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OSU's Mark Bloomston Discusses miRNA Expression and Pancreatic Disease

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Name: Mark Bloomston
 
Position: Assistant professor of surgery, Ohio State University
 
Background: Surgical oncology fellow, Ohio State University — 2004-2006
Resident, general surgery, University of South Florida — 1998-2004
Research fellow, University of South Florida — 2000-2002
Intern, general surgery, University of South Florida — 1997-1998
MD, University of South Florida — 1997
BS, biology, Florida State University — 1992
 

 
This week, researchers from Ohio State University published a report suggesting that expression patterns of particular microRNAs may help distinguish between pancreatitis and the most common form of pancreatic cancer, as well as survival rates of patients with the malignancy.
 
According to the data, which were published in this week’s Journal of the American Medical Association, the over- or under-expression of certain miRNAs could be used to identify adenocarcinoma of the pancreas and pancreatitis with 95 percent accuracy.
Additionally, the researchers were able to use a subgroup of miRNAs to differentiate long-term and short-term cancer survivors.
 
This week, RNAi News spoke with Mark Bloomston, a co-author of the JAMA paper, about the findings.
 
Let’s start with an overview of your lab.
 
My lab [operates] in conjunction with Carlo Croce’s lab. The focus of my lab is on microRNAs in various cancers, particularly pancreatic cancer and esophageal cancer. Dr. Croce’s lab expands well beyond that — he is a well-established researcher who has had a lot of success in discovering several types of gene defects in a variety of cancers.
 
You focus exclusively on microRNAs?
 
Yes.
 
Can you talk about the JAMA paper and the findings?
 
We first found 65 patients who had undergone an attempt at a curative removal of their pancreatic cancer. We microdissected out their tumors, along with a piece of the adjacent normal pancreas, and extracted the RNA from those [samples].
 
As another control, since chronic pancreatitis is so commonly associated with pancreatic cancer either as a cause or, more commonly, a result of the cancer, we also got chronic pancreatitis specimens from 42 other patients who had undergone surgery and extracted the RNA from [those samples].
 
We then did a global screening for microRNAs using a microarray chip that we have here that expresses all the known microRNAs in humans, and looked at the differences in expression patterns between each sample type.
 
Based upon that … we saw 30 microRNAs that were over-expressed, compared with three that were under-expressed, in the pancreatic cancers. Then, when we compared the cancer [samples] to the chronic pancreatitis [samples], we saw 15 [miRNAs] that were increased and eight that were decreased.
 
When we compared the chronic pancreatitis [samples] to the normal [samples], we saw 22 [miRNAs] that were increased and two that were decreased.
 
[The tumor samples] were all [from patients with] ductal adenocarcinoma of the pancreas, which is the most common cancer of the pancreas. We made sure they were all the same types of cancers — we went back and re-verified all the diagnoses beforehand … so we [could be] sure we had a common set of common pancreatic cancers.
 
What was the process by which the RNA was extracted?
 
We used a standard Ambion kit — the RecoverAll kit. There was nothing fancy about that; we stuck to the manufacturer’s recommendations.
 
What about the chip the analysis was conducted on?
 
That’s one that we created here. It’s the third version of [an miRNA microarray chip] created at Ohio State in Dr. Croce’s lab. We have used it for various different tumor types and have validated it.
 
What distinguishes the chip from previous generations?
 
We just added from previous generations. This is version three, which includes 326 human microRNA genes, plus it has mouse genes … [and] predicted microRNAs. What that has done is added to the previous versions … [because] every day there are new microRNAs being found. This [generation] added all the known microRNAs at that time, which is now actually two years old.
 
Is this chip available to researchers or kept in-house?
 
It’s available through our core lab, so we have people sending us specimens all the time. The university is constantly getting samples from various labs to run on our chip.
 
With the findings that were detailed in JAMA, what’s the next step for you? Are there planned follow-up experiments?
 
Absolutely. For the community at large, the next step is for other labs to work to validate our results. And we will try to validate our results going forward prospectively using our pancreas cancer tissue bank.
 
Also, in conjunction with clinical trials, [we want] to start seeing what the true impact is of these microRNAs. First of all, are they truly over- or under-expressed in pancreatic cancers, and do they have some kind of prognostic implication? That needs to be validated.
A parallel project for that would be to start trying to figure out what the underlying function [of the miRNAs] is. We’re seeing a lot of microRNAs pop up time and time again in various tumor types. For example, miR-21, miR-155, miR-221 — we’re seeing those pop up in a bunch of different tumor types. So those appear to be important in cancer in general, not necessarily just in pancreatic cancers.
 
We’re really interested in miR-21 and miR-155, and we’re starting to look at those in transgenic mouse models, and looking at in vitro experiments to see what role these play [in order] to start understanding the mechanism for how they function.
 
That’s really going to make a difference, because we know … a lot of these microRNAs … have predicted targets of interaction — target genes they go after — but we don’t really know the mechanism by which they work. They probably work very differently in different models.
 
There are already companies looking to commercialize this kind of thing. Are you working with any industry partners?
 
Not specifically. We are working with a company, not from a monetary standpoint, but just as a way to help validate and optimize some of the [experimental] conditions. For example, we’re working hard to optimize conditions for doing in situ hybridization for microRNAs, so we’re working with companies to do that.

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