol, Mark Stares, Ben Challacombe, Steve Hazell, Ashish Chandra, Thomas J Mitchell, Lewis Au, Claudia Eichler-Jonsson, Faiz Jabbar, Aspasia Soultati, Simon Chowdhury, Sarah Rudman, Joanna Lynch, Archana Fernando, Gordon Stamp, Emma Nye, Aengus Stewart, Wei Xing, Jonathan C Smith, Mickael Escudero, Adam Huffman, Nik Matthews, Greg Elgar, Ben Phillimore, Marta Costa, Sharmin Begum, Sophia Ward, Max Salm, Stefan Boeing, Rosalie Fisher, Lavinia Spain, Carolina Navas, Eva Grönroos, Sebastijan Hobor, Sarkhara Sharma, Ismaeel Aurangzeb, Sharanpreet Lall, Alexander Polson, Mary Varia, Catherine Horsfield, Nicos Fotiadis, Lisa Pickering, Roland F Schwarz, Bruno Silva, Javier Herrero, Nick M Luscombe, Mariam Jamal-Hanjani, Rachel Rosenthal, Nicolai J Birkbak, Gareth A Wilson, Orsolya Pipek, Dezso Ribli, Marcin Krzystanek, Istvan Csabai, Zoltan Szallasi, Martin Gore, Nicholas McGranahan, Peter Van Loo, Peter Campbell, James Larkin, Charles Swanton, TRACERx Renal Consortium
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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