Modeling of non-steroidal anti-inflammatory drug effect within signaling pathways and miRNA-regulation pathways

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

Cardiovascular risk assessment in hypertensive patients

OBJECTIVE: to assess cardiovascular risk by means of the traditional Framingham score and the version modified through the incorporation of emerging risk factors, such as family history of acute myocardial infarction, metabolic syndrome and chronic kidney disease. METHOD: participants were 50 hypertensive patients under outpatient treatment. The clinical data were collected through a semi-structured interview and the laboratory data from patients' histories. RESULTS: it was verified that the traditional Framingham score was predominantly low (74%), with 14% showing medium risk and 12% high risk. After the inclusion of emerging risk factors, the chance of a coronary event was low in 22% of the cases, medium in 56% and high in 22%. CONCLUSIONS: the comparison between the traditional Framingham risk score and the modified version demonstrated a significant difference in the cardiovascular risk classification, whose correlation shows discreet agreement between the two scales. Lifestyle elements seem to play a determinant role in the increase in cardiovascular risk levels