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  • American Association for Cancer Research (AACR)  (2)
  • Golub, Todd  (2)
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  • American Association for Cancer Research (AACR)  (2)
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  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 70, No. 8_Supplement ( 2010-04-15), p. 2620-2620
    Abstract: Cancer genome characterization efforts such as The Cancer Genome Atlas project are rapidly improving our knowledge of tumor genetic alterations. With the expanded use of massively parallel sequencing, the catalogue of known genetic alterations in cancer is expected to expand at an accelerating rate. In this context, the emphasis is shifting towards systematic identification of the genes and pathways targeted by recurrent genetic alterations, their functional impact in tumor biology, and the resulting cellular dependencies that might be exploited therapeutically. Anticipating the need for a companion resource to systematically probe tumor biology armed with cancer genomics knowledge, we have assembled a compendium of experimentally tractable cancer model systems consisting of ∼1000 human cancer cell lines and performed extensive genomic analysis (at the level of gene expression, DNA copy number and mutations) coupled with pharmacological profiling. This resource, which we call the Cancer Cell Line Encyclopedia (CCLE), is being used not only to identify the putative targets of prevalent genetic alterations, but also to systematically link the presence or absence of certain genetic alterations to drug sensitivity or resistance. To date, we have identified several previously unappreciated genomic predictors of response or intrinsic resistance to targeted anticancer agents. For instance, through integrative analysis, we have discovered additional mechanisms that may underlie sensitivity to MET inhibitors, beyond amplification of the MET receptor, highlighting the fact that response prediction in the clinic may require assessment of multiple variables. We have also broadened the potential relevance of known predictive biomarkers that might provide a rationale for future genotype-driven clinical trials. As an example, we have expanded on existing knowledge of resistance to receptor tyrosine kinase (RTK) inhibitors, showing that the presence of RAS mutations may predict lack of response to a broad spectrum of RTK inhibitors in addition to EGFR inhibitors. This work demonstrates that pharmacological profiling of large, genomically-annotated cancer model systems may uncover new tumor dependencies as well as positive and negative predictors of drug response. The results of this study are being made publicly available at a CCLE online portal, with the hope they will become a valuable resource for the cancer community to propel translation of the knowledge generated through in vitro integrative genomics into personalized cancer medicine. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2620.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2010
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 70, No. 8_Supplement ( 2010-04-15), p. 105-105
    Abstract: The Cancer Cell Line Encyclopedia (CCLE) represents a collaborative effort to assemble a comprehensive resource of human cancer models for basic and translational research. Thus far, the CCLE contains high-density SNP array data, gene expression microarray data and selected cancer gene mutation data for approximately 1,000 human cancer cell lines spanning many tumor types. Additionally, we are assessing the sensitivity of these same cell lines using a series of pharmacological compounds that represent both conventional cytotoxic and targeted agents. Another goal of the CCLE collaboration involves systematic integration of the genomic and pharmacologic datasets in order to identify putative targets of prevalent genetic alterations as well as predictors and modifiers of pharmacologic sensitivity and resistance. The availability of high-quality data generated by uniform criteria across hundreds of cell lines markedly enhances the statistical power to discover genetic alterations involved in carcinogenesis and molecular predictors of pharmacologic vulnerability. As proof of principle, we have carried out systematic nomination of putative targets of genetic alterations using integrative analyses. Here, significant regions of genomic gains and losses have been linked to expression and mutation data to find significant correlations at both single-gene and pathway levels. We have also begun to assemble systematic algorithms that identify genetic predictors of sensitivity or resistance to particular pharmacological compounds, taking advantage of the fact that the CCLE is a comprehensive resource with extensive genomic characterization. Toward this end, we integrated a preliminary sensitivity dataset for 28 compounds accurately profiled against more than 400 cell lines with all genomic data available in the CCLE. To enhance the robustness of our method, we reduced the number of significant genomic features for each cell line to a number that allows properly determined prediction of sensitivity. Expression data was converted to cell line-specific readouts of gene set expression; and DNA gains and losses are reduced to statistically significant regions using the GISTIC algorithm. These values were combined with critical oncogene mutations as inputs to a multifaceted prediction model for pharmacological sensitivity, the accuracy of which was assessed using cross-validation. Our results suggest that this integrative approach applied to a robust cancer cell line collection has considerable power to discover novel associations that augment ongoing basic research into cancer biology and drug discovery. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 105.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2010
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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