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Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis
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 pathologi...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593469/ https://www.ncbi.nlm.nih.gov/pubmed/28765873 http://dx.doi.org/10.3892/ijmm.2017.3083 |
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author | Serafim, Vlad Shah, Ajit Puiu, Maria Andreescu, Nicoleta Coricovac, Dorina Nosyrev, Alexander E. Spandidos, Demetrios A. Tsatsakis, Aristides M. Dehelean, Cristina Pinzaru, Iulia |
author_facet | Serafim, Vlad Shah, Ajit Puiu, Maria Andreescu, Nicoleta Coricovac, Dorina Nosyrev, Alexander E. Spandidos, Demetrios A. Tsatsakis, Aristides M. Dehelean, Cristina Pinzaru, Iulia |
author_sort | Serafim, Vlad |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5593469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-55934692017-09-22 Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis Serafim, Vlad Shah, Ajit Puiu, Maria Andreescu, Nicoleta Coricovac, Dorina Nosyrev, Alexander E. Spandidos, Demetrios A. Tsatsakis, Aristides M. Dehelean, Cristina Pinzaru, Iulia Int J Mol Med Articles 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. D.A. Spandidos 2017-10 2017-07-27 /pmc/articles/PMC5593469/ /pubmed/28765873 http://dx.doi.org/10.3892/ijmm.2017.3083 Text en Copyright: © Serafim et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Serafim, Vlad Shah, Ajit Puiu, Maria Andreescu, Nicoleta Coricovac, Dorina Nosyrev, Alexander E. Spandidos, Demetrios A. Tsatsakis, Aristides M. Dehelean, Cristina Pinzaru, Iulia Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
title | Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
title_full | Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
title_fullStr | Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
title_full_unstemmed | Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
title_short | Classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
title_sort | classification of cancer cell lines using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and statistical analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5593469/ https://www.ncbi.nlm.nih.gov/pubmed/28765873 http://dx.doi.org/10.3892/ijmm.2017.3083 |
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