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Classification of cancer cell lines using matrix-assisted laser desorption/ionization time­of­flight mass spectrometry and statistical analysis.
Serafim, Vlad; Shah, Ajit; Puiu, Maria; Andreescu, Nicoleta; Coricovac, Dorina; Nosyrev, Alexander; Spandidos, Demetrios A; Tsatsakis, Aristides M; Dehelean, Cristina; Pinzaru, Iulia.
Affiliation
  • Serafim V; Center of Genomic Medicine, 'Victor Babes' University of Medicine and Pharmacy, Timisoara 300041, Romania.
  • Shah A; Department of Natural Sciences, Middlesex University, London NW4 4BT, UK.
  • Puiu M; Center of Genomic Medicine, 'Victor Babes' University of Medicine and Pharmacy, Timisoara 300041, Romania.
  • Andreescu N; Center of Genomic Medicine, 'Victor Babes' University of Medicine and Pharmacy, Timisoara 300041, Romania.
  • Coricovac D; Department of Toxicology, Faculty of Pharmacy, 'Victor Babes' University of Medicine and Pharmacy, 300041 Timisoara, Romania.
  • Nosyrev A; Central Chemical Laboratory of Toxicology, I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia.
  • Spandidos DA; Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece.
  • Tsatsakis AM; Department of Forensic Sciences and Toxicology, Faculty of Medicine, University of Crete, 71003 Heraklion, Greece.
  • Dehelean C; Department of Toxicology, Faculty of Pharmacy, 'Victor Babes' University of Medicine and Pharmacy, 300041 Timisoara, Romania.
  • Pinzaru I; Department of Toxicology, Faculty of Pharmacy, 'Victor Babes' University of Medicine and Pharmacy, 300041 Timisoara, Romania.
Int J Mol Med ; 40(4): 1096-1104, 2017 Oct.
Article in En | MEDLINE | ID: mdl-28765873
ABSTRACT
Over the past decade, matrix-assisted laser desorption/ionization time­of­flight mass spectrometry (MALDI­TOF 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 MALDI­TOF 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 (B16­F0 and B164A5), one human melanoma (A375), two human breast carcinoma (MCF7 and MDA­MB­231) 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 non­invasive from invasive cells. The obtained results pave the way for developing a broad­based strategy for the identification and classification of cancer cells.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Breast Neoplasms / Proteome / Cell Line, Tumor / Liver Neoplasms / Neoplasm Proteins Limits: Animals / Female / Humans Language: En Journal: Int J Mol Med Journal subject: BIOLOGIA MOLECULAR / GENETICA MEDICA Year: 2017 Document type: Article Affiliation country: Romania

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Breast Neoplasms / Proteome / Cell Line, Tumor / Liver Neoplasms / Neoplasm Proteins Limits: Animals / Female / Humans Language: En Journal: Int J Mol Med Journal subject: BIOLOGIA MOLECULAR / GENETICA MEDICA Year: 2017 Document type: Article Affiliation country: Romania