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Determining the Impact of Spatial Heterogeneity on Genomic Prognostic Biomarkers for Localized Prostate Cancer.
Eur Urol Oncol. 2020 Jun 27 [Online ahead of print]EU

Abstract

Localized prostate tumors show remarkably diverse clinical courses, with some being cured by local therapy alone, while others rapidly relapse and have a lethal course despite precision surgery or radiotherapy. Many genomic biomarkers have been developed to predict this clinical behavior, but these are confounded by the extreme spatial heterogeneity of prostate tumors: most are multifocal and harbor multiple subclonal populations. To quantify the influence of spatial heterogeneity on genomic prognostic biomarkers, we developed a case-control high-risk cohort (n = 42) using a prospective registry, risk matched by clinicopathologic prognostic indices. Half of the cohort had early biochemical recurrence (BCR; ie, ≤18 mo), while half remained without evidence of disease for at least 48 mo after radical prostatectomy. We then genomically profiled multiple tumor foci per patient, analyzing 119 total specimens. These data allowed us to validate three published genomic prognostic biomarkers and quantify their sensitivity to tumor spatial heterogeneity. Remarkably, all three biomarkers robustly predicted early BCR, and all three were robust to spatiogenomic variability. These data suggest that DNA-based genomic biomarkers can overcome intratumoral heterogeneity: single biopsies may be sufficient to estimate the risk of early BCR after radical treatment in patients with high-risk disease. PATIENT

SUMMARY:

We investigated whether heterogeneity between tumor regions within the prostate affects the accuracy of DNA-based biomarkers predicting early relapse after prostatectomy. We observed persistent accuracy in predicting disease relapse, suggesting that spatial heterogeneity may not hinder biomarker performance.

Authors+Show Affiliations

Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Ontario Institute for Cancer Research, Toronto, ON, Canada; Department of Radiation Oncology, Queen's University, Kingston, ON, Canada.Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada.Ontario Institute for Cancer Research, Toronto, ON, Canada.Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada.Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Ontario Institute for Cancer Research, Toronto, ON, Canada.Department of Radiation Oncology, Queen's University, Kingston, ON, Canada.Division of Urology, Department of Surgery, Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada.Department of Pathology, Laboratory Medicine Program, University Health Network, Toronto, ON, Canada.Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Manchester Cancer Research Center, Manchester, UK.Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada; Department of Human Genetics, University of California, Los Angeles, CA, USA; Department of Urology, University of California, Los Angeles, CA, USA; Broad Stem Cell Research Center, University of California, Los Angeles, CA, USA; Institute for Precision Health, University of California, Los Angeles, CA, USA; Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA. Electronic address: PBoutros@mednet.ucla.edu.Radiation Medicine Program, Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada; Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada; Techna Institute, University Health Network, Toronto, ON, Canada. Electronic address: alejandro.berlin@rmp.uhn.ca.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32605887

Citation

Brastianos, Harry C., et al. "Determining the Impact of Spatial Heterogeneity On Genomic Prognostic Biomarkers for Localized Prostate Cancer." European Urology Oncology, 2020.
Brastianos HC, Murgic J, Salcedo A, et al. Determining the Impact of Spatial Heterogeneity on Genomic Prognostic Biomarkers for Localized Prostate Cancer. Eur Urol Oncol. 2020.
Brastianos, H. C., Murgic, J., Salcedo, A., Chua, M. L. K., Meng, A., Fraser, M., Brundage, M., Fleshner, N. E., van der Kwast, T., Bristow, R. G., Boutros, P. C., & Berlin, A. (2020). Determining the Impact of Spatial Heterogeneity on Genomic Prognostic Biomarkers for Localized Prostate Cancer. European Urology Oncology. https://doi.org/10.1016/j.euo.2020.06.005
Brastianos HC, et al. Determining the Impact of Spatial Heterogeneity On Genomic Prognostic Biomarkers for Localized Prostate Cancer. Eur Urol Oncol. 2020 Jun 27; PubMed PMID: 32605887.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Determining the Impact of Spatial Heterogeneity on Genomic Prognostic Biomarkers for Localized Prostate Cancer. AU - Brastianos,Harry C, AU - Murgic,Jure, AU - Salcedo,Adriana, AU - Chua,Melvin L K, AU - Meng,Alice, AU - Fraser,Michael, AU - Brundage,Michael, AU - Fleshner,Neil E, AU - van der Kwast,Theodorus, AU - Bristow,Robert G, AU - Boutros,Paul C, AU - Berlin,Alejandro, Y1 - 2020/06/27/ PY - 2020/02/17/received PY - 2020/06/07/revised PY - 2020/06/16/accepted PY - 2020/7/2/entrez KW - Biomarkers KW - Genomics KW - Heterogeneity KW - Prognostication KW - Prostate cancer JF - European urology oncology JO - Eur Urol Oncol N2 - Localized prostate tumors show remarkably diverse clinical courses, with some being cured by local therapy alone, while others rapidly relapse and have a lethal course despite precision surgery or radiotherapy. Many genomic biomarkers have been developed to predict this clinical behavior, but these are confounded by the extreme spatial heterogeneity of prostate tumors: most are multifocal and harbor multiple subclonal populations. To quantify the influence of spatial heterogeneity on genomic prognostic biomarkers, we developed a case-control high-risk cohort (n = 42) using a prospective registry, risk matched by clinicopathologic prognostic indices. Half of the cohort had early biochemical recurrence (BCR; ie, ≤18 mo), while half remained without evidence of disease for at least 48 mo after radical prostatectomy. We then genomically profiled multiple tumor foci per patient, analyzing 119 total specimens. These data allowed us to validate three published genomic prognostic biomarkers and quantify their sensitivity to tumor spatial heterogeneity. Remarkably, all three biomarkers robustly predicted early BCR, and all three were robust to spatiogenomic variability. These data suggest that DNA-based genomic biomarkers can overcome intratumoral heterogeneity: single biopsies may be sufficient to estimate the risk of early BCR after radical treatment in patients with high-risk disease. PATIENT SUMMARY: We investigated whether heterogeneity between tumor regions within the prostate affects the accuracy of DNA-based biomarkers predicting early relapse after prostatectomy. We observed persistent accuracy in predicting disease relapse, suggesting that spatial heterogeneity may not hinder biomarker performance. SN - 2588-9311 UR - https://www.unboundmedicine.com/medline/citation/32605887/Determining_the_Impact_of_Spatial_Heterogeneity_on_Genomic_Prognostic_Biomarkers_for_Localized_Prostate_Cancer L2 - https://linkinghub.elsevier.com/retrieve/pii/S2588-9311(20)30083-3 DB - PRIME DP - Unbound Medicine ER -
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