Development and validation of the gene-expression predictor of high-grade-serous ovarian carcinoma molecular subTYPE (PrOTYPE)

Talhouk, A. et al. (2020) Development and validation of the gene-expression predictor of high-grade-serous ovarian carcinoma molecular subTYPE (PrOTYPE). Clinical Cancer Research, 26(20), (doi: 10.1158/1078-0432.CCR-20-0103) (PMID:32554541) (PMCID:PMC7572656)

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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.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Ennis, Dr Darren and Lewsley, Ms Liz-Anne and Hinsley, Miss Samantha and Mcneish, Professor Iain and Glasspool, Dr Rosalind
Authors: Talhouk, A., George, J., Wang, C., Budden, T., Tan, T. Z., Chiu, D. S., Kommoss, S., Leong, H. S., Chen, S., Intermaggio, M. P., Gilks, B., Nazeran, T. M., Volchek, M., Elatre, W., Bentley, R. C., Senz, J., Lum, A., Chow, V., Sudderuddin, H., Mackenzie, R., Leung, S., Liu, G., Johnson, D., Chen, B., Ovarian Cancer Study, A., Alsop, J., Banerjee, S., Behrens, S., Bodelon, C., Brand, A. H., Brinton, L. A., Carney, M. E., Chiew, Y.-E., Cushing-Haugen, K. L., Cybulski, C., Ennis, D., Fereday, S., Fortner, R. T., García-Donás, J., Gentry-Maharaj, A., Glasspool, R., Goranova, T., Greene, C. S., Haluska, P., Harris, H. R., Hendley, J., Hernandez, B. Y., Herpel, E., Jimenez-Linan, M., Karpinskyj, C., Kaufmann, S. H., Keeney, G., Kennedy, C. J., Köbel, M., Koziak, J., Larson, M. C., Lester, J., Lewsley, L.-A., Lissowska, J., Lubiński, J., Luk, H., Macintyre, G., Mahner, S., McNeish, I. A., Menkiszak, J., Nevins, N., Osorio, A., Oszurek, O., Palacios, J., Hinsley, S., Pearce, C. L., Pike, M. C., Piskorz, A., Ray-Coquard, I., Rhenius, V., Rodríguez-Antona, C., Sharma, R., Sherman, M. E., Silva, D., Singh, N., Sinn, H.-P., Slamon, D. J., Song, H., Steed, H., Stronach, E. A., Thompson, P. J., Tołoczko-Grabarek, A., Trabert, B., Traficante, N., Tseng, C.-C., Widschwendter, M., Wilkens, L. R., Winham, S. J., Winterhoff, B. J., Beeghly-Fadiel, A., Benitez, J., Berchuck, A., Brenton, J. D., Brown, R., Chang-Claude, J., Chenevix-Trench, G., DeFazio, A., Fasching, P. A., Garcia, M. J., Gayther, S. A., Goodman, M. T., Gronwald, J., Henderson, M. J., Karlan, B. Y., Kelemen, L. E., Menon, U., Orsulic, S., Pharoah, P. D. P., Wentzensen, N., Wu, A. H., Shildkraut, J., Rossing, M. A., Konecny, G. E., Huntsman, D. G., Huang, R. Y.-J., Goode, E. L., Ramus, S. J., Doherty, J. A., Bowtell, D. D. L., and Anglesio, M. S.
College/School:College of Medical Veterinary and Life Sciences > School of Cancer Sciences
Journal Name:Clinical Cancer Research
Publisher:American Association for Cancer Research
ISSN (Online):1557-3265
Published Online:17 June 2020

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