C O R E C :
The aim of the Bioinformatics Core ('Core C ) is to identify and characterize genes and pathway activation patterns cnjcial for gliomagenesis or GBM homeostasis. Core C will use commonly applied methods for DNA copy analysis and gene expression analysis to identify and characterize genes and pathway activation patterns crucial for gliomagenesis or GBM homeostasis, on data from the model systems developed by each of the Projects. We will work closely with the project investigators to a) provide analytical support to their research and b) suggest follow up experiments guided by our genomic data analysis. We will apply commonly used analytical methods for preprocessing of Affymetrix 3'UTR and exon expression array data, such as quantile normalization and Robust Multi-array Averaging (RMA);parametric methods for identifying differentially expressed genes such as Significance Analysis of Microarrays (SAM) and limma, and Gene Set Enrichment Analysis (GSEA) as implemented in R (www.r-project.org) and Bioconductor (www.bioconductor.org). For analyzing DNA copy number data, we will use the GIST1C2.0 approach as implemented in Matlab (Mermel C et al. Genome Biology 2011) for data normalization and identification of genomic targets. For analysis of sequencing data we will make use of fast short read alignment methods such BWA, and the processing abilities of tools such as samtools (http://samtools.sourceforge.net) and the Genome Analysis Toolkit (www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit). Prior to analysis of xenograft data, we will correct for crossreactivity of mouse mRNA to the Affymetrix platforms that are being used, by mapping probes from each GeneChip to mm 10. We will then generate probe sets for each human gene only including probes that did not show significant alignment to mmlO. We will project findings from the mouse model from Project 2 through mapping of mouse genes to human genes using Ensembl. We will use our intimate knowledge of the data from The Cancer Genome Atlas to project our findings on human GBM data sets. Our core personnel are experienced in analysis of genomic data types and interpretation of the results in the context of larger studies. Moreover, we have been closely working with the TCGA analysis working groups and have shown the ability to collaborate and communicate. This ensures a productive research environment in which the different aims of this project proposal can effectively come to fruition.

Public Health Relevance

Malignant gliomas are now understood to consist of a variety of subtypes rather than a single disease. This Core will sen/e to elucidate the distinguishing signatures of these tumor subtypes in an effort to determine the underiying basis of their initiation and sensitivity or resistance to therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA085878-11
Application #
8745106
Study Section
Special Emphasis Panel (ZCA1-RPRB-W)
Project Start
Project End
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
11
Fiscal Year
2014
Total Cost
$147,529
Indirect Cost
$88,258
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Smith, Andrew; Pawar, Mercy; Van Dort, Marcian E et al. (2018) Ocular Toxicity Profile of ST-162 and ST-168 as Novel Bifunctional MEK/PI3K Inhibitors. J Ocul Pharmacol Ther 34:477-485
Akgül, Seçkin; Li, Yinghua; Zheng, Siyuan et al. (2018) Opposing Tumor-Promoting and -Suppressive Functions of Rictor/mTORC2 Signaling in Adult Glioma and Pediatric SHH Medulloblastoma. Cell Rep 24:463-478.e5
Pal, Anupama; Rehemtulla, Alnawaz (2018) Imaging Proteolytic Activities in Mouse Models of Cancer. Methods Mol Biol 1731:247-260
Durmo, Faris; Lätt, Jimmy; Rydelius, Anna et al. (2018) Brain Tumor Characterization Using Multibiometric Evaluation of MRI. Tomography 4:14-25
Van Dort, Marcian E; Galbán, Stefanie; Nino, Charles A et al. (2017) Structure-Guided Design and Initial Studies of a Bifunctional MEK/PI3K Inhibitor (ST-168). ACS Med Chem Lett 8:808-813
Galbán, Stefanie; Al-Holou, Wajd N; Wang, Hanxiao et al. (2017) MRI-Guided Stereotactic Biopsy of Murine GBM for Spatiotemporal Molecular Genomic Assessment. Tomography 3:9-15
Barthel, Floris P; Wei, Wei; Tang, Ming et al. (2017) Systematic analysis of telomere length and somatic alterations in 31 cancer types. Nat Genet 49:349-357
Hu, Xin; Martinez-Ledesma, Emmanuel; Zheng, Siyuan et al. (2017) Multigene signature for predicting prognosis of patients with 1p19q co-deletion diffuse glioma. Neuro Oncol 19:786-795
Nyati, Shyam; Young, Grant; Ross, Brian Dale et al. (2017) Quantitative and Dynamic Imaging of ATM Kinase Activity. Methods Mol Biol 1596:131-145
Galbán, Stefanie; Apfelbaum, April A; Espinoza, Carlos et al. (2017) A Bifunctional MAPK/PI3K Antagonist for Inhibition of Tumor Growth and Metastasis. Mol Cancer Ther 16:2340-2350

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