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Student research project

Supervisors: Associate Professor Bing Wang and Professor David Kaye

Project summary

Discovery of novel circulating miRNAs as predictive and diagnostic biomarkers for cardiovascular and related diseases such as heart failure through profiling analysis and validation in cell culture and animal models.

Heart failure (HF) represents a major health and economic burden with high hospital admission rates despite significant advances in treatment and management. Early detection and monitoring of therapeutic response is critical to the management of HF patients.

MicroRNAs (miRNAs) are members of a large class of non-coding RNAs of approximately 22 nucleotides in length, which regulate most genes in the human genome. MiRNAs function involves in transcriptional and post-transcriptional regulation of gene expression. There is high concentration/level of miRNAs in circulation that are stable, relatively easy to detect and measure with adequate analysis platform available. MiRNAs expression often tissue specific (may indicate the source of pathological processes) and their profiles in disease tissue are reflected in those of blood (serum or plasma) which is easily accessible surrogate for disease monitoring. Hence, microRNAs have great potential to serve as non-invasive diagnostic and prognostic biomarkers for diseases such as HF.

We have established most advance technology capable of high throughput profiling circulating miRNAs and have profiled circulating miRNAs in blood samples from HF patients.

This project will continue our study in miRNA profiling and investigate the potential link of certain miRNA with the disease progression for HF. Validation of circulating miRNAs as biomarker for HF will be performed and anti-miRNAs will be used in cell culture to demonstrate the biological function of the miRNA biomarkers.

The methodological approaches include RNA extraction, open array miRNA expression profiling, q-PCR quantification, primary cardiac cell culture and Western Blot analysis.

This project is suitable for a Masters or PhD student.

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