Osamu Natori
A5013663281- Cancer Immunotherapy and Biomarkers
- Ferroptosis and cancer prognosis
- Immune cells in cancer
- Lymphoma Diagnosis and Treatment
- Immune Cell Function and Interaction
- Cell Adhesion Molecules Research
- Cytokine Signaling Pathways and Interactions
- Immunotherapy and Immune Responses
- interferon and immune responses
- T-cell and B-cell Immunology
- Cancer Genomics and Diagnostics
- Atherosclerosis and Cardiovascular Diseases
- Monoclonal and Polyclonal Antibodies Research
- Acute Myeloid Leukemia Research
- Cancer Cells and Metastasis
- Chronic Lymphocytic Leukemia Research
- Radiopharmaceutical Chemistry and Applications
- Oxidative Organic Chemistry Reactions
- Synthesis and Reactivity of Sulfur-Containing Compounds
- Liver physiology and pathology
- Protein purification and stability
- Molecular Biology Techniques and Applications
- Cancer-related molecular mechanisms research
- Glycosylation and Glycoproteins Research
- Proteoglycans and glycosaminoglycans research
Yokohama University of Pharmacy
2018
The cancer stem cell (CSC) concept has been proposed as an attractive theory to explain development, and CSCs themselves have considered targets for the development of diagnostics therapeutics. However, many unanswered questions concerning existence slow cycling/quiescent, drug-resistant remain. Here we report establishment colon CSC lines, interconversion between a proliferating state, reconstitution tumor hierarchy from CSCs. Stable lines having properties were established human after...
Abstract Background : The precise mechanism governing the generation of haematopoietic stem cells still remains to be understood, partly because molecules required for early haematopoiesis have not fully been identified. Results We identified a novel gene expressed in embryonic tissues, designated ELYS (for large molecule derived from yolk sac), which has no significant homology with any other known molecules. Based on cDNA sequence, mouse protein is composed 2243 amino acid residues and...
Abstract Overcoming resistance to immune checkpoint inhibitors is an important issue in patients with non‐small‐cell lung cancer (NSCLC). Transcriptome analysis shows that adenocarcinoma can be divided into three molecular subtypes: terminal respiratory unit (TRU), proximal proliferative (PP), and inflammatory (PI), squamous cell carcinoma (LUSQ) four. However, the immunological characteristics of these subtypes are not fully understood. In this study, we investigated landscape NSCLC tissues...
Resistance to immune checkpoint blockade remains challenging in patients with non-small cell lung cancer (NSCLC). Tumor-infiltrating leukocyte (TIL) quantity, composition, and activation status profoundly influence responsiveness immunotherapy. This study examined the landscape NSCLC tumor microenvironment by analyzing TIL profiles of 281 fresh resected tissues. Unsupervised clustering based on numbers percentages 30 types classified adenocarcinoma (LUAD) squamous carcinoma (LUSQ) into cold,...
Tumor nests in lung squamous cell carcinoma (LUSC) have a hierarchical structure resembling epithelium. The consist of basal-like cells on the periphery and layers keratinocyte-like that differentiate towards center nest, forming keratin pearls. Reproducing this spatial heterogeneity vitro models would be useful for understanding biology LUSC. Here, we established three-dimensional (3D) culture model with epithelial using LUSC lines PLR327F-LD41 MCC001F, in-house. When were cultured mixture...
Assessing how gene expression analysis by RNA sequencing (RNA-Seq) correlates to a unique morphology is increasingly necessary, and laser capture microdissection (LCM) critical research tool for discovering the genes responsible in region of interest (ROI). Because RNA-Seq requires high-quality RNA, sample preparation procedure that can preserve give required quality essential. A PAXgene®-fixed paraffin-embedded (XFPE) block satisfy need but there are few reports on adapting method LCM, such...
<p>Percentage of PD-1+ CD8 T+ and PD-L1+ cells in respective immune subtypes. (a, b) Data were presented as a percentage (a) (b) per indicated CD8+ T cell subset LUAD LUSQ. % naïve CD8; or total cells. CM EM EMRA ns; not significant. * p<0.05. **P<0.01.</p>
<p>Percentage of PD-1+ CD8 T+ and PD-L1+ cells in respective immune subtypes. (a, b) Data were presented as a percentage (a) (b) per indicated CD8+ T cell subset LUAD LUSQ. % naïve CD8; or total cells. CM EM EMRA ns; not significant. * p<0.05. **P<0.01.</p>
<p>Antibodies for IHC</p>
<div><p>Resistance to immune checkpoint blockade remains challenging in patients with non–small cell lung cancer (NSCLC). Tumor-infiltrating leukocyte (TIL) quantity, composition, and activation status profoundly influence responsiveness immunotherapy. This study examined the landscape NSCLC tumor microenvironment by analyzing TIL profiles of 281 fresh resected tissues. Unsupervised clustering based on numbers percentages 30 types classified adenocarcinoma (LUAD) squamous...
<p>Activated and suppressed pathways identified by GSEA with GO gene set in respective immune subtypes. (a, b) Heatmap representing top scored enriched genes showing commonly increased decreased expression subtypes LUAD (a) LUSQ (b). Top signaling for are presented red those blue. (c, d) Running enrichment score of blood vessel morphogenesis, epidermis development, keratinocyte differentiation, T cell activation signatures as the activated (c) (d).</p>
<p>Number of each immune cell type, CD4+ T subset, and CD8 T+ subset by FCM from lung cancer NATs. (a) Cell density type. Data are presented as the number indicated cells per gram NAT, LUAD, LUSQ, other types tissues. (b, c) Density (b) CD8+ (c). ns; not significant. * p<0.05. **P<0.01. ***P<0.001. ****P<0.0001.</p>
<p>Characterization of histopathological factors in respective immune subtypes LUAD, LUSQ, and background NAT tissues. Ly: lymphatic vessel invasion, v: vascular pl; pleural pm: pulmonary metastasis, pT: tumor size, N: lymph node M: distant metastasis. In NATs, fibrosis frequencies lymphocytes, neutrophils, macrophages were assessed. The percentage each classification subtype was plotted LUAD (a) LUSQ (b) with NAT. number patients is specified column.</p>
<p>Activated and suppressed pathways identified by GSEA with GO gene set in respective immune subtypes. (a, b) Heatmap representing top scored enriched genes showing commonly increased decreased expression subtypes LUAD (a) LUSQ (b). Top signaling for are presented red those blue. (c, d) Running enrichment score of blood vessel morphogenesis, epidermis development, keratinocyte differentiation, T cell activation signatures as the activated (c) (d).</p>
<p>Relationship between immune subtypes and molecular subtypes. The were analyzed by unsupervised consensus clustering of RNA-seq. percentage each subtype in the is plotted. number patients specified column.</p>
<p>IHC of LUAD and LUSQ tissues a representative case from immune subtypes. The antibodies against CD20 FOXP3 are used in (a) (b).</p>
<p>CD33 IHC of LUAD and LUSQ tissues a representative case from immune subtypes. (a) LUAD. (b)LUSQ. The number is the ratio CD33 positive staining area per tissue (percentage).</p>
<p>The relationship between TERT amplification and immune cell types in LUSQ. The correlations of the degree with �45 T, CD8+ mMDSC, macrophage cells are plotted.</p>
<p>Boxplot showing the total number of non-synonymous mutations in respective immune subtypes. Non-synonymous were calculated from WES data. ns; not significant.</p>
<p>Antibodies for FACS</p>
<p>Patient characteristics</p>
<p>Relationship between the number of immune cell types and clinicopathological factors. Cells in matrix represent 1-Pearson correlation coefficient density indicated composition factors LUAD (left) LUSQ (right). * p<0.05.</p>
<p>Number of each immune cell type, CD4+ T subset, and CD8 T+ subset by FCM from lung cancer NATs. (a) Cell density type. Data are presented as the number indicated cells per gram NAT, LUAD, LUSQ, other types tissues. (b, c) Density (b) CD8+ (c). ns; not significant. * p<0.05. **P<0.01. ***P<0.001. ****P<0.0001.</p>
<p>Characterization of histopathological factors in respective immune subtypes LUAD, LUSQ, and background NAT tissues. Ly: lymphatic vessel invasion, v: vascular pl; pleural pm: pulmonary metastasis, pT: tumor size, N: lymph node M: distant metastasis. In NATs, fibrosis frequencies lymphocytes, neutrophils, macrophages were assessed. The percentage each classification subtype was plotted LUAD (a) LUSQ (b) with NAT. number patients is specified column.</p>