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Kidney Cancer UK News

Immune

Research Profiles Immune Landscape in Kidney Cancer

NEW YORK (GenomeWeb) – A team led by researchers at the University of Zurich has generated a profile of the immune cell landscape in clear cell renal cell carcinoma.

Published this week in Cell, the study used mass cytometry to characterize T cells and macrophages in samples from 73 ccRCC patients and five healthy matched kidney samples, identifying immune phenotypes associated with progression free-survival as well as potential biomarkers that could be useful for purposes including immunotherapy development.

Using Fluidigm’s Helios mass cytometry instrument, the researchers measured several dozen protein markers in 3.5 million immune cells, identifying 17 different tumor-associated macrophage (TAM) phenotypes and 22 T cell phenotypes.

The data provides insight into the basic biology of patient immune function in ccRCC, while also identifying markers that could be useful for guiding immunotherapy treatment for the disease, said Bernd Bodenmiller, assistant professor at University of Zurich and senior author on the study.

Developed as a commercial technology by DVS Sciences, which Fluidigm purchased in 2014, mass cytometry combines the capabilities of flow cytometry and atomic mass spectrometry, allowing it to measure large numbers of proteins in single cells with high throughput. The approach detects proteins using antibodies linked to stable isotopes of elements, which can then be read with high resolution via time-of-flight mass spectrometry.

The effort detailed in the Cell paper began around three years ago, Bodenmiller said, as he and his colleagues set out to generate a comprehensive picture of the ccRCC immune cell landscape. The first step, he noted, was determining what proteins would be most informative to measure.

In the case of T cells, the researchers used a panel consisting largely of canonical T cell markers providing an overview of the T cell phenotype landscape and proteins known to be relevant to immunotherapy.

For macrophages, we had to “develop a new [antibody] panel from scratch,” said Stéphane Chevrier, a University of Zurich researcher and first author of the study. They did this by isolating monocytes from the blood of healthy donors and then inducing them to differentiate into different macrophage types.

“Then we used an antibody screen to determine which markers were most informative for distinguishing between the [different] macrophages that we were able to generate in vitro,” he said. “And then it turned out that those markers were also highly informative for analyzing the macrophage subsets in the tumor samples.”

The authors did note, however, that it was possible the macrophage panel might be “biased towards these in vitro polarized cells.”

Looking at the macrophage data, Bodenmiller and his colleagues identified 17 TAM phenotypes, several of which appeared linked to patient survival. For instance, patients with larger presence of the M-11 and/or M-13 phenotype as well as a smaller presence of the M-5 phenotype had shorter progression-free survival.

The researchers also found that while the markers CD163, CD204, and CD206 have been interchangeably used to define pro-tumorigenic TAM populations, their results suggest that these markers distinguish subsets.

On the T cell side, the study yielded several findings of potential significance to immunotherapy research and treatment in ccRCC, Bodenmiller noted.

One key takeaway from the data, he said, was the fact that T cells “are heterogeneous in the expression of what people think of as the markers that should be targeted in immunotherapy.”

“An example is [the protein] CTLA-4,” Bodenmilller said. “It’s a target of immunotherapies, but we have shown that in many exhausted [T cell] phenotypes that we discovered, at least in ccRCC, it is actually not expressed.”

“We also show that the composition of T cell phenotypes is heterogenous across different patients, which means that in some patients a certain therapy might work, and in other patients it may not be very successful,” he added.

For instance, the study found that while the marker PD-1 was broadly expressed across the observed T cell phenotypes, the markers TIM-3, CTLA-4, and 4-1BB were expressed only in certain cases.

This, Bodenmiller said, suggests the importance of screening patient biopsies for various markers prior to immunotherapy treatment, particularly as the field moves towards using combinations of therapies targeting different molecules.

The study also identified a potential new marker for ccRCC immunotherapy, the protein CD38, which Chevrier said has been identified as a potential marker of T cell exhaustion in infectious disease, but has not been much discussed in the context of cancer.

He noted that there are differences between T cell exhaustion in cancer and infectious disease, but the high level of overlap that he and his colleagues observed between CD38 and PD-1 expression in ccRCC suggests it could also be a useful marker for that disease.

Bodenmiller said the researchers looked at ccRCC for several reasons, among them the fact that it is a relatively common and deadly cancer and that, while the US Food and Drug Administration has approved an immunotherapy targeting PD-1, patient response is mixed.

“So for us it was really relevant and interesting to try to better understand the immune system in this type of tumor,” he said.

The researchers are now taking the antibody panels they developed for the kidney work and applying them to a variety of other cancers, including breast and ovarian cancer, Bodenmiller said.

The data from the Cell study indicates that “there is structure in the immune landscape, meaning that the presence of one or several immune cell phenotypes is then predictive of the presence or absence of other immune cell phenotypes in the same tumor,” Bodenmiller said. “We also found that the immune landscape composition is related to the progression free survival of patients”

They are also using imaging mass cytometry to investigate in a larger cohort of ccRCC patients the spatial relationships between different kinds of immune and tumor cells.

 

read the full article on GenomeWeb HERE