Ask about this productRelated genes to: ZNF689 Blocking Peptide
- Gene:
- ZNF689 NIH gene
- Name:
- zinc finger protein 689
- Previous symbol:
- -
- Synonyms:
- FLJ90415, TIPUH1
- Chromosome:
- 16p11.2
- Locus Type:
- gene with protein product
- Date approved:
- 2005-05-09
- Date modifiied:
- 2018-01-26
Related products to: ZNF689 Blocking Peptide
Related articles to: ZNF689 Blocking Peptide
- Triple-negative breast cancer (TNBC) is an aggressive disease characterized by remarkable intratumor heterogeneity (ITH), which poses therapeutic challenges. However, the clinical relevance and key determinant of ITH in TNBC are poorly understood. Here, we comprehensively characterized ITH levels using multi-omics data across our center's cohort (n = 260), The Cancer Genome Atlas cohort (n = 134), and four immunotherapy-treated cohorts (n = 109). Our results revealed that high ITH was associated with poor patient survival and immunotherapy resistance. Importantly, we identified zinc finger protein 689 (ZNF689) deficiency as a crucial determinant of ITH formation. Mechanistically, the ZNF689-TRIM28 complex was found to directly bind to the promoter of long interspersed element-1 (LINE-1), inducing H3K9me3-mediated transcriptional silencing. ZNF689 deficiency reactivated LINE-1 retrotransposition to exacerbate genomic instability, which fostered ITH. Single-cell RNA sequencing, spatially resolved transcriptomics and flow cytometry analysis confirmed that ZNF689 deficiency-induced ITH inhibited antigen presentation and T-cell activation, conferring immunotherapy resistance. Pharmacological inhibition of LINE-1 significantly reduced ITH, enhanced antitumor immunity, and eventually sensitized ZNF689-deficient tumors to immunotherapy in vivo. Consistently, ZNF689 expression positively correlated with favorable prognosis and immunotherapy response in clinical samples. Altogether, our study uncovers a previously unrecognized mechanism underlying ZNF689 deficiency-induced ITH and suggests LINE-1 inhibition combined with immunotherapy as a novel treatment strategy for TNBC. - Source: PubMed
Publication date: 2024/01/02
Ge Li-PingJin XiMa DingWang Zi-YuLiu Cheng-LinZhou Chao-ZhengZhao ShenYu Tian-JianLiu Xi-YuDi Gen-HongShao Zhi-MingJiang Yi-Zhou - Among candidate neurodegenerative/neuropsychiatric risk-predictive biomarkers, platelet count, mean platelet volume and platelet distribution width have been associated with the risk of major depressive disorder (MDD), Alzheimer's disease (AD) and Parkinson's disease (PD) through epidemiological and genomic studies, suggesting partial co-heritability. We exploited these relationships for a multi-trait association analysis, using publicly available summary statistics of genome-wide association studies (GWASs) of all traits reported above. Gene-based enrichment tests were carried out, as well as a network analysis of significantly enriched genes. We analyzed 4,540,326 single nucleotide polymorphisms shared among the analyzed GWASs, observing 149 genome-wide significant multi-trait LD-independent associations ( < 5 × 10) for AD, 70 for PD and 139 for MDD. Among these, 27 novel associations were detected for AD, 34 for PD and 40 for MDD. Out of 18,781 genes with annotated variants within ±10 kb, 62 genes were enriched for associations with AD, 70 with PD and 125 with MDD ( < 2.7 × 10). Of these, seven genes were novel susceptibility loci for AD (EPPK1, TTLL1, PACSIN2, TPM4, PIF1, ZNF689, AZGP1P1), two for PD (SLC26A1, EFNA3) and two for MDD (, ). The resulting network showed a significant excess of interactions (enrichment = 1.0 × 10). The novel genes that were identified are involved in the organization of cytoskeletal architecture (, , , ), telomere shortening (), the regulation of cellular aging (, ) and neurodevelopment (), thus, providing novel insights into the shared underlying biology of brain disorders and platelet parameters. - Source: PubMed
Publication date: 2023/01/06
Tirozzi AlfonsinaQuiccione Miriam ShasaCerletti ChiaraDonati Maria Benedettade Gaetano GiovanniIacoviello LiciaGialluisi Alessandro - Non-obstructive azoospermia (NOA) is one of the most severe forms of male infertility, but its diagnosis biomarkers with high sensitivity and specificity are largely unknown. Transcription factors (TFs) play essential roles in many pathological processes in different diseases. Herein, we aimed to identify the TFs showing high diagnosis ability for NOA through machine learning algorithms. The transcriptome data of the testicular tissue from 11 control and 47 NOA subjects were set as the training dataset; meanwhile, 1665 TFs were retrieved from the HumanTFDB. Through the feature extraction methods, including genomic difference analysis, Lasso, Boruta, SVM-RFE, and logistic regression, ETV2, TBX2, and ZNF689 were ultimately screened and then were included in the random forest (RF) diagnosis model. The RF model displayed high predictive power in the training (F-measure = 1) and two external validation (n = 31, F-measure = 0.902; n = 20, F-measure = 0.941) cohorts. The seminal plasma and testicular biopsy samples of 20 control and 20 NOA patients were collected from the local hospital, and the expression levels of ETV2, TBX2, and ZNF689 were measured via RT-qPCR and immunohistochemistry. The RF model could also distinguish the NOA samples in the local cohort (F-measure = 0.741). Single-cell RNA sequencing analysis, which was based on the 432 testicular cell samples from an NOA patient, showed that ETV2, TBX2, and ZNF689 were all significantly associated with spermatogenesis. In all, a 3-TF random forest diagnosis model was successfully established, providing novel insights into the latent mechanisms of NOA. - Source: PubMed
Publication date: 2022/06/17
Zhou RanranLiang JingjingChen QiTian HuYang ChengLiu Cundong - Gastric cancer (GC) is the most common malignant tumor of the digestive system, and its mortality rate ranks first among malignant tumors. However, the pathogenesis of GC has not yet been fully elucidated. This study found that microRNA (miRNA)-339 is abnormally expressed in GC tissues. However, the role and molecular mechanism of miRNA-339 in the occurrence and development of GC are still unclear. - Source: PubMed
Jiang HouxiangLiu YinhuaHu KaifengXia YabinLiang LinhuZhu XiaoliCheng Xianfeng - BACKGROUND This study aimed to investigate the role of miRNA-339-5p in pancreatic cancer cell invasion and migration. MATERIAL AND METHODS The differences between exosomal miRNAs of PANC02 and PANC02-H7 were studied by microarray analysis. We measured miRNA-339-5p expression in different groups; differences in cell invasion and migration were evaluated using the Transwell and wound healing assays and expression of relative proteins (E-cadherin, vimentin and ZNF689) was measured by WB assay. The correlation between miRNA-339-5p and ZNF689 expression was evaluated by luciferase reporter gene assay. RESULTS Compared with PANC02 exosome, microarray analysis indicated that miRNA-339-5p mRNA expression was significantly suppressed (P<0.001) in the PANC02-H7 exosome. Supplementation with miR-339-5p mimics led to a significant decrease in the invasion cell number and wound healing rate (P<0.001), with significantly enhanced E-cadherin expression and suppressed vimentin expression (P<0.001). However, transfection of a miR-339-5p inhibitor led to a significant increase in the invasion cell number and wound healing rate (P<0.001), with significantly suppressed E-cadherin expression and increased vimentin expression (P<0.001). Luciferase reporter gene assay demonstrated ZNF689 gene to be the target of miR-339-5p in the PANC02-H7 cell. With miR-339-5p and ZNF689 transfection, the invasion cell number and wound healing rate were significantly increased compared with those in the miR-339-5p group (P<0.001), with significantly increased expression of ZNF689 and vimentin and suppressed E-cadherin expression (P<0.001). CONCLUSIONS miR-339-5p suppresses the invasion and migration of pancreatic cancer cells via direct regulation of ZNF689 in vitro. - Source: PubMed
Publication date: 2019/10/07
Yu ZeqianZhao SusuWang LishanWang JunyingZhou Jiahua