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.

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.

Objective: With trends in population aging an increasing number of older patients are visiting the emergency department (ED). This study aimed to identify the characteristics of ED utilization and risk factors for in-hospital mortality in older patients who visited EDs. Methods: This nationwide observational study used National Emergency Department Information System data collected during a 2-year period from January 2016 to December 2017. The characteristics of older patients aged 70 years or older were compared with those of younger patients aged 20 to 69 years. Risk factors associated with in-hospital mortality were analyzed by multivariable logistic regression. Results: A total of 6,596,423 younger patients and 1,737,799 older patients were included. In the medical and nonmedical older patient groups, significantly higher proportions of patients were transferred from another hospital, utilized emergency medical services, had Korean Triage and Acuity Scale scores of 1 and 2, required hospitalization, and required intensive care unit admission in the older patient group than in the younger patient group. ED and post-hospitalization mortality rates increased with age; in particular, older medical patients aged 90 or older had an in-hospital mortality rate of 9%. Older age, male sex, transfer from another hospital, emergency medical service utilization, a high Korean Triage and Acuity Scale score, systolic blood pressure <100 mmHg, respiratory rate >20/min, heart rate >100/min, body temperature <36°C, and altered mental status were associated with in-hospital mortality. Conclusion Development of appropriate decision-making algorithms and treatment protocols for high risk older patients visiting the ED might facilitate appropriate allocation of medical resources to optimize outcomes.

Objective: With trends in population aging an increasing number of older patients are visiting the emergency department (ED). This study aimed to identify the characteristics of ED utilization and risk factors for in-hospital mortality in older patients who visited EDs. Methods: This nationwide observational study used National Emergency Department Information System data collected during a 2-year period from January 2016 to December 2017. The characteristics of older patients aged 70 years or older were compared with those of younger patients aged 20 to 69 years. Risk factors associated with in-hospital mortality were analyzed by multivariable logistic regression. Results: A total of 6,596,423 younger patients and 1,737,799 older patients were included. In the medical and nonmedical older patient groups, significantly higher proportions of patients were transferred from another hospital, utilized emergency medical services, had Korean Triage and Acuity Scale scores of 1 and 2, required hospitalization, and required intensive care unit admission in the older patient group than in the younger patient group. ED and post-hospitalization mortality rates increased with age; in particular, older medical patients aged 90 or older had an in-hospital mortality rate of 9%. Older age, male sex, transfer from another hospital, emergency medical service utilization, a high Korean Triage and Acuity Scale score, systolic blood pressure <100 mmHg, respiratory rate >20/min, heart rate >100/min, body temperature <36°C, and altered mental status were associated with in-hospital mortality. Conclusion Development of appropriate decision-making algorithms and treatment protocols for high risk older patients visiting the ED might facilitate appropriate allocation of medical resources to optimize outcomes.

Objective: The chest compression depth recommended in the current guidelines for average adult cardiopulmonary resuscitation is approximately 1/4-1/5 depth of the external chest anteroposterior (AP) diameter and at least 50 mm but less than 60 mm. The purpose of this study was to determine the proper compression depth in patients with amyotrophic lateral sclerosis (ALS). Methods: A retrospective analysis of the chest computed tomography scans obtained between January 2014 and December 2018 was performed, and the chest anatomical parameters, such as external, internal chest, and heart AP diameters, were measured. The primary outcomes were a 1/4 and 1/5 depth of an external chest AP diameter. Based on the values of these parameters, the heart compression fractures (HCF) and over compression depth (OCD) from 40 to 60 mm depths with every 5 mm interval were calculated. All outcomes in the two groups were compared. Results: Ninety three of 108 ALS and 93 of 17,150 healthy individuals were selected randomly from a database and analyzed. The mean±standard deviations of 1/4 and 1/5 depth of the external chest AP diameter in ALS were significantly lower than in healthy individuals (48.57±4.60 mm vs. 53.43±4.93 mm, 38.86±3.68 mm vs. 42.75±3.94 mm, respectively, all P<0.001). The HCF values were similar in the two groups. The number of OCD with 55 and 60 mm in the ALS group were increased (all P<0.05, univariate analysis) Conclusion An approximately 50 mm depth of chest compression could be appropriate, but an excessive depth greater than 55 mm is more likely to cause complications for ALS patients.

Aberrant expression of BORIS/CTCFL (Brother of the Regulator of Imprinted Sites/CTCF-like protein) is reported in different malignancies. In this study, we characterized the entire promoter region of BORIS/CTCFL, including the CpG islands, to assess the relationship between BORIS expression and lung cancer. To simplify the construction of luciferase reporter cassettes with various-sized portions of the upstream region, genomic copies of BORIS were isolated using TAR cloning technology. We analyzed three promoter blocks: the GATA/CCAAT box, the CpG islands and the minisatellite region BORIS-MS2. Polymorphic minisatellite sequences were isolated from genomic DNA prepared from the blood of controls and cases. Of the three promoter blocks, the GATA/CCAAT box was determined to be a critical element of the core promoter, while the CpG islands and the BORIS-MS2 minisatellite region were found to act as regulators. Interestingly, the polymorphic minisatellite region BORIS-MS2 was identified as a negative regulator that repressed the expression levels of luciferase reporter cassettes less effectively in cancer cells compared with normal cells. We also examined the association between the size of BORIS-MS2 and lung cancer in a case–control study with 590 controls and 206 lung cancer cases. Rare alleles of BORIS-MS2 were associated with a statistically significantly increased risk of lung cancer (odds ratio, 2.04; 95% confidence interval, 1.02–4.08; and P=0.039). To conclude, our data provide information on the organization of the BORIS promoter region and gene regulation in normal and cancer cells. In addition, we propose that specific alleles of the BORIS-MS2 region could be used to identify the risk for lung cancer.
Alleles ; Clone Cells ; Cloning, Organism ; CpG Islands ; DNA ; Gene Expression* ; Luciferases ; Lung Neoplasms* ; Lung* ; Minisatellite Repeats* ; Promoter Regions, Genetic