Spatial biology pursues the analysis of cells in their native microenvironment, often with regard to morphology and gene- or protein expression. The spatial analysis of lipid and metabolic profiles by matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can add another layer of molecular information. A seamless integration of MSI data with other (multimodal) methods at a single-cell level is often hampered by insufficient co-registration and resolution. Here, we introduce a MALDI-MSI based method that integrates in-source bright-field and fluorescence microscopy, allowing for a coupled (sub-)cellular investigation of the same sample in both modalities. Presented examples from cell culture and tissue analysis include the visualization of intracellular lipid distributions in macrophages during phagocytosis, and the heterogeneity of lipid profiles of tumor infiltrating neutrophils correlated to their individual microenvironments. The achieved combination of lipid profiling with morphological features and protein expression on the single-cell level constitutes a powerful method for cell biology.

Background The inflammatory tumor microenvironment (TME) is formed by various immune cells, being closely associated with tumorigenesis. Especially, the interaction between tumor-infiltrating T-cells and macrophages has a crucial impact on tumor progression and metastatic spread. The purpose of this study was to investigate whether oscillating-gradient diffusion-weighted MRI (OGSE-DWI) enables a cell size-based discrimination between different cell populations of the TME. Methods Sine-shaped OGSE-DWI was combined with the Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion (IMPULSED) approach to measure microscale diffusion distances, here relating to cell sizes. The accuracy of IMPULSED-derived cell radii was evaluated using in vitro spheroid models, consisting of either pure cancer cells, macrophages, or T-cells. Subsequently, in vivo experiments aimed to assess changes within the TME and its specific immune cell composition in syngeneic murine breast cancer models with divergent degrees of malignancy (4T1, 67NR) during tumor progression, clodronate liposome-mediated depletion of macrophages, and immune checkpoint inhibitor (ICI) treatment. Ex vivo analysis of IMPULSED-derived cell radii was conducted by immunohistochemical wheat germ agglutinin staining of cell membranes, while intratumoral immune cell composition was analyzed by CD3 and F4/80 co-staining. Results OGSE-DWI detected mean cell radii of 8.8±1.3 µm for 4T1, 8.2±1.4 µm for 67NR, 13.0±1.7 for macrophage, and 3.8±1.8 µm for T-cell spheroids. While T-cell infiltration during progression of 4T1 tumors was observed by decreasing mean cell radii from 9.7±1.0 to 5.0±1.5 µm, increasing amount of intratumoral macrophages during progression of 67NR tumors resulted in increasing mean cell radii from 8.9±1.2 to 12.5±1.1 µm. After macrophage depletion, mean cell radii decreased from 6.3±1.7 to 4.4±0.5 µm. T-cell infiltration after ICI treatment was captured by decreasing mean cell radii in both tumor models, with more pronounced effects in the 67NR tumor model. Conclusions OGSE-DWI provides a versatile tool for non-invasive profiling of the inflammatory TME by assessing the dominating cell type T-cells or macrophages.

Background: With metabolic alterations of the tumor microenvironment (TME) contributing to cancer progression, metastatic spread and response to targeted therapies, non-invasive and repetitive imaging of tumor metabolism is of major importance. The purpose of this study was to investigate whether multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST-MRI) allows to detect differences in the metabolic profiles of the TME in murine breast cancer models with divergent degrees of malignancy and to assess their response to immunotherapy. Methods: Tumor characteristics of highly malignant 4T1 and low malignant 67NR murine breast cancer models were investigated, and their changes during tumor progression and immune checkpoint inhibitor (ICI) treatment were evaluated. For simultaneous analysis of different metabolites, multiparametric CEST-MRI with calculation of asymmetric magnetization transfer ratio (MTR_asym) at 1.2 to 2.0 ppm for glucose-weighted, 2.0 ppm for creatine-weighted and 3.2 to 3.6 ppm for amide proton transfer- (APT-) weighted CEST contrast was conducted. Ex vivo validation of MRI results was achieved by ¹H nuclear magnetic resonance spectroscopy, matrix-assisted laser desorption/ionization mass spectrometry imaging with laser postionization and immunohistochemistry. Results: During tumor progression, the two tumor models showed divergent trends for all examined CEST contrasts: While glucose- and APT-weighted CEST contrast decreased and creatine-weighted CEST contrast increased over time in the 4T1 model, 67NR tumors exhibited increased glucose- and APT-weighted CEST contrast during disease progression, accompanied by decreased creatine-weighted CEST contrast. Already three days after treatment initiation, CEST contrasts captured response to ICI therapy in both tumor models. Conclusion: Multiparametric CEST-MRI enables non-invasive assessment of metabolic signatures of the TME, allowing both for estimation of the degree of tumor malignancy and for assessment of early response to immune checkpoint inhibition.

Background: Response assessment of targeted cancer therapies is becoming increasingly challenging, as it is not adequately assessable with conventional morphological and volumetric analyses of tumor lesions. The tumor microenvironment is particularly constituted by tumor vasculature which is altered by various targeted therapies. The aim of this study was to noninvasively assess changes in tumor perfusion and vessel permeability after targeted therapy in murine models of breast cancer with divergent degrees of malignancy. Methods: Low malignant 67NR or highly malignant 4T1 tumor-bearing mice were treated with either the multi-kinase inhibitor sorafenib or immune checkpoint inhibitors (ICI, combination of anti-PD1 and anti-CTLA4). Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with i.v. injection of albumin-binding gadofosveset was conducted on a 9.4 T small animal MRI. Ex vivo validation of MRI results was achieved by transmission electron microscopy, immunohistochemistry and laser ablation-inductively coupled plasma-mass spectrometry. Results: Therapy-induced changes in tumor vasculature differed between low and highly malignant tumors. Sorafenib treatment led to decreased tumor perfusion and endothelial permeability in low malignant 67NR tumors. In contrast, highly malignant 4T1 tumors demonstrated characteristics of a transient window of vascular normalization with an increase in tumor perfusion and permeability early after therapy initiation, followed by decreased perfusion and permeability parameters. In the low malignant 67NR model, ICI treatment also mediated vessel-stabilizing effects with decreased tumor perfusion and permeability, while ICI-treated 4T1 tumors exhibited increasing tumor perfusion with excessive vascular leakage. Conclusion: DCE-MRI enables noninvasive assessment of early changes in tumor vasculature after targeted therapies, revealing different response patterns between tumors with divergent degrees of malignancy. DCE-derived tumor perfusion and permeability parameters may serve as vascular biomarkers that allow for repetitive examination of response to antiangiogenic treatment or immunotherapy.

A referencing strategy based on the element P is presented to compensate for cryosectioning tissue artifacts in laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) data. The study examines how the gadolinium-based contrast agent Gadofosveset is distributed in murine cancer tissue, and illustrates how referenced images can compensate for tissue artifacts like folds, overlaps, and density variations. Compared to non-referenced images that provide information on the absolute distribution of the analyte, referenced images allow for the representation of the analyte distribution relative to the amount of material introduced into the instrument, which in this case is correlated to the P signal. Tissue artifacts were corrected in referenced images for both Gadofosveset and endogenous elements, such as Fe and Zn. Additionally, the referencing approach provides valuable information on the Gd uptake relative to the tissue density in necrotic compared to vital tumor areas, which is not obtained from in vivo magnetic resonance imaging (MRI) data. However, validation of in vivo MRI and ex vivo LA-ICP-MS methods was possible by establishing a mean ratio of necrotic to vital tumor areas in the T1-weighted image post Gadofosveset injection and the non-referenced LA-ICP-MS image of Gd. In summary, P-based correction of LA-ICP-MS imaging data allows for a more accurate spatial representation of certain elements, including endogenous and exogenous elements such as injected contrast agents.