Abstract

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.

Public Health Relevance

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.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA129243-07
Application #
8563898
Study Section
Special Emphasis Panel (ZCA1-RPRB-J)
Project Start
Project End
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
7
Fiscal Year
2013
Total Cost
$132,027
Indirect Cost
$45,685

  Institution

Name
Sloan-Kettering Institute for Cancer Research
Department
Type
DUNS #
064931884
City
New York
State
NY
Country
United States
Zip Code
10065

  Publications

Yu, Helena A; Planchard, David; Lovly, Christine M (2018) Sequencing Therapy for Genetically Defined Subgroups of Non-Small Cell Lung Cancer. Am Soc Clin Oncol Educ Book :726-739
Yuan, Tina L; Amzallag, Arnaud; Bagni, Rachel et al. (2018) Differential Effector Engagement by Oncogenic KRAS. Cell Rep 22:1889-1902
Ruscetti, Marcus; Leibold, Josef; Bott, Matthew J et al. (2018) NK cell-mediated cytotoxicity contributes to tumor control by a cytostatic drug combination. Science 362:1416-1422
Du, Zhenfang; Lovly, Christine M (2018) Mechanisms of receptor tyrosine kinase activation in cancer. Mol Cancer 17:58
Yu, Helena A; Suzawa, Ken; Jordan, Emmet et al. (2018) Concurrent Alterations in EGFR-Mutant Lung Cancers Associated with Resistance to EGFR Kinase Inhibitors and Characterization of MTOR as a Mediator of Resistance. Clin Cancer Res 24:3108-3118
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

Showing the most recent 10 out of 188 publications