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

TY - JOUR

T1 - Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)

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 - Group, Aocs

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, Renée T

AU - García-Donas, Jesús

AU - Gentry-Maharaj, Aleksandra

AU - Glasspool, Rosalind

AU - Goranova, Teodora

AU - Greene, Casey S

AU - Haluska, Paul

AU - Harris, Holly R

AU - Hendley, Joy

AU - Hernandez, Brenda Y

AU - Herpel, Esther

AU - Jimenez-Linan, Mercedes

AU - Karpinskyj, Chloe

AU - Kaufmann, Scott H

AU - Keeney, Gary L

AU - Kennedy, Catherine J

AU - Köbel, Martin

AU - Koziak, Jennifer M

AU - Larson, Melissa C

AU - Lester, Jenny

AU - Lewsley, Liz-Anne

AU - Lissowska, Jolanta

AU - Lubiński, Jan

AU - Luk, Hugh

AU - Macintyre, Geoff

AU - Mahner, Sven

AU - McNeish, Iain A

AU - Menkiszak, Janusz

AU - Nevins, Nikilyn

AU - Osorio, Ana

AU - Oszurek, Oleg

AU - Palacios, José

AU - Hinsley, Samantha

AU - Pearce, Celeste L

AU - Pike, Malcolm C

AU - Piskorz, Anna M

AU - Ray-Coquard, Isabelle

AU - Rhenius, Valerie

AU - Rodriguez-Antona, Cristina

AU - Sharma, Raghwa

AU - Sherman, Mark E

AU - De Silva, Dilrini

AU - Singh, Naveena

AU - Sinn, Peter

AU - Slamon, Dennis

AU - Song, Honglin

AU - Steed, Helen

AU - Stronach, Euan A

AU - Thompson, Pamela J

AU - Tołoczko, Aleksandra

AU - Trabert, Britton

AU - Traficante, Nadia

AU - Tseng, Chiu-Chen

AU - Widschwendter, Martin

AU - Wilkens, Lynne R

AU - Winham, Stacey J

AU - Winterhoff, Boris

AU - Beeghly-Fadiel, Alicia

AU - Benitez, Javier

AU - Berchuck, Andrew

AU - Brenton, James D

AU - Brown, Robert

AU - Chang-Claude, Jenny

AU - Chenevix-Trench, Georgia

AU - deFazio, Anna

AU - Fasching, Peter A

AU - García, María J

AU - Gayther, Simon A

AU - Goodman, Marc T

AU - Gronwald, Jacek

AU - Henderson, Michelle J

AU - Karlan, Beth Y

AU - Kelemen, Linda E

AU - Menon, Usha

AU - Orsulic, Sandra

AU - Pharoah, Paul D P

AU - Wentzensen, Nicolas

AU - Wu, Anna H

AU - Schildkraut, Joellen M

AU - Rossing, Mary Anne

AU - Konecny, Gottfried E

AU - Huntsman, David G

AU - Huang, Ruby Yun-Ju

AU - Goode, Ellen L

AU - Ramus, Susan J

AU - Doherty, Jennifer A

AU - Bowtell, David D

AU - Anglesio, Michael S

N1 - ©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.See related commentary by McMullen et al., p. 5271.

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.See related commentary by McMullen et al., p. 5271.

U2 - 10.1158/1078-0432.CCR-20-0103

DO - 10.1158/1078-0432.CCR-20-0103

M3 - SCORING: Journal article

C2 - 32554541

VL - 26

SP - 5411

EP - 5423

JO - CLIN CANCER RES

JF - CLIN CANCER RES

SN - 1078-0432

IS - 20

ER -