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Takeda, D.

Publications and source records attributed to Takeda, D..

2 recordsLinked to original sources

Single-cell RNA sequencing reveals collagen interactions between detached osteoclasts and activated fibroblasts in granulation tissue surrounding sequestra in medication-related osteonecrosis of the jaw

ObjectivesMedication-related osteonecrosis of the jaw (MRONJ) is a rare but serious complication of anti-resorptive agents used for osteoporosis and bone metastasis. As the global population ages, the number of patients with MRONJ continues to rise. Resorptive osteoclasts firmly attached to bone surfaces cannot be detected using single-cell RNA-Seq (scRNA-Seq); however, we hypothesized that multinucleated giant and detached osteoclasts (DetOCs) can be detected by this method. This study aimed to characterize DetOCs with scRNA-seq. Materials and MethodsscRNA-Seq and immunohistochemistry staining was performed on granulation tissues surrounding sequestra from four patients with MRONJ and radicular cysts, a common odontogenic infectious disease with normal bone metabolism. ResultsscRNA-Seq and immunohistochemistry staining revealed that DetOCs were detected exclusively in the granulation tissues of MRONJ. These DetOCs expressed well-known osteoclast markers as well as COL27A1. Subcluster analysis revealed that SPP1+ TREM2+ macrophages differentiated into DetOCs and expressed several types of collagens. Immunostaining confirmed the expression of COL27A1 not only in DetOCs in MRONJ but also in osteoclasts in mandibular cancer. CellChat analysis revealed interactions mediated by collagen signaling pathways between DetOCs, myeloid cells, and activated fibroblasts. ConclusionsWe successfully characterized DetOCs and identified a distinctive microenvironment involving DetOCs and activated fibroblasts in the granulation tissues surrounding sequestra in MRONJ. Clinical RelevanceIdentification of DetOCs and their unique interaction with activated fibroblasts in MRONJ lesions provides novel insight into the pathophysiology of sequestrum formation, suggesting potential therapeutic targets to ameliorate MRONJ.

immunology↗

A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.\n\nHIGHLIGHTSO_LIA new gene expression profiling method, L1000, dramatically lowers cost\nC_LIO_LIThe Connectivity Map database now includes 1.3 million publicly accessible L1000 perturbational profiles\nC_LIO_LIThis expanded Connectivity Map facilitates discovery of small molecule mechanism of action and functional annotation of genetic variants\nC_LIO_LIThe work establishes feasibility and utility of a truly comprehensive Connectivity Map\nC_LI

genomics↗