Pipeline of Mass-Spectrometry Data Processing for Diagnostic Molecular Marker Panel Obtaining Using the Example of Search Markers of Breast Cancer Metastasis

Article Sidebar

pdf (Русский) html (Русский) html
Published: Sep 30, 2021
DOI: https://doi.org/10.18097/BMCRM00156
Keywords:
mass-spectrometry; data processing; biological markers

Main Article Content

A.O. Tokareva
Skolkovo Institute of Science and Technology, 30 bld. 1 Bolshoy Boulevard,Moscow, 121205, Russia; V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Center of Chemical Physic, Russian Academy of Sciences, 38 bld. 2 Leninsky avenue, Moscow, 119334 Russia
V.V. Chagovets
Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, 4 bld. 2 Oparina str., Moscow, 117513 Russia
A.S. Kononikhin
Skolkovo Institute of Science and Technology, 30 bld. 1 Bolshoy Boulevard,Moscow, 121205, Russia; Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, 4 bld. 2 Oparina str., Moscow, 117513 Russia
N.L. Starodubtseva
V.L. Talrose Institute for Energy Problems of Chemical Physics, N.N. Semenov Federal Center of Chemical Physic, Russian Academy of Sciences, 38 bld. 2 Leninsky avenue, Moscow, 119334 Russia; Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, 4 bld. 2 Oparina str., Moscow, 117513 Russia
V.E. Frankevich
Academician V.I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, 4 bld. 2 Oparina str., Moscow, 117513 Russia
E.N. Nikolaev
Skolkovo Institute of Science and Technology, 30 bld. 1 Bolshoy Boulevard,Moscow, 121205, Russia

Abstract

A pathology diagnostic using molecular marker is a perspective direction of clinical medicine. Mass-spectrometry (MS) is a one of methods, which are used for obtaining information about molecular profiles. Selection of species, essential for classification “case/control is an important task for data processing. Pipeline of data processing has been proposed using MS data, obtained during analysis of tumor breast tissue samples and health breast tissue samples, with the aim of metastasis marker selection. As a result, selection of lipid markers that belong to classes, related to metastasis and proliferation processes, makes it possible to create high sensitivity diagnostic model, based on logistic regression. The proposed method is applicable for data processing, obtained by MS analysis of other “omics”: metabolome, proteome, glycome.

Article Details

How to Cite
Tokareva, A., Chagovets, V., Kononikhin, A., Starodubtseva, N., Frankevich, V., & Nikolaev, E. (2021). Pipeline of Mass-Spectrometry Data Processing for Diagnostic Molecular Marker Panel Obtaining Using the Example of Search Markers of Breast Cancer Metastasis. Biomedical Chemistry: Research and Methods, 4(3), e00156. https://doi.org/10.18097/BMCRM00156
Issue
Vol. 4 No. 3 (2021)
Section
EXPERIMENTAL RESEARCH

References

  1. Podo, F., Canevari, S., Canese, R., Pisanu, M.E., Ricci, A., Iorio, E. (2011) Tumour Phospholipid Metabolism. Exp. Oncol. 19, 1–10.
  2. Wong, M.W., Braidy, N., Poljak, A., Pickford, R., Thambisetty, M., Sachdev, P.S. (2017) Dysregulation of lipids in Alzheimer’s disease and their role as potential biomarkers. Alzheimer’s Dement. 13(7), 810–27, DOI
  3. Liu, X., Li, J., Zheng, P., Zhao, X., Zhou, C., Hu, C., Hou, X., Wang, H., Xie, P., Xu, G. (2016) Plasma lipidomics reveals potential lipid markers of major depressive disorder. Anal. Bioanal. Chem. 408(23), 6497–507, DOI
  4. Anand, S., Barnes, J.M., Young, S.A., Garcia, D.M., Tolley, H.D., Kauwe, J.S.K., Graves, S.W. (2017) Discovery and Confirmation of Diagnostic Serum Lipid Biomarkers for Alzheimer’s Disease Using Direct Infusion Mass Spectrometry. J. Alzheimer’s Dis. 59(1), 277–90, DOI
  5. Hogan, S.R., Phan, J.H., Alvarado-Velez, M., Wang, M.D., Bellamkonda, R. V., Fernández, F.M., Laplaca, M.C. (2018) Discovery of Lipidome Alterations Following Traumatic Brain Injury via High-Resolution Metabolomics. J. Proteome Res. 17(6), 2131–43, DOI
  6. Folch, J., Lees, M., Sloane Stanley, G.H. (1957) A simple method for the isolation and purification of total lipides from animal tissues. J. Biol. Chem. 226(1), 497–509.
  7. 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, DOI
  8. Pluskal, T., Castillo, S., Villar-Briones, A., Orešič, M. (2010) MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics 11, DOI
  9. Sud, M., Fahy, E., Cotter, D., Brown, A., Dennis, E.A., Glass, C.K., Merrill, A.H., Murphy, R.C., Raetz, C.R.H., Russell, D.W., Subramaniam, S. (2007) LMSD: LIPID MAPS structure database. Nucleic Acids Res. 35(SUPPL. 1), 527–32,
  10. Wold, S., Sjöström, M., Eriksson, L. (2001) PLS-regression: a basic tool of chemometrics. Chemom. Intell. Lab. Syst. 58(2), 109–30, DOI
  11. Galindo-Prieto, B., Eriksson, L., Trygg, J. (2015) Variable influence on projection (VIP) for OPLS models and its applicability in multivariate time series analysis. Chemom. Intell. Lab. Syst. 146, 297–304, DOI
  12. Akaike, H. (1998) Information Theory and an Extension of the Maximum Likelihood Principle. Sel. Pap. Hirotugu Akaike, 199–213, DOI
  13. Roy, J., Dibaeinia, P., Fan, T.M., Sinha, S., Das, A. (2019) Global analysis of osteosarcoma lipidomes reveal altered lipid profiles in metastatic versus nonmetastatic cells. J. Lipid Res. 60(2), 375–87, DOI
  14. Peng, W., Tan, S., Xu, Y., Wang, L., Qiu, D., Cheng, C., Lin, Y., Liu, C., Li, Z., Li, Y., Zhao, Y., Li, Q. (2018) LC-MS/MS metabolome analysis detects the changes in the lipid metabolic profiles of dMMR and pMMR cells. Oncol. Rep. 40(2), 1026–34, DOI
  15. Garrett, R.H., Grisham, C.. (2016) Biochemistry. 6th ed., CENGAGE Learning.
  16. Fagone, P., Jackowski, S. (2013) Phosphatidylcholine and the CDP-choline cycle. Biochim. Biophys. Acta - Mol. Cell Biol. Lipids 1831(3), 523–32, DOI