Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis

Article


Serafim, V., Shah, A., Puiu, M., Andreescu, N., Coricovac, D., Nosyrev, A., Spandidos, D., Tsatsakis, A., Dehelean, C. and Pinzaru, I. 2017. Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis. International Journal of Molecular Medicine. 40 (4), pp. 1096-1104. https://doi.org/10.3892/ijmm.2017.3083
TypeArticle
TitleClassification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis
AuthorsSerafim, V., Shah, A., Puiu, M., Andreescu, N., Coricovac, D., Nosyrev, A., Spandidos, D., Tsatsakis, A., Dehelean, C. and Pinzaru, I.
Abstract

Over the past decade, matrix-assisted laser desorption/ionization time‑of‑flight mass spectrometry (MALDI‑TOF MS) has been established as a valuable platform for microbial identification, and it is also frequently applied in biology and clinical studies to identify new markers expressed in pathological conditions. The aim of the present study was to assess the potential of using this approach for the classification of cancer cell lines as a quantifiable method for the proteomic profiling of cellular organelles. Intact protein extracts isolated from different tumor cell lines (human and murine) were analyzed using MALDI‑TOF MS and the obtained mass lists were processed using principle component analysis (PCA) within Bruker Biotyper® software. Furthermore, reference spectra were created for each cell line and were used for classification. Based on the intact protein profiles, we were able to differentiate and classify six cancer cell lines: two murine melanoma (B16‑F0 and B164A5), one human melanoma (A375), two human breast carcinoma (MCF7 and MDA‑MB‑231) and one human liver carcinoma (HepG2). The cell lines were classified according to cancer type and the species they originated from, as well as by their metastatic potential, offering the possibility to differentiate non‑invasive from invasive cells. The obtained results pave the way for developing a broad‑based strategy for the identification and classification of cancer cells

LanguageEnglish
PublisherSpandidos Publications
JournalInternational Journal of Molecular Medicine
ISSN1107-3756
Electronic1791-244X
Publication dates
Online27 Jul 2017
Print01 Oct 2017
Publication process dates
Deposited14 Sep 2017
Accepted12 Jul 2017
Output statusPublished
Publisher's version
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Copyright Statement

Copyright: © Serafim et al. This is an open access article distributed under the terms of Creative Commons Attribution License (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Digital Object Identifier (DOI)https://doi.org/10.3892/ijmm.2017.3083
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