| Title: |
Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE) |
| Authors: |
Talhouk, A; George, J; Wang, C; Budden, T; Tan, TZ; Chiu, DS; Kommoss, S; Leong, HS; Chen, S; Intermaggio, MP; Gilks, B; Nazeran, TM; Volchek, M; Elatre, W; Bentley, RC; 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, AH; Brinton, LA; Carney, ME; Chiew, Y-E; Cushing-Haugen, KL; Cybulski, C; Ennis, D; Fereday, S; Fortner, RT; García-Donás, J; Gentry-Maharaj, A; Glasspool, R; Goranova, T; Greene, CS; Haluska, P; Harris, HR; Hendley, J; Hernandez, BY; Herpel, E; Jimenez-Linan, M; Karpinskyj, C; Kaufmann, SH; Keeney, G; Kennedy, CJ; Köbel, M; Koziak, J; Larson, MC; Lester, J; Lewsley, L-A; Lissowska, J; Lubiński, J; Luk, H; Macintyre, G; Mahner, S; McNeish, IA; Menkiszak, J; Nevins, N; Osorio, A; Oszurek, O; Palacios, J; Hinsley, S; Pearce, CL; Pike, MC; Piskorz, A; Ray-Coquard, I; Rhenius, V; Rodríguez-Antona, C; Sharma, R; Sherman, ME; Silva, D; Singh, N; Sinn, H-P; Slamon, DJ; Song, H; Steed, H; Stronach, EA; Thompson, PJ; Tołoczko-Grabarek, A; Trabert, B; Traficante, N; Tseng, C-C; Widschwendter, M; Wilkens, LR; Winham, SJ; Winterhoff, BJ; Beeghly-Fadiel, A; Benitez, J; Berchuck, A; Brenton, JD; Brown, R; Chang-Claude, J; Chenevix-Trench, G; DeFazio, A; Fasching, PA; Garcia, MJ; Gayther, SA; Goodman, MT; Gronwald, J; Henderson, MJ; Karlan, BY; Kelemen, LE; Menon, U; Orsulic, S; Pharoah, PDP; Wentzensen, N; Wu, AH; Shildkraut, J; Rossing, MA; Konecny, GE; Huntsman, DG; Huang, RY-J; Goode, EL; Ramus, SJ; Doherty, JA; Bowtell, DDL; Anglesio, MS |
| Source: |
Clinical Cancer Research , 26 (20) pp. 5411-5423. (2020) |
| Publication Year: |
2020 |
| Collection: |
University College London: UCL Discovery |
| Description: |
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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
text |
| Language: |
English |
| Relation: |
https://discovery.ucl.ac.uk/id/eprint/10102331/ |
| Availability: |
https://discovery.ucl.ac.uk/id/eprint/10102331/1/1078-0432.CCR-20-0103.full.pdf; https://discovery.ucl.ac.uk/id/eprint/10102331/ |
| Rights: |
open |
| Accession Number: |
edsbas.61E47189 |
| Database: |
BASE |