Literature DB >> 16986208

Proteome profile of the MCF7 cancer cell line: a mass spectrometric evaluation.

Hetal A Sarvaiya1, Jung H Yoon, Iulia M Lazar.   

Abstract

The development of novel proteomic technologies that will enable the discovery of disease specific biomarkers is essential in the clinical setting to facilitate early diagnosis and increase survivability rates. We are reporting a shotgun two-dimensional (2D) strong cationic exchange/reversed-phase liquid chromatography/electrospray ionization tandem mass spectrometry (SCX/RPLC/ESI-MS/MS) protocol for the analysis of proteomic constituents in cancerous cells. The MCF7 breast cancer cell line was chosen as a model system. A series of optimization steps were performed to improve the LC/MS experimental setup, sample preparation, data acquisition and database search protocols, and a data filtering strategy was developed to enable confident identification of a large number of proteins and potential biomarkers. This research has resulted in the identification of >2000 proteins using multiple filtering and p-value sorting. Approximately 1600-1900 proteins had p < 0.001, and, of these, approximately 60% were matched by >or=2 unique peptides. Alternatively, >99% of the proteins identified by >or=2 unique peptides had p < 0.001. When searching the data against a reversed database of proteins, the rate of false positive identifications was 0.1% at the peptide level and 0.4% at the protein level. The typical reproducibility in detecting overlapping proteins across replicate runs exceeded 90% for proteins matched by >or=2 unique peptides. According to their biological function, approximately 200 proteins were involved in cancer-relevant cellular processes, and over 25 proteins were previously described in the literature as putative cancer biomarkers, as they were found to be differentially expressed between normal and cancerous cell states. Among these, biomarkers such PCNA, cathepsin D, E-cadherin, 14-3-3-sigma, antigen Ki-67, TP53RK, and calreticulin were identified. These data were generated by subjecting to MS analysis approximately 42 microg of sample, analyzing 16 SCX peptide fractions, and interpreting approximately 55,000 MS2 spectra. Total MS time required for analysis was 40 h. Copyright 2006 John Wiley & Sons, Ltd.

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Year:  2006        PMID: 16986208     DOI: 10.1002/rcm.2677

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  16 in total

1.  Comparative proteomic profiling of dystroglycan-associated proteins in wild type, mdx, and Galgt2 transgenic mouse skeletal muscle.

Authors:  Jung Hae Yoon; Eric Johnson; Rui Xu; Laura T Martin; Paul T Martin; Federica Montanaro
Journal:  J Proteome Res       Date:  2012-07-30       Impact factor: 4.466

2.  Proteolytic Digestion and TiO2 Phosphopeptide Enrichment Microreactor for Fast MS Identification of Proteins.

Authors:  Jingren Deng; Iulia M Lazar
Journal:  J Am Soc Mass Spectrom       Date:  2016-02-16       Impact factor: 3.109

3.  A serum protein profile predictive of the resistance to neoadjuvant chemotherapy in advanced breast cancers.

Authors:  Seok-Won Hyung; Min Young Lee; Jong-Han Yu; Byunghee Shin; Hee-Jung Jung; Jong-Moon Park; Wonshik Han; Kyung-Min Lee; Hyeong-Gon Moon; Hui Zhang; Ruedi Aebersold; Daehee Hwang; Sang-Won Lee; Myeong-Hee Yu; Dong-Young Noh
Journal:  Mol Cell Proteomics       Date:  2011-07-28       Impact factor: 5.911

4.  Proteomic characterization of Her2/neu-overexpressing breast cancer cells.

Authors:  Hexin Chen; Genaro Pimienta; Yiben Gu; Xu Sun; Jianjun Hu; Min-Sik Kim; Raghothama Chaerkady; Marjan Gucek; Robert N Cole; Saraswati Sukumar; Akhilesh Pandey
Journal:  Proteomics       Date:  2010-11       Impact factor: 3.984

5.  Impact of peptide modifications on the isobaric tags for relative and absolute quantitation method accuracy.

Authors:  Milagros J Tenga; Iulia M Lazar
Journal:  Anal Chem       Date:  2011-01-06       Impact factor: 6.986

6.  Proteomic snapshot of breast cancer cell cycle: G1/S transition point.

Authors:  Milagros J Tenga; Iulia M Lazar
Journal:  Proteomics       Date:  2013-01       Impact factor: 3.984

7.  Microfluidic LC device with orthogonal sample extraction for on-chip MALDI-MS detection.

Authors:  Iulia M Lazar; Jarod L Kabulski
Journal:  Lab Chip       Date:  2013-06-07       Impact factor: 6.799

8.  Differential protein expression analysis using stable isotope labeling and PQD linear ion trap MS technology.

Authors:  Jenny M Armenta; Ina Hoeschele; Iulia M Lazar
Journal:  J Am Soc Mass Spectrom       Date:  2009-03-04       Impact factor: 3.109

9.  Identification of a putative protein profile associated with tamoxifen therapy resistance in breast cancer.

Authors:  Arzu Umar; Hyuk Kang; Annemieke M Timmermans; Maxime P Look; Marion E Meijer-van Gelder; Michael A den Bakker; Navdeep Jaitly; John W M Martens; Theo M Luider; John A Foekens; Ljiljana Pasa-Tolić
Journal:  Mol Cell Proteomics       Date:  2009-03-27       Impact factor: 5.911

10.  MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides.

Authors:  Xu Yang; Iulia M Lazar
Journal:  BMC Cancer       Date:  2009-03-27       Impact factor: 4.430

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