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Proteomic Discovery of Plasma Protein Biomarkers and Development of Models Predicting Prognosis of High-Grade Serous Ovarian Carcinoma

Institution:	1. Department of Obstetrics and Gynecology, Seoul National University College of Medicine, Seoul, Republic of Korea;2. Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea;3. Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea;4. Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea;5. Department of Obstetrics and Gynecology, Seoul National University Hospital, Seoul, Republic of Korea

Abstract:	Ovarian cancer is one of the most lethal female cancers. For accurate prognosis prediction, this study aimed to investigate novel, blood-based prognostic biomarkers for high-grade serous ovarian carcinoma (HGSOC) using mass spectrometry–based proteomics methods. We conducted label-free liquid chromatography–tandem mass spectrometry using frozen plasma samples obtained from patients with newly diagnosed HGSOC (n = 20). Based on progression-free survival (PFS), the samples were divided into two groups: good (PFS ≥18 months) and poor prognosis groups (PFS <18 months). Proteomic profiles were compared between the two groups. Referring to proteomics data that we previously obtained using frozen cancer tissues from chemotherapy-naïve patients with HGSOC, overlapping protein biomarkers were selected as candidate biomarkers. Biomarkers were validated using an independent set of HGSOC plasma samples (n = 202) via enzyme-linked immunosorbent assay (ELISA). To construct models predicting the 18-month PFS rate, we performed stepwise selection based on the area under the receiver operating characteristic curve (AUC) with 5-fold cross-validation. Analysis of differentially expressed proteins in plasma samples revealed that 35 and 61 proteins were upregulated in the good and poor prognosis groups, respectively. Through hierarchical clustering and bioinformatic analyses, GSN, VCAN, SND1, SIGLEC14, CD163, and PRMT1 were selected as candidate biomarkers and were subjected to ELISA. In multivariate analysis, plasma GSN was identified as an independent poor prognostic biomarker for PFS (adjusted hazard ratio, 1.556; 95% confidence interval, 1.073–2.256; p = 0.020). By combining clinical factors and ELISA results, we constructed several models to predict the 18-month PFS rate. A model consisting of four predictors (FIGO stage, residual tumor after surgery, and plasma levels of GSN and VCAN) showed the best predictive performance (mean validated AUC, 0.779). The newly developed model was converted to a nomogram for clinical use. Our study results provided insights into protein biomarkers, which might offer clues for developing therapeutic targets.

Keywords:	ovarian neoplasms high-grade serous carcinoma proteomics enzyme-linked immunosorbent assay prognosis aHR"} {"#name":"keyword" "$":{"id":"kwrd0040"} "$$":[{"#name":"text" "_":"adjusted hazard ratio AUC"} {"#name":"keyword" "$":{"id":"kwrd0050"} "$$":[{"#name":"text" "_":"area under the receiver operating characteristic curve CI"} {"#name":"keyword" "$":{"id":"kwrd0060"} "$$":[{"#name":"text" "_":"confidence interval FDR"} {"#name":"keyword" "$":{"id":"kwrd0070"} "$$":[{"#name":"text" "_":"false discovery rate FIGO"} {"#name":"keyword" "$":{"id":"kwrd0080"} "$$":[{"#name":"text" "_":"Federation of Gynecology and Obstetrics GO"} {"#name":"keyword" "$":{"id":"kwrd0090"} "$$":[{"#name":"text" "_":"gene ontology GSN"} {"#name":"keyword" "$":{"id":"kwrd0100"} "$$":[{"#name":"text" "_":"gelsolin HGSOC"} {"#name":"keyword" "$":{"id":"kwrd0110"} "$$":[{"#name":"text" "_":"high-grade serous ovarian carcinoma iBAQ"} {"#name":"keyword" "$":{"id":"kwrd0120"} "$$":[{"#name":"text" "_":"intensity-based absolute quantification IDS"} {"#name":"keyword" "$":{"id":"kwrd0130"} "$$":[{"#name":"text" "_":"interval debulking surgery MS"} {"#name":"keyword" "$":{"id":"kwrd0150"} "$$":[{"#name":"text" "_":"mass spectrometry NAC"} {"#name":"keyword" "$":{"id":"kwrd0160"} "$$":[{"#name":"text" "_":"neoadjuvant chemotherapy OS"} {"#name":"keyword" "$":{"id":"kwrd0155v"} "$$":[{"#name":"text" "_":"overall survival PARP"} {"#name":"keyword" "$":{"id":"kwrd0170"} "$$":[{"#name":"text" "_":"poly(ADP-ribose) polymerase PDS"} {"#name":"keyword" "$":{"id":"kwrd0180"} "$$":[{"#name":"text" "_":"primary debulking surgery PFS"} {"#name":"keyword" "$":{"id":"kwrd0190"} "$$":[{"#name":"text" "_":"progression-free survival PRMT1"} {"#name":"keyword" "$":{"id":"kwrd0200"} "$$":[{"#name":"text" "_":"protein arginine methyltransferase 1 SIGLEC14"} {"#name":"keyword" "$":{"id":"kwrd0220"} "$$":[{"#name":"text" "_":"sialic acid–binding Ig-like lectin 14 SND1"} {"#name":"keyword" "$":{"id":"kwrd0230"} "$$":[{"#name":"text" "_":"staphylococcal nuclease tudor domain containing 1 VCAN"} {"#name":"keyword" "$":{"id":"kwrd0240"} "$$":[{"#name":"text" "_":"versican
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