PURPOSE: For the vast majority of ovarian cancer patients, optimal surgical debulking remains a key prognostic factor associated with improved survival. A standardized, biomarker-based test, to preoperatively discriminate benign from malignant disease and inform appropriate patient triage, is highly desirable. However, no fit-for-purpose biomarkers have yet been identified. EXPERIMENTAL DESIGN: We conducted a pilot study consisting of 40 patient urine samples (20 from each group), using label-free quantitative (LFQ) mass spectrometry, to identify potential biomarker candidates in urine from individual ovarian cancer patients. To validate these changes, we used parallel reaction monitoring (PRM) to investigate their abundance in an independent validation cohort (n = 20) of patient urine samples. RESULTS: LFQ analyses identified 4394 proteins (17 027 peptides) in a discovery set of 20 urine samples. Twenty-three proteins were significantly elevated in the malignant patient group compared to patients with benign disease. Several proteins, including LYPD1, LYVE1, PTMA, and SCGB1A1 were confirmed to be enriched in the urine of ovarian cancer patients using PRM. We also identified the established ovarian cancer biomarkers WFDC2 (HE4) and mesothelin (MSLN), validating our approach. CONCLUSIONS AND CLINICAL RELEVANCE: This is the first application of a LFQ-PRM workflow to identify and validate ovarian cancer-specific biomarkers in patient urine samples.
PURPOSE: For the vast majority of ovarian cancerpatients, optimal surgical debulking remains a key prognostic factor associated with improved survival. A standardized, biomarker-based test, to preoperatively discriminate benign from malignant disease and inform appropriate patient triage, is highly desirable. However, no fit-for-purpose biomarkers have yet been identified. EXPERIMENTAL DESIGN: We conducted a pilot study consisting of 40 patient urine samples (20 from each group), using label-free quantitative (LFQ) mass spectrometry, to identify potential biomarker candidates in urine from individual ovarian cancerpatients. To validate these changes, we used parallel reaction monitoring (PRM) to investigate their abundance in an independent validation cohort (n = 20) of patient urine samples. RESULTS: LFQ analyses identified 4394 proteins (17 027 peptides) in a discovery set of 20 urine samples. Twenty-three proteins were significantly elevated in the malignant patient group compared to patients with benign disease. Several proteins, including LYPD1, LYVE1, PTMA, and SCGB1A1 were confirmed to be enriched in the urine of ovarian cancerpatients using PRM. We also identified the established ovarian cancer biomarkers WFDC2 (HE4) and mesothelin (MSLN), validating our approach. CONCLUSIONS AND CLINICAL RELEVANCE: This is the first application of a LFQ-PRM workflow to identify and validate ovarian cancer-specific biomarkers in patient urine samples.
Authors: Erin Curry; Megan E Philpott; Jessye Wojtusik; Wendy D Haffey; Michael A Wyder; Kenneth D Greis; Terri L Roth Journal: Life (Basel) Date: 2022-05-27
Authors: Eline Oeyen; Kurt Van Mol; Geert Baggerman; Hanny Willems; Kurt Boonen; Christian Rolfo; Patrick Pauwels; An Jacobs; Karin Schildermans; William C Cho; Inge Mertens Journal: J Extracell Vesicles Date: 2018-07-03