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dc.contributor.advisorLeona Samson.en_US
dc.contributor.authorValiathan, Chandni Rajanen_US
dc.contributor.otherMassachusetts Institute of Technology. Computational and Systems Biology Program.en_US
dc.date.accessioned2011-09-13T17:50:49Z
dc.date.available2011-09-13T17:50:49Z
dc.date.copyright2011en_US
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/65773
dc.descriptionThesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2011.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractMany organisms have evolved DNA damage response mechanisms to deal with the constant damage to DNA caused by endogenous and exogenous agents. These mechanisms activate cell cycle checkpoints to allow time for DNA repair or, in the case of severely damaged DNA, initiate cell death mechanisms to maintain genomic integrity. The cell's response to DNA damaging agents includes wide spread changes in the transcriptional state of the cell that have been implicated in cell death or survival decisions. However, we do not fully understand how the multiple and sometimes opposing transcriptional signals are interpreted to make these critical decisions. A computational and systems biology approach was taken to study the wide-spread transcriptional changes induced in human cell lines after exposure to a DNA damaging and chemotherapeutic agent, 1,3-bis-(2-chloroethyl)- 1 -nitrosourea (BCNU or carmustine). Cell lines with extreme sensitivity or resistance to BCNU were identified from a set of twenty four genetically diverse human lymphoblastoid cell lines using a high-throughput method that was developed as part of this thesis. This assay has broad applications and can be used to simultaneously screen multiple cell lines and drugs for accurate measurements of cell proliferation and survival after drug treatment. The assay has the advantage of having a large dynamic range that allows sensitivity measurements on a multi-log scale allowing better resolution of comparative sensitivities. Temporal transcription profiles were measured in cell lines with extreme BCNU sensitivity or resistance to generate a large transcription data set amenable to bioinformatics analysis. A transcriptional signature of 706 genes, differentially expressed between BCNU sensitive and resistant cell lines, was identified. Network and gene ontology enrichment identified these differentially expressed genes as being involved in key DNA damage response processes like apoptosis and mitosis. Experimental evidence showed that the transcription signature correlated with observed cellular phenotypes. Furthermore, the NF-Y transcription factor binding motif was enriched in the promoter region of 62 mitosis-related genes downregulated in BCNU sensitive but not resistant cell lines. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) confirmed NF-Y occupancy in 54 of the 62 genes, thus implicating NF-Y as a possible regulator of the observed stalling of entry into mitosis. Using experimental and computational techniques we deciphered the functional importance of differential transcription between BCNU sensitive and resistant cell lines and identified NF-Y as an important factor in the transcriptional and phenotypic cell response to BCNU such as the control of entry into mitosis.en_US
dc.description.statementofresponsibilityby Chandni Rajan Valiathan.en_US
dc.format.extent195 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectComputational and Systems Biology Program.en_US
dc.titleIdentifying a transcriptional signature for cell sensitivity to the cancer chemotherapy agent, BCNUen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Program
dc.identifier.oclc749453776en_US


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