To develop a small interfering Rna (siRNA) design and information resource to facilitate genetic manipulaton of human cells.
Shah, Jyoti Khetsi
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Part I: Small interfering RNAs (siRNAs) have revolutionized our ability to study the effects of altering the expression of single genes in mammalian (and other) cells through targeted knockdown of gene expression. In the past, there were a set of rules designed to develop siRNA which worked efficiently in most cases. There was further refinement performed in these rules in some modern research analyses which attempted to address the question of what most closely determines siRNA functionality. I have designed and implemented a new software tool siRNA Information Resource ('sIR') that incorporates the most recent refinements in the design algorithm in order to provide fast and efficient siRNA design. sIR is a web-based computational tool which takes these existing rules for designing synthetic siRNAs and puts them in a software architecture that allows the researcher to design siRNAs for every gene. It also provides a database containing information about already developed siRNA and thus allows the researcher to access the siRNA information database consisting of siRNA information from literature and various other sources. This will ultimately help in future siRNA related discoveries. It also includes a scoring system which helps in rational selection of efficient siRNA. sIR was successfully validated using already designed and developed target siRNA sequences. Part II: One of the major problems in using chemotherapy to treat cancer is whether patients, whose tumors do not respond to one drug, would respond to another. Thus, it would be very useful if one could rationally select the appropriate chemotherapy for each patient's tumor. We are asking is whether tumor gene "expression signatures" detected by microarray analysis could identify a set of genes correlating with sensitivity or resistance to a particular drug. A large panel of breast cancer cell lines was tested with cisplatin, paclitaxel, vinorelbine, doxorubicin and gemcitabine, in vitro using a colorimetric assay to determine the concentration of drug that gives 50% growth inhibition (IC50). Gene expression profiles were also performed using Affymetrix chips and the two data sets were merged. It was found that a panel of ~100 genes were significantly up regulated (4 fold or more) for each drug in resistant cells. As an alternative approach, Pearson correlations between each gene expression data and each drug IC50 across all cell lines analyzed were determined. A positive correlation for a pair of gene and drug indicates the gene may be associated with resistance to the drug whereas a negative correlation would associate that gene with sensitivity to the drug. Some of these genes might be associated with the drug mechanism of action. We conclude that gene expression signatures do exist for individual breast tumor cell chemosensitivity and these could be of clinical significance.