Sergio Rutella, M.D., Ph.D. FRCPath is a Professor of Cancer Immunotherapy at the John van Geest Cancer Research Centre at Nottingham Trent University. His research focuses on acute myeloid leukemia (AML), an aggressive form of cancer that originates in the bone marrow. We recently spoke with Dr. Rutella about his research and the challenges of studying this disease.
NanoString (NS): What is driving your research in this area?
Sergio Rutella (SR): In treating patients with AML, we see that there are a number who fail to respond to chemotherapy or have frequent relapses. The treatment of these patients has not changed much in 30 years. There is a lot of interest around generating immune gene signatures and seeing if these can be used to improve classification of patients into different risk groups. If there are unique signatures, can we then identify molecules to target in the clinic? We immediately thought that we should investigate these aspects in more detail.
NS: Why did you begin working with NanoString?
SR: In order to identify molecular signatures in our research we needed more efficient methods and a way to increase our data throughput. We were impressed with the way the NanoString® gene expression panels are built. They are designed based on published papers and public data sets to stay current with the field. This struck me immediately as something quite different from the conventional way of approaching gene expression analysis, which tends to be something more like a fishing expedition. We are currently profiling the bone marrow of AML patient samples with the NanoString PanCancer Immune Profiling Panel* and nCounter® Vantage 3D™ DNA:RNA:Protein Heme Assay*. This has not been done previously in such a comprehensive manner and the approach is totally new to this field.
NS: What are you learning with this technology?
SR: We have processed approximately 400 bone marrow samples from patients with AML in our research. AML is quite rare and so we use biobanked samples that come from around the world. The PanCancer Immune Profiling Panel* is a collection of 770 genes and we are collecting a lot of information from these samples. What we have seen thus far is that AML samples AML can be classified into different clusters based on immune signatures. We have detected at least two major groupings of AML samples: “Hot” AML with significant inflammation and “Cold”/non-inflamed AML. When there are high levels of inflammation there is an increased expression of negative regulators of the immune response and that can translate into the induction of T cell dysfunction. Our preliminary survival analysis has shown a correlation between these two groups where excessive inflammation in ‘Hot’ AML correlates with a worse prognosis for the patient.
NS: How is this new knowledge shaping the next phase of your research in AML?
SR: As I mentioned, AML is a rare disease and we need to maximize the amount of information we collect. We are now using the NanoString’s nCounter Vantage 3D DNA:RNA:Protein Heme Assay* to measure DNA, RNA, and protein in a single sample. We captured information about single nucleotide variants, mutations, and new antigens that could be compiled into a “super signature” for the disease. This super signature could be highly relevant in the clinic to stratify patients; stratification of patients can lead to improved treatment as it could be tailored to the genomic signature of the disease. Additionally, we could use immune gene expression profiles to identify secondary biomarkers that are not part of the “usual suspects” of checkpoint inhibitors that are commonly investigated. For example, research in the solid tumor field is trying to use biomolecules to increase T cell trafficking to tumor sites. It is highly possible, then, that we can use similar strategies with newly identified biomarkers to attract T cells to the bone marrow microenvironment. From there, one can envision a combination of immunotherapy approaches that simultaneously direct an influx of T cells to the bone marrow while inhibiting the immune-suppressive mechanisms there.
NS: What tools are you using to look at the bone marrow environment?
SR: NanoString’s Digital Spatial Profiling (DSP) Technology* provided us a unique opportunity to look at immune cell populations in FFPE tissue. DSP enables profiling of >30 different proteins with high coverage of potential therapeutic targets, including those against immune dysfunction. There is almost nothing in the literature about the patterns of immune cell infiltration in the bone marrow, let alone expression of novel negative checkpoints such as CD276 or VISTA. We have analyzed ten bone marrow biopsies from patients with AML. What we saw was a very unique pattern of T cell infiltration within the bone marrow, which looks quite patchy and non-uniform. We have also been able to visualize T cell:T cell interactions where T cells are possibly exchanging biological material, essentially talking to each other in that environment. Again, all of this is completely new to our field of study.
NS: Things seem to be coming together very quickly for AML translational research.
SR: All these NanoString technology elements – the Gene Expression Panels*, the 3D Biology™ Technology*, and the DSP Technology* contribute to our work to potentially create a proper stratification of patients. AML is very heterogeneous disease with more than 700 translocations, more than 5,000 driver mutations, and recently AML has been stratified into eleven genomic categories. As you can imagine, it would be very difficult to put together clinical trials to test one therapy that would be effective against so many different variants. Improving patient stratification algorithms and customizing therapeutics all comes back to creating a better prognosis for the patient. Patients with high risk AML really need and deserve something different.
NS: Where do you see the field going next?
SR: As I said, the general treatment strategy for AML has not changed in almost 30 years. But just this year there have been two FDA approvals for drugs that are targeting AML on a molecular level. Genetic abnormalities in AML can be exploited using these agents; there is a lot of hope and an expectation that these two drugs will improve patient prognosis in AML. The field is moving toward the use of personalized approaches. I think partnerships between industry and academia are going to be more and more important as we go forward. Working with NanoString has been a fantastic example of how productive this type of collaborative interaction can be.
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