TY - JOUR
T1 - Development and validation of the gene expression predictor of high-grade serous ovarian carcinoma molecular SubTYPE (PrOTYPE)
AU - AOCS Group
AU - Talhouk, Aline
AU - George, Joshy
AU - Wang, Chen
AU - Budden, Timothy
AU - Tan, Tuan Zea
AU - Chiu, Derek S.
AU - Kommoss, Stefan
AU - Leong, Huei San
AU - Chen, Stephanie
AU - Intermaggio, Maria P.
AU - Gilks, Blake
AU - Nazeran, Tayyebeh M.
AU - Volchek, Mila
AU - Elatre, Wafaa
AU - Bentley, Rex C.
AU - Senz, Janine
AU - Lum, Amy
AU - Chow, Veronica
AU - Sudderuddin, Hanwei
AU - Mackenzie, Robertson
AU - Leong, Samuel C.Y.
AU - Liu, Geyi
AU - Johnson, Dustin
AU - Chen, Billy
AU - Alsop, Jennifer
AU - Banerjee, Susana N.
AU - Behrens, Sabine
AU - Bodelon, Clara
AU - Brand, Alison H.
AU - Brinton, Louise
AU - Carney, Michael E.
AU - Chiew, Yoke Eng
AU - Cushing-Haugen, Kara L.
AU - Cybulski, Cezary
AU - Ennis, Darren
AU - Fereday, Sian
AU - Fortner, Renee T.
AU - García-Donas, Jesus
AU - Gentry-Maharaj, Aleksandra
AU - Glasspool, Rosalind
AU - Goranova, Teodora
AU - Greene, Casey S.
AU - Haluska, Paul R Jr.
AU - Harris, Holly R.
AU - Hendley, Joy
AU - Kaufmann, Scott H.
AU - Keeney, Gary L.
AU - Sherman, Mark E.
AU - Winham, Stacey J.
AU - Goode, Ellen L.
N1 - Publisher Copyright:
© 2020 American Association for Cancer Research.
PY - 2020/10/15
Y1 - 2020/10/15
N2 - 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.
AB - 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.
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U2 - 10.1158/1078-0432.CCR-20-0103
DO - 10.1158/1078-0432.CCR-20-0103
M3 - Article
C2 - 32554541
AN - SCOPUS:85087402115
SN - 1078-0432
VL - 26
SP - 5411
EP - 5423
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 20
ER -