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Lancet Oncol. 2014 Dec;15(13):1521-32. doi: 10.1016/S1470-2045(14)71021-6. Epub 2014 Nov 13.

Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study.

Author information

1
Informatics and Bio-Computing Program, Ontario Institute for Cancer Research, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
2
Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, USA.
3
Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
4
Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
5
Uro-Oncology Research Group, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
6
Research and Development, GenomeDx Biosciences, Vancouver, BC, Canada.
7
Bioinformatics Core, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
8
Uro-Oncology Research Group, Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK; Department of Urology, Cambridge Biomedical Campus, Addenbrooke's Hospital, Cambridge, UK.
9
Informatics and Bio-Computing Program, Ontario Institute for Cancer Research, Toronto, ON, Canada.
10
Department of Pathology, Addenbrooke's Hospital, Cambridge, UK.
11
Department of Pathology, Laboratory Medicine Program, University Health Network, Toronto, ON, Canada.
12
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Vancouver Prostate Centre and Department of Urological Sciences, University of British Columbia, Vancouver, BC, Canada.
13
Department of Integrative Oncology, BC Cancer Research Centre, Vancouver, BC, Canada.
14
Informatics and Bio-Computing Program, Ontario Institute for Cancer Research, Toronto, ON, Canada; Center for Addiction and Mental Health, Toronto, ON, Canada.
15
Informatics and Bio-Computing Program, Ontario Institute for Cancer Research, Toronto, ON, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
16
Vancouver Prostate Centre and Department of Urological Sciences, University of British Columbia, Vancouver, BC, Canada.
17
Department of Pathology and Forensic Medicine, University of São Paulo at Ribeirão Preto, Ribeirão Preto, Brazil.
18
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.
19
Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK; Department of Biological Sciences and School of Medicine, University of East Anglia, Norwich, UK.
20
Division of Genetics and Epidemiology, The Institute of Cancer Research, Sutton, UK; Royal Marsden National Health Service Foundation Trust, London, UK.
21
Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Department of Radiation Oncology, Bern University Hospital, Bern, Switzerland.
22
Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.
23
Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Department of Pathology, Laboratory Medicine Program, University Health Network, Toronto, ON, Canada.
24
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada.
25
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada. Electronic address: rob.bristow@rmp.uhn.on.ca.

Abstract

BACKGROUND:

Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors.

METHODS:

We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment.

FINDINGS:

Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4·5 [95% CI 2·1-9·8]; p=0·00013; area under the receiver operator curve [AUC] 0·70 [95% CI 0·65-0·76]) and radical prostatectomy (4·0 [1·6-9·7]; p=0·0024; AUC 0·57 [0·52-0·61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 [1·2-12]; p=0·019; AUC 0·67 [0·61-0·73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 [95% CI 2·0-19]; p=0·0015; AUC 0·74 [95% CI 0·65-0·83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 [95% CI 1·4-6·0]; p=0·0039; AUC 0·68 [95% CI 0·63-0·73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures.

INTERPRETATION:

This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials.

FUNDING:

Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.

PMID:
25456371
DOI:
10.1016/S1470-2045(14)71021-6
[Indexed for MEDLINE]
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