Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study.

Spatial patterns of tumour growth impact clonal diversification in a computational model and the TRACERx Renal study.
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DOI:
10.1038/s41559-021-01586-x
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发表时间:
2022-01
影响因子:
16.8
通讯作者:
Bates PA
Bates PA
中科院分区:
生物学1区
文献类型:
--
作者:
Fu X;Zhao Y;Lopez JI;Rowan A;Au L;Fendler A;Hazell S;Xu H;Horswell S;Shepherd STC;Spencer CE;Spain L;Byrne F;Stamp G;O'Brien T;Nicol D;Augustine M;Chandra A;Rudman S;Toncheva A;Furness AJS;Pickering L;Kumar S;Koh DM;Messiou C;Dafydd DA;Orton MR;Doran SJ;Larkin J;Swanton C;Sahai E;Litchfield K;Turajlic S;TRACERx Renal Consortium;Bates PA

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Genetic intra-tumour heterogeneity fuels clonal evolution, but our understanding of clinically relevant clonal dynamics remain limited. We investigated spatial and temporal features of clonal diversification in clear cell renal cell carcinoma through a combination of modelling and real tumour analysis. We observe that the mode of tumour growth, surface or volume, impacts the extent of subclonal diversification, enabling interpretation of clonal diversity in patient tumours. Specific patterns of proliferation and necrosis explain clonal expansion and emergence of parallel evolution and microdiversity in tumours. In silico time-course studies reveal the appearance of budding structures before detectable subclonal diversification. Intriguingly, we observe radiological evidence of budding structures in early-stage clear cell renal cell carcinoma, indicating that future clonal evolution may be predictable from imaging. Our findings offer a window into the temporal and spatial features of clinically relevant clonal evolution. A combined modelling and tumour analysis approach is used to study the temporal and spatial patterns of subclone evolution in the TRACERx renal study. Studying the tumour shape and spatial features of clonal diversity in early-stage tumours may allow the prediction of tumour progression and patterns of subclone diversification over time.
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