Lavanya Lokhande, PhD, Department of Immunotechnology, Lund University, Sweden, discusses results from a study which investigated T-cell subpopulations profiled by spatial proteome among patients with mantle cell lymphoma (MCL). These data were presented at the 2022 American Association of Cancer Research (AACR) Annual Meeting.

Transcript
Hi, I'm Lavanya Lokhande, I'm a doctoral student at the Department of Immunotechnology, Lund University, Sweden.

Oncology Learning Network: What existing data led you and you co-investigators to conduct this research?

Dr Lokhande: The lymphoma subtype that we are looking at is MCL.

Sadly, our understanding of the tumor immune microenvironment for this lymphoma subtype is quite lacking.

Previously, one of our group members, one of my colleagues, had looked at immunohistochemistry single-staining in a homogeneously treated MCL cohort, and they looked at different immune cell populations characterized by CD3, CD4, CD8, CD25, Foxp3 stain.

What they found were a couple of interesting things. They found a high number of CD8-positive cells. When it came to correlations with the clinical parameters, they saw that Foxp3-positive cells were more associated with progression, so more associated with relapse, but not really survival.

Our understanding of the microenvironment is quite limited. We wanted to get a better idea of what the immune profile is in MCL. Rather than just doing single stainings where we are limited by the panels that we could use, we wanted to do bulk omics.

Then the issue with bulk omics like single-cell or flow cytometry analysis is that you tend to lose the spatial architecture, which is also not something that we wanted. Since there have been developments, especially as all omic platforms, we wanted to use one such platform to study the immune microenvironment in MCL.

OLN: Could you briefly describe the study and its findings?

Dr Lokhande: My study is based on profiling different T cell subpopulations.

What we did was characterized for immune cell population based on 3 cell surface markers that were CD3, CD8, and CD57.

CD3 and CD8 would differentiate between your cytotoxic and non-cytotoxic compartment, whereas CD57 was used as a marker to differentiate between your early, more active cell types to dominantly differentiated or almost present cell types.

A combination of these markers gave us 4 subpopulations: the early cytotoxic, which was just CD3-positive and CD8-positive; the early non-cytotoxic, which was CD3-positive only; the late non-cytotoxic, which was CD3-positive, CD57-positive; and the late cytotoxic, which was positive for all 3 markers.

Additionally, what we have used is archival FFPE primary MCL samples that were collected from the BLISS Biobank, and they were added as a tissue microarray. Then we used this new technology by NanoString called GeoMx Digital Spatial Profiler (DSP) to look at specified regions of interest within these patient tissue cores.

We went down to look at not just the immune cells within the tumor enriched zone, but also look at immune cells adjacent to the tumor, so where you lack the tumor cells.

This was in another study, we had characterized where the relative position of the tumor cells were based on CD20 staining for the B cells in an adjacent slide. We had a very good confirmation on which region we are actually sampling.

This was sort of the overall maker of the study. The questions that we basically wanted to target was not just looking at the immune cell, but to study whether the immune cell profile would shift whether you sample them within or adjacent to the tumor enrich regions.

At the same time, you want to see whether they can be correlated with any clinical pathological outcomes such as survival or morphology.

What we have described in this poster is basically the first part of this entire study, which is whether localization has any impact on how these T cells behave functionally, and that is the main finding of this poster.

One of the first things we saw was that the distribution alone in these patients, so in 104 patients were sampled of which 38 had these both tumor within and tumor adjacent regions.

One of the first things we saw that in this subset of patients, there was a lot of immune cells, much more in the tumor adjacent regions than the tumor enriched regions. That was quite interesting because it obviously had an impact on what you would see downstream.

We saw that when you profiled the different immune cell populations, there was a complete sort of differential expression pattern of the different immune cell types depending on where they were sampled from. This was seen for early cytotoxic, early non-cytotoxic, and the late cytotoxic T cell subset.

One of the things we saw that factors like granzyme A and B, which were correlated with cytolytic activity were upregulated in the tumor enriched region for the early cytotoxic subsets.

Then in contrast, there were several more that were consistently, irrespective of which immune cell type you're looking for, they were enriched in the tumor adjacent regions, and this was like VISTA, IDO, SMA. This was quite interesting.

We tried to look a bit into what literature would tell us and they suggested that this is potentially related to a more suppressive state. This is something that we are still studying the functional aspects and the regulatory pathway a bit more in detail, but this was the initial results that we got and the main results, for now.

OLN: What are the possible real-world applications of these findings in clinical practice?

Dr Lokhande: We're in the era of immunotherapy, we're shifting from conventional chemotherapy to immunotherapy. Obviously studying the interaction of the tumor with the immune cells is kind of necessary.

Naturally, studies like this, where we are looking at different immune cells, where we are looking at immune versus tumor cell interaction, naturally are very important just in the development of what can be potentially targeted, and how patients might even respond to such kind of treatments.

OLN: Do you and your co-investigators intend to expand upon this research? If so, what will be your next steps?

Dr Lokhande: We're still looking a bit more into the functional aspects of this differential profile, but the next immediate step is to look at how these immune subtypes correlate to clinical pathological parameters that could be like mutational status, survival, (and) morphology.

We are also looking at right now, we have sampled the proteome, so we are only looking at 63 proteins that target various signaling and regulatory pathways.

We are also looking now at the transcriptome, so trying to correlate the transcriptome with the proteome and what it means with respect to the different immune cell types.

OLN: Is there anything else pertaining to your research and findings that you would like to add?

Dr Lokhande: When it comes to tissue-based analysis, we have limited ourselves to either looking at bulk omics through single-cell or flow cytometry analysis, but in that case, you're destroying the spatial architecture and you sample the cells completely.

Then, if you want to retain the spatial architecture, you use singleplex immunohistochemistry, which limits the number of biomolecules you're targeting.

What I feel is one of the main conclusions is how spatial omics should be now used as a complementary analysis, particularly since our analysis shows that sampling cells in different regions has a major impact on the functional status.

If you are acquiring cells from patients with such phenotypes of both tumor adjacent and tumor enrich regions, you might end up sampling, since you're taking the bulk, if you're sampling let's say bulk T cells, you don't know from which region of the tissue they belong to.

I think using such spatial information complementary to more now conventional methods of single-cell and flow cytometry, should be used or should start becoming more standardized, practiced, and more prevalent as we move forward.

Source:
Lokhande L, Rodrigues JDM, Gerdtsson AS, Porwit A, Jerkeman M, Ek S. Profiling T-cell subpopulations based on spatial proteome in mantle cell lymphoma. Abstract presented at: AACR Annual Meeting; April 8-13, 2022; New Orleans, LA. Abstract 6327.