Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

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.

Objective:To explore the value of REG3α,sST2 and TNFR1 in peripheral blood for risk stratification and prognostic evaluation of acute graft-versus-host disease(aGVHD)after allogeneic hematopoietic stem cell transplantation(allo-HSCT)in children.Methods:From January 2020 to March 2022,70 children with aGVHD after allo-HSCT in the First Affiliated Hospital of Zhengzhou University were selected as the research objects,of which 50 cases were mild aGVHD(grade Ⅰ-Ⅱ)and 20 cases were severe aGVHD(grade Ⅲ-Ⅳ).30 healthy children who underwent physical examinations in our hospital during the same period were selected as the control group.Luminex platform was used to detect the protein expression levels of REG3α,sST2 and TNFR1 during aGVHD occurrence,and the differences between the three groups were analyzed by one-way ANOVA.According to the outcome of aGVHD treatment within 28 days,the patients were divided into a good prognosis group of 58 cases and a poor prognosis group of 12 cases.The ROC curve was used to analyze the value of REG3α,sST2 and TNFR1 in predicting the prognosis of children with aGVHD.Results:The peripheral blood levels of REG3α,sST2 and TNFR1 in the mild aGVHD and severe aGVHD groups were significantly higher than those in the control group(P＜0.05),and those in the severe aGVHD group were significantly higher than those in the mild aGVHD group(P＜0.05).Compared with the good prognosis group,the peripheral blood levels of REG3α,sST2 and TNFR1 in the poor prognosis group were significantly higher(t=9.27,3.33,2.97;P＜0.01).ROC curve analysis showed that the area under the curve(AUC),sensitivity and specificity of the combined detection of REG3α,sST2 and TNFR1 in predicting the prognosis of children with aGVHD were higher than those of the above indicators detected alone or in pairs.Conclusion:The expression levels of REG3α,sST2 and TNFR1 were related to the severity of aGVHD.The combination of REG3α,sST2 and TNFR1 has a high clinical value in predicting the prognosis of children with aGVHD,which is expected to provide a reliable reference for clinical evaluation of the prognosis of children with aGVHD.

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.

Uveal melanoma(UM)is the most frequent and life-threatening ocular malignancy in adults.Aberrant histone methylation contributes to the abnormal transcriptome during oncogenesis.However,a comprehensive understanding of histone methylation patterns and their therapeutic potential in UM remains enigmatic.Herein,using a systematic epi-drug screening and a high-throughput transcriptome profiling of histone methylation modifiers,we observed that disruptor of telomeric silencing-1-like(DOT1L),a methyltransferase of histone H3 lysine 79(H3K79),was activated in UM,especially in the high-risk group.Concordantly,a systematic epi-drug library screening revealed that DOT1 L inhibitors exhibited salient tumor-selective inhibitory effects on UM cells,both in vitro and in vivo.Combining Cleavage Under Targets and Tagmentation(CUT&Tag),RNA sequencing(RNA-seq),and bioinformatics analysis,we identified that DOT1 L facilitated H3K79 methylation of nicotinate phosphoribosyltransferase(NAPRT)and epigenetically activated its expression.Importantly,NAPRT served as an oncogenic accel-erator by enhancing nicotinamide adenine dinucleotide(NAD+)synthesis.Therapeutically,DOT1L inhi-bition epigenetically silenced NAPRT expression through the diminishment of dimethylation of H3K79(H3K79me2)in the NAPRT promoter,thereby inhibiting the malignant behaviors of UM.Conclusively,our findings delineated an integrated picture of the histone methylation landscape in UM and unveiled a novel DOT1L/NAPRT oncogenic mechanism that bridges transcriptional addiction and metabolic reprogramming.

Objective:To investigate the correlation of hepatocellular carcinoma (HCC) classified by contrast-enhanced ultrasound (CEUS) Liver Imaging Data and Report System (LI-RADS) with differentiation degree and Ki-67 index.Methods:A multicenter, retrospective study was conducted.The clinical and CEUS imaging data of 208 patients with 208 HCC lesions from December 2017 to December 2020 in China CEUS database were included and analyzed. According to the CEUS LI-RADS version 2017 proposed by the American College of Radiology, the HCC was classified. The diagnosis and pathological information of all lesions were confirmed by pathology. The differentiation degree of HCC and the distribution of Ki-67 index in different LI-RADS categories were evaluated, and their correlation was analyzed.Results:The degree of differentiation and Ki-67 index among HCC of different CEUS LI-RADS were statistically significant ( P<0.001, P=0.009). LI-RADS M HCC was more likely to be poorly differentiated and showed a higher Ki-67 index. The category of LI-RADS was positively correlated with the degree of tumor differentiation (tau-b=-0.250, P<0.001) and the Ki-67 index (tau-b=0.178, P=0.002), that is, the higher the category of LI-RADS, the lower differentiation degree and the higher the Ki-67. Conclusions:The CEUS LI-RADS classification of HCC is correlating with the degree of differentiation and Ki-67 index.