Molecular Profiling of Breast Cancer Cell Lines Defines Relevant Tumor Models and Provides a Resource for Cancer Gene Discovery

By Jessica Kao, K. Salari, Melanie Bocanegra, Yoon-La Choi, Luc Girard, Jeet Gandhi, Kevin Kwei, Tina Hernandez-Boussard, Pei Wang, Adi F. Gazdar and 2 more. PLoS ONE, 2009

802 citations recorded by the source corpus.

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.

Subfields: Cancer Research, Genetics, Pathology and Forensic Medicine

View Paper: https://www.semanticscholar.org/paper/ef063184fbd024229a8b710f0ace9dd498adcc00

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In Cancer Research

1. K. J. Chavez
2. Tero Aittokallio
3. Jia Li
4. Krister Wennerberg
5. S. Garimella
6. Zhonghu Bai
7. Hongye Cheng
8. Xiaofeng Dai

In Genetics

1. Tero Aittokallio
2. James J. Collins
3. Krister Wennerberg
4. Xiaofeng Dai
5. B. Welm
6. Dongbin Xiu

In Pathology and Forensic Medicine

1. Joe W. Gray

Citations in the corpus

• A community effort to assess and improve drug sensitivity prediction algorithms (2014, background): “Comparisons have shown that cell lines mirror many aspects of the ‘omic’ diversity found in primary tumors 4,18,19 , suggesting that they can be used as a proxy for characterizing the response to therapeutic interventions.”
• Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes (2011, background): “This work revealed that (1) our current bank of tumor grafts, which is still growing, already comprises all major clinical types of breast cancer, and multiple molecular subtypes; (2) tumor grafts maintain critical features of the patient tumors including histology and pathology, clinical markers, g”
• Breast Cancer Cell Line Classification and Its Relevance with Breast Tumor Subtyping (2017, methodology): “MDAMB361 + +/- + WT LB MDA RPMI, DMEM AC L [1, 5, 6, 8, 10]”
• Choosing the right cell line for breast cancer research (2011, result): “In general, these studies have shown that the luminal, basal, HER2 and claudin-low clusters identifi ed in breast tumours can easily be distinguished in breast cancer cell lines (Table 1) [13,22-26].”
• Triple Negative Breast Cancer Cell Lines: One Tool in the Search for Better Treatment of Triple Negative Breast Cancer (2010, background): “Two groups have performed comparative genomic hybridization (CGH) on a large panel of breast cancer cell lines, including the TNBC cell lines [39, 40].”