Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer.

Autor: Fernandez-Mateos J; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK., Cresswell GD; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.; St. Anna Children's Cancer Research Institute, Vienna, Austria., Trahearn N; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK., Webb K; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.; The Royal Marsden NHS Foundation Trust, London, UK., Sakr C; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK., Lampis A; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK., Stuttle C; The Royal Marsden NHS Foundation Trust, London, UK.; Oncogenetics Team, The Institute of Cancer Research, London, UK., Corbishley CM; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.; St. George's Hospital Healthcare NHS Trust, London, UK., Stavrinides V; Division of Surgery and Interventional Science, UCL, London, UK., Zapata L; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK., Spiteri I; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK., Heide T; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.; Computational Biology Research Centre, Human Technopole, Milan, Italy., Gallagher L; Molecular Pathology Section, The Institute of Cancer Research, London, UK.; Clinical Genomics, The Royal Marsden NHS Foundation, London, UK., James C; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.; Computational Biology Research Centre, Human Technopole, Milan, Italy., Ramazzotti D; University of Milano Bicocca, Milan, Italy., Gao A; Bob Champion Cancer Unit, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK., Kote-Jarai Z; Oncogenetics Team, The Institute of Cancer Research, London, UK., Acar A; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.; Department of Biological Sciences, Middle East Technical University, Ankara, Turkey., Truelove L; Bob Champion Cancer Unit, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK., Proszek P; Molecular Pathology Section, The Institute of Cancer Research, London, UK.; Clinical Genomics, The Royal Marsden NHS Foundation, London, UK., Murray J; The Royal Marsden NHS Foundation Trust, London, UK.; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK., Reid A; The Royal Marsden NHS Foundation Trust, London, UK., Wilkins A; The Royal Marsden NHS Foundation Trust, London, UK.; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK., Hubank M; Molecular Pathology Section, The Institute of Cancer Research, London, UK.; Clinical Genomics, The Royal Marsden NHS Foundation, London, UK., Eeles R; The Royal Marsden NHS Foundation Trust, London, UK.; Oncogenetics Team, The Institute of Cancer Research, London, UK., Dearnaley D; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK. david.dearnaley@icr.ac.uk.; Academic Urology Unit, The Royal Marsden NHS Foundation Trust, London, UK. david.dearnaley@icr.ac.uk., Sottoriva A; Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK. andrea.sottoriva@fht.org.; Computational Biology Research Centre, Human Technopole, Milan, Italy. andrea.sottoriva@fht.org.
Jazyk: angličtina
Zdroj: Nature cancer [Nat Cancer] 2024 Sep; Vol. 5 (9), pp. 1334-1351. Date of Electronic Publication: 2024 Jul 12.
DOI: 10.1038/s43018-024-00787-0
Abstrakt: Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.
(© 2024. The Author(s).)
Databáze: MEDLINE
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