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

Aline Talhouk, Joshy George, Chen Wang, Timothy Budden, Tuan Zea Tan, Derek S Chiu, Stefan Kommoss, Huei San Leong, Stephanie Chen, Maria P Intermaggio, Blake Gilks, Tayyebeh M Nazeran, Mila Volchek, Wafaa Elatre, Rex C Bentley, Janine Senz, Amy Lum, Veronica Chow, Hanwei Sudderuddin, Robertson MackenzieSamuel C Y Leong, Geyi Liu, Dustin Johnson, Billy Chen, Aocs Group, Jennifer Alsop, Susana N Banerjee, Sabine Behrens, Clara Bodelon, Alison H Brand, Louise Brinton, Michael E Carney, Yoke-Eng Chiew, Kara L Cushing-Haugen, Cezary Cybulski, Darren Ennis, Sian Fereday, Renée T Fortner, Jesús García-Donas, Aleksandra Gentry-Maharaj, Rosalind Glasspool, Teodora Goranova, Casey S Greene, Paul Haluska, Holly R Harris, Joy Hendley, Brenda Y Hernandez, Esther Herpel, Mercedes Jimenez-Linan, Chloe Karpinskyj, Scott H Kaufmann, Gary L Keeney, Catherine J Kennedy, Martin Köbel, Jennifer M Koziak, Melissa C Larson, Jenny Lester, Liz-Anne Lewsley, Jolanta Lissowska, Jan Lubiński, Hugh Luk, Geoff Macintyre, Sven Mahner, Iain A McNeish, Janusz Menkiszak, Nikilyn Nevins, Ana Osorio, Oleg Oszurek, José Palacios, Samantha Hinsley, Celeste L Pearce, Malcolm C Pike, Anna M Piskorz, Isabelle Ray-Coquard, Valerie Rhenius, Cristina Rodriguez-Antona, Raghwa Sharma, Mark E Sherman, Dilrini De Silva, Naveena Singh, Peter Sinn, Dennis Slamon, Honglin Song, Helen Steed, Euan A Stronach, Pamela J Thompson, Aleksandra Tołoczko, Britton Trabert, Nadia Traficante, Chiu-Chen Tseng, Martin Widschwendter, Lynne R Wilkens, Stacey J Winham, Boris Winterhoff, Alicia Beeghly-Fadiel, Javier Benitez, Andrew Berchuck, James D Brenton, Robert Brown, Jenny Chang-Claude, Georgia Chenevix-Trench, Anna deFazio, Peter A Fasching, María J García, Simon A Gayther, Marc T Goodman, Jacek Gronwald, Michelle J Henderson, Beth Y Karlan, Linda E Kelemen, Usha Menon, Sandra Orsulic, Paul D P Pharoah, Nicolas Wentzensen, Anna H Wu, Joellen M Schildkraut, Mary Anne Rossing, Gottfried E Konecny, David G Huntsman, Ruby Yun-Ju Huang, Ellen L Goode, Susan J Ramus, Jennifer A Doherty, David D Bowtell, Michael S Anglesio

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

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 nonstandardized 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 1,650 tumors. We applied resulting models to NanoString data on 3,829 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 were 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 analytic 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.

Bibliographical note

©2020 American Association for Cancer Research.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

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