Abstract
Simple SummaryIn-time diagnosing ovarian cancer, intractable cancer that has no symptoms can increase the survival of women. The aim of this study was to discover biomarkers from liquid biopsy samples using multi-omics approach, metabolomics and proteomics for the diagnosis of ovarian cancer. To verify our biomarker candidates, we conducted comparative analysis with other previous published studies. Despite the limitations of non-invasive samples, our findings are able to discover emerging properties through the interplay between metabolites and proteins and mechanism-based biomarkers through integrated protein and metabolite analysis.The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified.
Highlights
Ovarian cancer is one of the fatal gynecological cancers, and the 5-year survival rate is approximately 47.7% which is the 8th lowest among cancers from 2008 to 2014 [1]
Asymptomatic cancer disease progression occurs in the early stages of ovarian cancer with a 5-year survival rate of 92%, and symptoms appear in the later stages with a 5-year survival rate of 29% [3,4]
We carried out flow injection analysis (FIA) or LC–MS/MS profiling to discover blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer and we presented an analysis of the plasma metabolome and proteome in the 20 clinical samples
Summary
Ovarian cancer is one of the fatal gynecological cancers, and the 5-year survival rate is approximately 47.7% which is the 8th lowest among cancers from 2008 to 2014 [1]. It is the fifth most common cause of cancer deaths in the United States, and about 14,000 women die from it each year [2]. Screening with plasma cancer antigen 125 (CA-125). A novel biomarker for diagnosing the cancer is needed, and for this purpose, we applied two-omics, proteomic and metabolic, approaches to clinical plasma samples from the same person
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