ITPK1 MaxPab Mouse Polyclonal Antibody
- Known as:
- ITPK1 MaxPab Mouse Polyclonal Antibody
- Catalog number:
- BIN-003705-B01
- Product Quantity:
- 0.05ml
- Category:
- -
- Supplier:
- Zyagen
- Gene target:
- ITPK1 MaxPab Mouse Polyclonal Antibody
Related genes to: ITPK1 MaxPab Mouse Polyclonal Antibody
- Gene:
- ITPK1 NIH gene
- Name:
- inositol-tetrakisphosphate 1-kinase
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 14q32.12
- Locus Type:
- gene with protein product
- Date approved:
- 1997-06-12
- Date modifiied:
- 2014-11-19
- Gene:
- ITPK1-AS1 NIH gene
- Name:
- ITPK1 antisense RNA 1
- Previous symbol:
- C14orf85, NCRNA00203, ITPK1AS, ITPK1-AS
- Synonyms:
- -
- Chromosome:
- 14q32.12
- Locus Type:
- RNA, long non-coding
- Date approved:
- 2003-01-13
- Date modifiied:
- 2012-10-12
Related products to: ITPK1 MaxPab Mouse Polyclonal Antibody
Related articles to: ITPK1 MaxPab Mouse Polyclonal Antibody
- Colorectal cancer (CRC) is one of the most prevalent cancers worldwide, which after breast, lung and, prostate cancers, is the fourth prevalent cancer in the United States. Long non-coding RNAs (lncRNAs) have an essential role in the pathogenesis of CRC. Therefore, bioinformatics studies on lncRNAs and their target genes have potential importance as novel biomarkers. In the current study, publicly available microarray gene expression data of colorectal cancer (GSE106582) was analyzed with the Limma, Geoquery, Biobase package. Afterward, identified differentially expressed lncRNAs and their target genes were inserted into Weighted correlation network analysis (WGCNA) to obtain modules and hub genes. A total of nine differentially expressed lncRNAs (LINC01018, ITCH-IT, ITPK1-AS1, FOXP1-IT1, FAM238B, PAXIP1-AS1, ATP2B1-AS1, MIR29B2CHG, and SNHG32) were identified using microarray data analysis. The WGCNA has identified several hub genes for black (LMOD3, CDKN2AIPNL, EXO5, ZNF69, BMS1P5, METTL21A, IL17RD, MIGA1, CEP19, FKBP14), blue (CLCA1, GUCA2A, UGT2B17, DSC2, CA1, AQP8, ITLN1, BEST4, KLF4, IQCF6) and turquoise (PAFAH1B1, LMNB1, CACYBP, GLO1, PUM3, POC1A, ASF1B, SDCCAG3, ASNS, PDCD2L) modules. The findings of the current study will help to improve our understanding of CRC. Moreover, the hub genes that we have identified could be considered as possible prognostic/diagnostic biomarkers. This study led to the determination of nine lncRNAs with no previous association with CRC development. - Source: PubMed
Publication date: 2022/02/22
Chodary Khameneh SepidehRazi SaraShamdani SaraUzan GeorgesNaserian Sina - Acute lymphoblastic leukemia (ALL) is a malignant disease most commonly diagnosed in adolescents and young adults. This study aimed to explore potential signatures and their functions for ALL. - Source: PubMed
Publication date: 2021/07/06
Wang WeiminLyu ChunhuiWang FeiWang CongcongWu FeifeiLi XueGan Silin - Long non‑coding RNAs (lncRNAs) represent potential biomarkers for the diagnosis and treatment of various diseases; however, the role of circulating acute ischemic stroke (AIS)‑related lncRNAs remains relatively unknown. The present study aimed to screen crucial lncRNAs for AIS based on the competing endogenous RNA (ceRNA) hypothesis. The expression profile datasets for one mRNA, accession no. GSE16561, and four microRNAs (miRNAs), accession nos. GSE95204, GSE86291, GSE55937 and GSE110993, were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified, and ClusterProfiler was used to interpret the function of the DEGs. Based on the protein‑protein interaction (PPI) network and module analyses, hub DEGs were identified. A ceRNA network was established based on miRNA‑mRNA or miRNA‑lncRNA interaction pairs. In total, 2,041 DEGs and 5 DELs were identified between the AIS and controls samples in GSE16561, and 10 DEMs between at least two of the four miRNA expression profiles. A PPI network was constructed with 1,235 DEGs, among which 20 genes were suggested to be hub genes. The hub genes paxillin (PXN), FYN‑proto‑oncogene, Src family tyrosine kinase (FYN), ras homolog family member A (RHOA), STAT1, and growth factor receptor‑bound protein 2 (GRB2), were amongst the most significantly enriched modules extracted from the PPI network. Functional analysis revealed that these hub genes were associated with inflammation‑related signaling pathways. An AIS‑related ceRNA network was constructed, in which 4 DELs were predicted to function as ceRNAs for 9 DEMs, to regulate the five identified hub genes; that is, minichromosome maintenance complex component 3 associated protein‑antisense RNA 1 (MCM3AP‑AS1)/long intergenic non‑protein coding RNA 1089 (LINC01089)/hsa‑miRNA (miR)‑125a/FYN, inositol‑tetrakisphosphate 1‑kinase‑antisense RNA 1 (ITPK1‑AS1)/hsa‑let‑7i/RHOA/GRB2/STAT1, and human leukocyte antigen complex group 27 (HCG27)/hsa‑-miR‑19a/PXN interaction axes. In conclusion, MCM3AP‑AS1, LINC01089, ITPK1‑AS1, and HCG27 may represent new biomarkers and underlying targets for the treatment of AIS. - Source: PubMed
Publication date: 2020/08/04
Zhang LiLiu BaihuiHan JinhuaWang TingtingHan Lin - The prognosis for patients with gastric cancer (GC) is usually poor, as the majority of patients have reached the advanced stages of disease at the point of diagnosis. Therefore, revealing the mechanisms of GC is necessary for the identification of key biomarkers and the development of effective targeted therapies. The present study aimed to identify long non-coding RNAs (lncRNAs) prominently expressed in patients with GC. The GC dataset (including 384 GC samples) was downloaded from The Cancer Genome Atlas database as the training set. A number of other GC datasets were obtained from the Gene Expression Omnibus database as validation sets. Following data processing, lncRNAs were annotated, followed by co-expression module analysis to identify stable modules, using the weighted gene co-expression network analysis (WGCNA) package. Prognosis-associated lncRNAs were screened using the 'survival' package. Following the selection of the optimal lncRNA combinations using the 'penalized' package, risk score systems were constructed and assessed. Consensus differentially-expressed RNAs (DE-RNAs) were screened using the MetaDE package, and an lncRNA-mRNA network was constructed. Additionally, pathway enrichment analysis was conducted for the network nodes using gene set enrichment analysis (GSEA). A total of seven modules (blue, brown, green, grey, red, turquoise and yellow) were obtained following WGCNA analysis, among which the green and turquoise modules were stable and associated with the histological grade of GC. A total of 12 prognosis-associated lncRNAs were identified in the two modules. Combined with the optimal lncRNA combinations, risk score systems were constructed. The risk score system based on the green module [including ITPK1 antisense RNA 1 (), KCNQ1 downstream neighbor (), long intergenic non-protein coding RNA 167 (), and ] was the more efficient at predicting risk compared with those based on the turquoise, or the green + turquoise modules. A total of 1,105 consensus DE-RNAs were identified; GSEA revealed that and had the same association directions with 4 pathways and the 32 genes involved in those pathways. In conclusion, a risk score system based on the green module may be applied to predict the survival of patients with GC. Furthermore, and may serve as biomarkers for GC pathogenesis. - Source: PubMed
Publication date: 2019/03/08
Hu ZunqiYang DejunTang YuanZhang XinWei ZiranFu HongbingXu JiapengZhu ZhenxinCai Qingping