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

Jessica Kao, Keyan Salari, Melanie Bocanegra, Yoon La Choi, Luc Girard, Jeet Gandhi, Kevin A. Kwei, Tina Hernandez-Boussard, Pei Wang, Adi F. Gazdar, John D. Minna, Jonathan R. Pollack

Research output: Contribution to journalArticle

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Abstract

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.

Original languageEnglish (US)
Article numbere6146
JournalPLoS One
Volume4
Issue number7
DOIs
StatePublished - Jul 3 2009

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Neoplasm Genes
Genetic Association Studies
breast neoplasms
Tumors
Genes
Cells
cell lines
Breast Neoplasms
Cell Line
neoplasms
Gene expression
Neoplasms
genes
Microarrays
Stem cells
stem cells
gene expression
Gene Dosage
DNA
Mesenchymal Stromal Cells

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery. / Kao, Jessica; Salari, Keyan; Bocanegra, Melanie; Choi, Yoon La; Girard, Luc; Gandhi, Jeet; Kwei, Kevin A.; Hernandez-Boussard, Tina; Wang, Pei; Gazdar, Adi F.; Minna, John D.; Pollack, Jonathan R.

In: PLoS One, Vol. 4, No. 7, e6146, 03.07.2009.

Research output: Contribution to journalArticle

Kao, J, Salari, K, Bocanegra, M, Choi, YL, Girard, L, Gandhi, J, Kwei, KA, Hernandez-Boussard, T, Wang, P, Gazdar, AF, Minna, JD & Pollack, JR 2009, 'Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery', PLoS One, vol. 4, no. 7, e6146. https://doi.org/10.1371/journal.pone.0006146
Kao, Jessica ; Salari, Keyan ; Bocanegra, Melanie ; Choi, Yoon La ; Girard, Luc ; Gandhi, Jeet ; Kwei, Kevin A. ; Hernandez-Boussard, Tina ; Wang, Pei ; Gazdar, Adi F. ; Minna, John D. ; Pollack, Jonathan R. / Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery. In: PLoS One. 2009 ; Vol. 4, No. 7.
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abstract = "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.",
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AU - Salari, Keyan

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AU - Girard, Luc

AU - Gandhi, Jeet

AU - Kwei, Kevin A.

AU - Hernandez-Boussard, Tina

AU - Wang, Pei

AU - Gazdar, Adi F.

AU - Minna, John D.

AU - Pollack, Jonathan R.

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N2 - 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.

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