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Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer.
Jiang, Guanglong; Zhang, Shijun; Yazdanparast, Aida; Li, Meng; Pawar, Aniruddha Vikram; Liu, Yunlong; Inavolu, Sai Mounika; Cheng, Lijun.
  • Jiang G; Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Zhang S; Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Yazdanparast A; Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Li M; Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Pawar AV; Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Liu Y; Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Inavolu SM; Center for Computational Biology and Bioinformatics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
  • Cheng L; Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN, 46202, USA.
BMC Genomics ; 17 Suppl 7: 525, 2016 08 22.
Article en En | MEDLINE | ID: mdl-27556158
ABSTRACT

BACKGROUND:

Proper cell models for breast cancer primary tumors have long been the focal point in the cancer's research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented.

RESULTS:

Using whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors.

CONCLUSIONS:

The integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Línea Celular Tumoral / Proteínas de Neoplasias Tipo de estudio: Prognostic_studies Límite: Female / Humans Idioma: En Año: 2016 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Línea Celular Tumoral / Proteínas de Neoplasias Tipo de estudio: Prognostic_studies Límite: Female / Humans Idioma: En Año: 2016 Tipo del documento: Article