The Biostatistics and Bioinformatics Core B will provide statistics and bioinformatics support and expertise in experimental design, data analysis and interpretation ofthe results as needed by the Projects and other Cores to achieve their Specific Aims. The studies in this POl require a variety of statistical and bioinformatic data analysis strategies such as modeling time course experiment data, tesfing synergisfic effect of kinase inhibitor combination, and analyzing genomic profiling data of RNA expression and DNA copy number. In addition. Core B will develop and maintain a bioinformatics infrastructure to enable collaboration and data sharing among research projects. This infrastructure includes: 1) a gene signature database 2) a somafic mutation database and functional characterization tools, and 3) a virtual cell line repository. A broad range of bioinformatics, computational, and statistical techniques will be applied to create this infrastructure.
The Biostatistics and Bioinformatics Core B forms an integral part ofthe P01 and will provide services that are essential for many of the different projects within the POl, assisting the POl investigators in their achievement of the overall research objective: developing new targets for therapy for carcinomas of the lung.
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|Westover, D; Zugazagoitia, J; Cho, B C et al. (2018) Mechanisms of acquired resistance to first- and second-generation EGFR tyrosine kinase inhibitors. Ann Oncol 29:i10-i19|
|Li, Bob T; Shen, Ronglai; Buonocore, Darren et al. (2018) Ado-Trastuzumab Emtansine for Patients With HER2-Mutant Lung Cancers: Results From a Phase II Basket Trial. J Clin Oncol 36:2532-2537|
|Fan, Pang-Dian; Narzisi, Giuseppe; Jayaprakash, Anitha D et al. (2018) YES1 amplification is a mechanism of acquired resistance to EGFR inhibitors identified by transposon mutagenesis and clinical genomics. Proc Natl Acad Sci U S A 115:E6030-E6038|
|Mo, Qianxing; Shen, Ronglai; Guo, Cui et al. (2018) A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data. Biostatistics 19:71-86|
|Childress, Merrida A; Himmelberg, Stephen M; Chen, Huiqin et al. (2018) ALK Fusion Partners Impact Response to ALK Inhibition: Differential Effects on Sensitivity, Cellular Phenotypes, and Biochemical Properties. Mol Cancer Res 16:1724-1736|
|Gao, Yijun; Chang, Matthew T; McKay, Daniel et al. (2018) Allele-Specific Mechanisms of Activation of MEK1 Mutants Determine Their Properties. Cancer Discov 8:648-661|
|Arbour, Kathryn C; Jordan, Emmett; Kim, Hyunjae Ryan et al. (2018) Effects of Co-occurring Genomic Alterations on Outcomes in Patients with KRAS-Mutant Non-Small Cell Lung Cancer. Clin Cancer Res 24:334-340|
|Gallant, Jean-Nicolas; Lovly, Christine M (2018) Established, emerging and elusive molecular targets in the treatment of lung cancer. J Pathol 244:565-577|
|Hellmann, Matthew D; Nathanson, Tavi; Rizvi, Hira et al. (2018) Genomic Features of Response to Combination Immunotherapy in Patients with Advanced Non-Small-Cell Lung Cancer. Cancer Cell 33:843-852.e4|
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