Abstract

BackgroundProper 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.ResultsUsing 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2911-z) contains supplementary material, which is available to authorized users.

Highlights

  • Proper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research

  • One thousand seven hundred five breast cancer tumor samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO)

  • Different subsets of samples were assayed on four different level platforms, including Affymetrix HU133 and Agilent G4502A_07_3 for mRNA expression microarrays irrespectively, Affymetrix 6.0 single nucleotide polymorphism (SNP) arrays for copy number variation, whole-exome sequencing in TCGA and hybrid capture sequencing 1651 genes in Cell Line Encyclopedia (CCLE) for mutation analysis

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Summary

Introduction

Proper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. 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. The protein expression status of estrogen receptor alpha (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2) decide the group of breast cancers. It can be subtyped as Luminal A (ER+/PR+, HER2+), Luminal B (ER+/PR+, HER2-), HER2amp (HER2 positive) and Basal-like/triple negative (ER-,PR-, HER2-) [3, 4]. Basal-like triple negative tumors still do not have recognizable therapies. The target identification and its subtype classification is an important aspect for therapy development in breast cancer [5, 6]

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