The PS-OC has organized a leadership structure to provide expertise and fully support all initiatives. The leadership consists of the Principal Investigator, Franziska Michor, PhD, and the Senior Co-investigator, Eric Holland, MD, PhD. Support personnel consists of the Administrator/Education Director, Desert Horse-Grant, Research/Project Manager, Raquel Sanchez, MBA, and Biostatistician, Mithat Gonen, PhD. The PS-OC leadership and support personnel, also known as the Administration, will work collectively to support and accomplish the proposed research projects, core, educational and training unit, outreach and dissemination unit, and pilot and trans-network projects. The PS-OC Steering Committee (PSC) will meet annually and will consist of two investigators from each PS-OC. The Principal Investigator, Dr. Franziska Michor, and the Senior Co-investigator, Dr. Holland, will represent our PS-OC at the PSC. The Center Advisory Committee (CAC) will bring together investigators with expertise in both the physical sciences and the basic sciences to form a group of voting and non-voting members. Specifically, the CAC will be made up of the following voting members: two physical sciences members, Franziska Michor (PD/Principal Investigator), PhD, and Chris Sander, PhD;two biological/clinical members, William Pao, MD/PhD, and Eric Holland, MD/PhD;and an NCI appointed voting member. Non-voting members will include at least two external advisors with a wide spectrum of expertise, One external advisor will have a broad proficiency in signal transduction, cancer biology, program management and a focus on a tumor type unaffiliated with the projects of the PS-OC. At least one other external advisor will have advanced knowledge of one or more of the following: evolutionary theory, non-evolutionary cancer systems, developmental biology, brain cancer, lung cancer, leukemia, applied mathematics or engineering/micro fabrication.

Public Health Relevance

The work proposed in this PS-OC will help to bridge the gap between the physical sciences and cancer biology while answering several key questions in oncology. Furthermore, we will drive forward the development of evolutionary theory and will establish evolutionary modeling of cancer as an independent discipline.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
7U54CA143798-02
Application #
7941059
Study Section
Special Emphasis Panel (ZCA1-SRLB-9 (O1))
Program Officer
Lee, Jerry S
Project Start
2009-09-30
Project End
2011-08-31
Budget Start
2010-09-23
Budget End
2011-08-31
Support Year
2
Fiscal Year
2010
Total Cost
$2,201,840
Indirect Cost
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
02215
Wala, Jeremiah A; Bandopadhayay, Pratiti; Greenwald, Noah F et al. (2018) SvABA: genome-wide detection of structural variants and indels by local assembly. Genome Res 28:581-591
Chakrabarti, Shaon; Michor, Franziska (2017) Pharmacokinetics and Drug Interactions Determine Optimum Combination Strategies in Computational Models of Cancer Evolution. Cancer Res 77:3908-3921
Wala, Jeremiah; Beroukhim, Rameen (2017) SeqLib: a C?++ API for rapid BAM manipulation, sequence alignment and sequence assembly. Bioinformatics 33:751-753
Amankulor, Nduka M; Kim, Youngmi; Arora, Sonali et al. (2017) Mutant IDH1 regulates the tumor-associated immune system in gliomas. Genes Dev 31:774-786
Garvey, Colleen M; Gerhart, Torin A; Mumenthaler, Shannon M (2017) Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques. J Vis Exp :
Badri, H; Pitter, K; Holland, E C et al. (2016) Optimization of radiation dosing schedules for proneural glioblastoma. J Math Biol 72:1301-36
Wee, Boyoung; Pietras, Alexander; Ozawa, Tatsuya et al. (2016) ABCG2 regulates self-renewal and stem cell marker expression but not tumorigenicity or radiation resistance of glioma cells. Sci Rep 6:25956
Pitter, Kenneth L; Tamagno, Ilaria; Alikhanyan, Kristina et al. (2016) Corticosteroids compromise survival in glioblastoma. Brain 139:1458-71
Garvey, Colleen M; Spiller, Erin; Lindsay, Danika et al. (2016) A high-content image-based method for quantitatively studying context-dependent cell population dynamics. Sci Rep 6:29752
Bolouri, Hamid; Zhao, Lue Ping; Holland, Eric C (2016) Big data visualization identifies the multidimensional molecular landscape of human gliomas. Proc Natl Acad Sci U S A 113:5394-9

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