Takashi Nishizawa
A5019141720- Cancer Immunotherapy and Biomarkers
- Ferroptosis and cancer prognosis
- Immune cells in cancer
- Immune Cell Function and Interaction
- Lymphoma Diagnosis and Treatment
- Cell Adhesion Molecules Research
- interferon and immune responses
- Cytokine Signaling Pathways and Interactions
- Immunotherapy and Immune Responses
- Atherosclerosis and Cardiovascular Diseases
- Cancer Genomics and Diagnostics
- T-cell and B-cell Immunology
- Radiopharmaceutical Chemistry and Applications
- Chronic Lymphocytic Leukemia Research
- Acute Myeloid Leukemia Research
- Monoclonal and Polyclonal Antibodies Research
- Lung Cancer Treatments and Mutations
- Pacific and Southeast Asian Studies
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,...
<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>
<p>Patient outcomes in immune subtypes. <b>A</b> and <b>B,</b> Kaplan–Meier EFS curves for subtypes of LUAD (A) LUSQ (B). <i>P</i> values were calculated by multivariate Cox regression. <b>C</b> <b>D,</b> Relationships cell density (left) with �45 (right) each type infiltrated tumors to patient prognosis (C) (D). Z-scores from proportional hazards analysis are plotted; the plots, red dots indicate ≤ 0.05. <b>E</b>...
<p>Number and percentage of immune cell types, CD4+ T subsets, CD8 T+ myeloid type in respective subtypes. (a–d) Cell density �45 (a), �4 subset (b), �8 CD8+ (c), %myeloid (d) are presented subtypes LUAD LUSQ. ns; not significant. * p<0.05. **P<0.01. ***P<0.001. ****P<0.0001.</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>Immune cell compositions in LUAD and LUSQ; NAT (<i>n</i> = 157), 85), LUSQ 50), other types of lung cancer 21). <b>A,</b> Percentages immune cells per CD45<sup>+</sup> (�45) NSCLC NATs. <b>B,</b> CD4<sup>+</sup> T-cell subsets total T for LUSQ. <b>C,</b> CD8<sup>+</sup> cells. <b>D,</b> myeloid <b>E</b> <b>F,</b> Relationships to clinicopathologic factors. Cells...
<p>Univariate and multivariate analyses of prognostic factors in LUAD LUSQ</p>