Dr. Glenn Simmons Jr. from Cornell University College of Veterinary Medicine, and Dr. Stefani Thomas from University of Minnesota School of Medicine, detail a recent review they co-authored that was published by Oncotarget, entitled, “Targeting lipid metabolism in the treatment of ovarian cancer.”
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Hi, my name is Dr. Glenn Simmons Jr. I’m at Cornell University College of Veterinary Medicine in the Department of Biomedical Sciences.
And I’m Dr. Stephani Thomas, I’m an assistant professor in the Department of Laboratory Medicine and Pathology in the School of Medicine at the University of Minnesota.
The paper that we co-authored together, along with a undergraduate trainee, is titled “Targeting lipid metabolism in the treatment of ovarian cancer.” One of the main reasons that we were interested in doing this work, was because both of our research programs in our individual laboratories kind of work in areas that are separate, but end up converging on this particular disease model. My research is interested in how lipid metabolism can affect the ability of the immune system to target tumors and help improve patient outcomes, and through that work, we’ve been working in several different cancer models. The one that we’re currently looking in has been lung cancer over the last year, but looking at some of the literature that we’ve put together, in studying both lung cancer as well as other cancer models, we found that ovarian cancer has very similar characteristics that makes it such that lipid metabolism is an interesting area to start looking into developing research programs around.
And as Dr. Simmons mentioned, so our research areas are kind of complimentary. So my research laboratory focuses on proteomics, and we are taking a proteomics approach to studying ovarian cancer. So determining the molecular mechanisms, and also studying some of the altered signaling pathways that confer sensitivity or resistance to treatment.
So the thing that was really surprising when looking at this particular work, looking at ovarian cancer, and specifically this high-grade serious subtype of ovarian cancer, was this idea that the role of lipid metabolism has been pretty divisive in the field. So there’s a lot of research that suggests that limiting lipid metabolism within cancer cells specifically is a very viable way of treating and eliminating tumors. But there’s also a lot of research that suggests that lipid metabolism itself isn’t something that you would want to target, but it’s actually a consequence of several upstream mechanisms, pathways that converge on lipid metabolism. But it’s also kind of interwoven into the global metabolism of the tumor micro environment. So I think to me, that meant that the questions being asked in regard to lipid metabolism and cancer are very far from being solved, and I think we need to continue to ask more questions using more sophisticated techniques to investigate just which way we should go, in terms of improving therapeutic outcomes.
Yes, I definitely wholeheartedly agree. Then I think that was a great dovetail with the area of my research, in that we do have a lot of targeted therapies that are available, but they’re not a 100% efficacious. So some of the targeted therapies that are available, the patients that are stratified to be on those targeted therapies, only maybe about half of them do respond. Then these are the patients that supposedly have the favorable genetic predisposition to respond to these targeted therapies.
So from my laboratory’s approach, that means that we have a lot of work to do, there’s still a lot that we don’t know about the signaling pathways that are aberrant in ovarian cancer, and then what are some of the opportunities for us to identify novel drug targets? But before we can identify novel drug targets, there’s still a lot of work that we need to do to figure out, what are some of the alterations that are occurring, just on the basic fundamental molecular mechanism level? So for me, it was very exciting to really dig into the research, and find out more about the role of lipid metabolism, with the synthesis with lipid metabolism in conferring sensitivity or resistance to treatment, and also some of these lipids, thinking about them from the perspective of them being prognostic or diagnostic biomarkers. So really along the theme of, we have targeted therapies, but they’re not great, they’re not efficient, they don’t work for all patients. So there’s really a lot of opportunity for us to study additional areas, and lipids is one of those areas.
Right, and based on the work that my laboratory is interested in, we’re actually looking to take this basic understanding of how lipid metabolism is central to what we’re now understanding is this altered metabolism within the cancer disease state. But then also to find new models to investigate these things, so that we can come up with new targets to kind of understand the interconnectedness of various protein interactions, and in protein or gene environment interactions. So for us to do that, my laboratory is now utilizing three-dimensional bioprinting to develop new models. To ask questions of how these different cell types are interacting with each other in a three-dimensional space, and then manipulating the environment in which these cells are growing to show that how those two things – the cells in a three-dimensional space and the environmental nutrient space – interact with each other. And how that impacts how therapies are received, and the overall effect of those therapies on removing or eliminating tumors.
So for my research, our laboratory is predominantly based on… We do take a mass spectrometry based approach to most of our analyses, so we are really interested in deploying some discovery based studies, and also some target based studies. So the way that that pipeline looks, is we have an experimental model, so right now we have some cell lines that we’re working with, and also some patient derived xenograft models that we’re looking at. We can look at differences in protein relative abundance, and then once we have some viable candidates, those candidates are then moved along the pipeline for the development and deployment of some targeted mass spec based proteomic assays, to really figure out whether these changes are indeed correlating with disease stage.
So I think the final thing that we really want to make sure that we do before we close this out, is to thank all of those that were involved in this work. Together, Dr. Thomas and I actually co-mentored an undergraduate student who helped us put together this manuscript, by the name of Saliha Chaudhry. So we definitely want to acknowledge her, as well as both of our institutions, for supporting the work that we do. Because at one point, we were at the same institution when we started this work. I was once at the University of Minnesota along with Dr. Thomas.
Yes, I don’t think I have anything else to add. Definitely this was a great collaboration. I think there’s a lot of more work that needs to be done in the realm of ovarian cancer and lipid metabolism.
Absolutely. And one other thing, I guess an additional addendum, is just to say that the experience that we have both had with publishing with Oncotarget thus far has been pretty smooth, especially compared to other journals. I think the process is pretty straightforward, and the review process is not too arduous to getting the information out there for the public to get a hold of, and help to broaden the knowledge base, and help other researchers develop more interesting research questions, and help move the entire field forward.
Great. Thank you very much, it’s been a pleasure working with Dr. Simmons. He was the one who spearheaded this project. I’m definitely thankful for the opportunity to be involved in this project, and to really provide my laboratory with other opportunities for exploring other avenues of ovarian cancer.
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