Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).
Aged
Algorithms
Cystadenoma, Serous
/ classification
Female
Gene Expression Regulation, Neoplastic
/ genetics
Humans
Lymphocytes, Tumor-Infiltrating
/ pathology
Middle Aged
Neoplasm Grading
Neoplasm Proteins
/ genetics
Neoplasm, Residual
/ classification
Ovarian Neoplasms
/ classification
Transcriptome
/ genetics
Journal
Clinical cancer research : an official journal of the American Association for Cancer Research
ISSN: 1557-3265
Titre abrégé: Clin Cancer Res
Pays: United States
ID NLM: 9502500
Informations de publication
Date de publication:
15 10 2020
15 10 2020
Historique:
received:
11
01
2020
revised:
31
03
2020
accepted:
11
06
2020
pubmed:
20
6
2020
medline:
24
11
2021
entrez:
20
6
2020
Statut:
ppublish
Résumé
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. 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. Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a 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.
Identifiants
pubmed: 32554541
pii: 1078-0432.CCR-20-0103
doi: 10.1158/1078-0432.CCR-20-0103
pmc: PMC7572656
mid: NIHMS1605101
doi:
Substances chimiques
Neoplasm Proteins
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
5411-5423Subventions
Organisme : NCI NIH HHS
ID : R01 CA172404
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA034196
Pays : United States
Organisme : Medical Research Council
ID : MC_UU_12023/20
Pays : United Kingdom
Organisme : NCATS NIH HHS
ID : UL1 TR000124
Pays : United States
Organisme : Cancer Research UK
ID : 15601
Pays : United Kingdom
Organisme : CIHR
ID : MOP-86727
Pays : Canada
Organisme : NCI NIH HHS
ID : R01 CA200854
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA008748
Pays : United States
Organisme : NCI NIH HHS
ID : K22 CA193860
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA168758
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA071789
Pays : United States
Organisme : NCI NIH HHS
ID : P50 CA136393
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA042014
Pays : United States
Organisme : Cancer Research UK
ID : 13086
Pays : United Kingdom
Commentaires et corrections
Type : CommentIn
Informations de copyright
©2020 American Association for Cancer Research.
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