Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study
Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.
The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.
A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.
Using partial least squares-discriminant analysis, we observed significant separation between all groups (p < 0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI) = 0.940 and 0.929 for HG and LG, respectively.
These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.
KeywordsSerous ovarian cancer 1H NMR Targeted mass spectrometry Metabolomics Multivariate data analysis
This research was supported by seed grant funding from the Cancer Research Seed Grant Award at Beaumont Health.
RBS supervised and designed the experiment, SFG and GG supervised all experimental procedures, AY and PK collected the metabolomics data, AY wrote the manuscript, AY performed statistical data analysis and bioinformatics, all authors read and reviewed the manuscript.
Compliance with ethical standards
Conflict of interest
The authors report no conflict of interest.
- Anastasi, E., Granato, T., Falzarano, R., Storelli, P., Ticino, A., Frati, L., et al. (2013). The use of HE4, CA125 and CA72-4 biomarkers for differential diagnosis between ovarian endometrioma and epithelial ovarian cancer. Journal of Ovarian Research, 6(1), 44–44. https://doi.org/10.1186/1757-2215-6-44.CrossRefPubMedPubMedCentralGoogle Scholar
- Atrih, A., Mudaliar, M. A. V., Zakikhani, P., Lamont, D. J., Huang, J. T. J., Bray, S. E., et al. (2014). Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling. British Journal of Cancer, 110(6), 1622–1633. https://doi.org/10.1038/bjc.2014.24.CrossRefPubMedPubMedCentralGoogle Scholar
- Bosse, K., Rhiem, K., Wappenschmidt, B., Hellmich, M., Madeja, M., Ortmann, M., et al. (2006). Screening for ovarian cancer by transvaginal ultrasound and serum CA125 measurement in women with a familial predisposition: A prospective cohort study. Gynecologic Oncology, 103(3), 1077–1082. https://doi.org/10.1016/j.ygyno.2006.06.032.CrossRefPubMedGoogle Scholar
- Cho, K. R., & Shih, I.-M. (2009). Ovarian cancer. Annual Review of Pathology, 4, 287–313. https://doi.org/10.1146/annurev.pathol.4.110807.092246.CrossRefPubMedPubMedCentralGoogle Scholar
- Graham, S. F., Kumar, P., Bahado-Singh, R. O., Robinson, A., Mann, D., & Green, B. D. (2016). Novel metabolite biomarkers of Huntington’s disease as detected by high-resolution mass spectrometry. Journal of Proteome Research, 15(5), 1592–1601. https://doi.org/10.1021/acs.jproteome.6b00049.CrossRefPubMedGoogle Scholar
- Hensley, K., & Denton, T. T. (2015). Alternative functions of the brain transsulfuration pathway represent an underappreciated aspect of brain redox biochemistry with significant potential for therapeutic engagement. Free Radical Biology & Medicine, 0, 123–134. https://doi.org/10.1016/j.freeradbiomed.2014.10.581.CrossRefGoogle Scholar
- Jarboe, E., Folkins, A., Nucci, M. R., Kindelberger, D., Drapkin, R., Miron, A., et al. (2008). Serous carcinogenesis in the fallopian tube: A descriptive classification. International Journal of Gynecological Pathology, 27(1), 1–9. https://doi.org/10.1097/pgp.0b013e31814b191f.CrossRefPubMedGoogle Scholar
- Kozar, N., Kruusmaa, K., Bitenc, M., Argamasilla, R., Adsuar, A., Goswami, N., et al. (2018). Metabolomic profiling suggests long chain ceramides and sphingomyelins as a possible diagnostic biomarker of epithelial ovarian cancer. Clinica Chimica Acta, 481, 108–114. https://doi.org/10.1016/j.cca.2018.02.029.CrossRefGoogle Scholar
- Kurman, R. J., Vang, R., Junge, J., Hannibal, C. G., Kjaer, S. K., & Ie, S., M (2011). Papillary tubal hyperplasia: The putative precursor of ovarian atypical proliferative (borderline) serous tumors, noninvasive implants, and endosalpingiosis. The American Journal of Surgical Pathology, 35(11), 1605–1614. https://doi.org/10.1097/PAS.0b013e318229449f.CrossRefPubMedPubMedCentralGoogle Scholar
- Moore, R. G., McMeekin, D. S., Brown, A. K., DiSilvestro, P., Miller, M. C., Allard, W. J., et al. (2009). A novel multiple marker bioassay utilizing HE4 and CA125 for the prediction of ovarian cancer in patients with a pelvic mass. Gynecologic Oncology, 112(1), 40–46. https://doi.org/10.1016/j.ygyno.2008.08.031.CrossRefPubMedGoogle Scholar
- Moreno, A., & Arus, C. (1996). Quantitative and qualitative characterization of 1H NMR spectra of colon tumors, normal mucosa and their perchloric acid extracts: Decreased levels of myo-inositol in tumours can be detected in intact biopsies. NMR in Biomedicine, 9(1), 33–45, https://doi.org/10.1002/(sici)1099-1492(199602)9:1%3C33::aid-nbm391%3E3.0.co;2-g.CrossRefPubMedGoogle Scholar
- Pencina, M. J., D’Agostino, R. B. Sr., D’Agostino, R. B. Jr., & Vasan, R. S. (2008). Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond. Statistics in Medicine, 27(2), 157–172. https://doi.org/10.1002/sim.2929 (discussion 207–112).CrossRefPubMedGoogle Scholar
- Perets, R., Wyant, G. A., Muto, K. W., Bijron, Jonathan, G., Poole, B. B., Chin, K. T., et al. (2013). Transformation of the fallopian tube secretory epithelium leads to high-grade serous ovarian cancer in Brca; Tp53; Pten models. Cancer Cell, 24(6), 751–765. https://doi.org/10.1016/j.ccr.2013.10.013.CrossRefPubMedPubMedCentralGoogle Scholar
- Petrillo, M., Anchora, L. P., Scambia, G., & Fagotti, A. (2016). Cytoreductive surgery plus platinum-based hyperthermic intraperitoneal chemotherapy in epithelial ovarian cancer: A promising integrated approach to improve locoregional control. The Oncologist, 21(5), 532–534. https://doi.org/10.1634/theoncologist.2015-0500.CrossRefPubMedPubMedCentralGoogle Scholar
- Piotto, M., Moussallieh, F.-M., Dillmann, B., Imperiale, A., Neuville, A., Brigand, C., et al. (2008). Metabolic characterization of primary human colorectal cancers using high resolution magic angle spinning 1H magnetic resonance spectroscopy. Metabolomics, 5(3), 292. https://doi.org/10.1007/s11306-008-0151-1.CrossRefGoogle Scholar
- Rauh-Hain, J. A., Krivak, T. C., del Carmen, M. G., & Olawaiye, A. B. (2011). Ovarian cancer screening and early detection in the general population. Reviews in Obstetrics & Gynecology, 4(1), 15–21.Google Scholar
- Salani, R., Kurman, R. J., Giuntoli, R. 2nd, Gardner, G., Bristow, R., Wang, T. L., et al. (2008). Assessment of TP53 mutation using purified tissue samples of ovarian serous carcinomas reveals a higher mutation rate than previously reported and does not correlate with drug resistance. International Journal of Gynecological Cancer, 18(3), 487–491. https://doi.org/10.1111/j.1525-1438.2007.01039.x.CrossRefPubMedGoogle Scholar
- Schmeler, K. M., Sun, C. C., Bodurka, D. C., Deavers, M. T., Malpica, A., Coleman, R. L., et al. (2008). Neoadjuvant chemotherapy for low-grade serous carcinoma of the ovary or peritoneum. Gynecologic Oncology, 108(3), 510–514. https://doi.org/10.1016/j.ygyno.2007.11.013.CrossRefPubMedGoogle Scholar
- Seidman, J. D. (2015). Serous tubal intraepithelial carcinoma localizes to the tubal-peritoneal junction: A pivotal clue to the site of origin of extrauterine high-grade serous carcinoma (ovarian cancer). International Journal of Gynecological Pathology, 34(2), 112–120. https://doi.org/10.1097/pgp.0000000000000123.CrossRefPubMedGoogle Scholar
- Timmermans, M., Sonke, G. S., Van de Vijver, K. K., van der Aa, M. A., & Kruitwagen, R. (2018). No improvement in long-term survival for epithelial ovarian cancer patients: A population-based study between 1989 and 2014 in the Netherlands. European Journal of Cancer, 88, 31–37. https://doi.org/10.1016/j.ejca.2017.10.030.CrossRefPubMedGoogle Scholar
- Turkoglu, O., Zeb, A., Graham, S., Szyperski, T., Szender, J. B., Odunsi, K., et al. (2016). Metabolomics of biomarker discovery in ovarian cancer: A systematic review of the current literature. Metabolomics, 12(4), 60. https://doi.org/10.1007/s11306-016-0990-0.CrossRefPubMedPubMedCentralGoogle Scholar
- Vang, R., Shih, I.-M., & Kurman, R. J. (2009). Ovarian low-grade and high-grade serous carcinoma: Pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems. Advances in Anatomic Pathology, 16(5), 267–282. https://doi.org/10.1097/PAP.0b013e3181b4fffa.CrossRefPubMedPubMedCentralGoogle Scholar
- Williams, T. I., Toups, K. L., Saggese, D. A., Kalli, K. R., Cliby, W. A., & Muddiman, D. C. (2007). Epithelial ovarian cancer: Disease etiology, treatment, detection, and investigational gene, metabolite, and protein biomarkers. Journal of Proteome Research, 6(8), 2936–2962. https://doi.org/10.1021/pr070041v.CrossRefPubMedGoogle Scholar