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Application Stories

microRNAs as prognostic biomarkers in serum

miRCURY LNA™ Universal RT microRNA PCR
Yu Li
Dr. Yu Li
Yu Li is a senior postdoctoral research associate at the Benaroya Research Institute at Virginia Mason Medical Center and a pioneer in the microRNA qPCR field. He has been using Exiqon's miRCURY LNA™ Universal RT microRNA PCR system to identify serum-based biomarkers for prognosis of patients with primary sclerosing cholangitis in a ursodeoxycholic acid (UDCA) trial.

1. What is the main focus of your research?

My research is focused on identification of novel microRNA biomarkers in body fluids for diagnosis and prognosis of rare but potentially life-threatening liver diseases, as well as for patient response in drug trials. Our goal is to develop a safe, accurate, and inexpensive alternative approach to liver biopsy.

2. How did you come to be interested in microRNAs?

I have been working on microRNA since 2005 when I was a research intern at Rosetta Inpharmatics, the Seattle site of the Merck Research Laboratories. When Drs. Jopling and Sarnow’s groundbreaking work on miR-122/HCV first came out in Science, my group was also working on profiling liver microRNAs associated with HCV replication using the in-house real-time PCR microRNA profiling systems. I had first-hand experience of using the real-time PCR microRNA profiling system in biomarker discovery and pharmacodynamic studies. I was truly impressed by its robustness.

3. Tell us about the background to your current project.

It was an interesting story about an ancient drug, ursodeoxycholic acid or UDCA. UDCA has been used for thousands of years in Chinese traditional medicine as the treatment for liver diseases. Nowadays, UDCA is often used to treat gallstones and has been approved by FDA in treating primary biliary cirrhosis, a serious inflammatory liver disease. For this reason, clinicians started to test the efficacy of UDCA on patients with primary sclerosing cholangitis, a different inflammatory liver disease that often causes liver and bile duct cancers.

Initial studies on low and medium dose UDCA showed improvement in sero-biochemistry tests in patients taking the drug. When high-dose UDCA was tested in a trial study involving multiple medical centers including us, more serious adverse events were surprisingly observed in the UDCA group in comparison with the placebo group, despite the improvement in sero-biochemistry. Basically, the conventional tests failed to alarm the clinicians. We were thinking that microRNA biomarkers in serum may be able to predict the worse prognosis of high-dose UDCA treatment.

4. Which questions would you specifically like to address?

Our goal is to identify serum microRNA biomarkers for prognosis of patients with primary sclerosing cholangitis in a ursodeoxycholic acid (UDCA) trial. We specifically wanted to test whether serum microRNA signatures could predict unexpected serious adverse events in a drug trial.

5. Tell us about your previous experience with microRNA qPCR.

I was one of the first researchers using microRNA qPCR platforms on the market back in 2006. I used the panels and individual assays from Applied Biosystems. I remember I ran the ABI panels on 7500. The protocol recommended using miR16 for normalization. In 2006, 96 well plate was considered as high-throughput, as only 300 or so microRNA had been identified at the moment. I used SDS software to process raw data and MS Excel to make figures.

6. Can you comment on how you think the field of microRNA qPCR has developed since then and what the main challenges are today?

Over the years, the sensitivity and specificity of microRNA real-time PCR has been increased significantly due to the LNA™ technology by which the Tm of individual assays can be normalized to a specific temperature. It is very important as the GC%, hence the natural Tm, varies greatly among microRNAs. Without the LNA™ technology, it would be unrealistic to have consistent amplification efficiency of hundreds of unique assays on the same 384/1536 well plate. Having reliable profiling data would save more resource in down-stream validation studies. I can think of one challenge ahead. High-throughput real-time PCR assays need to be made more user friendly.

7. What were the key factors for you in choosing a microRNA qPCR system?

Data quality is the top priority. Under data quality, I put affordability over user friendly. Since I am currently supported by a NIH grant which is relatively small, I want to include as many clinical samples as possible to increase the statistical power of the study. However, if budget is less an issue, user friendly is more important as a user friendly platform produces more consistent data.

I chose the Exiqon’s microRNA PCR systems for its LNA™ technology, its reliability and relatively lower cost.

8. What do you find to be the main advantage of the miRCURY LNA™ microRNA PCR system?

The LNA™ technology and the resulting data quality is the main advantage. As all the LNA™ primers are wet-lab tested, false-rate is supposedly lower.

9. How do you feel about your results so far?

I have great confidence in my results using the Exiqon LNA™ platform.

10. What were some specific challenges in your current experiments and how did you overcome them?

Normalization is an important consideration in every qPCR experiment. I did rigorous tests on both endogenous and spike-in controls using clinical samples. Our manuscript describing the tests in greater detail has been accepted by the journal of Analytical Biochemistry. In this paper, we demonstrated that the Exiqon LNA™ platform works well for identification of serum microRNA biomarkers.

11. What would be your advice to colleagues about getting started with microRNA qPCR?

Try qPCR assays from different companies and test them the same group of genes. Remember to choose not so common ones. You will find out yourself which platform performs better.

Finding a good normalization strategy is the key. Literature may give you some clue, but you have to test yourself in your own experimental settings.

12. What are the next steps in the current project and how do you plan to perform them?

We have gotten a lot of interesting results. I am writing a grant proposal based on these results to extend our study to the next level. My goal is two-fold, developing the microRNA biomarkers for clinical testing and generating a hypothesis for further research.

13. When and where will be hear /read more about your studies?

The study was presented as an oral presentation at NIH in last June. I am preparing a manuscript as well as a grant proposal for a follow-up study

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