Solid tumors have a dynamic ecosystem in which malignant and non-malignant (endothelial, stromal, and immune) cell types constantly interact. Importantly, the abundance, localization, and functional orientation of each cell component within the tumor microenvironment vary significantly over time and in response to treatment. Such intratumoral heterogeneity influences the tumor course and its sensitivity to treatments. Recently, high-dimensional imaging mass cytometry (IMC) has been developed to explore the tumor ecosystem at the single-cell level. In the last years, several studies demonstrated that IMC is a powerful tool to decipher the tumor complexity. In this review, we summarize the potential of this technology and how it may be useful for cancer research (from preclinical to clinical studies).
Currently, the study of resistance mechanisms and disease progression in cancer relies on the capacity to analyze tumors as a complex ecosystem of healthy and malignant cells. Therefore, one of the current challenges is to decipher the intra-tumor heterogeneity and especially the spatial distribution and interactions of the different cellular actors within the tumor. Preclinical mouse models are widely used to extend our understanding of the tumor microenvironment (TME). Such models are becoming more sophisticated and allow investigating questions that cannot be addressed in clinical studies. Indeed, besides studying the tumor cell interactions within their environment, mouse models allow evaluating the efficacy of new drugs and delivery approaches, treatment posology, and toxicity. Spatially resolved analyses of the intra-tumor heterogeneity require global approaches to identify and localize a large number of different cell types. For this purpose, imaging mass cytometry (IMC) is a major asset in the field of human immuno-oncology. However, the paucity of validated IMC panels to study TME in pre-clinical mouse models remains a critical obstacle to translational or basic research in oncology. Here, we validated a panel of 31 markers for studying at the single-cell level the TME and the immune landscape for discovering/characterizing cells with complex phenotypes and the interactions shaping the tumor ecosystem in mouse models.
BackgroundImaging mass cytometry (IMC) is a high-plex imaging technique that incorporates flow cytometry principles while preserving the histological and architectural components of the tissue sample. Characterizing the entire cellular component of temporal artery (TA) in patients with giant cell arteritis (GCA) may provide clues towards novel diagnostic and therapeutic approaches.ObjectivesWe aimed at a comprehensive summary of the immune cells and pathways involved GCA by using IMC approach.MethodsTA samples from biopsy-proven GCA patients (n=2) and controls (CTLs, n=2) were analyzed using IMC with a panel of 15 staining antibodies.ResultsEleven cell populations were identified in arterial wall from GCA patients including both immune (CD20+ B cells, CD8+ T cells, CD4+ T cells, FOXP3+ Tregs, CD66b+ granulocytes, CD11b+ myeloid cells, CD14+ monocytes, CD68+ macrophages) and non-immune (aSMA+ smooth muscle cells, CD31+ endothelial cells, Vimentin+ fibroblasts) cells (Figure 1). The 3 layers (intima, media and adventitia) of the arterial wall was enriched by all the immune cell subsets in GCA except for granulocytes and myeloid cells. CD8+, CD4+ and FOXP3+ regulatory T cells were significantly increased in any layer of the TA. The proportion of B cells was also enhanced in both intima and adventitia and displayed a high level of Ki67 expression.Figure 1.Unbiased clustering of cellular infiltrate in temporal arteritis using Imaging Mass Cytometry.Heatmap of different cell type markers expressed by the 11 cell populations identified in the arterial wall of GCA patients: CD20+ B cells, CD8+ T cells, CD4+ T cells, FOXP3+ Tregs, CD66b+ granulocytes, CD11b+ myeloid cells, CD14+ monocytes, CD68+ macrophages, Vimentin+ fibroblasts, aSMA+ smooth muscle cells and CD31+ endothelial cells. A population of unidentified cells is also represented (A). Donut chart representing the relative composition of immune cells in the arterial wall of GCA patients (B). tSNE dimensional plots of the different cell clusters identified in the arterial wall of CTL and GCA patients (C). Percent and Heatmap of immune cells identified in the arterial wall of each patient (D).GCA: giant cell arteritis, CTL: controls, Tregs: regulatory T cells.ConclusionOur study provides an exhaustive overview of the distinct cell lineages involved in GCA and supports IMC approach to further characterize the immune networks active in GCA.Disclosure of InterestsNone declared
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