Serum lipid profiling analysis and potential marker discovery for ovarian cancer based on liquid chromatography–Mass spectrometry

Highlights

• Lipid profiling was found significantly changed in benign ovarian tumor (BOT) and epithelial ovarian cancer (EOC).

• Fatty acid, glycerophospholipid and ether-containing glycerophospholipid metabolism are mainly reprogrammed in BOT and EOC.

• Ceramide and ether-containing glycerophospholipid associated with eicosanoids showed distinct changes in EOC.

• The combinational lipid marker presented good performance in identifying early-stage EOC.

Abstract

Low early diagnosis rate and unclear pathogenesis are the primary reasons for the high mortality of epithelial ovarian cancer (EOC). Lipidomics is a powerful tool for marker discovery and mechanism explanation. Hence, a ultra high-performance liquid chromatography-mass spectrometry based non-targeted lipidomics analysis was performed to acquire lipid profiling of 153 serum samples including healthy control (HC, n = 50), benign ovarian tumor (BOT, n = 41), and EOC (n = 62) to reveal lipid disturbance, then differential lipids were verified in another sample set including 187 sera. Significant lipid disturbance occurred in BOT and EOC, fatty acid, lyso-phosphatidylcholine, and lyso-phosphatidylethanolamine were observed to be increased in BOT and EOC subjects, while phosphatidylcoline, ether phosphatidylcoline (PC-O), ether phosphatidylethanolamine (PE-O), and sphingomyelin significantly decreased. Compared with BOT, PC-Os and PE-Os presented a greater reduction in EOC, and serum ceramide increased only in EOC. Moreover, potential markers consisting of 4 lipids were defined and validated for EOC diagnosis. High areas under the curve (0.854∼0.865 and 0.903∼0.923 for distinguishing EOC and early EOC from non-cancer, respectively) as well as good specificity and sensitivity were obtained. This study not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.

Introduction

Ovarian cancer is a gynecological malignancy with the highest mortality rate in developed country [1]. Recently, the ovarian cancer morbidity has increased year by year [2] and the ovarian cancer patients have become younger at average age [3]. According to the classification method formulated by the world health organization, ovarian cancer is classified into epithelial ovarian cancer (EOC), germ cell tumors (GCT) and sex cord stromal tumors. Among all ovarian cancer cases, EOC accounts for 85%–90% with a low 5-years survival rate at 15%–45% [4]. Although researches about EOC based on genomics, proteomics, metabolomics and lipidomics have achieved considerable progresses, pathogenesis of EOC has not been well defined. In addition, ovarian cancer screening based on vaginal ultrasound and serum cancer antigen 125 (CA125) level still have high misdiagnosis rates, and other markers, such as antigens and antibodies, hormones, enzymes and non-coding RNAs, play limited roles in early EOC diagnosis. Because of the lack of specific early symptoms and pathological characteristics, most EOC patients have been diagnosed at stage III/IV or deteriorated into abdominal metastases in the first diagnosis time [5]. Research reported that most ovarian cancer patients at stage I were successfully cured, and the 5-year relative survival rate could reach 90 % [6]. Therefore, pathogenesis exploring and early diagnostic markers screening has a great value in EOC diagnosis and treatment.

Researches based on molecular biology, genomics, and proteomics suggested that lipid metabolism and changes in the expression and activity of enzymes involved in lipid metabolism in ovarian cancer were regulated by oncogenic signaling pathways [7]. For examples, the increased activity of fatty acid synthase in ovarian cancer promoted endoplasmic reticulum homeostasis by driving the synthesis of phospholipids in the endoplasmic reticulum, thereby promoting cell survival [8]. Lysophosphatidic acid (LPA) was found to be able to activate proteolytic enzymes, thereby enhancing the invasion and metastasis ability of ovarian cancer [7]. Moreover, changes in sphingolipid metabolism pathways including sphingomyelin, ceramide, and sphingosine 1-phosphate (S1P) were generally considered to be related to the apoptosis or survival of ovarian cancer cells [9]. These results demonstrated that dysfunction of lipid metabolism caused by the abnormal expression of lipid-related genes and enzyme has become an indispensable part of the pathogenesis of ovarian cancer. Hence, comprehensive study of lipid molecules in ovarian cancer should be focused to further understand the pathogenesis of ovarian cancer at the level of lipid metabolism.

Lipidomics is defined as whole qualitative and quantitative determination of lipid molecules in biological samples [10]. As a branch of metabolomics, lipidomics could not only evaluate lipid alterations throughout different periods of diseases process, but also systematically investigate the effects of abnormal lipids on the occurrence and development of diseases [11]. Recently, evidences from lipidomics research on ovarian cancer suggested glycerophospholipids were down-regulated in ovarian cancer patients compared with the control group, especially phosphatidylcoline (PC), phosphoethanolamine (PE) and plasmalogen [[12], [13], [14]]. In addition, several lipids such as sphingomyelin (SM) 41:1, Ceramide (Cer) (d20:1/24:1), lyso-phosphatidylglycerol (LPG) (20:5) and lysophosphatidic acid (LPA) were selected as potential biomarkers, but not as early diagnostic markers [14,15]. While the limitation of the existing research lies not only in the small sample size with total sample number less than 100 [[14], [15], [16]], but also in the lack of simultaneous multiple non-EOC controls including BOT, HC and other gynecological diseases [12]. Therefore, comprehensive lipid disturbance understanding and candidate markers screening for early diagnoses of EOC patients are urgently needed.

In this work, liquid chromatography-mass spectrometry (LC–MS) based non-targeted lipidomics was applied to acquire lipid profiling of serum samples from multi-center. Firstly, lipid characteristics and disordered lipid pathways of ovarian cancer were investigated, and then candidate diagnostic markers for EOC diagnosis, especially for EOC at early stage were screened and validated. The workflow of this study is displayed in Fig. 1.