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• W2911321981 abstract "Although many cardioprotective strategies have demonstrated benefits in animal models of myocardial infarction, they have failed to demonstrate cardioprotection in the clinical setting highlighting that new therapeutic target and treatment strategies aimed at reducing infarct size are urgently needed. Completion of the Human Genome Project in 2001 fostered the post-genomic research era with the consequent development of high-throughput omics platforms including transcriptomics, proteomics, and metabolomics. Implementation of these holistic approaches within the field of cardioprotection has enlarged our understanding of ischemia/reperfusion injury with each approach capturing a different angle of the global picture of the disease. It has also contributed to identify potential prognostic/diagnostic biomarkers and discover novel molecular therapeutic targets. In this latter regard, omic data analysis in the setting of ischemic conditioning has allowed depicting potential therapeutic candidates, including non-coding RNAs and molecular chaperones, amenable to pharmacological development. Such discoveries must be tested and validated in a relevant and reliable myocardial infarction animal model before moving towards the clinical setting. Moreover, efforts should also focus on integrating all omic datasets rather than working exclusively on a single omic approach. In the following manuscript, we will discuss the power of implementing omic approaches in preclinical animal models to identify novel molecular targets for cardioprotection of interest for drug development." @default.
• W2911321981 created "2019-02-21" @default.
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• W2911321981 date "2019-01-25" @default.
• W2911321981 modified "2023-10-18" @default.
• W2911321981 title "Post-Genomic Methodologies and Preclinical Animal Models: Chances for the Translation of Cardioprotection to the Clinic" @default.
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• W2911321981 doi "https://doi.org/10.3390/ijms20030514" @default.
• W2911321981 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6387468" @default.
• W2911321981 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30691061" @default.
• W2911321981 hasPublicationYear "2019" @default.
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