Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)

• Type of Material: Article
• Authors: Aline Talhouk, Vancouver General Hospital; Joshy George, Jackson Laboratory for Genomic Medicine; Chen Wang, Mayo Clinic; Timothy Budden, University of NSW Sydney; Tuan Zea Tan, National University of Singapore; Derek S. Chiu, Vancouver General Hospital; Stefan Kommoss, Tuebingen University Hospital; Huei San Leong, Peter MacCallum Cancer Center; Stephanie Chen, Cedars Sinai Medical Center; Maria P. Intermaggio, University of NSW Sydney; Blake Gilks, Vancouver General Hospital; Tayyebeh M. Nazeran, Vancouver General Hospital; Mila Volchek, Royal Womens Hospitall; Joellen Schildkraut, Emory University; Ellen L. Goode, Mayo Clinic; Susan J. Ramus, University of NSW Sydney; Jennifer A. Doherty, University of NSW Sydney; David D. Bowtell, Peter MacCallum Cancer Center; Michael S. Anglesio, Vancouver General Hospital
• Language: English
• Date: 2020-10-15
• Publisher: American Association for Cancer Research
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2020 American Association for Cancer Research.
• Final Published Version (URL): http://dx.doi.org/10.1158/1078-0432.CCR-20-0103
• Title of Journal or Parent Work: Clinical Cancer Research
• Volume: 26
• Issue: 20
• Start Page: 5411
• End Page: 5423
• Grant/Funding Information: BriTROC-1 was funded by Ovarian Cancer Action (to IAM and JDB, grant number 006) and supported by Cancer Research UK (grant numbers A15973, A15601, A18072, A17197, A19274 and A19694) and the National Institute for Health Research Cambridge and Imperial Biomedical Research Centres.; M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation.; C. Wang was a Career Enhancement Awardee of the Mayo Clinic SPORE in Ovarian Cancer (P50 CA136393). D.G. Huntsman receives support from the Dr. Chew Wei Memorial Professorship in Gynecologic Oncology, and the Canada Research Chairs program (Research Chair in Molecular and Genomic Pathology).; Canadian Institutes for Health Research (Proof-of-Principle I program, PIs: D.G. Huntsman and M.S. Anglesio), the United States Department of Defense Ovarian Cancer Research Program (OC110433, PI: D.D. Bowtell) and others.; A. Talhouk is funded through a Michael Smith Foundation for Health Research Scholar Award.; Direct funding for this project was provided by the National Institutes of Health (R01-CA172404, PI: S.J. Ramus; and R01-CA168758, PIs: J.A. Doherty and M.A. Rossing),; In addition, other co-author, biobanks, patient-recruitment studies, and programs received funding that has indirectly supported this work.; M.J. Henderson received funding from Cancer Australia (1067110).; The AOV study is supported by the Canadian Institutes of Health Research (MOP-86727). The Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group, was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16.; H.R. Harris is supported by the NIH/National Cancer Institute award number K22 CA193860. OVCARE (including the VAN study) receives support through the BC Cancer Foundation and The VGH+UBC Hospital Foundation (authors AT, BG, DGH, and MSA).; G.E. Konecny is supported by the Miriam and Sheldon Adelson Medical Research Foundation. B.Y. Karlan is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124.; The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID199600; ID400413 and ID400281).; Core funding for this project was provided by the National Institutes of Health (R01-CA172404, PI: S.J. Ramus; and R01-CA168758, PIs: J.A. Doherty and M.A. Rossing); M. Widschwendter receives funding from the European Union’s Horizon 2020 European Research Council Programme, H2020 BRCA-ERC under Grant Agreement No. 742432 as well as the charity, The Eve Appeal (https://eveappeal.org.uk/), and support of the National Institute for Health Research (NIHR) and the University College London Hospitals (UCLH) Biomedical Research Centre.; J. George was partially supported by the NIH/National Cancer Institute award number P30CA034196.; Canadian Institutes for Health Research (Proof-of-Principle I program, PIs: D.G. Huntsman and M.S. Anglesio) and the United States Department of Defense Ovarian Cancer Research Program (OC110433, PI: D.D. Bowtell)
• Keywords: Women; Survival; Oncology; Life Sciences & Biomedicine; Disease dissemination; Signature; Classification; Bevacizumab; Poor-prognosis; T-cells; Cancer; Science & Technology; Clinical impact
• Research Categories: Health Sciences, Oncology; Health Sciences, Epidemiology; Biology, Cell; Biology, Genetics

Abstract

Purpose: Gene-expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by non-standardized methods which are not applicable in a clinical setting. We sought to generate a clinical-grade minimal gene-set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. Experimental Design: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene-expression data from 1650 tumors. We applied resulting models to NanoString data on 3829 HGSOCs from the Ovarian Tumor Tissue Analysis Consortium. We further developed, confirmed, and validated a reduced, minimal gene-set predictor, with methods suitable for a single patient setting. Results: Gene-expression data was used to derive the Predictor of high-grade-serous Ovarian carcinoma molecular subTYPE (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor infiltrating lymphocytes, and outcome. The locked-down clinical-grade PrOTYPE test includes a model with 55 genes that predicted gene-expression subtype with >95% accuracy that was maintained in all analytical and biological validations. Conclusions: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical-grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.