A Computational Framework to Identify Therapeutic MicroRNAs - A contemporary approach in treating pancreatic cancer
Advisor Information
Dhundy Bastola
Location
UNO Criss Library, Room 249
Presentation Type
Oral Presentation
Start Date
6-3-2015 9:15 AM
End Date
6-3-2015 9:30 AM
Abstract
Cancer research has generated valuable body of knowledge about the mutations that play significant role in cell proliferation. These mutations have led to gain of function in oncogenes whereas detrimental loss of function in tumor suppressor genes. Pancreatic cancer (PC), in particular pancreatic adenocarcinoma (PA), is one of the deadliest forms of cancer, resulting in 38000 deaths in the United States per year. The current 5-year survival rate for patients treated with state-of-the-art therapies is merely 5%. The most reliable diagnostic serum marker are not effective in detecting the cancer early enough for available therapy to be effective. This lack of early diagnosis has been recognized as the major cause for the high mortality rate observed in pancreatic cancer. More recently, microRNAs (or miRNAs) have been identified as potential therapeutic agents in the treatment of patients with pancreatic cancer. MicroRNAs are short ~21-22 nucleotide long non-coding RNAs that act as regulators of expression of mRNA. In this study, we developed a computational approach to identify relationship between miRNAs and the mRNA for various biological processes or pathways involved in pancreatic cancer. The long-term goal of our research is to establish a computational framework for integrating multiple-relevant knowledgebase (miRNA-mRNA interaction, gene expression, biological process and metabolic pathway data) to identify candidate therapeutic miRNA(s). Successful completion of this project is expected to increase the specificity of therapeutics and reduce the side effects associated with current therapies.
A Computational Framework to Identify Therapeutic MicroRNAs - A contemporary approach in treating pancreatic cancer
UNO Criss Library, Room 249
Cancer research has generated valuable body of knowledge about the mutations that play significant role in cell proliferation. These mutations have led to gain of function in oncogenes whereas detrimental loss of function in tumor suppressor genes. Pancreatic cancer (PC), in particular pancreatic adenocarcinoma (PA), is one of the deadliest forms of cancer, resulting in 38000 deaths in the United States per year. The current 5-year survival rate for patients treated with state-of-the-art therapies is merely 5%. The most reliable diagnostic serum marker are not effective in detecting the cancer early enough for available therapy to be effective. This lack of early diagnosis has been recognized as the major cause for the high mortality rate observed in pancreatic cancer. More recently, microRNAs (or miRNAs) have been identified as potential therapeutic agents in the treatment of patients with pancreatic cancer. MicroRNAs are short ~21-22 nucleotide long non-coding RNAs that act as regulators of expression of mRNA. In this study, we developed a computational approach to identify relationship between miRNAs and the mRNA for various biological processes or pathways involved in pancreatic cancer. The long-term goal of our research is to establish a computational framework for integrating multiple-relevant knowledgebase (miRNA-mRNA interaction, gene expression, biological process and metabolic pathway data) to identify candidate therapeutic miRNA(s). Successful completion of this project is expected to increase the specificity of therapeutics and reduce the side effects associated with current therapies.