1. Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow, Russia 2. Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang, China 3. Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow, Russia; Siberian State Medical University, Tomsk, 634050 Russia
The molecular profile of a tumor is associated with its histological type and can be used both to study the mechanisms of tumor progression and to diagnose it. In this work, changes in the lipid profile of a malignant breast tumor and the adjacent tissue were studied. The potential possibility of determining the histological type of the tumor by its lipid profile was evaluated. Lipid profiling was performed by reverse-phase chromato-mass-spectrometric analysis the tissue of lipid extract with identification of lipids by characteristic fragments. Potential lipid markers of the histological type of tumor were determined using the Kruskal-Wallis test. Impact of lipid markers was calculated by MetaboAnalyst. Classification models were built by support vector machines with linear kernel and 1-vs-1 architecture. Models were validated by leave-one out cross-validation. Accuracy of models based on microenvironment tissue, were 99% and 75%, accuracy of models, based on tumor tissue, were 90% and 40% for the positive ion mode and negative ion mode respectively. The lipid profile of marginal (adjacent) tissue can be used for identification histological types of breast cancer. Glycerophospholipid metabolism pathway changes were statistically significant in the adjacent tissue and tumor tissue.
Download PDF:
Keywords: mass-spectrometry, lipidomics, breast cancer, tumor microenvironment, histology tumor type
Supplementary materials:
Citation:
Tokareva A.O., Chagovets V.V., Starodubtseva N.L., Rodionov V.V., Kometova V.V., Chingin K.S., Frankevich V.E. (2022) Lipidomic markers of breast cancer malignant tumor histological types. Biomeditsinskaya Khimiya, 68(5), 375-382.
Tokareva A.O. et al. Lipidomic markers of breast cancer malignant tumor histological types // Biomeditsinskaya Khimiya. - 2022. - V. 68. -N 5. - P. 375-382.
Tokareva A.O. et al., "Lipidomic markers of breast cancer malignant tumor histological types." Biomeditsinskaya Khimiya 68.5 (2022): 375-382.
Tokareva, A. O., Chagovets, V. V., Starodubtseva, N. L., Rodionov, V. V., Kometova, V. V., Chingin, K. S., Frankevich, V. E. (2022). Lipidomic markers of breast cancer malignant tumor histological types. Biomeditsinskaya Khimiya, 68(5), 375-382.
References
Ferlay J., Colombet M., Soerjomataram I., Parkin D.M., Piñeros M., Znaor A., Bray F. (2021) Cancer statistics for the year 2020: An overview. Int. J. Cancer, 149(4), 778-789. CrossRef Scholar google search
Durhan G., Poker A., Settarzade E., Karakaya J., Kösemehmetoğlu K., Akpınar M.G., Demirkazık F.B. (2021) Magnetic resonance imaging findings of invasive breast cancer in different histological grades and different histopathological types. Clin. Imaging, 76(1), 98-103. CrossRef Scholar google search
Metzger-Filho O., Ferreira A.R., Jeselsohn R., Barry W.T., Dillon D.A., Brock J.E., Vaz-Luis I., Hughes M.E., Winer E.P., Lin N.U. (2019) Mixed invasive ductal and lobular carcinoma of the breast: Prognosis and the importance of histologic grade. Oncologist, 24(7), e441-e449. CrossRef Scholar google search
Weigelt B., Geyer F.C., Reis-Filho J.S. (2010) Histological types of breast cancer: How special are they? Mol. Oncol., 4(3), 192-208. CrossRef Scholar google search
Kunnuru S.K.R., Thiyagarajan M., Martin Daniel J., Balaji Singh K. (2020) A study on clinical and pathological responses to neoadjuvant chemotherapy in breast carcinoma. Breast Cancer: Targets and Therapy, 12, 259-266. CrossRef Scholar google search
Bonacho T., Rodrigues F., Liberal J. (2020) Immunohistochemistry for diagnosis and prognosis of breast cancer: A review. Biotech. Histochem., 95(2), 71-91. CrossRef Scholar google search
Bandyopadhyay S., Bluth M.H., Ali-Fehmi R. (2018) Breast Carcinoma: Updates in molecular profiling 2018. Clin. Lab. Med., 38(2), 401-420. CrossRef Scholar google search
Becker-Putsche M., Bocklitz T., Clement J., Rösch P., Popp J. (2013) Toward improving fine needle aspiration cytology by applying Raman microspectroscopy. J. Biomed. Optics, 18(4), 047001. CrossRef Scholar google search
Talari A.C.S., Rehman S., Rehman I.U. (2019) Advancing cancer diagnostics with artificial intelligence and spectroscopy: identifying chemical changes associated with breast cancer. Exp. Rev. Mol. Diagn., 19(10), 929-940. CrossRef Scholar google search
Mas S., Torro A., Fernández L., Bec N., Gongora C., Larroque C., Martineau P., de Juan A., Marco S. (2020) MALDI imaging mass spectrometry and chemometric tools to discriminate highly similar colorectal cancer tissues. Talanta, 208(10), 120455. CrossRef Scholar google search
Sun R., Lyu M., Liang S., Ge W., Wang Y., Ding X., Zhang C., Zhou Y., Chen S., Chen L., Guo T. (2022) A prostate cancer tissue specific spectral library for targeted proteomic analysis. Proteomics, 22(7), 2100147. CrossRef Scholar google search
Tokareva A.O., Starodubtseva N.L., Chagovets V.V., Rodionov V.V., Kometova V.V., Chingin K.S., Frankevich V.E. (2022) Lipidomic markers of tumor progress in breast cancer patients. Biomeditsinskaya Khimiya, 68(2), 144-152. CrossRef Scholar google search
Folch J., Lees M., Sloane Stanley G. (1957) A simple method for the isolation and purification of total lipides from animal tissues. J. Biol. Chem., 226(1), 497-509. CrossRef Scholar google search
Koelmel J.P., Kroeger N.M., Ulmer C.Z., Bowden J.A., Patterson R.E., Cochran J.A., Beecher C.W.W., Garrett T.J., Yost R.A. (2017) LipidMatch: An automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data. BMC Bioinformatics, 18(1), 1-11. CrossRef Scholar google search
Pang Z., Chong J., Zhou G., De Lima Morais D.A., Chang L., Barrette M., Gauthier C., Jacques P.É., Li S., Xia J. (2021) MetaboAnalyst 5.0: Narrowing the gap between raw spectra and functional insights. Nucl. Acids Res., 49(W1), W388-W396. CrossRef Scholar google search
Ogata H., Goto S., Fujibuchi W., Kanehisa M. (1998) Computation with the KEGG pathway database. BioSystems, 47(1-2), 119-128. CrossRef Scholar google search
Yang T., Hui R., Nouws J., Sauler M., Zeng T., Wu Q. (2022) Untargeted metabolomics analysis of esophageal squamous cell cancer progression. J. Transl. Med., 20(1), 1-11. CrossRef Scholar google search
Montero J., Mari M., Colell A., Morales A., Basañez G., Garcia-Ruiz C., Fernández-Checa J.C. (2010) Cholesterol and peroxidized cardiolipin in mitochondrial membrane properties, permeabilization and cell death. Biochim. Biophys. Acta – Bioenergetics, 1797(6-7), 1217-1224. CrossRef Scholar google search
Piyarathna D.W.B., Rajendiran T.M., Putluri V., Vantaku V., Soni T., von Rundstedt F.C., Donepudi S.R., Jing F., Maity S., Ambati C.R., Dong J., Gödde D., Roth S., Störkel S., Degener S., Michailidis G., Lerner S.P., Pennathur S., Lotan Y., Coarfa C., Sreekumar A., Putluri N. (2018) Distinct lipidomic landscapes associated with clinical stages of urothelial cancer of the bladder. European Urology Focus, 4(6), 907-915. CrossRef Scholar google search
Podo F., Paris L., Cecchetti S., Spadaro F., Abalsamo L., Ramoni C., Ricci A., Pisanu M.E., Sardanelli F., Canese R., Iorio E. (2016) Activation of phosphatidylcholinespecific phospholipase C in breast and ovarian cancer: Impact on MRS-detected choline metabolic profile and perspectives for targeted therapy. Front. Oncol., 6(8), 2-9. CrossRef Scholar google search
Paris L., Podo F., Spadaro F., Abalsamo L., Pisanu M.E., Ricci A., Cecchetti S., Altabella L., Buoncervello M., Lozneanu L., Bagnoli M., Ramoni C., Canevari S., Mezzanzanica D., Iorio E., Canese R. (2017) Phosphatidylcholine-specific phospholipase C inhibition reduces HER2-overexpression, cell proliferation and in vivo tumor growth in a highly tumorigenic ovarian cancer model. Oncotarget, 8(33), 55022-55038. CrossRef Scholar google search
Akech J., Roy S.S., Das S.K. (2005) Modulation of cholinephosphotransferase activity in breast cancer cell lines by Ro5-4864, a peripheral benzodiazepine receptor agonist. Biochem. Biophys. Res. Commun., 333(1), 35-41. CrossRef Scholar google search
Lesko J., Triebl A., Stacher-Priehse E., Fink-Neuböck N., Lindenmann J., Smolle-Jüttner F.M., Köfeler H.C., Hrzenjak A., Olschewski H., Leithner K. (2021) Phospholipid dynamics in ex vivo lung cancer and normal lung explants. Exp. Mol. Med., 53(1), 81-90. CrossRef Scholar google search
Yu J., Qu L., Xia Y., Zhang X., Feng J., Duan M., Guo P., Lou Y., Lv P., Lu W., Chen Y. (2022) TMEM189 negatively regulates the stability of ULK1 protein and cell autophagy. Cell Death Disease, 13(4), 1-10. CrossRef Scholar google search
Rubio J.M., Astudillo A.M., Casas J., Balboa M.A., Balsinde J. (2018) Regulation of phagocytosis in macrophages by membrane ethanolamine plasmalogens. Front. Immunol., 9(7), 1-14. CrossRef Scholar google search
Tokareva A.O., Chagovets V.V., Rodionov V.V., Kometova V.V., Rodionova M.V., Starodubtseva N.L., Frankevich V.E. (2020) Lipid markers of metastatic lesions in regional lymph nodes in patients with breast cancer. Obstetrics and gynecology, no. 8, 133-140. CrossRef Scholar google search
Maley C., Aktipis A., Graham T., Sottoriva A., Boddy A., Janiszewska M., Silva A., Gerlinger M., Yuan Y., Pienta K., Anderson K., Gatenby R., Swanton C., Posada D., Wu C., Schiffman J., Hwang E., Polyak K., Anderson A., Brown J., Greaves M., Shibata D. (2017) Classifying the evolutionary and ecological features of neoplasms. Nature Reviews Cancer, 17(10), 605-619. CrossRef Scholar google search
