Resistance prediction in HGSOC with NACT using data-independent acquisition proteomics and an ovarian tissue-specific spectral library

ABSTRACT: We firstly built a high-quality ovarian tissue-specific spectral library containing 130,735 peptides and 10,696 proteins on Orbitrap instruments. Compared to a published pan-human spectral library (DPHL), this spectral library provides 10% more ovary-specific and 3% more ovary-enriched proteins. This library was then applied to analyze data-independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10,070 proteins quantified, which is 9.73% more than that with DPHL. We then established a six-protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance of additional chemotherapy after IDS (Log-rank test, p = 0.002), which was further validated with 57 patients from an independent clinical center (p = 0.014). Together, we provided an ovary-specific spectral library for targeted proteome analysis, and proposed a six-protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT-IDS treatment.

ORGANISM(S): Homo Sapiens

SUBMITTER: Tiannan Guo  

PROVIDER: PXD039160 | iProX | Mon Jan 02 00:00:00 GMT 2023

REPOSITORIES: iProX