Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal
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Date
2018-04-19Author
Turajlic, Samra
Xu, Hang
Litchfield, Kevin
Rowan, Andrew
Horswell, Stuart
Chambers, Tim
O'Brien, Tim
Watkins, Thomas B. K.
Nicol, David
Stares, Mark
Challacombe, Ben
Hazell, Steve
Chandra, Ashish
Mitchell, Thomas J.
Au, Lewis
Eichler-Jonsson, Claudia
Jabbar, Faiz
Soultati, Aspasia
Chowdhury, Simon
Rudman, Sarah
Lynch, Joanna
Archana Sinduri, Fernando
Stamp, Gordon
Nye, Emma
Stewart, Aengus
Xing, Wei
Smith, Jonathan C.
Escudero, Mickael
Huffman, Adam
Matthews, Nik
Elgar, Greg
Phillimore, Ben
Costa, Marta
Begum, Sharmin
Ward, Sophia
Salm, Max
Boeing, Stefan
Fisher, Rosalie
Spain, Lavinia
Navas, Carolina
Gronroos, Eva
Hobor, Sebastijan
Sharma, Sarkhara
Aurangzeb, Ismaeel
Lall, Sharanpreet
Polson, Alexander
Varia, Mary
Horsfield, Catherine
Fotiadis, Nicos
Pickering, Lisa
Schwarz, Roland F.
Silva, Bruno
Herrero, Javier
Luscombe, Nick M.
Jamal-Hanjani, Mariam
Rosenthal, Rachel
Birkbak, Nicolai J.
Wilson, Gareth A.
Pipek, Orsolya
Ribli, Dezso
Krzystanek, Marcin
Csabai, Istvan
Szállási, Zoltán
Gore, Martin E.
McGranahan, Nicholas
Van Loo, Peter
Campbell, Peter
Larkin, James
Swanton, Charles
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Cell 173(3) : 595-610 (2018)
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.