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Magrill J, Moldoveanu D, Gu J, Lajoie M, Watson IR. Mapping the single cell spatial immune landscapes of the melanoma microenvironment. Clin Exp Metastasis 2024; 41:301-312. [PMID: 38217840 PMCID: PMC11374855 DOI: 10.1007/s10585-023-10252-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Accepted: 11/27/2023] [Indexed: 01/15/2024]
Abstract
Melanoma is a highly immunogenic malignancy with an elevated mutational burden, diffuse lymphocytic infiltration, and one of the highest response rates to immune checkpoint inhibitors (ICIs). However, over half of all late-stage patients treated with ICIs will either not respond or develop progressive disease. Spatial imaging technologies are being increasingly used to study the melanoma tumor microenvironment (TME). The goal of such studies is to understand the complex interplay between the stroma, melanoma cells, and immune cell-types as well as their association with treatment response. Investigators seeking a better understanding of the role of cell location within the TME and the importance of spatial expression of biomarkers are increasingly turning to highly multiplexed imaging approaches to more accurately measure immune infiltration as well as to quantify receptor-ligand interactions (such as PD-1 and PD-L1) and cell-cell contacts. CyTOF-IMC (Cytometry by Time of Flight - Imaging Mass Cytometry) has enabled high-dimensional profiling of melanomas, allowing researchers to identify complex cellular subpopulations and immune cell interactions with unprecedented resolution. Other spatial imaging technologies, such as multiplexed immunofluorescence and spatial transcriptomics, have revealed distinct patterns of immune cell infiltration, highlighting the importance of spatial relationships, and their impact in modulating immunotherapy responses. Overall, spatial imaging technologies are just beginning to transform our understanding of melanoma biology, providing new avenues for biomarker discovery and therapeutic development. These technologies hold great promise for advancing personalized medicine to improve patient outcomes in melanoma and other solid malignancies.
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Affiliation(s)
- Jamie Magrill
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Dan Moldoveanu
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Jiayao Gu
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Mathieu Lajoie
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada
| | - Ian R Watson
- Rosalind and Morris Goodman Cancer Institute, McGill University, Montréal, QC, Canada.
- Department of Human Genetics, McGill University, Montréal, QC, Canada.
- Department of Biochemistry, McGill University, Montréal, QC, Canada.
- Research Institute of the McGill University Health Centre, Montréal, QC, Canada.
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Suman S, Nevala WK, Leontovich AA, Ward C, Jakub JW, Kim Y, Geng L, Stueven NA, Atherton CL, Moore RM, Schimke JM, Lucien-Matteoni F, McLaughlin SA, Markovic SN. Melanoma-Derived Extracellular Vesicles Induce CD36-Mediated Pre-Metastatic Niche. Biomolecules 2024; 14:837. [PMID: 39062552 PMCID: PMC11275097 DOI: 10.3390/biom14070837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 06/25/2024] [Accepted: 07/08/2024] [Indexed: 07/28/2024] Open
Abstract
CD36 expression in both immune and non-immune cells is known to be directly involved in cancer metastasis. Extracellular vesicles (EVs) secreted by malignant melanocytes play a vital role in developing tumor-promoting microenvironments, but it is unclear whether this is mediated through CD36. To understand the role of CD36 in melanoma, we first analyzed the SKCM dataset for clinical prognosis, evaluated the percentage of CD36 in lymphatic fluid-derived EVs (LEVs), and tested whether melanoma-derived EVs increase CD36 expression and induce M2-macrophage-like characteristics. Furthermore, we performed a multiplex immunofluorescence (MxIF) imaging analysis to evaluate the CD36 expression and its colocalization with various other cells in the lymph node (LN) of patients and control subjects. Our findings show that cutaneous melanoma patients have a worse clinical prognosis with high CD36 levels, and a higher percentage of CD36 in total LEVs were found at baseline in melanoma patients compared to control. We also found that monocytic and endothelial cells treated with melanoma EVs expressed more CD36 than untreated cells. Furthermore, melanoma-derived EVs can regulate immunosuppressive macrophage-like characteristics by upregulating CD36. The spatial imaging data show that cells in tumor-involved sentinel LNs exhibit a higher probability of CD36 expression than cells from control LNs, but this was not statistically significant. Conclusively, our findings demonstrated that CD36 plays a vital role in controlling the immunosuppressive microenvironment in the LN, which can promote the formation of a protumorigenic niche.
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Affiliation(s)
- Shankar Suman
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Wendy K. Nevala
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Alexey A. Leontovich
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Caitlin Ward
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN 55455, USA
| | - James W. Jakub
- Department of Surgery, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Yohan Kim
- Department of Urology, Mayo Clinic, Rochester, MN 55905, USA
| | - Liyi Geng
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Noah A. Stueven
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Raymond M. Moore
- Department of Computational Biology, Mayo Clinic, Rochester, MN 55905, USA
| | - Jill M. Schimke
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
| | - Fabrice Lucien-Matteoni
- Department of Urology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Immunology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Svetomir N. Markovic
- Department of Oncology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Immunology, Mayo Clinic, Rochester, MN 55905, USA
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Suman S, Markovic SN. Melanoma-derived mediators can foster the premetastatic niche: crossroad to lymphatic metastasis. Trends Immunol 2023; 44:724-743. [PMID: 37573226 PMCID: PMC10528107 DOI: 10.1016/j.it.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 08/14/2023]
Abstract
The natural history of advanced malignant melanoma demonstrates that, in most cases, widespread tumor dissemination is preceded by regional metastases involving tumor-draining lymph nodes [sentinel lymph nodes (SLNs)]. Under physiological conditions, LNs play a central role in immunosurveillance to non-self-antigens to which they are exposed via afferent lymph. The dysfunctional immunity in SLNs is mediated by tumor secretory factors that allow the survival of metastatic melanoma cells within the LN by creating a premetastatic niche (PMN). Recent studies outline the altered microenvironment of LNs shaped by melanoma mediators. Here, we discuss tumor secretory factors involved in subverting tumor immunity and remodeling LNs and highlight emerging therapeutic strategies to reinvigorate antitumoral immunity in SLNs.
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Affiliation(s)
- Shankar Suman
- Department of Oncology, Mayo Clinic, Rochester, MN, USA
| | - Svetomir N Markovic
- Department of Oncology, Mayo Clinic, Rochester, MN, USA; Mayo Clinic Cancer Center, Mayo Clinic, Rochester, MN, USA.
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Jiang J, Moore R, Jordan CE, Guo R, Maus RL, Liu H, Goode E, Markovic SN, Wang C. Multiplex Immunofluorescence Image Quality Checking Using DAPI Channel-referenced Evaluation. J Histochem Cytochem 2023; 71:121-130. [PMID: 36960831 PMCID: PMC10084566 DOI: 10.1369/00221554231161693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 02/14/2023] [Indexed: 03/25/2023] Open
Abstract
Multiplex immunofluorescence (MxIF) images provide detailed information of cell composition and spatial context for biomedical research. However, compromised data quality could lead to research biases. Comprehensive image quality checking (QC) is essential for reliable downstream analysis. As a reliable and specific staining of cell nuclei, 4',6-diamidino-2-phenylindole (DAPI) signals were used as references for tissue localization and auto-focusing across MxIF staining-scanning-bleaching iterations and could potentially be reused for QC. To confirm the feasibility of using DAPI as QC reference, pixel-level DAPI values were extracted to calculate signal fluctuations and tissue content similarities in staining-scanning-bleaching iterations for identifying quality issues. Concordance between automatic quantification and human experts' annotations were evaluated on a data set consisting of 348 fields of view (FOVs) with 45 immune and tumor cell markers. Cell distribution differences between subsets of QC-pass vs QC-failed FOVs were compared to investigate the downstream effects. Results showed that 87.3% FOVs with tissue damage and 73.4% of artifacts were identified. QC-failed FOVs showed elevated regional gathering in cellular feature space compared with the QC-pass FOVs. Our results supported that DAPI signals could be used as references for MxIF image QC, and low-quality FOVs identified by our method must be cautiously considered for downstream analyses.
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Affiliation(s)
- Jun Jiang
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Raymond Moore
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Clarissa E. Jordan
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Ruifeng Guo
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
| | - Rachel L. Maus
- Department of Oncology, Mayo Clinic, Rochester, Minnesota
| | - Hongfang Liu
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Ellen Goode
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | | | - Chen Wang
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
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