Literature DB >> 23386393

Coupling proteomics and transcriptomics in the quest of subtype-specific proteins in breast cancer.

Maria P Pavlou1, Apostolos Dimitromanolakis, Eleftherios P Diamandis.   

Abstract

Breast-cancer subtypes present with distinct clinical characteristics. Therefore, characterization of subtype-specific proteins may augment the development of targeted therapies and prognostic biomarkers. To address this issue, MS-based secretome analysis of eight breast cancer cell lines, corresponding to the three main breast cancer subtypes was performed. More than 5200 non-redundant proteins were identified with 23, four, and four proteins identified uniquely in basal, HER2-neu-amplified, and luminal breast cancer cells, respectively. An in silico mRNA analysis using publicly available breast cancer tissue microarray data was carried out as a preliminary verification step. In particular, the expression profiles of 15 out of 28 proteins included in the microarray (from a total of 31 in our subtype-specific signature) showed significant correlation with estrogen receptor (ER) expression. A MS-based analysis of breast cancer tissues was undertaken to verify the results at the proteome level. Eighteen out of 31 proteins were quantified in the proteomes of ER-positive and ER-negative breast cancer tissues. Survival analysis using microarray data was performed to examine the prognostic potential of these selected candidates. Three proteins correlated with ER status at both mRNA and protein levels: ABAT, PDZK1, and PTX3, with the former showing significant prognostic potential.
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2013        PMID: 23386393     DOI: 10.1002/pmic.201200526

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  7 in total

1.  Inferring alterations in cell-to-cell communication in HER2+ breast cancer using secretome profiling of three cell models.

Authors:  David J Klinke; Yogesh M Kulkarni; Yueting Wu; Christina Byrne-Hoffman
Journal:  Biotechnol Bioeng       Date:  2014-04-18       Impact factor: 4.530

2.  Systematic nucleo-cytoplasmic trafficking of proteins following exposure of MCF7 breast cancer cells to estradiol.

Authors:  Gabriella Pinto; Abdulrab Ahmed M Alhaiek; Sepan Amadi; Amal T Qattan; Mark Crawford; Marko Radulovic; Jasminka Godovac-Zimmermann
Journal:  J Proteome Res       Date:  2014-01-24       Impact factor: 4.466

3.  Elevated Pentraxin 3 in bone metastatic breast cancer is correlated with osteolytic function.

Authors:  Bongkun Choi; Eun-Jin Lee; Da-Hyun Song; Sung-Chul Yoon; Yeon-Ho Chung; Youngsaeng Jang; Sang-Min Kim; Youngsup Song; Sang-Wook Kang; Seung-Yong Yoon; Eun-Ju Chang
Journal:  Oncotarget       Date:  2014-01-30

4.  Covariation of Peptide Abundances Accurately Reflects Protein Concentration Differences.

Authors:  Bo Zhang; Mohammad Pirmoradian; Roman Zubarev; Lukas Käll
Journal:  Mol Cell Proteomics       Date:  2017-03-16       Impact factor: 5.911

5.  Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry.

Authors:  Pavel Bouchal; Olga T Schubert; Jakub Faktor; Lenka Capkova; Hana Imrichova; Karolina Zoufalova; Vendula Paralova; Roman Hrstka; Yansheng Liu; Holger Alexander Ebhardt; Eva Budinska; Rudolf Nenutil; Ruedi Aebersold
Journal:  Cell Rep       Date:  2019-07-16       Impact factor: 9.423

6.  A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression.

Authors:  Erika L Knott; Nancy J Leidenheimer
Journal:  Int J Mol Sci       Date:  2020-11-11       Impact factor: 5.923

7.  Transcriptomic and Proteomic Investigation of HSP90A as a Potential Biomarker for HCC.

Authors:  Yi Zhou; Xiaofang Deng; Ning Zang; Hongtao Li; Gang Li; Cuiping Li; Min He
Journal:  Med Sci Monit       Date:  2015-12-25
  7 in total

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