Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Purpose: We aimed to comprehensively analyze the immune cell and stromal components of tumor microenvironment at the single-cell level and identify tumor heterogeneity among the major top-derived oncogene mutations in non-small cell lung cancer (NSCLC) using single-cell RNA sequencing (scRNA-seq) data. Materials and Methods: The scRNA-seq dataset utilized in this study comprised 64369 primary tumor tissue cells from 21 NSCLC patients, focusing on mutations in EGFR, ALK, BRAF, KRAS, TP53, and the wild-type. Results: Tumor immune microenvironment (TIM) analysis revealed differential immune responses across NSCLC mutation subtypes. TIM analysis revealed different immune responses across the mutation subtypes. Two mutation clusters emerged: KRAS, TP53, and EGFR+TP53 mutations (MC1); and EGFR, BRAF, and ALK mutations (MC2). MC1 showed higher tertiary lymphoid structures signature scores and enriched populations of C2-T-IL7R, C3-T/NK-CXCL4, C9-T/NK-NKG, and C1-B-MS4A1 clusters than cluster 2. Conversely, MC2 cells exhibited higher expression levels of TNF, IL1B, and chemokines linked to alternative immune pathways. Remarkably, co-occurring EGFR and TP53 mutations were grouped as MC1. EGFR+TP53 mutations showed upregulation of peptide synthesis and higher synthetic processes, as well as differences in myeloid and T/NK cells compared to EGFR mutations. In T/NK cells, EGFR+TP53 mutations showed a higher expression of features related to cell activity and differentiation, whereas EGFR mutations showed the opposite. Conclusion Our research indicates a close association between mutation types and tumor microenvironment in NSCLC, offering insights into personalized approaches for cancer diagnosis and treatment.

Metabolic abnormalities in the liver are closely associated with diverse metabolic diseases such as non-alcoholic fatty liver disease, type 2 diabetes, and obesity. The aim of this study was to evaluate the ameliorating effect of robinetin (RBN) on the significant pathogenic features of metabolic failure in the liver and to identify the underlying molecular mechanism. RBN significantly decreased triglyceride (TG) accumulation by downregulating lipogenesis-related transcription factors in AML-12 murine hepatocyte cell line. In addition, mice fed with Western diet (WD) containing 0.025% or 0.05% RBN showed reduced liver mass and lipid droplet size, as well as improved plasma insulin levels and homeostatic model assessment of insulin resistance (HOMA-IR) values.CD38 was identified as a target of RBN using the BioAssay database, and its expression was increased in OPA-treated AML-12 cells and liver tissues of WD-fed mice. Furthermore, RBN elicited these effects through its anti-histone acetyltransferase (HAT) activity. Computational simulation revealed that RBN can dock into the HAT domain pocket of p300, a histone acetyltransferase, which leads to the abrogation of its catalytic activity. Additionally, knock-down of p300 using siRNA reduced CD38 expression.The chromatin immunoprecipitation (ChIP) assay showed that p300 occupancy on the promoter region of CD38 was significantly decreased, and H3K9 acetylation levels were diminished in lipid-accumulated AML-12 cells treated with RBN. RBN improves the pathogenic features of metabolic failure by suppressing the p300–CD38 axis through its anti-HAT activity, which suggests that RBN can be used as a new phytoceutical candidate for preventing or improving this condition.

Purpose: By utilizing both protein and mRNA expression patterns, we can identify more detailed and diverse immune cells, providing insights into understanding the complex immune landscape in cancer ecosystems. Materials and Methods: This study was performed by obtaining publicly available Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) data of peripheral blood mononuclear cells (PBMCs) from the Gene Expression Omnibus database. A total of 94674 total cells were analyzed, of which 32412 were T cells. There were 228 protein features and 16262 mRNA features in the data.The Seurat package was used for quality control and preprocessing, principal component analysis was performed, and Uniform Manifold Approximation and Projection was used to visualize the clusters. Protein and mRNA levels in the CITE-seq were analyzed. Results: We observed that a subset of T cells in the clusters generated at the protein level divided better. By identifying mRNA markers that were highly correlated with the CD4 and CD8 proteins and cross-validating CD26 and CD99 markers using flow cytometry, we found that CD4 + and CD8+ T cells were better discriminated in PBMCs. Weighted Nearest Neighbor clustering results identified a previously unobserved T cell subset. Conclusion In this study, we used CITE-seq data to confirm that protein expression patterns could be used to identify cells more precisely. These findings will improve our understanding of the heterogeneity of immune cells in the future and provide valuable insights into the complexity of the immune response in health and disease.

Purpose: Agonists of the stimulator of interferon genes (STING) play a key role in activating the STING pathway by promoting the production of cytokines. In this study, we investigated the antitumor effects and activation of the systemic immune response of treatment with DMXAA (5,6-dimethylxanthenone-4-acetic acid), a STING agonist, in EML4-ALK lung cancer and CT26 colon cancer. Materials and Methods: The abscopal effects of DMXAA in the treatment of metastatic skin nodules were assessed. EML4-ALK lung cancer and CT26 colon cancer models were used to evaluate these effects after DMXAA treatment. To evaluate the expression of macrophages and T cells, we sacrificed the tumor-bearing mice after DMXAA treatment and obtained the formalin-fixed paraffin-embedded (FFPE) tissue and tumor cells. Immunohistochemistry and flow cytometry were performed to analyze the expression of each FFPE and tumor cell. Results: We observed that highly infiltrating immune cells downstream of the STING pathway had increased levels of chemokines after DMXAA treatment. In addition, the levels of CD80 and CD86 in antigen-presenting cells were significantly increased after STING activation. Furthermore, innate immune activation altered the systemic T cell-mediated immune responses, induced proliferation of macrophages, inhibited tumor growth, and increased numbers of cytotoxic memory T cells. Tumor-specific lymphocytes also increased in number after treatment with DMXAA. Conclusion The abscopal effect of DMXAA treatment on the skin strongly reduced the spread of EML4-ALK lung cancer and CT26 colon cancer through the STING pathway and induced the presentation of antigens.

Background: Neuroinflammation plays an important role in cognitive decline and memory impairment in neurodegenerative disorders. Previously, we demonstrated that Humulus japonicus (HJ) has anti-inflammatory effects in rodent models of Alzheimer’s disease and Parkinson’s disease. The present study aimed to examine the protective potential of HJ extracts against lipopolysaccharide (LPS)-induced cognitive impairment and scopolamine-induced amnesia in mouse models. Cognitive improvement of mice was investigated by novel object recognition test. For analyzing effects on neuroinflammation, immunohistochemistry and quantitative real-time polymerase chain reaction (qRTPCR) assays were performed. Results: We found that the oral administration of HJ significantly improved cognitive dysfunction induced by LPS in a novel object recognition test. The LPS-induced activation of microglia was notably decreased by HJ treatment in the cortex and hippocampus. HJ administration with LPS also significantly increased the mRNA expression of interleukin (IL)-10 and decreased the mRNA expression of IL-12 in the parietal cortex of mice. The increased expression of LPS-induced complement C1q B chain (C1bq) and triggering receptor expressed on myeloid cells 2 (Trem2) genes was significantly suppressed by HJ treatment. In addition, HJ administration significantly improved novel object recognition in a scopolamine-induced amnesia mouse model. Conclusions These findings revealed that HJ has a beneficial effect on cognitive impairment and neuroinflammation induced by systemic inflammation and on amnesia induced by scopolamine in mice.

Purpose: The objective of this study was to modify and validate an emergency department (ED) triage system with improved prediction performance on hospital outcomes by modifying the Korean Triage and Acuity Scale (KTAS). Materials and Methods: We performed a retrospective observational study at three academic universities in South Korea. The KTAS code, determined by the chief complaint and the selected modifier of a patient, was used to derive the Modified KTAS (MKTAS). We calculated the area under the receiver operating characteristics curve (AUC) and the test characteristics to evaluate the performance of MKTAS to predict hospital mortality, critical outcome, and admission. Results: A total of 272402 and 128831 ED visits were used for the derivation and validation of MKTAS, respectively. Compared to KTAS, MKTAS had significantly higher AUC values for the prediction of hospital mortality [MKTAS 0.826 (0.818–0.835) vs. KTAS 0.794 (0.784–0.803)], critical outcome [MKTAS 0.836 (0.830–0.841) vs. 0.798 (0.792–0.804)], and admission [MKTAS 0.725 (0.723– 0.728) vs. KTAS 0.685 (0.682–0.688)]. The sensitivity for predicting hospital mortality and critical outcome, as well as the specificity for predicting admission, were significantly improved. Conclusion MKTAS was derived by modifying the KTAS, and then validated. Compared with KTAS, MKTAS showed better discriminating ability to predict hospital outcomes. Continuous efforts to evaluate and modify widely used triage systems are required to improve their performance.