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The National Cancer Institute's Integrative Cancer Biology Program2013Summer Cancer Research Fellowships/InternshipsProject DescriptionsBroad Institute/Dana-Farber Cancer InstituteBoston, MAWebsite: http://www.broadinstitute.org/science/programs/cancer/icbp/broad-institute-icbpPrincipal Investigator:Todd R. Golub, M.D.Mentor:Jesse Boehm, Ph.D.Duration of Program:June 3 through August 2, 2013Title:Predicting cancer vulnerabilities based on genomic features of tumorsProject Description: The overarching goal of the Broad Institute CCSB is to predict the vulnerabilities of tumors based upon their genomic features. To accomplish this goal we are systematically cataloging cancer dependencies utilizing genome-wide RNA interference screens on hundreds of cancer cell lines that have been undergone comprehensive genomic characterization. Despitethis exciting experimental progress, major challenges in computational modeling(e.g. can we develop statistical and analytical methods to link tumor features with dependencies?) as well as experimental confirmation(e.g. are experiments done in cell lines predictive of the vulnerabilities of established tumors in vivo?) must be overcome if we are to understand how to use genomic biomarkers to predict how to effectively kill real tumorsin humans. We are looking for a highly motivated, dedicated and talented individualfor the 2013 Summer Internship Program to help further this work on either computational or experimental fronts (or both), depending on the interests of the applicant. The project may include work in the cancer laboratory performing overexpression and RNAi experiments in cancer cell linesas well as confirmatory studies in mouse models, and/or developing computational methodson these genome-scale tumor vulnerability data sets. Requirements:The ideal applicant will have a strong passion and driveto learn new concepts and work with others. Prior experience in a molecular biology laboratory and having basic programming skills are ideal but not a requirement. Project Type: Intheir application, the student should state which type of project (computational or experimental) they are interested in and describe their rationale.Columbia UniversityNew York, NYWebsites: http://magnet.c2b2.columbia.edu/http://hiccc.columbia.edu/Principal Investigator:Andrea Califano, Ph.D.Mentor:DanaPe'er, Ph.D.Duration of Program:June 3 through August 2, 2013Title:Response of individual tumors to individual and combination drug therapyProject Description:Our lab uses systems biology approaches towards personalized cancer care.We use genomics and data-driven computational methodsto understand patient specifictumor networksthat can predict how individual tumors will respond to certain drug and drug combinations. The summer intern will use advanced machine learning approaches to analyze and integrate diverse high-throughput tumor data that includes DNA mutations, gene expression, miRNA expression, RNAi screens, epigenetics and drug screensto derive which genes and pathways have gone awry and how these might impact drug response.Requirements:The candidate is expected to have competence in programming (preferably Matlab, Python and/or Perl) and knowledge of statistics.Project Type:ComputationalGeorgetown UniversityWashington, D.C. (Georgetownarea)Website: http://lombardi.georgetown.edu/breastcancer/ccsb/Principal Investigator:Robert Clarke, Ph.D.Mentor:Leena Hilakivi-Clarke, Ph.D.Duration of Program:June 3through August 2, 2013Title: Origins of anti-estrogen resistanceProject Description: Resistance to tamoxifen(TAM) or other endocrine therapies is a significant problem in the treatment of estrogen receptor positive (ER+) breast cancer, and factors determining its development remain largely unknown. Although multiple candidates have been identified, mostly through the work done using human breast cancer cells in culture, a limitation of this approach is that breast cancer grows in an environment that involves stroma and immune cells embedded therein. TAM is known to affect mammary stromain a manner that may contri

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