Probes for CD68

Patients with peripheral nerve injury, viral infection or metabolic disorder often suffer neuropathic pain due to inadequate pharmacological options for relief. Developing novel therapies has been challenged by incomplete mechanistic understanding of the cellular microenvironment in sensory nerve that trigger the emergence and persistence of pain. In this study, we report a high resolution transcriptomics map of the cellular heterogeneity of naïve and injured rat sensory nerve covering more than 110,000 individual cells. Annotation reveals distinguishing molecular features of multiple major cell types totaling 45 different subtypes in naïve nerve and an additional 23 subtypes emerging after injury. Ligand-receptor analysis revealed a myriad of potential targets for pharmacological intervention. This work forms a comprehensive resource and unprecedented window into the cellular milieu underlying neuropathic pain and demonstrates that nerve injury is a dynamic process orchestrated by multiple cell types in both the endoneurial and epineurial nerve compartments.

Diffuse Large B-Cell Lymphoma (DLBCL) presents a high clinical and biological heterogeneity, and the tumor microenvironment chracteristics are important in its  progression. The aim of this study was to evaluate tumor T, B cells, macrophages and mast cells distribution in GBC and ABC DLBCL subgroups through a set of morphometric parameters allowing to provide a quantitative evaluation of the morphological features of the spatial patterns generated by these inflammatory cells.   Histological ABC and GCB samples were immunostained for CD4, CD8, CD68, CD 163, and tryptase in order to determine both percentage and position of positive cells in the tissue characterizing their spatial distribution. The results evidenced that cell patterns generated by CD4-, CD8-, CD68-, CD163- and tryptase-positive cell profiles exhibited a significantly higher uniformity index in ABC than in GCB subgroup. The positive-cell distributions appeared clustered in tissues from GCB, while in tissues from ABC such a feature was lower or absent. The combinations of spatial statistics-derived parameters can lead to better predictions of tumor cell infiltration than any classical morphometric method providing a more accurate description of the functional status of the tumor, useful for patient prognosis.

Complex tissues such as tumors are comprised of multiple cells types and extracellular matrix. These cells include heterogenous populations of immune cells that infiltrate the tumors. Understanding the composition of these immune infiltrates in the tumor microenvironment (TME) can provide key insights to guide therapeutic intervention and predict treatment response. Thorough understanding of complex tissue dynamics and immune cell characterization requires a multi-omics approach. Simultaneous detection of RNA and protein using in situ hybridization (ISH) and immunohistochemistry/immunofluorescence (IHC/IF) can reveal cellular sources of secreted proteins, identify specific cell types, and visualize the spatial organization of cells within the tissue. However, a sequential workflow of ISH followed by IHC/IF frequently yields suboptimal protein detection because the protease digestion step in the ISH protocol resulting in poor antibody signal. Here we demonstrate a newly developed integrated ISH/IHC workflow that can substantially improve RNA-protein co-detection, enabling the visualization and characterization of tumor immune infiltrates at single-cell resolution with spatial and morphological context. To characterize tumor-infiltrating immune cells in a tumor TMA (tumor microarray), we utilized the RNAscope Multiplex Fluorescence assay in combination with the RNA-Protein Co-detection Kit to detect multiple immune cell populations. Immune cells such as macrophages, T cells and NK cells were detected using specific antibodies against CD68, CD8, CD4 and CD56, respectively. Precise characterization of these immune cells was achieved by using probes against targets such as CCL5, IFNG, GNZB, IL-12, NCR1 etc. that not only help in identifying specific immune cells but also assist in determining their activation states. We identified subsets of T cells such as CD4+ regulatory T cells and CD8+ cytotoxic T lymphocytes. Additionally, we were able to determine the activation states of CD8+ T cells by visualizing the expression of IFNG and GZMB. Furthermore, infiltrating macrophages were identified by detecting the CD68 protein expression while the M1 and M2 subsets were differentiated by detecting the M2-specific target RNA for CD163. Similarly, NK cells were identified by detecting CD56 protein in combination with CCL5 and NCR1 RNA expression. Interestingly, the degree of infiltration of the different immune cell populations varied based on the tumor type. In conclusion, the new RNAscope-ISH-IHC co-detection workflow and reagents enable optimized simultaneous visualization of RNA and protein targets by enhancing the compatibility of antibodies - including many previously incompatible antibodies - with RNAscope. This new workflow provides a powerful new approach to identifying and characterizing tumor infiltrating populations of immune cells.