Epithelial ovarian cancer is the leading cause of death from gynecologic malignancy among women in developed countries, and accounts for about 15,000 deaths in the US annually. Although the prognosis in cases detected at an early stage is quite favorable, the vast majority of cases are diagnosed at an advanced stage when five-year survival rates are only 30-40%. The poor prognosis of ovarian cancer is due to a combination of the aggressive characteristics of the disease and a lack of effective therapy, further compounded by late detection and resistance of most relapsed tumors to current treatments. Malignant ascites, a complication observed in terminal ovarian cancer, is a devastating condition that significantly contributes to poor quality of life and to mortality. In our orthotopic ovarian cancer models, mice frequently develop ascites. We have been working with 2 ovarian cancer cell lines that induce ascites differently. The mouse cell line ID8-VEGF-Defb29 induces large volumes of ascites, often more than 10 mL, the human OVCAR3 cell line, on the other hand, induces ascites less frequently and at smaller volumes of usually less than 0.2 mL. We compared the metabolic composition of the two different ascitic fluids, and their relationship to cell and cell culture media metabolites to characterize the ascites composition and better understand the differences between both cell lines, using high-resolution 1H magnetic resonance spectroscopy (MRS). The metabolomic analysis of biofluids, detected by high-resolution MRS, may help to identify metabolite profiles, which could serve as useful biomarkers for ovarian cancer detection. Such MRS derived biomarkers would not only help in ovarian cancer detection, but also expand our understanding of the biochemical and metabolic changes associated with ovarian cancer.Two ovarian cancer cell lines were used in the present study, the human OVCAR3 and the mouse ID8-VEGF-Defb29 (1) cell lines. Both cell lines were grown in RPMI medium with 10% fetal bovine serum. For the media analysis, once the cells were 80% confluent, 3 mL of media was spun down to remove cell debris. 400 µL of the supernatant was added to 200 µL of deuterium saline buffer for NMR analysis. For the cell analysis, we used 3 million cells per sample. After trypsinization, cells were washed 3 times in saline, and resuspended in 750 µL of saline buffer. The samples were then sonicated for 3 minutes with 1 second of pulse interval time under ice-cold condition, vortexed, centrifuged, and 600 µL of supernatant was used for NMR analysis. The ascitic fluids were obtained from orthotopic implanted OVCAR3 and ID8-VEGF-Defb29 tumor bearing mice. We performed microsurgical orthotopic implantation of ovarian cancer tissue onto the ovary of SCID and C57BL6 female mice respectively. The tumor tissue pieces used for the implantation were obtained from subcutaneous tumors after inoculation of 2 x 106 cells in the flank of female SCID and C57BL6 mice. The ascitic fluid was obtained directly from the peritoneal cavity, spun down to remove any cells. For the MRS acquisition, 50 μL of ascitic fluid supernatant was diluted in 550 μL of D2O saline buffer. High-resolution proton MRS was performed on an Avance III 750 MHz (17.6 T) Bruker MR spectrometer equipped with a 5 mm broad band inverse probe. 1H MR spectra with water suppression were acquired using a one-dimensional Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence with the following parameters: spectral width of 15,495.8 Hz, time domain data points of 64K, effective 90° flip angle, relaxation delay 10 s, acquisition time of 2.1 s, 128 number of scan with 8 dummy scan, a receiver gain of 1030, echo time 25 ms. CPMG pulse sequence with water suppression [PRESET-90°-(d-180-d)n-Aq] was performed to remove short T2 components arising due to the presence of proteins as well as to obtain a better baseline in the spectra (2). All spectra were processed using line broadening for exponential window function of 0.3 Hz prior to Fourier transformation, they were manually phased and automatically baseline corrected using TOPSPIN 2.1. The 1H NMR spectra were referenced to the methyl resonance of alanine at 1.48 ppm. Characterization of the metabolites was carried out on the basis of chemical shift, coupling constant, and splitting pattern of metabolites, as reported in literature and by comparison with standard MR spectra of metabolites reported by the Biological Magnetic Resonance Bank (BMRB, www.bmrb.wisc.edu) and one and two dimensional NMR spectroscopy (3).The ascites, cells and media MRS analysis revealed significant differences between OVCAR3 and ID8-VEGF-Defb29. Representative spectra obtained from ascites are shown in Figure 1. The ID8-VEGF-Defb29 ascitic fluid was characterized by higher levels of glutamine and glucose compared to the OVCAR3 fluid (Figure 2), and by lower levels of glutamate, lactate, choline and acetate. Metabolite patterns in cells and cell culture media differed from what was observed in ascitic fluid. The ID8-VEGF-Defb29 cells and their culture media were characterized by higher concentrations of lactate, alanine, glutamate, pyruvate, and by lower glutamine, choline, glucose, tyrosine, phenylalanine, leucine, and valine. The creatine level, higher in the ID8-VEGF-Defb29 cells compared to the OVCAR3 cells, was lower in the ID8-VEGF-Defb29 culture medium compared to the OVCAR3 culture medium. Our results showed significant differences between the metabolite profiles observed in the ascites compared to the ones from the cells and culture media for the 2 cell lines used in our study, especially for glucose, glutamine, and glutamate. Further investigations are necessary to better understand these differences. This study is a first step in profiling ovarian cancer biofluids, and can be extended to the analysis of serum and urine to provide information about changes in metabolite profiles, about ascites formation and to identify potential new biomarkers.