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Cellular and Molecular Biology

Abstract #LB-312: Integrated omic analysis of breast cancer cell lines

Anguraj Sadanandam, William Gibb, Laura Heiser, Wen-Lin Kuo, Paul Spellman and Joe Gray
Anguraj Sadanandam
Lawrence Berkeley National Laboratory, Berkeley, CA; Lawrence Berkeley National Lab, Berkeley, CA
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William Gibb
Lawrence Berkeley National Laboratory, Berkeley, CA; Lawrence Berkeley National Lab, Berkeley, CA
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Laura Heiser
Lawrence Berkeley National Laboratory, Berkeley, CA; Lawrence Berkeley National Lab, Berkeley, CA
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Wen-Lin Kuo
Lawrence Berkeley National Laboratory, Berkeley, CA; Lawrence Berkeley National Lab, Berkeley, CA
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Paul Spellman
Lawrence Berkeley National Laboratory, Berkeley, CA; Lawrence Berkeley National Lab, Berkeley, CA
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Joe Gray
Lawrence Berkeley National Laboratory, Berkeley, CA; Lawrence Berkeley National Lab, Berkeley, CA
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DOI:  Published May 2009
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AACR Annual Meeting-- Apr 18-22, 2009; Denver, CO

Abstract

Recent studies suggest the role of thousands of genes in breast tumorigenesis and metastasis. However, identifying crucial and druggable genes necessary for diagnosis and treatment of breast cancer requires appropriate model system that reflects the heterogeneous nature of tumors and integrated analysis of different molecular events occurring in tumors. Previously, our laboratory described a model system using a panel of more than 50 breast cancer cell lines (ICBP 50) that exhibits the substantial genomic and transcriptional changes associated with patient primary tumors. However, that study was limited to the analysis of data acquired by low genome-resolution techniques. In this study, we have performed integrated analysis of various molecular changes in ICBP 50 cell lines at high-throughput levels to understand the driver events that lead to breast cancer pathophysiology. The consensus clustering of ICBP 50 cell lines using exon expression array and reverse phase protein array data revealed molecular subtypes (basal and luminal) that are found in primary breast tumors. The analysis of DNA copy number aberrations using Affymetrix single nucleotide polymorphism (SNP 6.0) array not only revealed that ICBP 50 cell lines resemble primary tumors but also identified known and novel copy number aberrations and crucial genes at the aberrant locus. The integrated analysis of the genome copy number, gene expression and mutation revealed interesting candidates genes that have coordinated aberrant expression that are lineage and subtype specific. Overall, cell line collection can serve as a model system to identify and understand the driver events leading to the pathogenesis of primary breast tumors. In addition, this study demonstrates that high genome-resolution techniques can provide additional insights into breast cancer pathology that were not obtained from low-resolution techniques.

Citation Information: In: Proc Am Assoc Cancer Res; 2009 Apr 18-22; Denver, CO. Philadelphia (PA): AACR; 2009. Abstract nr LB-312.

Footnotes

  • 100th AACR Annual Meeting-- Apr 18-22, 2009; Denver, CO

  • American Association for Cancer Research
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Cancer Research: 69 (9 Supplement)
May 2009
Volume 69, Issue 9 Supplement
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Abstract #LB-312: Integrated omic analysis of breast cancer cell lines
Anguraj Sadanandam, William Gibb, Laura Heiser, Wen-Lin Kuo, Paul Spellman and Joe Gray
Cancer Res May 1 2009 (69) (9 Supplement) LB-312;

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Abstract #LB-312: Integrated omic analysis of breast cancer cell lines
Anguraj Sadanandam, William Gibb, Laura Heiser, Wen-Lin Kuo, Paul Spellman and Joe Gray
Cancer Res May 1 2009 (69) (9 Supplement) LB-312;
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Cancer Research Online ISSN: 1538-7445
Cancer Research Print ISSN: 0008-5472
Journal of Cancer Research ISSN: 0099-7013
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