Localization of mRNAs to dendrites is a fundamental mechanism by which neurons achieve spatiotemporal control of gene expression. Translationally repressed neuronal mRNA transport granules, also referred to as ribonucleoprotein particles (RNPs), have been shown to be trafficked as single or low copy number RNPs and as larger complexes with multiple copies and/or species of mRNAs. However, there is little evidence of either population in intact neuronal circuits. Using single molecule fluorescence in situ hybridization studies in the dendrites of adult rat and mouse hippocampus, we provide evidence that supports the existence of multi-transcript RNPs with the constituents varying in amounts for each RNA species. By competing-off fluorescently labeled probe with serial increases of unlabeled probe, we detected stepwise decreases in Arc RNP number and fluorescence intensity, suggesting Arc RNAs localize to dendrites in both low- and multiple-copy number RNPs. When probing for multiple mRNAs, we find that localized RNPs are heterogeneous in size and colocalization patterns that vary per RNA. Further, localized RNAs that are targeted by the same trans-acting element (FMRP) display greater levels of colocalization compared to an RNA not targeted by FMRP. Simultaneous visualization of a dozen FMRP-targeted mRNA species using highly multiplexed imaging demonstrates that dendritic RNAs are mostly trafficked as heteromeric cargoes of multiple types of RNAs (at least one or more RNAs). Moreover, the composition of these RNA cargoes, as assessed by colocalization, correlates with the abundance of the transcripts even after accounting for the expected differences in colocalization based on expression. Collectively, these results suggest that dendritic RNPs are packaged as heterogeneous co-assemblies of different mRNAs and that RNP contents may be driven, at least partially, by highly abundant dendritic RNAs; a model that favors efficiency over fine-tuned control for sustaining long-distance trafficking of thousands of messenger molecules.

Identifying cell types and states remains a time-consuming, error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data. TACIT uses unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integrating TACIT-identified cell types with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discovered under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

Head and neck squamous cell carcinoma (HNSCC) is one of the most common tumor entities worldwide, with human papillomavirus (HPV) infection contributing to cancer development. Conventional therapies achieve only limited efficiency, especially in recurrent or metastatic HNSCC. As the immune landscape decisively impacts the survival of patients and treatment efficacy, this study comprehensively investigated the immunological tumor microenvironment (TME) and its association with patient outcome, with special focus on several dendritic cell (DC) and T lymphocyte subpopulations. Therefore, formalin-fixed paraffin-embedded tumor samples of 56 HNSCC patients, who have undergone resection and adjuvant radiotherapy, were analyzed by multiplex immunohistochemistry focusing on the detailed phenotypic characterization and spatial distribution of DCs, CD8+ T cells, and T-helper cell subsets in different tumor compartments. Immune cell densities and proportions were correlated with clinical characteristics of the whole HNSCC cohort and different HPV- or hypoxia-associated subcohorts. Tumor stroma was highly infiltrated by plasmacytoid DCs and T lymphocytes. Among the T-helper cells and CD8+ T cells, stromal regulatory T cells and intraepithelial exhausted CD8+ T cells expressing programmed cell death protein-1 (PD-1+) and/or lymphocyte-activation gene-3 (LAG-3+) were the predominant phenotypes, indicating an immunosuppressive TME. HPV-associated tumors showed significantly higher infiltration of type I and type II conventional DCs (cDC1, cDC2) as well as several CD8+ T cell phenotypes including exhausted, activated, and proliferating T cells. On the contrary, tumors with hypoxia-associated gene signatures exhibited reduced infiltration for these immune cells. By multivariate Cox regression, immune-related prognostic factors were identified. Patient clusters defined by high infiltration of DCs and T lymphocytes combined with HPV positivity or low hypoxia showed significantly prolonged survival. Thereby, cDC1 and CD8+ T cells emerged as independent prognostic factors for local and distant recurrence. These results might contribute to the implementation of an immune cell infiltration score predicting HNSCC patients\' survival and such patient stratification might improve the design of future individualized radiochemo-(immuno)therapies.

BACKGROUND: Ultrasound and photoacoustic (US/PA) imaging is a promising tool for in vivo visualization and assessment of drug delivery. However, the acoustic properties of the skull limit the practical application of US/PA imaging in the brain. To address the challenges in targeted drug delivery to the brain and transcranial US/PA imaging, we introduce and evaluate an intracerebral delivery and imaging strategy based on the use of laser-activated perfluorocarbon nanodroplets (PFCnDs).
METHODS: Two specialized PFCnDs were developed to facilitate blood‒brain barrier (BBB) opening and contrast-enhanced US/PA imaging. In mice, PFCnDs were delivered to brain tissue via PFCnD-induced BBB opening to the right side of the brain. In vivo, transcranial US/PA imaging was performed to evaluate the utility of PFCnDs for contrast-enhanced imaging through the skull. Ex vivo, volumetric US/PA imaging was used to characterize the spatial distribution of PFCnDs that entered brain tissue. Immunohistochemical analysis was performed to confirm the spatial extent of BBB opening and the accuracy of the imaging results.
RESULTS: In vivo, transcranial US/PA imaging revealed localized photoacoustic (PA) contrast associated with delivered PFCnDs. In addition, contrast-enhanced ultrasound (CEUS) imaging confirmed the presence of nanodroplets within the same area. Ex vivo, volumetric US/PA imaging revealed PA contrast localized to the area of the brain where PFCnD-induced BBB opening had been performed. Immunohistochemical analysis revealed that the spatial distribution of immunoglobulin (IgG) extravasation into the brain closely matched the imaging results.
CONCLUSIONS: Using our intracerebral delivery and imaging strategy, PFCnDs were successfully delivered to a targeted area of the brain, and they enabled contrast-enhanced US/PA imaging through the skull. Ex vivo imaging, and immunohistochemistry confirmed the accuracy and precision of the approach.

Identifying cell types and states remains a time-consuming and error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data, using unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integration of TACIT-identified cell with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discover under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

BACKGROUND: Previous studies using animal models and cultured cells suggest that vascular smooth muscle cells (SMCs) and inflammatory cytokines are important players in atherogenesis. Validating these findings in human disease is critical to designing therapeutics that target these components. Multiplex imaging is a powerful tool for characterizing cell phenotypes and microenvironments using biobanked human tissue sections. However, this technology has not been applied to human atherosclerotic lesions and needs to first be customized and validated.
RESULTS: For validation, we created an 8-plex imaging panel to distinguish foam cells from SMC and leukocyte origins on tissue sections of early human atherosclerotic lesions (n=9). The spatial distribution and characteristics of these foam cells were further analyzed to test the association between SMC phenotypes and inflammation. Consistent with previous reports using human lesions, multiplex imaging showed that foam cells of SMC origin outnumbered those of leukocyte origin and were enriched in the deep intima, where the lipids accumulate in early atherogenesis. This new technology also found that apoptosis or the expression of pro-inflammatory cytokines were not more associated with foam cells than with nonfoam cells in early human lesions. More CD68+ SMCs were present among SMCs that highly expressed interleukin-1β. Highly inflamed SMCs showed a trend of increased apoptosis, whereas leukocytes expressing similar levels of cytokines were enriched in regions of extracellular matrix remodeling.
CONCLUSIONS: The multiplex imaging method can be applied to biobanked human tissue sections to enable proof-of-concept studies and validate theories based on animal models and cultured cells.

UNASSIGNED: Mitochondrial health has gained attention in a number of diseases, both as an indicator of disease state and as a potential therapeutic target. The quality and amount of mitochondrial DNA (mtDNA) and RNA (mtRNA) can be important indicators of mitochondrial and cell health, but are difficult to measure in complex tissues.
UNASSIGNED: mtDNA and mtRNA in zebrafish retina samples were fluorescently labeled using RNAscope™ in situ hybridization, then mitochondria were stained using immunohistochemistry. Pretreatment with RNase was used for validation. Confocal images were collected and analyzed, and relative amounts of mtDNA and mtRNA were reported. Findings regarding mtDNA were confirmed using qPCR.
UNASSIGNED: Signals from probes detecting mtDNA and mtRNA were localized to mitochondria, and were differentially sensitive to RNase. This labeling strategy allows for quantification of relative mtDNA and mtRNA levels in individual cells. As a demonstration of the method in a complex tissue, single photoreceptors in zebrafish retina were analyzed for mtDNA and mtRNA content. An increase in mtRNA but not mtDNA coincides with proliferation of mitochondria at night in cones. A similar trend was measured in rods.
UNASSIGNED: Mitochondrial gene expression is an important component of cell adaptations to disease, stress, or aging. This method enables the study of mtDNA and mtRNA in single cells of an intact, complex tissue. The protocol presented here uses commercially-available tools, and is adaptable to a range of species and tissue types.

The accurate detection of multiplex collagen biomarkers is vital for diagnosing and treating various critical diseases such as tumors and fibrosis. Despite the attractive optical properties of quantum dots (QDs), it remains technically challenging to create stable and specific QDs-based probes for multiplex biological imaging. We report for the first time the construction of multi-color QDs-based peptide probes for the simultaneous fingerprinting of multiplex collagen biomarkers in connective tissues. A bipeptide system composed of a glutathione (GSH) host peptide and a collagen-targeting guest peptide (CTP) has been developed, yielding CTP-QDs probes that exhibit exceptional luminescence stability when exposed to ultraviolet irradiation and mildly acidic conditions. The versatile bipeptide system allows for facile one-pot synthesis of high-quality multicolor CTP-QDs probes, exhibiting superior selectivity in targeting critical collagen biomarkers including denatured collagen, type I collagen, type II collagen, and type IV collagen. The multicolor CTP-QDs probes have demonstrated remarkable efficacy in simultaneously fingerprinting multiple collagen types in diverse connective tissues, irrespective of their status, whether affected by injury, diseases, or undergoing remodeling processes. The innovative multicolor CTP-QDs probes offer a robust toolkit for the multiplex fingerprinting of the collagen suprafamily, demonstrating significant potential in the diagnosis and treatment of collagen-related diseases.

Imaging platforms for generating highly multiplexed histological images are being continually developed and improved. Significant improvements have also been made in the accuracy of methods for automated cell segmentation and classification. However, less attention has focused on the quantification and analysis of the resulting point clouds, which describe the spatial coordinates of individual cells. We focus here on a particular spatial statistical method, the cross-pair correlation function (cross-PCF), which can identify positive and negative spatial correlation between cells across a range of length scales. However, limitations of the cross-PCF hinder its widespread application to multiplexed histology. For example, it can only consider relations between pairs of cells, and cells must be classified using discrete categorical labels (rather than labeling continuous labels such as stain intensity). In this paper, we present three extensions to the cross-PCF which address these limitations and permit more detailed analysis of multiplex images: topographical correlation maps can visualize local clustering and exclusion between cells; neighbourhood correlation functions can identify colocalization of two or more cell types; and weighted-PCFs describe spatial correlation between points with continuous (rather than discrete) labels. We apply the extended PCFs to synthetic and biological datasets in order to demonstrate the insight that they can generate.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.