Project description:Summary: 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. 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. 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-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 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. 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, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. HEEBO oligonucleotide microarrays from the Stanford Functional Genomics Facility were used to perform gene expression profiling of 50 human breast epithelial cell lines, in comparison to a universal RNA reference. Expression data were analyzed by hierarchical clustering to identify subgroups, and gene set enrichment analysis to identify subgroup-specific gene pathways.

Project description: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. 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. 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-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 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. 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, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. cDNA microarrays from the Stanford Functional Genomics Facility were used to carry out array-based Comparative Genomic Hybridization (array CGH) analysis of 52 human breast epithelial cell lines, in comparison to normal female DNA. Three reference arrays of normal male vs. normal female DNA were also done. Map positions for arrayed cDNA clones were assigned using the NCBI genome assembly, accessed through the UCSC genome browser database (NCBI Build 36). The cghFLasso method was used to call DNA gains and losses.

Project description:Summary: 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. 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. 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-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 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. 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, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.

Project description:Breast cancer is a heterogeneous disease comprised of at least five major subtypes. Luminal subtype tumors confer a more favourable patient prognosis, which is in part, attributed to the Estrogen Receptor-alpha (ER) positivity and anti-hormone responsiveness of these tumors. Expression of the forkhead box transcription factor, FOXA1, also correlates with the luminal subtype and patient survival, but is present in a subset of ER-negative tumors. Similarly, FOXA1 is consistently expressed in luminal breast cancer cell lines even in the absence of ER. In contrast, basal breast cancer cell lines do not express FOXA1, and loss of FOXA1 in luminal cells increases migration and invasion, characteristics of the basal subtype. To delineate an ER-independent role for FOXA1 in maintaining the luminal phenotype, and hence a more favourable prognosis, we performed cDNA microarray analyses on luminal FOXA1-positive, ER-positive (MCF7, T47D) and FOXA1-positive, ER-negative (MDA-MB-453, SKBR3) cell lines in the presence or absence of transient FOXA1 silencing. This resulted in three FOXA1 transcriptomes: (1) a luminal-signature (consistent across cell lines), (2) an ER-positive signature (restricted to MCF7 and T47D) and (3) an ER-negative signature (restricted to MDA-MB-453 and SKBR3). Use of Gene Set Enrichment Analyses (GSEA) as a phenotyping tool revealed that FOXA1 silencing resulted in a transcriptome shift from luminal to basal gene expression signatures. FOXA1 binds to both luminal and basal genes within luminal breast cancer cells, suggesting that it not only transactivates luminal genes, but also represses basal-associated genes. From these results we conclude that FOXA1 controls plasticity between basal and luminal cells, playing a dominant role in repressing the basal phenotype, and thus tumor aggressiveness, in luminal breast cancer cells. Although it has been proposed that FOXA1-targeting agents may be useful for treating luminal tumors, these data suggest that this approach may promote transitions toward a more aggressive cancer. FOXA1 siRNA treated breast cell lines compared directly to nonspecific siRNA treated cell lines using Agilent 4X44 microarrays.

Project description:Breast cancer is a heterogeneous disease comprised of at least five major subtypes. Luminal subtype tumors confer a more favorable patient prognosis, which is in part, attributed to the Estrogen Receptor-α (ER) positivity and anti-hormone responsiveness of these tumors. Expression of the forkhead box transcription factor, FOXA1, also correlates with the luminal subtype and patient survival, but is present in a subset of ER-negative tumors. Similarly, FOXA1 is consistently expressed in luminal breast cancer cell lines even in the absence of ER. In contrast, basal breast cancer cell lines do not express FOXA1, and loss of FOXA1 in luminal cells increases migration and invasion, characteristics of the basal subtype. To delineate an ER-independent role for FOXA1 in maintaining the luminal phenotype, and hence a more favorable prognosis, we performed cDNA microarray analyses on luminal FOXA1-positive, ER-positive (MCF7, T47D) and FOXA1-positive, ER-negative (MDA-MB-453, SKBR3) cell lines in the presence or absence of transient FOXA1 silencing. This resulted in three FOXA1 transcriptomes: (1) a luminal-signature (consistent across cell lines), (2) an ER-positive signature (restricted to MCF7 and T47D) and (3) an ER-negative signature (restricted to MDA-MB-453 and SKBR3). Use of Gene Set Enrichment Analyses (GSEA) as a phenotyping tool revealed that FOXA1 silencing resulted in a transcriptome shift from luminal to basal gene expression signatures. FOXA1 binds to both luminal and basal genes within luminal breast cancer cells, suggesting that it not only transactivates luminal genes, but also represses basal-associated genes. From these results we conclude that FOXA1 controls plasticity between basal and luminal cells, playing a dominant role in repressing the basal phenotype, and thus tumor aggressiveness, in luminal breast cancer cells. Although it has been proposed that FOXA1-targeting agents may be useful for treating luminal tumors, these data suggest that this approach may promote transitions toward a more aggressive cancer.

Project description:Breast cancer is a profoundly heterogeneous disease with respect to biological and clinical behavior. Gene expression profiling has been used to dissect this complexity and stratify tumors into intrinsic gene expression subtypes associated with distinct biology, patient outcome and different genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. We applied global DNA copy number and gene expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy number aberrations and genomic subgroups of breast cancer. We identified 31 genomic regions that were highly amplified in >1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions (66 and 67 with DNA copy number gain and loss, respectively) revealed six genomic subtypes, termed: 17q12, basal-complex, luminal-simple, luminal-complex, amplifier and mixed subtype. Four of them had striking similarity to intrinsic gene expression subtypes and showed association to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having better prognosis while the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene expression subtypes, the former being enriched for 8p12-amplified cases while the mixed subtype included many tumors with predominantly DNA copy number losses and poor prognosis. Genomic profiling of 359 breast tumors using tiling BAC aCGH. A number of cases were hybridized as replicates or replicate as dye-swaps. Gene expression profiling of 359 breast tumors using 55K oligonucleotide microarrays.

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Molecular profiling of breast cancer cell lines defines relevant tumor models (aCGH)

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