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Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

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Technical Report,15 Jul 2015,14 Jul 2016

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University of Nebraska Medical Center Omaha United States

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Prostate cancer PCa is most commonly diagnosed and second leading cause of death in the US men, representing 8 of all male cancer deaths. Currently, PCa is monitored and managed by prostate-specific antigen PSA screening combined with digital rectal examination DRE. PSA screening had made a paradigm-shifting impact on the detection and management of PCa. However, these tests have limitations, because of low predictive value 25-37 and high false positive results due to lack of sensitivity and specificity, resulting in significant overtreatment of PCa patient. Hence, there is an urgent need to develop novel, non-invasive and more accurate biomarkers in conjugation with highly sensitive detection platform for more precise diagnosis of PCa. Recently, an altered expression of miRNAs miRs have been observed in PCa and correlated them as a potential biomarker for PCa. In the present study, we are quantifying the expression level of deregulated miRNAs in mouse and human PCa tissues as well as serum samples using an advanced nanotechnology-based sensing nanoparticle probes i.e. nanoprobes. Overall, the proposed studies will lead to the development of efficient technology for the accurate and early detection of differentially expressed miRNAs using sensitive Au-nanoprobes. This could enable us to develop early detection markers for PCa and differentiate between androgen independent and aggressive PCa. Recently, we have successfully synthesized and characterized fluorescently-labeled DNA-gold nanoparticle probes via bioconjugation. The result of fluorescence-based assay revealed that successful conjugation of 150-200 oligonucleotides per Au nanoparticle. In parallel, our qPCR analysis on prostate tissues excised from PTEN conditional knockout and wild-type littermate controls identified differential expression level of miRNAs. We also analyzed expression patterns of miRNAs identified through meta-analysis of previously published reports in mouse PCa tissue

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