CRISPR Technology Seeking to Inactivate Mutated Genes in Lung Cancer

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Monte Winslow, PhD, shares the work on CRISPR being developed in his lab, and how this technology might help advance treatment for the non-driver NSCLC population.

Monte Winslow, PhD

Monte Winslow, PhD

Monte Winslow, PhD

Academic researchers are hoping that their efforts on the gene-editing technology of CRISPR (clustered regularly interspaced short palindromic repeats) will lead to the ability of turning off mutated genes in patients with a variety of malignancies, including lung cancer.

CRISPR technology allows for editing or alteration of a cell’s genome, and inactivating or repairing genes as needed by changing the DNA sequences.

In the lab, researchers are currently exploring the diversity of various tumor genotypes in mouse models to learn more about cancer biology and exactly how mutated genes impact lung cancer progression, according to Monte Winslow, PhD, assistant professor, Department of Genetics and Department of Pathology at Stanford Medicine. Moreover, he adds, they are exploring mutated genes to determine which ones are associated with drug sensitivity.

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OncLive: What did you highlight regarding CRISPR technology in your presentation?

In an interview with Winslow during the 2017 OncLive® State of the Science Summit on Advanced Non—Small Cell Lung Cancer, he shared the work on CRISPR being developed in his lab, and how this technology might help advance treatment for the non-driver NSCLC population.Winslow: The main thing that we are interested in doing is developing model systems where we can generate many different types of tumors in mouse models. These are very important cancer genes. Can we create mouse models of human cancer? We have a diversity of different genes mutated. We are looking at the diversity of different genotypes of tumors in individual mice so we can first learn about the biology of how these genes being mutated impacts cancer development, or cancer progression, in the lung.

What is the history of CRISPR?

Secondly, we want to use these models to understand if there are certain genes, when mutated, in the human disease that might lead to sensitivity to different therapies. These might be therapies that are already FDA approved for other cancer types, but we don’t know if there are some rare genotypes of tumors that are going to be exceptional responders to these sorts of drugs. It helps that these platforms we are developing can help prioritize to get to patients with the right genotypes of tumors. It is a very interesting history of CRISPR; it is originally from various model organ systems where they discovered it. Then, it’s applied now to this genome engineering, where it’s quite easy to engineer these components to create breaks in the DNA. Those breaks can be repaired in a way where the gene is now inactivated.

So, as far as the cancer modeling side, what we have been involved in is trying to harness this CRISPR system to be able to inactivate genes in these sort of cancer models. Other people have also contributed to this field, so that has been a real advance. Before being able to do these things, it would really take years or longer to look at a function of any individual gene in a cancer model. Now, we can look at tens of genes in the same amount of time, and that has really been a huge advance. Our hope now is to do more of that— more efficient, quantitative ways and then start applying these question of looking for different drug sensitivities, which is a very open question. Lots of people are interested in it.

At some point, do you envision this being able to work more in human models?

Can any of this be applied to clinical practice for community oncologists?

For us, with these types of systems, we want to address this in tumors growing in vivo, not in cell lines that are growing in petri dishes in the lab but rather in an animal, or sort of host. This is where we’ll acknowledge that what we’re looking at is how they grow in these mouse model systems, but it’s pretty close to people. So, we hope we are going to gain some insight to this sort of therapy. Certainly, people are using CRISPR to inactivate genes of interest in cancer cell lines or different type of models. There is going to be some benefit to doing these mouse systems because this is the only system where you can initiate tumors from a single cell—in this case, the mouse lung—and it will develop all the way to being metastatic lung adenocarcinoma. With a lot of these other systems, every system has its own advantages and disadvantages, so we think that is a major advantage here—that all of that happens naturally in vivo. Whereas, all of the human systems will be transplanting into mice or growing in vitro. They have the advantage of being human, but there are some disadvantages related to that. I don’t think there is much from our work that is going to be rapidly applied to clinical practice, unless that they realize the amount of academic effort going into understanding this disease and thinking about new therapies. It is not all coming out of drug companies; it really is a huge academic interest in that.

There are not that many mutations that lead to drug sensitivity and, while there have been amazing efforts, there are a lot of patients who don’t have any actionable mutations as of today. But, how do you make those actionable? How do you do things to help those patients? We are working hard to get them better and knowledge-based therapies. We’ll see how that works out.

There's a lot to be said for that, especially since patients without driver mutations make up the majority of the lung cancer population.

We don’t really know what the future holds. Are we going to find that there is a reasonable-size fraction of the lung population that can be targeted with these drugs that maybe are already FDA approved for other cancer types? That could very well be. I feel like I’m a little bit late to this idea of personalized therapy, but that’s what we're getting into now.

Is there anything else you’re working on in your lab that you would like to share?

Can we at least categorize people? For example, perhaps 1% of patients look like this? And now, maybe you figure out how to treat that 1% of patients. Years ago, we would have thought it was so complicated—like a problem. Now, I feel that, on the academic side, that complexity is manageable and we don’t have to be scared that it’s complicated. We can sort of deal with it. If it is 1% of patients who are responding to therapies, that is fine with us. That is the direction we’re going with. Most of my lab is interested in understanding the mechanisms that drive metastasis. Not tumor growth and how big they get, but whether they gain these characteristics that allow them to leave the primary tumor, spread around, and form these metastases in distant organs. What we are doing there is quite basic science. How did the cells change to be able to do that? What are the requirements for it to grow in distant sites? It is something we find interesting; whether that becomes targetable is another question.

If you can block metastasis with a small molecule, are there patient populations that will benefit from this? This is what we're taking to our clinical colleagues at Stanford Medicine about because we think it’s really interesting. Again, it might be a small fraction of patients, but metastasis is a really terrible part of the disease, so that’s our other main interest.

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