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

Emilie Lalonde, Adrian S. Ishkanian, Jenna Sykes, Michael Fraser, Helen Ross-Adams, Nicholas Erho, Mark J. Dunning, Silvia Halim, Alastair D. Lamb, Nathalie C. Moon, Gaetano Zafarana, Anne Y. Warren, Xianyue Meng, John Thoms, Michal R. Grzadkowski, Alejandro Berlin, Cherry L. Have, Varune R. Ramnarine, Cindy Q. Yao, Chad A. MalloffLucia L. Lam, Honglei Xie, Nicholas J. Harding, Denise Y.F. Mak, Kenneth C. Chu, Lauren C. Chong, Dorota H. Sendorek, Christine P'ng, Colin C. Collins, Jeremy A. Squire, Igor Jurisica, Colin Cooper, Rosalind Eeles, Melania Pintilie, Alan Dal Pra, Elai Davicioni, Wan L. Lam, Michael Milosevic, David E. Neal, Theodorus van der Kwast, Paul C. Boutros, Robert G. Bristow

Research output: Contribution to journalArticlepeer-review

189 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1521-1532
Number of pages12
JournalThe Lancet Oncology
Issue number13
StatePublished - 2014
Externally publishedYes

ASJC Scopus subject areas

  • Oncology


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