Abstract
To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.
Original language | English (US) |
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Pages (from-to) | 3476-3498.e35 |
Journal | Cell |
Volume | 186 |
Issue number | 16 |
DOIs | |
State | Published - Aug 3 2023 |
Bibliographical note
Publisher Copyright:© 2023 The Authors
Keywords
- chemorefractory
- high-grade serous ovarian cancer
- machine learning
- mass spectrometry
- multiple reaction monitoring
- platinum
- precision oncology
- predictive biomarker
- prognostic biomarker
- proteogenomic
PubMed: MeSH publication types
- 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.