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Q&A: MSKCC's Hans-Guido Wendel on Developing an Unbiased Screen for microRNA Targets

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wendelheadshot.jpgName: Hans-Guido Wendel

Position: Assistant member, cancer biology/genetics program, Memorial Sloan-Kettering

Background:

• Postdoc, Cold Spring Harbor Laboratory — 2002-2006
• Postdoc, pharmacology, Memorial Sloan-Kettering Cancer Center — 2000-2001
• Resident, hematology/oncology, RWTH-Aachen — 1998-2000
• MD, Medical School of the Technical University of Aachen — 2000

Late last month, Memorial Sloan-Kettering Cancer Center researcher Hans-Guido Wendel and colleagues published a paper in Nature Cell Biology showing how a novel functional genetics approach could be used to identify miRNA target genes.

Specifically, the team used a short hairpin library screen to identify genes whose knockdown mimicked the effect of microRNA-19, a member of the oncogenic miR-17-92 cluster, in lymphocytes, hypothesizing that this would reveal the genes responsible for the miRNA's activity.

"Strikingly, the results of this screen were enriched for miR-19 target genes, and include Bim, AMP-activated kinase, and the phosphatases Pten and PP2A," they wrote in the paper. "Hence, an unbiased, functional genomics approach reveals a coordinate clampdown on several regulators of phosphatidylinositol-3-OH kinase-related survival signals by the leukaemogenic miR-19."

This week, RNAi News spoke with Wendel about the findings.

Let's start with an overview of your lab's research focus.

We're interested in genetic interactions that lead to hematopoietic cancers — leukemia and lymphoma. We look at candidate genes [and also] do screens, for example, of short hairpin libraries, cDNA libraries, [and] microRNA libraries to identify new genes.

Then, given our affiliation with Memorial Hospital here, we look at primary patient samples using genomic tools to identify regions of genomic loss, over-expressed microRNAs, and so on, as a different way to find genes that are likely [to be] important in the development of these hematopoietic cancers.

The paper focused on the miR-17-92 cluster. Can you provide a little background on it?

The cluster is known as oncomiR-1, which was originally identified in Greg Hannon's lab [at Cold Spring Harbor Laboratory] as the first cluster of microRNAs that is able to accelerate lymphoma development in mice and is highly expressed in [the cancer].

It's a cluster that has six or seven microRNAs in it and there are different paralogs of it, so the question we were interested in is, "Which of those microRNAs [is the source] of activity?" If there are multiple [miRNAs] in it, you have to wonder if they are all important, is there is one more important than another, or is [its effect] maybe due to one individual microRNA.

There, we find that miR-19 seems to be the most important one.

Can you give an overview of the experiments you did in the paper and what you found?

The problem with microRNAs is that, at the moment, we don't have a good handle on them. For example, if you take a genetic lesion — the loss of [the tumor suppressor] Pten in cancer — we know what it means: these cancers are going to be resistant to certain types of drugs and they'll be sensitive to certain types of drugs.

For microRNAs, we just don't have a way to say these things yet, because if we think of how they work, we find that they can target hundreds and hundreds of genes. The challenge is to find out which of these are actually important for the mechanism of the microRNAs — how do the microRNAs work, what are the key effectors?

Here, we've [developed] a completely different way from everyone else. We screened a short hairpin library of RNAi [molecules], basically as an unbiased way to tell us which things are important, how they work downstream. The striking thing is that we find we can actually nail it down to a pathway, very much in the way we think about Pten or p53. We can now say, "Quite similarly, miR-19 seems to act through [phosphatidylinositol-3-OH] kinase signaling." That, now, makes it an entity we can handle clinically. Conceptually, we can say, "There are drugs that work well in cancers that have loss of Pten, [which is a regulator of the PI3 kinase pathway]. So what about these drugs in cancers that over-express miR-19?"

We were trying to find an unbiased way [to do this] — not meaning that we cherry-picked our favorite pathway, but that we let a library tell us how it works … and turn it into something we can handle.

And this is a novel approach?

Yes. So far, nobody has done this. There are very elegant experimental approaches that tell you all the genes that are targeted by microRNAs, and typically you end up with several hundred or a thousand genes. These are either computational predictions, or they are very elegant biochemical or genomic experiments.

But if [a microRNA] targets these one thousand genes, you could speculate that either all of them are important or perhaps some of them are relevant for the cancer-causing activity of the microRNA. In that sense, we can now [establish] that it targets some 900 genes, but really there are only four or five of them that are critical to the function.

It's kind of difficult to think about something that targets hundreds of genes. What are you going to do with that? How do you conceptualize how it works? Now we can say, "This is how it works."

Are you now applying this approach elsewhere?

No. This is the first [such experiment] we've done in this way. But we are going to [use the approach] with other [miRNAs]. …

There are several microRNAs that are important in cancer. … For example, in chronic lymphatic leukemia, about 50 percent or so have a deletion that targets a specific microRNA, so you have to think it's a tumor suppressor. But we don't really know how it works, how it prevents leukemia, and why leukemia cells need to get rid of it. So we'd like to apply this same approach to that in order to pinpoint the pathway that acts downstream from it.

Looking forward, if you think about microRNAs as sort of new types of genes that cause cancer, you have to wonder what you can do about it. You could target these microRNAs directly, and there are different approaches [such as] making an antisense [molecule] that targets these microRNAs. But the problem is that these are difficult to deliver and gene therapy has had its ups and downs.

I'm a doctor by training, so for me, the interesting question is how you can move [these findings toward] therapy. We can now say, "miR-19 works for PI3 kinase signaling, and … companies are making drugs that can target this specific pathway. Are leukemias that have high levels of miR-19 particularly sensitive to these drugs?"

Can we exploit this and translate this into therapy? That is where we'd like to take this.

So not necessarily looking to target miR-19 itself?

Other people are doing that, and that's fine and great. I think that it is going to be [a] difficult [route], especially in leukemias. How are you going to get these antisense molecules into literally billions of leukemic cells? It's very, very difficult. So I think having a small molecule that can exploit these pathways is [more likely to succeed].

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