10.4225/03/5934e59062798
A. K. M. AZAD
A. K. M.
AZAD
Computational modelling and characterisation of cell signalling cross-talks in acquired drug resistance
Monash University
2017
Bayesian Statistical Modelling
Bypass Mechanism
Breast Cancer
Signalling Cross-talk
Lapatinib Resistance
Acquired Resistance
p1-model
Signalling Rewiring
Gene Expression
Systems Biology
Bioinformatics
Computational Biology
2017-06-05 05:01:01
Thesis
https://bridges.monash.edu/articles/thesis/Computational_modelling_and_characterisation_of_cell_signalling_cross-talks_in_acquired_drug_resistance/5057020
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.