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1
Defining principles of
combination drug
mechanism of action
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Introduction : Cancer and chemotherapy
 There are as many cancer-types as there are cancer-patients.
 Cancer development
Inactivation of Tumor
suppressor gene
Onset of tumor
development
Activation of Oncogene
 Multiple targets for chemotherapy
 Combinatory chemotherapy - standard treatment
 Combinatorial effect are unknown
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Objectives
 Exploring combination drug mechanism of action
 Meaning to define combination therapy statistically and
experimentally, similar to single drug treatment.
 signature”-based prediction has provided a powerful new strategy
for examining drug mechanism
 Understand why multy-drug treatment results in better outcome.
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Overview of research
inactivation
• Infection of
cells by shRNA
8 shRNA
• Targeting
checkpoint
kinases or cell
death regulator
categorization
• Exposure to
chemotherapy
regulation
• Assessment of
drug effect
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Methods - Drug categories
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Methods - Drug clustering
Comparing drug signatures
with the drug categories in our
reference set. The initial drug
category size in the reference
set is defined
Calculating negative control by
adding drugs known to be in
other cathegories to the
equation. Gives fals linkage
ratio.
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Results - Mechanistic prediction
Principal components
analysis (PCA)- replotting
drug combination behavior
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In comparison to:
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Discussion
 Using informatics tools to characterizes the genetic
consequences of combining drug treatments
 combination mechanisms of action tend to represent
weighted composites of single-drug classes. In some
combinations, the mechanistic contribution of a singledrug component is negligible.
 Combination therapies act via the minimization of
acquired resistance, the existence of cell-intrinsic drug
synergy, or the maximization of the cumulative drug dose.
 Either drug A potentiates the mechanism of drug B or drug
A plus drug B produces additive, yet distinguishable,
effects.
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Conclusion
 Combination therapy allow synergy or even neomorphic
mechanism of action.
 Lower dosage of each of the drug components.
 Knowing the single- drug responses , “it will be possible to
compute solutions that can minimize drug resistance
over all variants of that population.”
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Acknowledgment
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