Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

Background and Objectives: SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins play crucial roles as neuronal postsynaptic scaffolds. Alongside neuropsychiatric symptoms, individuals with SHANK3 mutations often exhibit symptoms related to dysfunctions in other organs, including the heart. However, detailed insights into the cardiac functions of Shank3 remain limited. This study aimed to characterize the cardiac phenotypes of Shank3-overexpressing transgenic mice and explore the underlying mechanisms. Methods: Cardiac histological analysis, electrocardiogram and echocardiogram recordings were conducted on Shank3-overexpressing transgenic mice. Electrophysiological properties, including action potentials and L-type Ca2+ channel (LTCC) currents, were measured in isolated cardiomyocytes. Ca2+ homeostasis was assessed by analyzing cytosolic Ca2+transients and sarcoplasmic reticulum Ca2+ contents. Depolarization-induced cell shortening was examined in cardiomyocytes. Immunoprecipitation followed by mass spectrometrybased identification was employed to identify proteins in the cardiac Shank3 interactome.Western blot and immunocytochemical analyses were conducted to identify changes in protein expression in Shank3-overexpressing transgenic cardiomyocytes. Results: The hearts of Shank3-overexpressing transgenic mice displayed reduced weight and increased fibrosis. In vivo, sudden cardiac death, arrhythmia, and contractility impairments were identified. Shank3-overexpressing transgenic cardiomyocytes showed prolonged action potential duration and increased LTCC current density. Cytosolic Ca2+ transients were increased with prolonged decay time, while sarcoplasmic reticulum Ca2+ contents remained normal. Cell shortening was augmented in Shank3-overexpressing transgenic cardiomyocytes. The cardiac Shank3 interactome comprised 78 proteins with various functions. Troponin I levels were down-regulated in Shank3-overexpressing transgenic cardiomyocytes. Conclusions This study revealed cardiac dysfunction in Shank3-overexpressing transgenic mice, potentially attributed to changes in Ca2+ homeostasis and contraction, with a notable reduction in troponin I.

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.