Abstract
Simple SummaryOvarian cancer is a lethal disease due to its late phase discovery. Any steps towards improving early diagnostics will dramatically increase survival rates. To identify new ovarian cancer biomarker panels, we need to focus on early-stage disease and all histologic subtypes. In this study we have, based on prior discoveries, constructed a multiplexed targeted selected-reaction-monitoring assay to detect peptides from 177 proteins in only 20 µL of plasma. The assay was evaluated in patients with a focus on early-stages and all ovarian cancer histologies in separate groups. With multivariate analysis, we found the highest predictive value in the benign vs. low-grade serous (Q2 = 0.615) and mucinous (Q2 = 0.611) early stage compared to all malignant (Q2 = 0.226) or late stage (Q2 = 0.43) ovarian cancers. The results show that each ovarian cancer histology subgroup can be identified by a unique panel of proteins.Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I–II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 µL of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes.
Highlights
High-grade serous ovarian cancer (HGSC) accounts for 65–70% of all ovarian cancers (OC) and, are the ones that define the poor prognosis of the disease [1]
Phase I—Discovery—Biomarker discovery was performed in OC tumor biopsies and ovarian cyst fluids using shotgun mass spectrometry (Figure 1) [10,12,13]
Phase II—Verification—Proteins differentially expressed comparing OC histology subgroups and benign subjects were evaluated in patient plasma using targeted mass spectrometry applying selected reaction monitoring (SRM) [19]
Summary
High-grade serous ovarian cancer (HGSC) accounts for 65–70% of all ovarian cancers (OC) and, are the ones that define the poor prognosis of the disease [1]. The earlier cancer can be detected, the better the chance for a successful treatment. Survival increases from approximately 30% to 90% if diagnosed in early stages. The localized cancer can be treated with surgery alone, leaving adjuvant chemotherapy superfluous. OC is a highly diverse disease with several histologic subtypes. Supported by new insights in molecular genetics, OC was nearly 20 years ago designated two major groups, Type 1 and Type 2, revised in 2014 [2]. The Type 1, which included low-grade serous carcinoma (LGSC), endometrioid, clear-cell and mucinous OC, is very heterogenous, while
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