Singh, Kunal Kumar
(2016)
Multi Drug Resistance on Cancer Cell Lines.
Masters thesis, Indian Institute of Technology Hyderabad.
Abstract
This document can be treated as Final Thesis Report for the project titled "Multi-Drug Resistance on Cancer Cell Lines". Drug is said to be resistant on cancer site if it doesn't bind the specified cancer tumor target or site. Drug Resistant mutant is a major obstacle in cancer treatment and a lot of research have been done to overcome this phenomenon with the present technology and also with limited success. My interests lies in understanding drug resistance or more specifically multi-drug resistance with the help of mathematical modeling through the lens of system biology. The processes and underlying experimental research is much applied than the simple mathematics which explains it here. You may find some experimental quotations and results which I have to believe to be true in order to address the problem. The central theme of this project is two-fold. First, we look at a stochastic processes describing cancer growth, mutant formation and treatment success or failure based on whether resistant mutants are created prior-to/after treatment or based on the rate of growth of cancer cells under simultaneous treatment with single/multiple drugs. Further refinement in the existing model is necessary to include biological complexity and realism. So, we incorporate cross-resistance effects of drugs which happens when multiple drugs are used for treatment. Result shows that cross-resistant two drugs are superior than single drug in use as most of the mutation confers resistant to that single drug in first line therapy. Adding second drug in combination with the first drug, despite of cross-resistance effect, improves the treatment success. We will also look into the aspects of quiescence effects and its relation to drug resistance. Finally, at the end we will review an optimal drug dozing regimen based on continuous and pulsed dosing scheme to delay the resistance formation to a maximum extent that arises due to single (epi) genetic alteration only. The stochastic process described here is multi-type branching process. We will calculate the resistance generation probability based on initial cancer tumor load and growth or death rate of cell colony. We will also find an average population size of resistant cells over time scale and other useful parameters defining the multi-type branching process.
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