Ask about this productRelated genes to: RBM34 Blocking Peptide
- Gene:
- RBM34 NIH gene
- Name:
- RNA binding motif protein 34
- Previous symbol:
- -
- Synonyms:
- KIAA0117
- Chromosome:
- 1q42.3
- Locus Type:
- gene with protein product
- Date approved:
- 2005-06-01
- Date modifiied:
- 2016-04-25
Related products to: RBM34 Blocking Peptide
Related articles to: RBM34 Blocking Peptide
- Peripheral blood mononuclear cells (PBMCs) represent a critical component of the immune system, orchestrating both cellular and humoral responses while maintaining immunological homeostasis. This study investigates the PBMC immune response to Pasteurella multocida (P. multocida) infection in goats using single-cell RNA sequencing (scRNA-seq). PBMCs from goats before and after P. multocida infection were used for scRNA-seq), and pathological examinations were performed on different tissues of the infected hosts. Results demonstrated that recombinase polymerase amplification-lateral flow dipstick (RPA-LFD) detected P. multocida in peripheral blood and lungs, with histopathology confirming lesions. A total of 42 615 cells were annotated as nine cell subgroups, revealed dynamic alterations in immune cell populations, including significant increase in B cells and monocytes alongside decreased T cells and megakaryocytes post-infection. Further analysis identified 48 differentially expressed genes consistently modulated across comparison groups, with significant enrichment in immune-related Gene Ontology (GO) terms, as well as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways including IL-17 signaling pathway and cytokine-cytokine receptor interactions. Pseudotime trajectory uncovered four B cell and two T cell differentiation lineages. Inter-cell communication exhibited enhanced activity post-infection. Integration with RNA-seq data revealed key genes (IL1R2, RBM34, EDEM3, and MZB1) potentially critical in early infection. These findings substantially advance the understanding of PBMCs-mediated immune responses during the early stage of P. multocida infection in goats, identifying key genes and immune pathways. The study not only provides valuable insights into goat immunology but also establishes a foundation for developing improved diagnostic tools and targeted therapeutic interventions against this economically significant pathogen. - Source: PubMed
Publication date: 2026/05/05
An QiChen TaoyuJiang JunmingWu HuiWu GuanshengJiao ZizhuoLi ShiyuanMeng YongTang JiayangChen YuanyuanPan HaojuLi HongZhang ZhenxingCheng YiwenFu YujingHuang ZijingManchu RigaChen QiaolingWang Fengyang - Enhancing disease resistance is one of the primary objectives of the poultry industry through breeding. The heterophil to lymphocyte ratio (H/L ratio) represents a critical indicator of stress and immune status in chickens. However, the essential genetic networks and functional genes governing the H/L ratio remain uncharacterized. In this study, by combining genomic and transcriptomic data, we aimed to identify functional variants and key genes regulating the H/L ratio in white-feathered broilers. Using a genome-wide association study (GWAS) analysis of 218 birds, we identified single-nucleotide polymorphisms (SNPs) significantly associated with H/L ratio and H count, respectively. These SNPs were annotated to several candidate genes, including MYO16, AKT3, RBM34, SMOC2, and TOMM20. Functional enrichment analysis revealed that candidate genes were involved in FoxO signalling pathway, mTOR signalling pathway, and other immune-related pathways. Fine-mapping analysis identified potential causal variants at multiple sites, specifically chr1:138395826, chr3:34663003, chr3:34663053, and chr3:34663073. Additionally, through integrating transcriptomic and immune-related phenotypic data using weighted gene co-expression network analysis, key hub genes were identified in the bursa and thymus, respectively. Moreover, combined analysis of candidate and hub genes from the GWAS and transcriptomic analyses, respectively, illustrated that these genes were co-enriched in functionally important pathways, including mTOR, FoxO, and MAPK signaling pathways. In summary, our results indicated that MYO16 and AKT3 may represent potential causal genes associated with H/L ratio, and that multiple immune signaling pathways regulate the balance between heterophil and lymphocyte immune cells in chickens. These findings provide new insights into the genetic architecture of immune-related traits in poultry. Moreover, it is crucial to confirm the biological function of these candidate genes and variants by conducting further verification in larger populations with genetic diversity. - Source: PubMed
Publication date: 2026/01/08
Zheng JumeiWang QiaoO'Grady John FWang ZixuanDeng ManZhang JinLi XiangZhu YuqingMacHugh David EZhao Guiping - High telomerase activity has been detected in over 85 % of tumors, with the activation of hTERT being the most crucial mechanism for re-establishing telomerase activity. Activation of hTERT maintains telomere length in cells, enabling cancer cells to proliferate indefinitely. Nevertheless, the specific mechanism of telomerase activation in non-small cell lung cancer (NSCLC) remains unclear, and post-transcriptional regulation of hTERT could be a potential activation mechanism. - Source: PubMed
Publication date: 2024/12/20
Gu WeiLi HongshuiSun LeiShen ZiyiWang YuanhuiHu XiaomengWu YanLiu WeiWan Chunpeng CraigCai YiYan Tingdong - To demonstrate the efficacy of machine learning models in predicting mortality in melanoma cancer, we developed an interpretability model for better understanding the survival prediction of cancer. To this end, the optimal features were identified, ten different machine learning models were utilized to predict mortality across various datasets. Then we have utilized the important features identified by those machines learning methods to construct a new model named NKECLR to forecast mortality of patient with cancer. To explicitly clarify the model's decision-making process and uncover novel findings, an interpretable technique incorporating machine learning and SHapley Additive exPlanations (SHAP), as well as LIME, has been employed, and four genes EPGN, PHF11, RBM34, and ZFP36 were identified from those machine learning(ML). The experimental analysis conducted on training and validation datasets demonstrated that the proposed model has a good performance com- pared to existing methods with AUC value 81.8%, and 79.3%, respectively. Moreover, when combined our NKECLR with PD-L1, PD-1, and CTLA-4 the AUC value was 83%0. Finally, these findings have been applied to comprehend the response of drugs and immunotherapy. Our research introduced an innovative predictive NKECLR model utilizing natural killer(NK) cell marker genes for cohorts with melanoma cancer. The NKECLR model can effectively predict the survival of melanoma cancer cohorts and treatment results, revealing distinct immune cell infiltration in the high-risk group. - Source: PubMed
Publication date: 2024/12/04
Hounye Alphonse HoussouXiong LiHou Muzhou - RNA binding proteins (RBPs) are increasingly recognized as potential factors influencing the advancement, prognostication, and immune response in various solid tumors. Nevertheless, the comprehensive understanding of RBM34's biological mechanisms within the tumor microenvironment remains incomplete, necessitating further systematic pan-cancer investigations to ascertain its diagnostic, prognostic, and immunological significance. In this study, the TCGA, CCLE, HPA, GTEX, and TARGET databases were employed to analyze the expression abundance and subcellular localization of RBM34 in diverse tumor types. Kaplan-Meier survival analyses were used to investigate the impact of RBM34 on clinical prognosis. We implemented the TISIDB portal, CIBERSORT, and ESTIMATE algorithms to assess the correlation between RBM34 expression and immunomodulators, chemokines, and tumor-infiltrating lymphocytes (TILs) in both pan-cancer and osteosarcoma. The CGP database was applied to evaluate the half-maximal inhibitory concentrations of targeted drugs, while TMB, MSI, and MMR were utilized to predict the efficacy of tumor immunotherapy. Furthermore, an RBM34-derived prognostic index (RDPI) was constructed for osteosarcoma patients and linked to outcomes and immune status. Finally, we examined the modulation of RBM34 knockdown on osteosarcoma proliferation and migration capacity. Our results indicate that RBM34 was predominantly localized in the nucleus and differentially expressed in most human cancer types. Kaplan-Meier curve analysis and Cox regression demonstrated that RBM34 expression affected four survival metrics including overall survival (OS) in multiple tumors and was an independent prognostic factor for osteosarcoma. In immunological characterization, RBM34 expression was significantly associated with pan-cancer immunomodulator-related molecules, lymphocyte subpopulation infiltration, and biomarkers of immunotherapy response. Subsequent in vitro experiments provided additional evidence that the suppression of RBM34 impeded the migratory and invasive capabilities of osteosarcoma. Moreover, the utilization of RDPI demonstrated its reliability in prognosticating patient outcomes and estimating the individual immune landscape. Marked differences in multiple TILs (including naive B cells, CD8+ T cells, resting dendritic cells, and activated CD4+ memory T cells) and cancer-associated fibroblast proportion were observed in diverse RDPI score subgroups. Generally, RBM34 exhibited associations with clinical prognosis, immune infiltration, and immunotherapy across various cancer types, and may also serve as a viable therapeutic target for osteosarcoma. - Source: PubMed
Publication date: 2023/11/15
Zhang WenchaoHe RongCao WenbingLi DapengZheng QipingZhang Yiming