Browsing by Author "Wagle, Pragat"

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    An Analysis of Pancreatic Cancer
    (Office of the Vice Chancellor for Research, 2015-04-17) Wagle, Pragat
    The pancreas is extremely important in various enzymatic activities, such as the production of numerous enzymes such as insulin. Pancreatic Cancer is an extremely deadly disease, which 40,000 people of the 46,000 diagnosed each year fail to survive. It is the 12th most common type of cancer and the 4th leading cause of cancer related deaths. There are 4 stages to Pancreatic ranging from stage 1 to stage 4, where the cancer has spread to a distant organ. Pancreatic cancer is an extremely difficult to diagnose as early symptoms aren’t suggestive as many other illnesses have similar signs and symptoms. Diagnosis can be done through the use of physical examinations, ct scan, ultrasound, endoscopic ultrasound, PET scan, and most effectively a needle biopsy. Currently in development are numerous different therapies. A collective effort is being put forth to further improve current established methods to combat Pancreatic Cancer. A current four-drug chemotherapy, that had results published in May 2011 has shown a 4-month improvement using a regimen called Folfirinox. Compared to treatment with gemcitabine, which is the current therapy mainly utilized, Folfirinox showed improvement on 16 percent more patients in a phase 3 trial. Another trial with a combination of Nab-Paclitaxel and Gemcitabine was conducted against just gemcitabine. Patients with the combination showed a 1.8 months higher average survival rate than without, and showed a significantly higher survival rate through two years of 13% and 5% respectively. Overall these therapies must be reformed to be compatible with a bigger patient population. Subsequently the side effects of the treatments also need to be improved as the side effects include high risk of neutropenia. Both these treatments demonstrate a more efficient therapy and have been implemented into practice but still require improvement.
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    Drug Discovery Through Drug Perturbation Pathway Modeling and Network Analysis
    (Office of the Vice Chancellor for Research, 2014-04-11) Ho, Tung; Hakola, Krista; Wagle, Pragat; Rouse, Evan; Shadmand, Mehdi; Han, Juyeon; Ibrahim, Sara
    Due to intrinsic complex molecular interactions, the “one disease – one target – one drug” strategy for disease treatment is no longer the best option to treat cancers. To assess drug pharmacological effects, we assume that “ideal” drugs for a patient can treat or prevent the disease by modulating gene expression profiles of this patient to the similar level with those in healthy people. A new approach for drug-protein interactions curation, drug-drug similarity network comparison, and integrative pathway model construction and evaluation was introduced to determine optimal drugs for various cancers. Drug-protein interaction curation is conducted to discover novel drug-protein relationships and is categorized as: up regulated, down regulated, indirect up or down, ambiguous and unknown. The manual curation can be utilized for drug repurposing and examining drug mechanism on a pathway level. A drug-drug similarity network model is built by examining similar targets, therapeutic mechanisms, side effects, and chemical structures. Drug similarity analysis is useful for drug repositioning because similar drugs may have compatible therapeutic or toxic effects for a disease. Drug similarity networks are constructed and examined through a molecular network visualization platform. An integrative disease-specific pathway model is also built to gain a more holistic view of disease mechanisms by including every significant disease-specific protein. Including drugs on the pathway through target information can also offer a clear mechanism for the drug’s action. We also transform integrated pathways into network models and ranked drugs based on the network topological features of drug targets, drug-affecting genes/proteins, and curated disease-specific proteins. Combining our three approaches could potentially lead to advances in drug repurposing and repositioning.
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    Utilizing the C2Maps Platform for Characterizing Drug-Protein Relations, Generating Mobile Games, and Constructing Integrated Pathway Models
    (Office of the Vice Chancellor for Research, 2013-04-05) Shadmand, Mehdi; Wen, Dian; Wagle, Pragat; Stark, Ryan; Smith, Ashley; Ibrahim, Sara
    The C2Maps platform is a collection of genome-wide data that display the connections between drugs, diseases and genes. The C2Maps is used as a tool to compare and extrapolate known map data into unknown areas. By using C2Maps, researchers can compare genetic, sequential and physical information about disease specific proteins. Manual curation is important for the C2Maps platform in order to validate the literature mining approach and to overcome high levels of data noise generated from molecular networks. Currently we are examining specific drug-protein relationships in several diseases. In this research, the C-Maps website is being used to manually curate abstracts about disease specific drugprotein relations and then it is determined whether a drug “Up Regulates”, “Down Regulates”, or “Indirectly” affects a specific protein. Presently, more than 2000 specific protein-drug relations have been examined through the platform. We theorize that new drug-protein relations will be discovered through curation efforts. To broaden the scope of curation data generated, a C2Maps mobile game is in the process of being developed. This game takes advantage of novel technology in mobile development to create a game that will allow several researchers to contribute to the curation process. The data generated from the manual curation approach can be used to validate various protein-drug relationships in pharmacology and can determine the best possible drugs targeting specific proteins in cancer. Optimal drugs and their respective targets for a specific disease can then be incorporated into an integrative pathway model to analyze the mechanism of the drug. Specific properties of the drug, including chemical structure, can then be examined to determine how a specific drug acts on particular target proteins.