Email this article Diagnosis of Ia–Ic stages of serous high-grade ovarian cancerby the lipid profile of blood serum
- Authors: Iurova M.V.1,2, Frankevich V.E.1, Pavlovich S.V.1,2, Chagovets V.V.1, Starodubtseva N.L.1, Khabas G.N.1, Ashrafyan L.A.1, Sukhikh G.T.1,2
-
Affiliations:
- Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
- Sechenov First Moscow State Medical University (Sechenov University)
- Issue: Vol 23, No 4 (2021)
- Pages: 335-340
- Section: ORIGINAL ARTICLE
- URL: https://bakhtiniada.ru/2079-5831/article/view/80338
- DOI: https://doi.org/10.26442/20795696.2021.4.200911
- ID: 80338
Cite item
Full Text
Abstract
Background. Ovarian cancer is the first fatal malignancy of the female reproductive system. Early detection is associated with better outcomes, but is significantly difficult because of asymptomatic or low-symptomatic course.
Aim. To study the possibility of detecting of OC in early stages (Ia–Ic) by the lipid profile of blood serum obtained using high-performance liquid chromatography with mass spectrometric (MS) detection.
Materials and methods. An observational "case-control" study was conducted in period November 2019 – July 2020 in the Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology. 41 patients were included: group 1 (main) – 28 patients with histologically verified high grade serous ovarian cancer of I–IV FIGO stage, group 2 (control) – 13 conditionally healthy women. Venous blood samples were collected immediately before the operation. Extracts of serum lipids were obtained in accordance with the modified Folch method. The composition of the samples was analyzed by electrospray ionization MS. Using the method of discriminant analysis and orthogonal projections to latent structures (OPLS-DA) were building OPLS-models based on profile of significant lipids. The comparison based on the non-parametric Mann–Whitney test.
Results. The presence of 128 lipids in blood serum samples makes a major contribution to the OPLS-models, that are different for patients with I–IV OC stage and controls. The OPLS-model parameters are: R2=0.87 and Q2=0.80, the area under the ROC curve reached 1, sensitivity and specificity of the model – 100%. The second OPLS-model was developed to assign patients to 13 blood serum samples of the control group or to 5 blood samples of patients with I-II stages of OC: 108 lipids made the main contribution to this model (R2=0.97, Q2=0.86). The third OPLS-model was constructed to distinguish patients with earlier (Ia–Ia stages; n=5) and advanced (IIa–IVa; n=23) stages: R2=0.96 and Q2=1.00, AUC=0.99. Diglycerides, triglycerides, phosphatidylcholines, ethanolamines, sphingomyelins, ceramides, phosphatidylserines, phosphoinositols and prostaglandins significantly differ in the blood serum samples of patients with Ia–Ic stages of OC and patients with II–IV stages and controls, that indicates the diagnostic value.
Conclusion. It is possible to distinguish a healthy person from patient with Ia–Ic or II–IV stages of OC. Serum oncolipids profile obtained by high-performance liquid chromatography with MS detection can be used as markers of early stages of OC, that are associated with better prognosis.
Keywords
Full Text
##article.viewOnOriginalSite##About the authors
Mariia V. Iurova
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology; Sechenov First Moscow State Medical University (Sechenov University)
Email: m_yurova@oparina4.ru
ORCID iD: 0000-0002-0179-7635
Graduate Student, Sechenov First Moscow State Medical University (Sechenov University), Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
Russian Federation, Moscow; MoscowVladimir E. Frankevich
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
Email: v_frankevich@oparina4.ru
Cand. Sci. (Phys.-Math.)
Russian Federation, MoscowStanislav V. Pavlovich
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology; Sechenov First Moscow State Medical University (Sechenov University)
Email: s_pavlovich@oparina4.ru
Cand. Sci. (Med.), Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Sechenov First Moscow State Medical University (Sechenov University)
Russian Federation, Moscow; MoscowVitali V. Chagovets
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
Email: vvchagovets@gmail.com
Cand. Sci. (Phys.-Math.)
Russian Federation, MoscowNataliya L. Starodubtseva
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
Email: n_starodubtseva@oparina4.ru
Cand. Sci. (Biol.)
Russian Federation, MoscowGrigory N. Khabas
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
Email: g_khabas@oparina4.ru
Cand. Sci. (Med.)
Russian Federation, MoscowLev A. Ashrafyan
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology
Email: levaa2004@yahoo.com
ORCID iD: 0000-0001-6396-4948
D. Sci. (Med.), Prof., Acad. RAS
Russian Federation, MoscowGennady T. Sukhikh
Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology; Sechenov First Moscow State Medical University (Sechenov University)
Author for correspondence.
Email: g_sukhikh@oparina4.ru
Sci. (Med.), Prof., Acad. RAS, Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Sechenov First Moscow State Medical University (Sechenov University)
Russian Federation, Moscow; MoscowReferences
- USCS Data Visualizations – CDC. 2020 Available at: https://gis.cdc.gov/Cancer/USCS/DataViz.html Accessed: 15.04.2021.
- Koirala P, Moon AS, Chuang L. Clinical Utility of Preoperative Assessment in Ovarian Cancer Cytoreduction. Diagnostics (Basel). 2020;10(8):568.
- Schorge JO, Clark RM, Lee SI, Penson RT. Primary debulking surgery for advanced ovarian cancer: Are you a believer or a dissenter? Gynecol Oncol. 2014;135(3):595-605.
- Maringe C, Walters S, Butler J, et al. Stage at diagnosis and ovarian cancer survival: Evidence from the international cancer benchmarking partnership. Gynecol Oncol. 2012;127(1):75-82.
- Warren LA, Shih A, Renteira SM, et al. Analysis of menstrual effluent: Diagnostic potential for endometriosis. Mol Med. 2018;24(1):1.
- Devouassoux-Shisheboran M, Genestie C. Pathobiology of ovarian carcinomas. Chin J Cancer. 2015;34(1):50-5.
- Pavlovich SV, Yurova MV, Melkumyan AG, et al. Biomarkers in ovarian neoplasms: opportunities, limitations, and prospects for using in reproductive-aged women. Obstetrics and Gynegology. 2019;11:65-73. doi: 10.18565/aig.2019.11.65-73
- Xu Y. Lysophospholipid signaling in the epithelial ovarian cancer tumor microenvironment. Cancers (Basel). 2018;10(7):227.
- Hilvo M, de Santiago I, Gopalacharyulu P, et al. Accumulated metabolites of hydroxybutyric acid serve as diagnostic and prognostic biomarkers of ovarian high-grade serous carcinomas. Cancer Res. 2016;76(4):796-804.
- Trygg J, Wold S. Orthogonal projections to latent structures (O-PLS). J Chemometrics. 2002;16(3):119-28.
- R CoreTeam (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available at: https://www.R-project.org/ Accessed: 15.04.2021.
- RStudio Team (2016). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA. Available at: http://www.rstudio.com/ Accessed: 15.04.2021.
- Braicu EI, Darb-Esfahani S, Schmitt WD, et al. High-grade ovarian serous carcinoma patients exhibit profound alterations in lipid metabolism. Oncotarget. 2017;8(61):102912-22.
- Buas MF, Gu H, Djukovic D, et al. Identification of novel candidate plasma metabolite biomarkers for distinguishing serous ovarian carcinoma and benign serous ovarian tumors. Gynecol Oncol. 2016;140(1):138-44.
- Hou Y, Li J, Xie H, et al. Differential plasma lipids profiling and lipid signatures as biomarkers in the early diagnosis of ovarian carcinoma using UPLC-MS. Metabolomics. 2016;12(2):1-12.
Supplementary files
