Abstract
To date, it is widely recognized that Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) can exert considerable anti-tumor effects regarding many types of cancers. The prolonged use of NSAIDs is highly associated with diverse side effects. Therefore, tailoring down the NSAID application onto individual patients has become a necessary and relevant step towards personalized medicine. This study conducts the systemsbiological approach to construct a molecular model (NSAID model) containing a cyclooxygenase (COX)-pathway and its related signaling pathways. Four cancer hallmarks are integrated into the model to reflect different developmental aspects of tumorigenesis. In addition, a Flux-Comparative-Analysis (FCA) based on Petri net is developed to transfer the dynamic properties (including drug responsiveness) of individual cellular system into the model. The gene expression profiles of different tumor-types with available drug-response information are applied to validate the predictive ability of the NSAID model. Moreover, two therapeutic developmental strategies, synthetic lethality and microRNA (miRNA) biomarker discovery, are investigated based on the COX-pathway. In conclusion, the result of this study demonstrates that the NSAID model involving gene expression, gene regulation, signal transduction, protein interaction and other cellular processes, is able to predict the individual cellular responses for different therapeutic interventions (such as NS-398 and COX-2 specific siRNA inhibition). This strongly indicates that this type of model is able to reflect the physiological, developmental and pathological processes of an individual. The approach of miRNA biomarker discovery is demonstrated for identifying miRNAs with oncogenic and tumor suppressive functions for individual cell lines of breast-, colon- and lung-tumor. The achieved results are in line with different independent studies that investigated miRNA biomarker related to diagnostics of cancer treatments, therefore it might shed light on the development of biomarker discovery at individual level. Particular results of this study might contribute to step further towards personalized medicine with the systemsbiological approach.
Highlights
Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) are a class of drugs with distinct chemical structures
These lead to the COX protein products that bind to the available arachidonic acid in the model and catalyze its conversion into prostaglandin G2 (PGG2) under oxygen condition (Figure 1)
We investigated the state of Tumor + COX-2 siRNA vs. Tumor state (CT comparison), and the state of Tumor + NS-398 vs. Tumor (NT comparison), in order to validate whether the NSAID model could reveal the differences of these two types of therapeutic inhibition as Denkert et al [28] demonstrated in their study
Summary
NSAIDs are a class of drugs with distinct chemical structures They can invoke the common therapeutic effect: an anti-inflammatory and anti-neoplastic effect [1]. The key molecular mechanism for this type of anti-tumor drug is the inhibition of cyclooxygenase (COX) pathway, whose center components include cyclooxygenase-2 (COX-2), cytosolic glutathione transferases (GSTM2, 3), and prostaglandin E2 (PGE2). In this pathway, key steps are the enzymatic conversion from arachidonic acid to prostaglandin G2 (PGG2) catalyzed by COXs (COX-1 and -2) and subsequent conversion from PGG2 to prostaglandin H2 (PGH2) catalyzed by the same enzymes. It was estimated that in the USA alone, more than 20 billion aspirin (1st generation NSAID) tablets are purchased annually, and that more than 1% of the world population consumes at least one aspirin tablet daily [10]
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