https://scholars.lib.ntu.edu.tw/handle/123456789/567407
標題: | Development and validation of the gene expression predictor of high-grade serous ovarian carcinoma molecular SubTYPE (PrOTYPE) | 作者: | 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. Leong S.C.Y. Liu G. Johnson D. Chen B. Alsop J. Banerjee S.N. Behrens S. Bodelon C. Brand A.H. Brinton L. Carney M.E. Chiew Y.-E. Cushing-Haugen K.L. Cybulski C. Ennis D. Fereday S. Fortner R.T. Garc?a-Donas 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.L. Kennedy C.J. Kobel M. Koziak J.M. Larson M.C. Lester J. Lewsley L.-A. Lissowska J. Lubi?ski 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.M. Ray-Coquard I. Rhenius V. Rodriguez-Antona C. Sharma R. Sherman M.E. de Silva D. Singh N. Sinn P. Slamon D. Song H. Steed H. Stronach E.A. Thompson P.J. To?oczko A. Trabert B. Traficante N. Tseng C.-C. Widschwendter M. Wilkens L.R. Winham S.J. Winterhoff B. Beeghly-Fadiel A. Benitez J. Berchuck A. Brenton J.D. Brown R. Chang-Claude J. Chenevix-Trench G. deFazio A. Fasching P.A. Garc?a 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. Schildkraut J.M. Rossing M.A. Konecny G.E. Huntsman D.G. RUBY YUN-JU HUANG Goode E.L. Ramus S.J. Doherty J.A. Bowtell D.D. Anglesio M.S. AOCS Group |
公開日期: | 2020 | 出版社: | American Association for Cancer Research Inc. | 卷: | 26 | 期: | 20 | 起(迄)頁: | 5411-5423 | 來源出版物: | Clinical Cancer Research | 摘要: | 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. ? 2020 American Association for Cancer Research. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087402115&doi=10.1158%2f1078-0432.CCR-20-0103&partnerID=40&md5=ed80bca017c98de2f42d58f459ddbff0 https://scholars.lib.ntu.edu.tw/handle/123456789/567407 |
ISSN: | 1078-0432 | DOI: | 10.1158/1078-0432.CCR-20-0103 | SDG/關鍵字: | accuracy; age; algorithm; Article; cancer classification; cancer staging; clinical outcome; consensus; gene expression; genetic association; high grade serous ovarian cancer molecular subtype; minimal residual disease; model; omics; ovary carcinoma; personalized medicine; prediction; predictive value; standard; tumor associated leukocyte; validation process; aged; cancer grading; classification; cystadenoma; female; gene expression regulation; genetics; human; middle aged; ovary tumor; pathology; transcriptome; tumor protein; Aged; Algorithms; Cystadenoma, Serous; Female; Gene Expression Regulation, Neoplastic; Humans; Lymphocytes, Tumor-Infiltrating; Middle Aged; Neoplasm Grading; Neoplasm Proteins; Neoplasm, Residual; Ovarian Neoplasms; Transcriptome |
顯示於: | 醫學系 |
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