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Biology subjects

Yokote, K.

Publications and source records attributed to Yokote, K..

5 recordsLinked to original sources

Myeloid-instructed CD14+CD4+ T cells within the tumor microenvironment are associated with TNFα signaling and prolonged survival in non-small cell lung cancer

The tumor microenvironment (TME) harbors a diverse array of innate and adaptive immune cells that can either support anti-tumor immunity or facilitate tumor progression. Among these, myeloid cells are key drivers of immunosuppression, yet therapeutic strategies targeting their function have achieved limited clinical success. A deeper understanding of the mechanisms by which immunosuppressive myeloid cells promote tumor progression is needed to guide the development of more effective treatments. Using spatial multi-omics analyses, we identified a population of myeloid-instructed CD14+ T cells present in both the tumor core and adjacent non-malignant lung tissue of patients with non-small cell lung cancer (NSCLC). CD4+ T cells acquired CD14 from myeloid cells by trogocytosis, resulting in an atypical T cell phenotype. High infiltration of CD14+CD4+ T cells in the tumor core was associated with poor patient survival. Spatial transcriptomics profiling revealed that tumors enriched in CD14+CD4+ T cells exhibited increased TNF signaling. Functional assays demonstrated that TNF enhanced trogocytosis, promoting the transfer of myeloid membrane components to CD4{square} T cells and driving the accumulation of CD14{square}CD4{square} T cells. These findings uncover a novel TNF-mediated mechanism of immunosuppression in the TME, whereby TNF promotes aberrant myeloid-T cell interactions that may contribute to tumor progression. This work highlights a previously unrecognized axis of innate-adaptive immune crosstalk in NSCLC and suggests that targeting TNF could disrupt this pathway, restore effective T cell function, and improve therapeutic outcomes.

cancer biology↗

Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments

Tumor microenvironments (TMEs) contain vast amounts of information on patients cancer through their cellular composition and the spatial distribution of tumor cells and immune cell populations. Exploring variations in TMEs among patients and cancer types, as well as determining the extent to which this information can predict variables such as patient survival or treatment success with emerging immunotherapies, is of great interest. Moreover, in the face of a large number of potential spatial cell interactions to consider, we often wish to identify specific interactions that are useful in making such predictions. We present an approach to achieve these goals based on summarizing spatial relationships in the TME using spatial K functions, and then applying functional data analysis and random forest models to both predict outcomes of interest and identify important spatial relationships. This approach is shown to be effective in simulation experiments. We further used the proposed approach to interrogate two real data sets of Multiplexed Ion Beam Images of TMEs in triple negative breast cancer and lung cancer patients. The methods proposed are publicly available in a companion R package funkycells. Author summarySpatial data on the tumor microenvironment (TME) are becoming more prevalent. Existing methods to interrogate such data often have several deficiencies: (1) they rely on estimating the spatial relationships among cells by examining simple counts of cells within a single radius, (2) they do not come with ways to evaluate the statistical significance of any findings, or (3) they consider multiple individual interactions resulting in overly optimistic estimates of interaction importances. Our approach, which leverages techniques in spatial statistics and uses a benchmark ensemble machine learning method addresses (1), since the K functions used encode the relative densities of cells over all radii up to a user-selected maximum radius, and (2) we have developed a custom approach based on permutation and cross-validation to evaluate the statistical significance of any findings of significant spatial interactions in the TME, (3) over potentially multiple interactions. Our approach is also freely available with an R implementation called funkycells. In the analysis of two real data sets, we have seen that the method performs well, and gives the expected results. We think this will be a robust tool to add to the toolbox for researchers looking to interrogate, what can be sometimes unwieldy, TME data.

bioinformatics↗

Semaphorin 3G exacerbates joint inflammation through the accumulation and proliferation of macrophages in the synovium

ObjectiveMethotrexate (MTX) is an anchor drug for rheumatoid arthritis (RA) treatment; however, the exact mechanisms by which MTX improves RA activity are still debatable. This study aimed to understand the roles of molecules whose expression is affected by MTX in RA patients and find novel therapeutic targets. MethodsCD4+ T cells from 28 treatment naive RA patients before and 3 months after the initiation of MTX treatment were subjected to DNA microarray analyses. The expression of Semaphorin 3G (Sema3G), as one of the differentially-expressed genes, and its receptor, Neuropilin-2 (Nrp2), was evaluated in RA synovium and collagen-induced arthritis (CIA) synovium. CIA and collagen antibody-induced arthritis (CAIA) were induced in Sema3G-deficient (Sema3G-/-) mice and control mice, and the clinical score, histological score, and serum cytokines were assessed. The migration and proliferation of Sema3G-stimulated bone marrow-derived macrophages (BMMs) were analyzed in vitro. The effect of local Sema3G administration during CAIA on the clinical score and the quantity of infiltrating macrophages was evaluated. ResultsThe expression of Sema3G in CD4+ T cells was downregulated by MTX treatment in RA patients. Sema3G was expressed in RA but not osteoarthritis synovium, and its receptor Nrp2 was mainly expressed on activated macrophages. Sema3G deficiency ameliorated CIA and CAIA. Sema3G stimulation enhanced the migration and proliferation of BMMs. The local administration of Sema3G deteriorated CAIA and increased infiltrating macrophages. ConclusionsUpregulation of Sema3G in RA synovium is a novel mechanism to deteriorate joint inflammation through the accumulation of macrophages. Key messagesSemaphorin 3G is expressed in the inflamed synovium in human and mice. The receptor of Semaphorin 3G is mainly expressed on M1 macrophages. Semaphorin 3G deteriorates inflammatory arthritis through macrophage proliferation and migration.

pathology↗

Immunological features that determine the strength of antibody responses to BNT162b2 mRNA vaccine against SARS-CoV-2

We analyzed peripheral blood mononuclear cells (PBMCs) of each 20 individuals with a high anti-SARS-CoV-2 antibody titer and a low antibody titer out of 1,774 healthcare workers who received BNT162b2 mRNA vaccine. A higher antibody titer was associated with the frequencies of naive and transitional B cells before vaccination. In addition, fold changes in the frequency of activated CD8+ T cells upon vaccination were correlated with the antibody titers.

immunology↗

Stem cell therapy for skin regeneration using mesenchymal stem cells derived from the progeroid Werner syndrome-specific iPS cells

Adult progeria, Werner syndrome (WS), is an autosomal recessive disorder that develops accelerated aging-associated symptoms after puberty. Refractory skin ulcer of limbs, which is one of the symptoms specific to WS, is seriously painful and sometimes results in amputation. In recent years, cell therapy using mesenchymal stem cells (MSCs) has been attracting attention; however, the effect of WS-derived MSCs on skin ulcers is still unclear. In this study, we generated iPS cells from a patient with WS and a normal subject, differentiated them into MSCs (WS- and NM-iMSC, respectively), and performed cell therapy to a refractory skin ulcer mouse model. As a result, WS-iMSC recapitulated premature senescence phenotypes in vitro. Upon subcutaneous injection around the wounds of mice, WS-iMSC was significantly inferior in wound healing effect compared to NM-iMSC. Proteome and transcriptome analysis revealed altered expression of genes related to angiogenesis, inflammation, and proliferation in WS-iMSC with remarkable downregulation of VEGF, a potent angiogenic factor. In addition, simultaneous administration of recombinant human VEGF and WS-iMSC improved the wound healing effect in vivo. These results indicate that the expression of angiogenic factors is reduced in WS-iMSC, and its supplementation restores the wound healing ability. This finding may pave the way to develop the treatment of intractable skin ulcers of WS.

cell biology↗