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.

Background: We explored the utility of a small multi-gene DNA panel for assessing molecular profiles of thyroid nodules and influencing clinical decisions by comparing outcomes between tested and untested nodules. Methods: Between April 2022 and May 2023, we prospectively performed fine-needle aspiration (FNA) with gene testing via DNA panel of 11 genes (BRAF, RAS [NRAS, HRAS, KRAS], EZH1, DICER1, EIF1AX, PTEN, TP53, PIK3CA, TERT promoter) in 278 consecutive nodules (panel group). Propensity score-matching (1:1) was performed with 475 nodules that consecutively underwent FNA without gene testing between January 2021 and December 2021 (control group). Results: In the panel group, positive call rate for mutations was 41.7% (BRAF 16.2%, RAS 12.6%, others 11.5%, double mutation 1.4%) for all nodules, and 40.0% (BRAF 4.3%, RAS 19.1%, others 15.7%, double mutation 0.9%) for indeterminate nodules. Benign call rate was 69.8% for all nodules, and 75.7% for indeterminate nodules. In four nodules, additional TP53 (in addition to BRAF or EZH1) or PIK3CA (in addition to BRAF or TERT) mutations were co-detected. Sensitivity, specificity, positive predictive value, and negative predictive value were 80.0%, 53.3%, 88.1%, 38.1% for all nodules, and 78.6%, 45.5%, 64.7%, 62.5% for indeterminate nodules, respectively. Panel group exhibited lower surgical resection rates than the control group for all nodules (27.0% vs. 52.5%, P<0.001), and indeterminate nodules (23.5% vs. 68.2%, P<0.001). Malignancy risk was significantly different between the panel and control groups (81.5% vs. 63.9%, P=0.008) for all nodules. Conclusion Our panel aids in managing thyroid nodules by providing information on malignancy risk based on mutations, potentially reducing unnecessary surgery in benign nodules or patients with less aggressive malignancies.

Objective: Differentiating intracranial aneurysms from normal variants using CT angiography (CTA) or MR angiography (MRA) poses significant challenges. This study aimed to evaluate the efficacy of proton-density MRA (PD-MRA) compared to highresolution time-of-flight MRA (HR-MRA) in diagnosing aneurysms among patients with indeterminate findings on conventional CTA or MRA. Materials and Methods: In this retrospective analysis, we included patients who underwent both PD-MRA and HR-MRA from August 2020 to July 2022 to assess lesions deemed indeterminate on prior conventional CTA or MRA examinations. Three experienced neuroradiologists independently reviewed the lesions using HR-MRA and PD-MRA with reconstructed voxel sizes of 0.253 mm3 or 0.23 mm3 , respectively. A neurointerventionist established the gold standard with digital subtraction angiography.We compared the performance of HR-MRA, PD-MRA (0.253 -mm3 voxel), and PD-MRA (0.23 -mm3 voxel) in diagnosing aneurysms, both per lesion and per patient. The Fleiss kappa statistic was used to calculate inter-reader agreement. Results: The study involved 109 patients (average age 57.4 ± 11.0 years; male:female ratio, 11:98) with 141 indeterminate lesions. Of these, 78 lesions (55.3%) in 69 patients were confirmed as aneurysms by the reference standard. PD-MRA (0.253 -mm3voxel) exhibited significantly higher per-lesion diagnostic performance compared to HR-MRA across all three readers: sensitivity ranged from 87.2%–91.0% versus 66.7%–70.5%; specificity from 93.7%–96.8% versus 58.7%–68.3%; and accuracy from 90.8%–92.9% versus 63.8%–69.5% (P ≤ 0.003). Furthermore, PD-MRA (0.253 -mm3 voxel) demonstrated significantly superior per-patient specificity and accuracy compared to HR-MRA across all evaluators (P ≤ 0.013). The diagnostic accuracy of PD-MRA (0.23 -mm3 voxel) surpassed that of HR-MRA and was comparable to PD-MRA (0.253 -mm3 voxel). The kappa values for inter-reader agreements were significantly higher in PD-MRA (0.820–0.938) than in HR-MRA (0.447–0.510). Conclusion PD-MRA outperformed HR-MRA in diagnostic accuracy and demonstrated almost perfect inter-reader consistency in identifying intracranial aneurysms among patients with lesions initially indeterminate on CTA or MRA.

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.

Background: Peripheral blood mononuclear cells (PBMCs) are commonly used to assess in vitro immune responses. However, PBMC isolation is a time-consuming procedure, introduces technical variability, and requires a relatively large volume of blood. By contrast, whole blood assay (WBA) is faster, cheaper, maintains more physiological conditions, and requires less sample volume, laboratory training, and equipment. Objectives: Herein, this study aimed to develop a porcine WBA for in vitro evaluation of immune responses. Methods: Heparinized whole blood (WB) was diluted (non-diluted, 1/2, 1/8, and 1/16) in RPMI-1640 media, followed by phorbol myristate acetate and ionomycin. After 24 h, cells were stained for interferon (IFN)-γ secreting T-cells followed by flow cytometry, and the supernatant was analyzed for tumor necrosis factor (TNF)-α. In addition, diluted WB was stimulated by lipopolysaccharide (LPS) and polyinosinic:polycytidylic acid (poly I:C), reference strain KCTC3557 (RS), field isolate (FI), of heat-killed (HK) Streptococcus suis, and porcine reproductive and respiratory syndrome virus (PRRSV). Results: The frequency of IFN-γ + CD3 + T-cells and concentration of TNF-α in the supernatant of WB increased with increasing dilution factor and were optimal at 1/8. WB TNF-α and interleukin (IL)-10 cytokine levels increased significantly following stimulation with LPS or poly I:C. Further, FI and RS induced IL-10 production in WB. Additionally, PRRSV strains increased the frequency of IFN-γ + CD4 - CD8 + cells, and IFN-γ was non-significantly induced in the supernatant of re-stimulated samples. Conclusions We propose that the WBA is a rapid, reliable, and simple method to evaluate immune responses and WB should be diluted to trigger immune cells.

Purpose: To propose standardized and feasible imaging protocols for constructing artificial intelligence (AI) database in acute stroke by assessing the current practice at tertiary hospitals in South Korea and reviewing evolving AI models. Materials and Methods: A nationwide survey on acute stroke imaging protocols was conducted using an electronic questionnaire sent to 43 registered tertiary hospitals between April and May 2021. Imaging protocols for endovascular thrombectomy (EVT) in the early and late time windows and during follow-up were assessed. Clinical applications of AI techniques in stroke imaging and required sequences for developing AI models were reviewed. Standardized and feasible imaging protocols for data curation in acute stroke were proposed. Results: There was considerable heterogeneity in the imaging protocols for EVT candidates in the early and late time windows and posterior circulation stroke. Computed tomography (CT)-based protocols were adopted by 70% (30/43), and acquisition of noncontrast CT, CT angiography and CT perfusion in a single session was most commonly performed (47%, 14/30) with the preference of multiphase (70%, 21/30) over single phase CT angiography. More hospitals performed magnetic resonance imaging (MRI)-based protocols or additional MRI sequences in a late time window and posterior circulation stroke. Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) were most commonly performed MRI sequences with considerable variation in performing other MRI sequences. AI models for diagnostic purposes required noncontrast CT, CT angiography and DWI while FLAIR, dynamic susceptibility contrast perfusion, and T1-weighted imaging (T1WI) were additionally required for prognostic AI models. Conclusion Given considerable heterogeneity in acute stroke imaging protocols at tertiary hospitals in South Korea, standardized and feasible imaging protocols are required for constructing AI database in acute stroke. The essential sequences may be noncontrast CT, DWI, CT/MR angiography and CT/MR perfusion while FLAIR and T1WI may be additionally required.