PrincipalInvestigator(Fakhouri,WalidD.),Co-?I(Qutub,Amina) Modeling of pathological significance of non-coding DNA variants in cis-overlapping motifs of P53 and cMYC Layperson's Summary This research proposal seeks to identify functional DNA variations that lie outside the protein-coding regions and develop a computational model that predicts their effect on alterations of target gene expression. Identification of causative DNA variants is critical for better prognosis of cancer and other genetic diseases in high-risk individuals, and for targeted therapies in patients with existing genetic disease. Research has been previously directed towards DNA variations located within coding sequences due to their effect on the function of the corresponding gene/protein product. There are several available computational programs that can predict how mutations may affect protein activity prior to experimental investigation. However, the technical knowledge to predict the effect of variations located outside the protein-coding regions that affect expression rather than protein function are not available yet. Recent genetic studies reported that a large number of DNA variants associated with cancer and other common diseases are non-coding, however, few causative non- coding DNA variants were identified thus far. Therefore, there is a tremendous need to understand the underlying mechanism by which non-coding DNA variations alter gene expression and to develop a powerful computational model that predicts etiologic variants and expected change in target gene expression. Our bioinformatic analysis of DNA-protein binding signals in both cancer and embryonic cells showed that a significant number of genomic regions contain overlapping binding sites for the tumor suppressor protein P53 and the oncogene cMYC. This data suggests an important mechanism of gene regulation where both transcription factors P53 and cMyc compete at regulatory elements to regulate the expression of target genes by a competitive inhibitory mechanism. Our goal is to decipher the impact of this mechanism by P53 and cMYC on target gene expression at the genome-wide level and predict the effect of non-coding DNA variants on target genes in normal and cancer cells. The goal of this proposal is clinically important because it will accelerate the identification of causative mutations and associated genes in cancer and other genetic diseases.
(PUBLIC HEALTH RELEVANCE STATEMENT) Identification of etiologic DNA variants is critical to understand the underlying mechanisms of disease cause and to develop targeted therapies for common diseases. Genome-wide association studies have shown that the majority of disease-associated variants are located in non-coding regions that might alter the expression of affected genes. However, there are currently no computational programs that precisely predict functional non- coding DNA variants and their effect on target gene. The goal of this proposal is to develop a computational model that predicts the effect of non-coding DNA variations within cis-overlapping motifs for P53 and cMYC in normal and cancer cells.
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