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TRACERx Renal 100

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.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001004067 1714
Publications Citations
Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal.
Cell 173: 2018 595-610.e11
310
Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.
Cell 173: 2018 581-594.e12
361
Selection of metastasis competent subclones in the tumour interior.
Nat Ecol Evol 5: 2021 1033-1045
31
Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study.
Nat Ecol Evol 6: 2022 88-102
22