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Computational modelling and characterisation of cell signalling cross-talks in acquired drug resistance

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thesis
posted on 2017-06-05, 05:01 authored by A. K. M. AZAD
Acquired resistance (AR) to cancer therapies reduces drug efficacy, and signalling cross-talks play a significant role as an underlying mechanism. In this thesis, I combined a computational and a fully Bayesian statistical approach to model and identify aberrant signalling cross-talks, and characterise their roles in AR in two breast cancer cell-lines: SKBR3 and BT474. The results suggested that many compensatory pathways cross-talk in an aberrant manner with targeted signalling pathways, which were also found to be significantly dysregulated in AR. The results provide further insights into the bypass mechanisms of targeted inhibition in AR.

History

Campus location

Australia

Principal supervisor

Jonathan Macgregor Keith

Additional supervisor 1

Alfons Lawen

Additional supervisor 2

Tianhai Tian

Year of Award

2017

Department, School or Centre

Mathematics

Course

Doctor of Philosophy

Degree Type

Doctorate

Faculty

Faculty of Science