Imaging MC Session

Department of Neurosurgery, Medical Center University of Freiburg

Transitioning spatially resolved multi-omics into clinical application
Advancements in single cell genomics have led to improved understanding of cellular plasticity and evolution in gliomas over the course of the disease. However, the reorganization of the tumor architecture and cellular interactions within the tumor microenvironment remains elusive. To address this knowledge gap, we employed spatially resolved multi-omic technologies on glioma specimens from various treatment modalities and timepoints. Our efforts have resulted in a map of longitudinal architectural reformation in glioblastoma, which offers insight into the molecular mechanisms responsible for therapy resistance. Post-standard treatment, only minor shared modifications of the spatial architecture was found after adjusting for confounders such as sample collection region and histology. However, significant inter-patient heterogeneity was noted, including many unique transcriptional programs observed in recurrent samples. Exploration of spatial genomic and metabolic alterations identified hypoxic-driven adaptations in distinct niches as a source for the development of resistant subclones. After immunotherapy, we found significant re-education of the microenvironment, leading to anti-inflammatory responses from myeloid cells and the accumulation of regulatory T cells, resulting in CD8 dysfunction. By integrating spatial transcriptomics, imaging, and clinical parameters into graph-based convolutional neural networks with contextual learning strategies, we identified recurrent patterns that can forecast transcriptional responses to treatment, derived from the de-novo tumor architecture. The spatial perspective on glioma evolution through descriptive and predictive models will enhance accuracy of the decision-making process in precision oncology in the future. 

Biosketch
Henrik Heiland is a Neurosurgical Scientist affiliated with the Medical Center Freiburg and Northwestern University. His research expertise lies in analyzing spatially resolved multi-omic data and developing in-silico models for complex systems. During his PhD and postdoctoral work, Heiland focused on understanding the epigenetic regulation of brain tumors and its influence on transcriptional variability. His studies also encompassed innovative approaches to predict transcriptional diversity using radio-genomic and metabolic imaging. Currently, he leads the “Microenvironment and Immunology Research Laboratory,” where his team is dedicated to unraveling cellular states and tissue structures. Their goal is to map transcriptional diversity within spatial contexts and explore potential clinical applications of these findings.

Medical Department (Gastroenterology, Infectious Diseases, Rheumatology) Campus Benjamin Franklin, Charité – Universitätsmedizin Berlin

Mass cytometry-based immune profiling of human peyer’s patches in Crohn’s disease

Inflammatory bowel diseases (IBD) such as Crohn’s disease (CD), are characterized by chronic inflammation of the intestinal tract. Peyer’s patches, as specialized lymphoid follicles located in the terminal ileum, play a crucial role in the development of oral tolerance due to a constant exposition to environmental factors like microbial or food antigens. Murine data indicate an activation and subsequent apoptosis of food-reactive CD4⁺ T-cells thus maintaining the healthy balance of the mucosal immune system. In IBD, this homeostasis is disturbed, which could drive the course of the disease. To investigate the immune cell composition of PP in healthy individuals and CD patients, we collected human biopsies of a prospective patient cohort and performed multiplexed mass and flow cytometry for deep immunophenotyping on single cell suspensions. To further evaluate the spatial distribution and cellular interactions of these subsets, we used imaging mass cytometry (IMC) on FFPE samples. Using flow cytometry analysis, we could show a reduction of activated B cells and an increase of CD8⁺ effector memory T Cells in active Crohn’s disease. For CD4⁺ T-cells, total numbers were similar, but CD patients showed an increase of central memory and a reduction of effector memory T-cells. Furthermore, CD4⁺ T-cells of CD patients in PP revealed a significantly reduced apoptotic rate compared to healthy controls. As the IMC data of lymphoid follicles such as PPs presented several challenges regarding their highly condensed cellular structure, several improvements had to be implemented into our analysis pipeline including cell segmentation, cell type identification and sample integration. Using an IMC analysis pipeline optimized towards the specific features of lymphoid follicles, we were able to resolve differences in immune cell densities as well as immune cell interactions between Crohn’s disease patients and healthy individuals but also between different tissue areas like lymphoid follicle vs lamina propria.

Leiden University Medical Center

Integration of Mass Cytometry and Mass Spectrometry Imaging for Spatially Resolved Single Cell Metabolic Profiling

Spatial omics technologies have paved the road for in-depth characterisation of the tumour microenvironment. Spatial proteomics achieves the assessment of cell types in situ using, among others, imaging mass cytometry, allowing the visualization of over 40 cellular markers at single cell resolution. Complementary to visualizing where cells are located in a tissue, characterizing their metabolic profile is of tremendous value to understand their function. Metabolism is an essential aspect, both in homeostasis and pathogenesis, and current approaches to investigate them are either limited by loss of spatial context, when using single cell approaches, or the limited resolution of imaging mass spectrometry.

We overcame these limitations by developing a novel multimodal imaging approach for the analysis of metabolites at single cell resolution in situ. This was achieved by integrating the experimental workflows of spatial metabolomics using MALDI-MSI and spatial immunophenotyping using Imaging mass cytometry (IMC). Our optimized wet-lab and data integration strategy allows the application of both techniques on a single tissue section and thus the quantification and localization of metabolites (MALDI-MSI) at single cell level (IMC).

We applied our workflow to three CRC tumour samples, performed co-registration of the MALDI-MSI and IMC images and inferred the metabolic profiles of each cell type identified by IMC. This approach allowed the determination of metabolic profiles distinct for cancer cells or the stromal compartment. Furthermore, our IMC analysis revealed six different macrophage populations and clustering these by their metabolic profiles revealed that different metabolic patterns can be distinguished between macrophages, but independent of the IMC assigned phenotypes, which may provide us with new insights into macrophage function.

Overall, our multimodal imaging and analysis approach enables the evaluation of metabolites at the single-cell resolution and emphasizes the presence of differences in metabolite abundance both between and within cellular phenotypes. Furthermore, by utilizing one tissue section for both techniques, the methodology is not hampered by differences between consecutive sections. This approach has the potential to be invaluable for, but not limited to, cancer immunology where the metabolism of immune cells is of great importance and can make or break the efficiency of immunotherapy.