18 Apr Primary Melanoma: Spatial Analysis Toolkit Allows Deeper Study of Cancer Cells and Their Environment
MedicalResearch.com Interview with:
Dr. Nirmal
Ajit Johnson Nirmal PhD
Instructor of Medicine, DFCI, HMS
Laboratory of systems pharmacology
Harvard Medical School
MedicalResearch.com: What is the background for this study?
Response: Like many other types of cancers, melanoma arises from gene mutations within cells that impact cell growth and division. These abnormal cells should be rapidly eliminated by our immune system, however, the failure to do so leads to the development of cancer. Hence researchers have long been interested to study the tumor environment that nurtures and sustains these dangerous cells. In the past, researchers have used single-cell technologies to delineate the cell types and cell states that make up the tumor microenvironment. However, the spatial relationships between these cell types and how they organize themselves such as to provide a favorable environment for the tumor to develop remains unknown.
In the last couple of years, researchers have developed a new suite of new technologies called spatial omics which includes CYCIF a method that was developed at Sorger lab. Using this method, we can not only measure the molecular information of cells at a single cell level but also their spatial context. This allows us to build a google map like view of the skin with melanoma and study what is exactly happening that allows the tumors to develop.
MedicalResearch.com: What are the main findings?
Response: As a testament to the need for such spatial data, when we looked at the very early stages of the tumor development, we noticed that there was no change in the absolute proportion of cell types between early precursor lesions compared to adjacent normal skin but the interaction patterns between them changed drastically which also included signs of immune suppression. This is a very important result as it pushes our search for cancer progression risk signatures further back in evolutionary time and a theme that we believe will be echoed across multiple cancer types as these technologies are more widely applied.
We also found that PDL1 (a well-known immune-suppressive molecule) was expressed by myeloid cells & not tumor cells. By spatial analysis we showed that the interaction between PDL1+ myeloid cells and PD1+ T cells increases with disease progression, highlighting the immunosuppressive role of myeloid cells in melanoma development.
In more advanced invasive stages of the disease, we were able to identify several spatially restricted tumor cell states primarily driven by proximity to immune cells. These observations support an emerging framework in cancer science that tumor heterogeneity is not primarily driven by genetic mutations, but rather by epigenetic changes that occur in cancer cells because of their interactions with normal cells in the surrounding environment. This is an important finding because the degree and type of immune infiltration into a tumor can add substantial complexity to tumor heterogeneity and consequently response to targeted drugs.
Lastly, we also see a highly complex microenvironment at the tumor-stroma interface (where the tumor and immune cells meet) which showed evidence of multiple immune suppressive mechanisms all activated at the same time within a single tumor, highlighting that cancer does not just rely on one mechanism for immune evasion.
MedicalResearch.com: What should readers take away from your report?
Response: From a technical perspective, we have developed several computational methods that allow researchers to study the spatial relationships between cells and signaling between them at scale and we have made all of these tools freely available to the public (Image processing: https://mcmicro.org; Spatial analysis toolkit: https://scimap.xyz). With the manuscript, we are also releasing the largest imaging-based melanoma dataset to date—and the entire dataset is also made freely available (https://www.tissue-atlas.org/atlas-datasets/nirmal-maliga-vallius-2021/).
From a biological standpoint, we are beginning to realize that the heterogeneous nature of the tumor that we have long observed could also be microenvironment-driven in addition to genetic mutations. The microenvironment does not just provide nutrients for the tumor to grow but also creates a favorable environment for the tumor to survive by very locally suppressing the immune system. Depending on the microenvironment cancer cells in various parts of the tumor can be markedly different and hence targeting them with a single or even a few different combinations of drugs may not be sufficient.
MedicalResearch.com: What recommendations do you have for future research as a result of this work?
Response: We have released a rich dataset with this manuscript, when further mined with advanced computer vision techniques, this data could tell us a lot more about the progression of melanoma and maybe even whether a tumor will metastasize. Further development of these technologies can have enormous potential for personalized medicine that goes beyond the conventional tumor-centric drug targeting but rather by considering cancer as a systemic disease where we target the tumor eco-system as a whole. Our data also justifies expanding conventional pathology practices of H&E or single-marker IHC to broader multiplexed panels that could help determine how the tumor evolution is monitored over time and provide insight into what treatment cocktail might best fit a patient to target the entire tumor eco-system.
MedicalResearch.com: Is there anything else you would like to add?
Response: We have built visualization software providing a simple way for users to interact with the data. I highly recommend browsing through it (https://labsyspharm.github.io/HTA-MELATLAS-1/stories/MEL1-full-story.html). You can also read the full manuscript here:
(https://doi.org/10.1158/2159-8290.CD-21-1357)
Citation:
Ajit J. Nirmal, Zoltan Maliga, Tuulia Vallius, Brian Quattrochi, Alyce A. Chen, Connor A. Jacobson, Roxanne J. Pelletier, Clarence Yapp, Raquel Arias-Camison, Yu-An Chen, Christine G. Lian, George F. Murphy, Sandro Santagata, Peter K. Sorger; The spatial landscape of progression and immunoediting in primary melanoma at single cell resolution. Cancer Discov 2022; candisc.1357.2021. https://doi.org/10.1158/2159-8290.CD-21-1357
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Last Updated on April 18, 2022 by Marie Benz MD FAAD