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.

PURPOSE: We investigated the number of test takers of the Korean-Developmental Screening Test (K-DST) in a single children's hospital within a year, according to age, referral rate, and follow-up percentage. METHODS: For this study, 4,062 children who visited and received K-DST at Woorisoa Children's Hospital between January and December 2015 were enrolled. Seven test sets were used according to the Korean National Health Screening Program for infants and children in the following age groups: 4 to 6, 9 to 12, 18 to 24, 30 to 36, 42 to 48, 54 to 60, and 66 to 71 months. The results of the K-DST were categorized into 4 groups as follows: further evaluation (<−2 standard deviation [−2SD]), follow-up test (−2SD to −1SD), peer level (−1SD to 1SD), and high level (>1SD). RESULTS: The test participants' population and follow-up population were concentrated before the age of 24 months (2,532, 62.3%). The children most commonly referred for further evaluation were those in the 30- to 41-month age group. A mismatch was found between the results of the K-DST and the additional questions. Most of the infants and children with suspicious developmental delays showed catch-up development in their follow-up tests (43 of 55, 78.2%). CONCLUSION: The use of K-DST should be encouraged, especially among children aged over 24 months. Multiple-choice question format for the additional questions is recommended to avoid confusion. We suggest a nationwide study to evaluate and revise the K-DST.
Child* ; Follow-Up Studies ; Humans ; Infant* ; Korea ; Mass Screening* ; Referral and Consultation

PURPOSE: We investigated the causes, clinical features, and risk factors of bee venom anaphylaxis in Korea. METHODS: The medical records of the diagnosis of anaphylaxis during a 5-year period from the 14 hospitals in Korea have been retrospectively reviewed. Cases of bee venom anaphylaxis were identified among anaphylaxis patients, and subgroup analyses were done. RESULTS: A total of 291 patients were included. The common cause of bee species was vespid (24.6%) in bee venom anaphylaxis, followed by honeybee and vespid (8.8%), apitherapy (7.7%), and honeybee (2.0%), although the causative bee species were commonly unknown (56.9%). The severity of anaphylaxis was mostly mild-moderate (72.9%), and common clinical manifestations included cutaneous (80.6%), cardiovascular (39.2%), respiratory (38.1%), and gastrointestinal (13.1%) symptoms. Portable epinephrine auto-injectors were prescribed to 12.1% of the patients. Subject positive to both vespid and honeybee showed more severe symptoms and higher epinephrine use (P<0.05). The severity was significantly associated with older age, but not with gender, underlying allergic disease, or family history. Apitherapy-induced anaphylaxis showed a higher rate of hospitalization and epinephrine use than bee sting anaphylaxis (P<0.05). CONCLUSION: Vespid is the most common cause of bee venom anaphylaxis in Korea. It is suggested that positivity to honeybee and vespid may be associated with more severe symptoms.
Adult* ; Anaphylaxis* ; Apitherapy ; Bee Venoms ; Bees ; Bites and Stings ; Diagnosis ; Epinephrine ; Hospitalization ; Humans ; Hymenoptera* ; Korea ; Medical Records ; Retrospective Studies* ; Risk Factors ; Venoms*

PURPOSE: Exaggerated pro-inflammatory reactions during the acute phase of Kawasaki disease (KD) suggest the role of immune dysregulation in the pathogenesis of KD. We investigated the profiles of T regulatory cells and their correlation with the clinical course of KD. METHODS: Peripheral blood mononuclear cells were collected from 17 KD patients during acute febrile and subacute afebrile phases. T cells expressing CD4, CD25, and Foxp3 were analyzed using flow cytometry, and the results were correlated with the clinical course of KD. RESULTS: The percentage of circulating CD4+CD25highFoxp3+ T cells among CD4+ T cells was significantly higher during the subacute afebrile phase than during the acute febrile phase (1.10%+/-1.22% vs. 0.55%+/-0.53%, P=0.049). Although levels of CD4+CD25lowFoxp3+ T cells and CD4+CD25-Foxp3+ T cells were only slightly altered, the percentage of CD4+CD25+Foxp3- T cells among CD4+ T cells was significantly lower during the subacute afebrile phase than during the acute febrile phase (2.96%+/-1.95% vs. 5.64%+/-5.69%, P=0.036). Consequently, the ratio of CD25highFoxp3+ T cells to CD25+Foxp3- T cells was higher during the subacute afebrile phase than during the acute febrile phase (0.45%+/-0.57% vs. 0.13%+/-0.13%, P=0.038). CONCLUSION: Decreased CD4+CD25highFoxp3+ T cells and/or an imbalanced ratio of CD4+CD25highFoxp3+ T cells to CD4+CD25+Foxp3- T cells might play a role in KD development. Considering that all KD patients were treated with intravenous immunoglobulin (IVIG), recovery of CD4+CD25highFoxp3+ T cells during the subacute afebrile phase could be a mechanism of IVIG.
Flow Cytometry ; Humans ; Immunoglobulins ; Immunoglobulins, Intravenous ; Mucocutaneous Lymph Node Syndrome ; T-Lymphocytes

Tuberculosis is primarily a pulmonary disease, but extra-pulmonary manifestations are not uncommon, especially in children and adolescents. Ten percent of extra pulmonary tuberculosis localizes to the bones and joints, and 56% of such cases affect the spine. We treated a childhood case of spinal tuberculosis misdiagnosed as muscular dystrophy in a patient without specific constitutional symptoms. We report this case because the patient had an unusual presentation of spinal tuberculosis.
Adolescent ; Child ; Humans ; Joints ; Lung Diseases ; Muscular Dystrophies ; Neurologic Manifestations ; Spine ; Tuberculosis ; Tuberculosis, Pulmonary ; Tuberculosis, Spinal