Prediction of Potential Prognostic Tumor Markers of Re-ascites After Chemotherapy for Ovarian Cancer Based on LC/MS Method ​

Abstract

Background: Tumor cells are not only in a state of exuberant metabolism, but also inseparable from the surrounding microenvironment for the occurrence and development of tumors. By means of metabonomics technology, the metabolic profiles of re-ascites after chemotherapy in ovarian cancer ascites microenvironment were compared, and new tumor markers were screened for the treatment and prognosis of ovarian cancer.Methods: Thirty-seven cases of ovarian cancer were selected, of which 12 cases had ovarian cancer tissues, ascites supernatant and precipitated cells. By using UHPLC-Q-TOF MS/MS and combined with HMDB database, differential metabolites are identified and then differential pathways are enriched. Results: The results revealed that 10 differential metabolites were screened between chemotherapy and no-chemotherapy groups, and 9 differential metabolites were found in chemotherapy-sensitive and chemotherapy-resistant groups, in the ascites of ovarian cancer. Among the 19 differential metabolites, 9 metabolites combined with serum CA125 were analyzed by receiver operating characteristic analyses, which showed more the predictive value of diagnosis of malignancy. Among them, Tow differential metabolites (2/9) were correlated with the expression of CA125, five differential metabolite (5/9) related enzyme genes were statistically significant in overall survival and progression free survival (PFS) analysis. Four differential metabolites (4/9) were correlated with the expression of uric acid, creatinine, γ-GGT and ALP in serum. Conclusions: The results suggest that differential metabolites are mainly involved in PPAR signal pathway, steroid biosynthesis, fatty acid metabolism, secondary bile acid biosynthesis and so on. Lipid metabolites of ovarian cancer ascites cells may promote fatty acid oxidation by activating AMPK, promote lipid synthesis through mTOR/PPAR, provide energy for cancer cells, inhibit apoptosis and promote metastasis. Thus targeted lipid metabolism signal transduction axis can inhibit ovarian cancer metastasis and drug resistance.