ABSTRACT
A hallmark of bone marrow changes with aging is the increase in adipocyte composition, but how this impacts development of multiple myeloma (MM) is unknown. Here, we report the role of the adipokine leptin as master regulator of anti-myeloma tumor immunity by modulating the invariant natural killer T (iNKT) cell function. A marked increase in serum leptin levels and leptin receptor (LR) expression on iNKT cells in MM patients and the 5T33 murine MM model was observed. MM cells and leptin synergistically counteracted anti-tumor functionality of both murine and human iNKT cells. In vivo blockade of LR signaling combined with iNKT stimulation resulted in superior anti-tumor protection. This was linked to persistent IFN-γ secretion upon repeated iNKT cell stimulation and a restoration of the dynamic antigen-induced motility arrest as observed by intravital microscopy, thereby showing alleviation of iNKT cell anergy. Overall our data reveal the LR axis as novel therapeutic target for checkpoint inhibition to treat MM.
Subject(s)
Antineoplastic Agents/pharmacology , Multiple Myeloma/metabolism , Natural Killer T-Cells/drug effects , Natural Killer T-Cells/metabolism , Receptors, Leptin/antagonists & inhibitors , Animals , Antibodies, Monoclonal , Cell Line, Tumor , Cell Proliferation/drug effects , Cytokines/biosynthesis , Disease Models, Animal , Galactosylceramides/pharmacology , Humans , Leptin/metabolism , Lymphocyte Activation/drug effects , Lymphocyte Activation/immunology , Mice , Mice, Knockout , Molecular Targeted Therapy , Multiple Myeloma/drug therapy , Multiple Myeloma/immunology , Natural Killer T-Cells/immunology , Xenograft Model Antitumor AssaysABSTRACT
Glaucomatous optic neuropathies are characterized by progressive loss of retinal ganglion cells (RGCs), the neurons that connect the eye to the brain. Quantification of these RGCs is a cornerstone in experimental optic neuropathy research and commonly performed via manually quantifying parts of the retina. However, this is a time-consuming process subject to inter- and intra-observer variability. Here we present a freely available ImageJ script to semi-automatically quantify RGCs in entire retinal flatmounts after immunostaining for the RGC-specific transcription factor Brn3a. The blob-like signal of Brn3a-immunopositive RGCs is enhanced via eigenvalues of the Hessian matrix and the resulting local maxima are counted as RGCs. After the user has outlined the retinal flatmount area, the total RGC number and retinal area are reported and an isodensity map, showing the RGC density distribution across the retina, is created. The semi-automated quantification shows a very strong correlation (Pearson's r ≥ 0.99) with manual counts for both widefield and confocal images, thereby validating the data generated via the developed script. Moreover, application of this method in established glaucomatous optic neuropathy models such as N-methyl-D-aspartate-induced excitotoxicity, optic nerve crush and laser-induced ocular hypertension revealed RGC loss conform with literature. Compared to manual counting, the described automated quantification method is faster and shows user-independent consistency. Furthermore, as the script detects the RGC number in entire retinal flatmounts, the method allows detection of regional differences in RGC density. As such, it can help advance research investigating the degenerative mechanisms of glaucomatous optic neuropathies and the effectiveness of new neuroprotective treatments. Because the script is flexible and easy to optimize due to a low number of critical parameters, it can potentially be applied in combination with other tissues or alternative labeling protocols.
