Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study
Summary 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 stratificatio...
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Published in | The lancet oncology Vol. 15; no. 13; pp. 1521 - 1532 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.12.2014
Elsevier Limited |
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Abstract | Summary 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. |
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AbstractList | 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. 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. 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. 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. 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. 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. 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 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 4·5 [95% CI 2·1-9·8]; p=0·00013; area under the receiver operator curve 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. Summary 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. |
Author | Collins, Colin C, Prof Dal Pra, Alan, MD Dunning, Mark J, PhD Moon, Nathalie C, MMath Fraser, Michael, PhD Eeles, Rosalind, Prof Davicioni, Elai, PhD Milosevic, Michael, MD Have, Cherry L, BSc Squire, Jeremy A, Prof Lalonde, Emilie, MSc Chong, Lauren C, BCS Bristow, Robert G, Prof Thoms, John, MD Neal, David E, Prof Lam, Lucia L, BSc Ramnarine, Varune R, BCS Erho, Nicholas, MSc van der Kwast, Theodorus, Prof Berlin, Alejandro, MD Ishkanian, Adrian S, MD Mak, Denise Y F, PhD Sykes, Jenna, MMath Lamb, Alastair D, FRCS Sendorek, Dorota H, BSc Jurisica, Igor, Prof Zafarana, Gaetano, PhD Yao, Cindy Q, MSc Xie, Honglei, MMath P'ng, Christine, BSc Malloff, Chad A, MSc Grzadkowski, Michal R, BMath Chu, Kenneth C, PhD Warren, Anne Y, FRCPath Cooper, Colin, PhD Pintilie, Melania, MSc Halim, Silvia, MSc Meng, Xianyue, MSc Ross-Adams, Helen, PhD Harding, Nicholas J, PhD Lam, Wan L, Prof Boutros, Paul C, Prof |
Author_xml | – sequence: 1 fullname: Lalonde, Emilie, MSc – sequence: 2 fullname: Ishkanian, Adrian S, MD – sequence: 3 fullname: Sykes, Jenna, MMath – sequence: 4 fullname: Fraser, Michael, PhD – sequence: 5 fullname: Ross-Adams, Helen, PhD – sequence: 6 fullname: Erho, Nicholas, MSc – sequence: 7 fullname: Dunning, Mark J, PhD – sequence: 8 fullname: Halim, Silvia, MSc – sequence: 9 fullname: Lamb, Alastair D, FRCS – sequence: 10 fullname: Moon, Nathalie C, MMath – sequence: 11 fullname: Zafarana, Gaetano, PhD – sequence: 12 fullname: Warren, Anne Y, FRCPath – sequence: 13 fullname: Meng, Xianyue, MSc – sequence: 14 fullname: Thoms, John, MD – sequence: 15 fullname: Grzadkowski, Michal R, BMath – sequence: 16 fullname: Berlin, Alejandro, MD – sequence: 17 fullname: Have, Cherry L, BSc – sequence: 18 fullname: Ramnarine, Varune R, BCS – sequence: 19 fullname: Yao, Cindy Q, MSc – sequence: 20 fullname: Malloff, Chad A, MSc – sequence: 21 fullname: Lam, Lucia L, BSc – sequence: 22 fullname: Xie, Honglei, MMath – sequence: 23 fullname: Harding, Nicholas J, PhD – sequence: 24 fullname: Mak, Denise Y F, PhD – sequence: 25 fullname: Chu, Kenneth C, PhD – sequence: 26 fullname: Chong, Lauren C, BCS – sequence: 27 fullname: Sendorek, Dorota H, BSc – sequence: 28 fullname: P'ng, Christine, BSc – sequence: 29 fullname: Collins, Colin C, Prof – sequence: 30 fullname: Squire, Jeremy A, Prof – sequence: 31 fullname: Jurisica, Igor, Prof – sequence: 32 fullname: Cooper, Colin, PhD – sequence: 33 fullname: Eeles, Rosalind, Prof – sequence: 34 fullname: Pintilie, Melania, MSc – sequence: 35 fullname: Dal Pra, Alan, MD – sequence: 36 fullname: Davicioni, Elai, PhD – sequence: 37 fullname: Lam, Wan L, Prof – sequence: 38 fullname: Milosevic, Michael, MD – sequence: 39 fullname: Neal, David E, Prof – sequence: 40 fullname: van der Kwast, Theodorus, Prof – sequence: 41 fullname: Boutros, Paul C, Prof – sequence: 42 fullname: Bristow, Robert G, Prof |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25456371$$D View this record in MEDLINE/PubMed |
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Snippet | Summary Background Clinical prognostic groupings for localised prostate cancers are imprecise, with 30–50% of patients recurring after image-guided... Clinical prognostic groupings for localised prostate cancers are imprecise, with 30–50% of patients recurring after image-guided radiotherapy or radical... Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or radical... Background Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or... |
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SubjectTerms | Antigens Biomarkers, Tumor - genetics Biopsy Cancer therapies Deoxyribonucleic acid DNA DNA, Neoplasm - genetics Follow-Up Studies Gene Expression Profiling Genomes Genomics Hematology, Oncology and Palliative Medicine Humans Hypoxia Male Men Metastasis Mortality Neoplasm Recurrence, Local - diagnosis Neoplasm Recurrence, Local - genetics Oligonucleotide Array Sequence Analysis Patients Prognosis Prostate cancer Prostatic Neoplasms - genetics Radiation therapy Retrospective Studies Time Factors Tumor Microenvironment - genetics |
Title | Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study |
URI | https://www.clinicalkey.es/playcontent/1-s2.0-S1470204514710216 https://dx.doi.org/10.1016/S1470-2045(14)71021-6 https://www.ncbi.nlm.nih.gov/pubmed/25456371 https://www.proquest.com/docview/1627109999 https://search.proquest.com/docview/1694978289 |
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