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pmid:37046833
Label-Free Quantification Mass Spectrometry Identifies Protein Markers of Chemotherapy Response in High-Grade Serous Ovarian Cancer.
Georgia Arentz · Parul Mittal · Manuela Klingler-Hoffmann · Mark R Condina · Carmela Ricciardelli · Noor A Lokman · Gurjeet Kaur · Martin K Oehler · Peter Hoffmann
Cancers · 2023 doi:10.3390/cancers15072172
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Experiment
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Data
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Complete file
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In addition, 20% of patients do not respond to treatment at all, as their disease is intrinsically chemotherapy resistant. Data-independent acquisition nano-flow liquid chromatography-mass spectrometry (DIA LC-MS) identified the three protein markers: gelsolin (GSN), calmodulin (CALM1), and thioredoxin (TXN), to be elevated in high-grade serous ovarian cancer (HGSOC) tissues from patients that responded to chemotherapy compared to those who did not; the differential expression of the three protein markers was confirmed by immunohistochemistry. Analysis of the online GENT2 database showed that mRNA levels of GSN, CALM1, and TXN were decreased in HGSOC compared to fallopian tube epithelium. Elevated levels of GSN and TXN mRNA expression correlated with increased overall and progression-free survival, respectively, in a Kaplan-Meier analysis of a large online repository of HGSOC patient data. Importantly, differential expression of the three protein markers was further confirmed when comparing parental OVCAR-5 cells to carboplatin-resistant OVCAR-5 cells using DIA LC-MS analysis. Our findings suggest that GSN, CALM1, and TXN may be useful biomarkers for predicting chemotherapy response and understanding the mechanisms of chemotherapy resistance. Proteomic data are available via ProteomeXchange with identifier PXD033785.", "claims": [{"id": "claim-method", "statement": "The quantification was performed using the summed area intensity of each peptide in each sample and the standard deviations and p values using un-paired t-tests were calculated using the GraphPad Prism 6 v008 (GraphPad Software, La Jolla, CA, USA).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37046833", "locator": "sections[9] \"2.7. 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