Genomics

Dataset Information

0

TRACERx Renal 100


ABSTRACT: Evolutionary dynamics of clear cell renal cell carcinoma (ccRCC) have not been studied prospectively or across all disease stages. Through the multi-centre prospective cohort study, Renal TRACERx Renal, we analysed 1209 primary tumour regions from 101 patients with ccRCC. We detect up to 30 driver events in a single tumour, and show that subclonal diversification is associated with known clinical parameters. Defining driver event co-occurrence, mutual exclusivity and timing at clone level, we reveal deterministic patterns of clonal evolution and disease progression. We find that ccRCC can be grouped into seven distinct evolutionary subtypes, ranging from tumours characterised by early fixation of multiple mutational and copy number driver events that can disseminate widely and rapidly; to highly branched tumours with >10 subclonal drivers and extensive parallel evolution presenting with oligometastatic disease. We identify either heterogeneity or chromosome instability, or both, as determinants of patient outcome. Our insights reconcile the variable clinical behaviour of ccRCC and the benefit of surgical intervention in early and late-stage disease; and offer potential biomarker opportunities to maximise the benefit of both surgery and active surveillance.

PROVIDER: EGAS00001002793 | EGA |

REPOSITORIES: EGA

Similar Datasets

2015-09-18 | GSE73121 | GEO
2015-09-18 | GSE73119 | GEO
2022-04-04 | GSE113204 | GEO
2022-04-04 | GSE113205 | GEO
2013-06-03 | E-GEOD-40435 | biostudies-arrayexpress
2015-09-18 | E-GEOD-73119 | biostudies-arrayexpress
2015-09-18 | E-GEOD-73121 | biostudies-arrayexpress
2017-02-02 | GSE94378 | GEO
2013-06-03 | GSE40435 | GEO
2015-01-27 | E-MTAB-3269 | biostudies-arrayexpress