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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| creator | Lalonde, Emilie, MSc Ishkanian, Adrian S, MD Sykes, Jenna, MMath Fraser, Michael, PhD Ross-Adams, Helen, PhD Erho, Nicholas, MSc Dunning, Mark J, PhD Halim, Silvia, MSc Lamb, Alastair D, FRCS Moon, Nathalie C, MMath Zafarana, Gaetano, PhD Warren, Anne Y, FRCPath Meng, Xianyue, MSc Thoms, John, MD Grzadkowski, Michal R, BMath Berlin, Alejandro, MD Have, Cherry L, BSc Ramnarine, Varune R, BCS Yao, Cindy Q, MSc Malloff, Chad A, MSc Lam, Lucia L, BSc Xie, Honglei, MMath Harding, Nicholas J, PhD Mak, Denise Y F, PhD Chu, Kenneth C, PhD Chong, Lauren C, BCS Sendorek, Dorota H, BSc P'ng, Christine, BSc Collins, Colin C, Prof Squire, Jeremy A, Prof Jurisica, Igor, Prof Cooper, Colin, PhD Eeles, Rosalind, Prof Pintilie, Melania, MSc Dal Pra, Alan, MD Davicioni, Elai, PhD Lam, Wan L, Prof Milosevic, Michael, MD Neal, David E, Prof van der Kwast, Theodorus, Prof Boutros, Paul C, Prof Bristow, Robert G, Prof |
| description | 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 D |
| doi_str_mv | 10.1016/S1470-2045(14)71021-6 |
| format | Article |
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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.</description><identifier>ISSN: 1470-2045</identifier><identifier>EISSN: 1474-5488</identifier><identifier>DOI: 10.1016/S1470-2045(14)71021-6</identifier><identifier>PMID: 25456371</identifier><identifier>CODEN: LANCAO</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>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</subject><ispartof>The lancet oncology, 2014-12, Vol.15 (13), p.1521-1532</ispartof><rights>Lalonde et al. Open Access article distributed under the terms of CC BY</rights><rights>2014 Lalonde et al. Open Access article distributed under the terms of CC BY</rights><rights>Copyright © 2014 Lalonde et al. Open Access article distributed under the terms of CC BY. Published by Elsevier Ltd. All rights reserved.</rights><rights>Copyright Elsevier Limited Dec 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c580t-dc719dbffbc5280255f1589d1c1c65963a86904f95c011bc5470792a581468653</citedby><cites>FETCH-LOGICAL-c580t-dc719dbffbc5280255f1589d1c1c65963a86904f95c011bc5470792a581468653</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1470204514710216$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25456371$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lalonde, Emilie, MSc</creatorcontrib><creatorcontrib>Ishkanian, Adrian S, MD</creatorcontrib><creatorcontrib>Sykes, Jenna, MMath</creatorcontrib><creatorcontrib>Fraser, Michael, PhD</creatorcontrib><creatorcontrib>Ross-Adams, Helen, PhD</creatorcontrib><creatorcontrib>Erho, Nicholas, MSc</creatorcontrib><creatorcontrib>Dunning, Mark J, PhD</creatorcontrib><creatorcontrib>Halim, Silvia, MSc</creatorcontrib><creatorcontrib>Lamb, Alastair D, FRCS</creatorcontrib><creatorcontrib>Moon, Nathalie C, MMath</creatorcontrib><creatorcontrib>Zafarana, Gaetano, PhD</creatorcontrib><creatorcontrib>Warren, Anne Y, FRCPath</creatorcontrib><creatorcontrib>Meng, Xianyue, MSc</creatorcontrib><creatorcontrib>Thoms, John, MD</creatorcontrib><creatorcontrib>Grzadkowski, Michal R, BMath</creatorcontrib><creatorcontrib>Berlin, Alejandro, MD</creatorcontrib><creatorcontrib>Have, Cherry L, BSc</creatorcontrib><creatorcontrib>Ramnarine, Varune R, BCS</creatorcontrib><creatorcontrib>Yao, Cindy Q, MSc</creatorcontrib><creatorcontrib>Malloff, Chad A, MSc</creatorcontrib><creatorcontrib>Lam, Lucia L, BSc</creatorcontrib><creatorcontrib>Xie, Honglei, MMath</creatorcontrib><creatorcontrib>Harding, Nicholas J, PhD</creatorcontrib><creatorcontrib>Mak, Denise Y F, PhD</creatorcontrib><creatorcontrib>Chu, Kenneth C, PhD</creatorcontrib><creatorcontrib>Chong, Lauren C, BCS</creatorcontrib><creatorcontrib>Sendorek, Dorota H, BSc</creatorcontrib><creatorcontrib>P'ng, Christine, BSc</creatorcontrib><creatorcontrib>Collins, Colin C, Prof</creatorcontrib><creatorcontrib>Squire, Jeremy A, Prof</creatorcontrib><creatorcontrib>Jurisica, Igor, Prof</creatorcontrib><creatorcontrib>Cooper, Colin, PhD</creatorcontrib><creatorcontrib>Eeles, Rosalind, Prof</creatorcontrib><creatorcontrib>Pintilie, Melania, MSc</creatorcontrib><creatorcontrib>Dal Pra, Alan, MD</creatorcontrib><creatorcontrib>Davicioni, Elai, PhD</creatorcontrib><creatorcontrib>Lam, Wan L, Prof</creatorcontrib><creatorcontrib>Milosevic, Michael, MD</creatorcontrib><creatorcontrib>Neal, David E, Prof</creatorcontrib><creatorcontrib>van der Kwast, Theodorus, Prof</creatorcontrib><creatorcontrib>Boutros, Paul C, Prof</creatorcontrib><creatorcontrib>Bristow, Robert G, Prof</creatorcontrib><title>Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study</title><title>The lancet oncology</title><addtitle>Lancet Oncol</addtitle><description>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.</description><subject>Antigens</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biopsy</subject><subject>Cancer therapies</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>DNA, Neoplasm - genetics</subject><subject>Follow-Up Studies</subject><subject>Gene Expression Profiling</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Hematology, Oncology and Palliative Medicine</subject><subject>Humans</subject><subject>Hypoxia</subject><subject>Male</subject><subject>Men</subject><subject>Metastasis</subject><subject>Mortality</subject><subject>Neoplasm Recurrence, Local - diagnosis</subject><subject>Neoplasm Recurrence, Local - genetics</subject><subject>Oligonucleotide Array Sequence Analysis</subject><subject>Patients</subject><subject>Prognosis</subject><subject>Prostate cancer</subject><subject>Prostatic Neoplasms - genetics</subject><subject>Radiation therapy</subject><subject>Retrospective Studies</subject><subject>Time Factors</subject><subject>Tumor Microenvironment - genetics</subject><issn>1470-2045</issn><issn>1474-5488</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkc9u1DAQxiMEoqXwCCBLXMohYGdtx-FQhCr-SZU4UM6W1550XRJ7sZ2V8jS8KpNNAakXfBlr9JvP4--rqueMvmaUyTffGG9p3VAuzhl_1TLasFo-qE6xzWvBlXp4vK_ISfUk51tKGXLicXXSCC7kpmWn1a_raYxTIjcQ4ugtMcERrClCOPgUwwihmIHsoECKCIEvM-ljIj4UuEmmgCP7BM7b4mMgsSeinsEksvXR7gClcDqBnVKCYGEB9inmgoPEGuykt8QgULC5BxQ5YD_uYiokl8nNT6tHvRkyPLurZ9X3jx-uLz_XV18_fbl8f1VboWipnW1Z57Z9v7WiUbQRomdCdY5ZZqXo5MYo2VHed8JSxhBCZ9quMUIxLpUUm7PqfNXF7X5OkIsefbYwDCZAnLJmsuNdqxrVIfryHnqLDgbcDqkGHe7wICVWCr3MOUGv98mPJs2aUb0kqI8J6iUezbg-Jqglzr24U5-2I7i_U38iQ-DdCgDacfCQdLZ-8dZ59LloF_1_n7i4p2AHH5akfsAM-d9vdG40XUUWDayLgtz8BkjAwhs</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Lalonde, Emilie, MSc</creator><creator>Ishkanian, Adrian S, MD</creator><creator>Sykes, Jenna, 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prostate cancer: a retrospective cohort study</title><author>Lalonde, Emilie, MSc ; Ishkanian, Adrian S, MD ; Sykes, Jenna, MMath ; Fraser, Michael, PhD ; Ross-Adams, Helen, PhD ; Erho, Nicholas, MSc ; Dunning, Mark J, PhD ; Halim, Silvia, MSc ; Lamb, Alastair D, FRCS ; Moon, Nathalie C, MMath ; Zafarana, Gaetano, PhD ; Warren, Anne Y, FRCPath ; Meng, Xianyue, MSc ; Thoms, John, MD ; Grzadkowski, Michal R, BMath ; Berlin, Alejandro, MD ; Have, Cherry L, BSc ; Ramnarine, Varune R, BCS ; Yao, Cindy Q, MSc ; Malloff, Chad A, MSc ; Lam, Lucia L, BSc ; Xie, Honglei, MMath ; Harding, Nicholas J, PhD ; Mak, Denise Y F, PhD ; Chu, Kenneth C, PhD ; Chong, Lauren C, BCS ; Sendorek, Dorota H, BSc ; P'ng, Christine, BSc ; Collins, Colin C, Prof ; Squire, Jeremy A, Prof ; Jurisica, Igor, Prof ; Cooper, Colin, PhD ; Eeles, Rosalind, Prof ; Pintilie, Melania, MSc ; Dal Pra, Alan, MD ; Davicioni, Elai, PhD ; Lam, Wan L, Prof ; Milosevic, Michael, MD ; Neal, David E, Prof ; van der Kwast, Theodorus, Prof ; Boutros, Paul C, Prof ; Bristow, Robert G, Prof</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c580t-dc719dbffbc5280255f1589d1c1c65963a86904f95c011bc5470792a581468653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Antigens</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biopsy</topic><topic>Cancer therapies</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>DNA, Neoplasm - genetics</topic><topic>Follow-Up Studies</topic><topic>Gene Expression Profiling</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Hematology, Oncology and Palliative Medicine</topic><topic>Humans</topic><topic>Hypoxia</topic><topic>Male</topic><topic>Men</topic><topic>Metastasis</topic><topic>Mortality</topic><topic>Neoplasm Recurrence, Local - diagnosis</topic><topic>Neoplasm Recurrence, Local - genetics</topic><topic>Oligonucleotide Array Sequence Analysis</topic><topic>Patients</topic><topic>Prognosis</topic><topic>Prostate cancer</topic><topic>Prostatic Neoplasms - genetics</topic><topic>Radiation therapy</topic><topic>Retrospective Studies</topic><topic>Time Factors</topic><topic>Tumor Microenvironment - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lalonde, Emilie, MSc</creatorcontrib><creatorcontrib>Ishkanian, Adrian S, MD</creatorcontrib><creatorcontrib>Sykes, Jenna, MMath</creatorcontrib><creatorcontrib>Fraser, Michael, PhD</creatorcontrib><creatorcontrib>Ross-Adams, Helen, PhD</creatorcontrib><creatorcontrib>Erho, Nicholas, MSc</creatorcontrib><creatorcontrib>Dunning, Mark J, PhD</creatorcontrib><creatorcontrib>Halim, Silvia, MSc</creatorcontrib><creatorcontrib>Lamb, Alastair D, FRCS</creatorcontrib><creatorcontrib>Moon, Nathalie C, MMath</creatorcontrib><creatorcontrib>Zafarana, Gaetano, PhD</creatorcontrib><creatorcontrib>Warren, Anne Y, FRCPath</creatorcontrib><creatorcontrib>Meng, Xianyue, MSc</creatorcontrib><creatorcontrib>Thoms, John, MD</creatorcontrib><creatorcontrib>Grzadkowski, Michal R, BMath</creatorcontrib><creatorcontrib>Berlin, Alejandro, MD</creatorcontrib><creatorcontrib>Have, Cherry L, BSc</creatorcontrib><creatorcontrib>Ramnarine, Varune R, BCS</creatorcontrib><creatorcontrib>Yao, Cindy Q, MSc</creatorcontrib><creatorcontrib>Malloff, Chad A, MSc</creatorcontrib><creatorcontrib>Lam, Lucia L, BSc</creatorcontrib><creatorcontrib>Xie, Honglei, MMath</creatorcontrib><creatorcontrib>Harding, Nicholas J, PhD</creatorcontrib><creatorcontrib>Mak, Denise Y F, PhD</creatorcontrib><creatorcontrib>Chu, Kenneth C, PhD</creatorcontrib><creatorcontrib>Chong, Lauren C, BCS</creatorcontrib><creatorcontrib>Sendorek, Dorota H, BSc</creatorcontrib><creatorcontrib>P'ng, Christine, BSc</creatorcontrib><creatorcontrib>Collins, Colin C, Prof</creatorcontrib><creatorcontrib>Squire, Jeremy A, Prof</creatorcontrib><creatorcontrib>Jurisica, Igor, Prof</creatorcontrib><creatorcontrib>Cooper, Colin, PhD</creatorcontrib><creatorcontrib>Eeles, Rosalind, Prof</creatorcontrib><creatorcontrib>Pintilie, Melania, MSc</creatorcontrib><creatorcontrib>Dal Pra, Alan, MD</creatorcontrib><creatorcontrib>Davicioni, Elai, PhD</creatorcontrib><creatorcontrib>Lam, Wan L, Prof</creatorcontrib><creatorcontrib>Milosevic, Michael, MD</creatorcontrib><creatorcontrib>Neal, David E, Prof</creatorcontrib><creatorcontrib>van der Kwast, Theodorus, Prof</creatorcontrib><creatorcontrib>Boutros, Paul C, Prof</creatorcontrib><creatorcontrib>Bristow, Robert G, Prof</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE 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Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>The lancet oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lalonde, Emilie, MSc</au><au>Ishkanian, Adrian S, MD</au><au>Sykes, Jenna, MMath</au><au>Fraser, Michael, PhD</au><au>Ross-Adams, Helen, PhD</au><au>Erho, Nicholas, MSc</au><au>Dunning, Mark J, PhD</au><au>Halim, Silvia, MSc</au><au>Lamb, Alastair D, FRCS</au><au>Moon, Nathalie C, MMath</au><au>Zafarana, Gaetano, PhD</au><au>Warren, Anne Y, FRCPath</au><au>Meng, Xianyue, MSc</au><au>Thoms, John, MD</au><au>Grzadkowski, Michal R, BMath</au><au>Berlin, Alejandro, MD</au><au>Have, Cherry L, BSc</au><au>Ramnarine, Varune R, BCS</au><au>Yao, Cindy Q, MSc</au><au>Malloff, Chad A, MSc</au><au>Lam, Lucia L, BSc</au><au>Xie, Honglei, MMath</au><au>Harding, Nicholas J, PhD</au><au>Mak, Denise Y F, PhD</au><au>Chu, Kenneth C, PhD</au><au>Chong, Lauren C, BCS</au><au>Sendorek, Dorota H, BSc</au><au>P'ng, Christine, BSc</au><au>Collins, Colin C, Prof</au><au>Squire, Jeremy A, Prof</au><au>Jurisica, Igor, Prof</au><au>Cooper, Colin, PhD</au><au>Eeles, Rosalind, Prof</au><au>Pintilie, Melania, MSc</au><au>Dal Pra, Alan, MD</au><au>Davicioni, Elai, PhD</au><au>Lam, Wan L, Prof</au><au>Milosevic, Michael, MD</au><au>Neal, David E, Prof</au><au>van der Kwast, Theodorus, Prof</au><au>Boutros, Paul C, Prof</au><au>Bristow, Robert G, Prof</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study</atitle><jtitle>The lancet oncology</jtitle><addtitle>Lancet Oncol</addtitle><date>2014-12-01</date><risdate>2014</risdate><volume>15</volume><issue>13</issue><spage>1521</spage><epage>1532</epage><pages>1521-1532</pages><issn>1470-2045</issn><eissn>1474-5488</eissn><coden>LANCAO</coden><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.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>25456371</pmid><doi>10.1016/S1470-2045(14)71021-6</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1470-2045 |
| ispartof | The lancet oncology, 2014-12, Vol.15 (13), p.1521-1532 |
| issn | 1470-2045 1474-5488 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1694978289 |
| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | 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 |
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