Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery.

BACKGROUND: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes-luminal A, luminal B, ERBB2-associated, basal-like and normal-like-with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. METHODS: Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. FINDINGS: Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem/progenitor-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 multi-copy deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. CONCLUSIONS: Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, cancer stem cell biology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.

Alterations in genes of the EGFR signaling pathway and their relationship to EGFR tyrosine kinase inhibitor sensitivity in lung cancer cell lines.

BACKGROUND: Deregulation of EGFR signaling is common in non-small cell lung cancers (NSCLC) and this finding led to the development of tyrosine kinase inhibitors (TKIs) that are highly effective in a subset of NSCLC. Mutations of EGFR (mEGFR) and copy number gains (CNGs) of EGFR (gEGFR) and HER2 (gHER2) have been reported to predict for TKI response. Mutations in KRAS (mKRAS) are associated with primary resistance to TKIs. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the relationship between mutations, CNGs and response to TKIs in a large panel of NSCLC cell lines. Genes studied were EGFR, HER2, HER3 HER4, KRAS, BRAF and PIK3CA. Mutations were detected by sequencing, while CNGs were determined by quantitative PCR (qPCR), fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH). IC50 values for the TKIs gefitinib (Iressa) and erlotinib (Tarceva) were determined by MTS assay. For any of the seven genes tested, mutations (39/77, 50.6%), copy number gains (50/77, 64.9%) or either (65/77, 84.4%) were frequent in NSCLC lines. Mutations of EGFR (13%) and KRAS (24.7%) were frequent, while they were less frequent for the other genes. The three techniques for determining CNG were well correlated, and qPCR data were used for further analyses. CNGs were relatively frequent for EGFR and KRAS in adenocarcinomas. While mutations were largely mutually exclusive, CNGs were not. EGFR and KRAS mutant lines frequently demonstrated mutant allele specific imbalance i.e. the mutant form was usually in great excess compared to the wild type form. On a molar basis, sensitivity to gefitinib and erlotinib were highly correlated. Multivariate analyses led to the following results: 1. mEGFR and gEGFR and gHER2 were independent factors related to gefitinib sensitivity, in descending order of importance. 2. mKRAS was associated with increased in vitro resistance to gefitinib. CONCLUSIONS/SIGNIFICANCE: Our in vitro studies confirm and extend clinical observations and demonstrate the relative importance of both EGFR mutations and CNGs and HER2 CNGs in the sensitivity to TKIs.