PI4K2B

Last update 08 May 2025

Basic Info

Synonyms

FLJ11105, phosphatidylinositol 4-kinase type 2 beta, Phosphatidylinositol 4-kinase type 2-beta

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Introduction

Together with PI4K2A and the type III PI4Ks (PIK4CA and PIK4CB) it contributes to the overall PI4-kinase activity of the cell (PubMed:11923287, PubMed:12324459). This contribution may be especially significant in plasma membrane, endosomal and Golgi compartments (PubMed:11923287, PubMed:12324459). The phosphorylation of phosphatidylinositol (PI) to PI4P is the first committed step in the generation of phosphatidylinositol 4,5-bisphosphate (PIP2), a precursor of the second messenger inositol 1,4,5-trisphosphate (InsP3) (PubMed:11923287, PubMed:12324459). Contributes to the production of InsP3 in stimulated cells and is likely to be involved in the regulation of vesicular trafficking.

100 Clinical Results associated with PI4K2B

100 Translational Medicine associated with PI4K2B

0 Patents (Medical) associated with PI4K2B

Literatures (Medical) associated with PI4K2B

30 Oct 2024·Bioscience Reports

Identification of the GABARAP binding determinant in PI4K2A

Article

Author: Chen, Yan ; Barylko, Barbara ; Eichorst, John P. ; Mueller, Joachim D. ; Albanesi, Joseph P.

AbstractGABARAP is a member of the ATG8 family of ubiquitin-like autophagy related proteins. It was initially discovered as a facilitator of GABA-A receptor translocation to the plasma membrane and has since been shown to promote the intracellular transport of a variety of other proteins under non-autophagic conditions. We and others have shown that GABARAP interacts with the Type II phosphatidylinositol 4-kinase, PI4K2A, and that this interaction is important for autophagosome-lysosome fusion. Here, we identify a 7-amino acid segment within the PI4K2A catalytic domain that contains the GABARAP interaction motif (GIM). This segment resides in an exposed loop that is not conserved in the other mammalian Type II PI 4-kinase, PI4K2B, explaining the specificity of GABARAP binding to the PI4K2A isoform. Mutation of the PI4K2A GIM inhibits GABARAP binding and PI4K2A-mediated recruitment of cytosolic GABARAP to subcellular organelles. We further show that GABARAP binds to mono-phosphorylated phosphoinositides, PI3P, PI4P, and PI5P, raising the possibility that these lipids contribute to the binding energies that drive GABARAP–protein interactions on membranes.

15 Jun 2024·Aging

Identification of key genes and biological pathways associated with vascular aging in diabetes based on bioinformatics and machine learning

Article

Author: Wang, Min ; Zhang, Chi ; Chen, Jing ; Wang, Sha ; Wang, Xia

Vascular aging exacerbates diabetes-associated vascular damage, a major cause of microvascular and macrovascular complications. This study aimed to elucidate key genes and pathways underlying vascular aging in diabetes using integrated bioinformatics and machine learning approaches. Gene expression datasets related to vascular smooth muscle cell (VSMC) senescence and diabetic vascular aging were analyzed. Differential expression analysis identified 428 genes associated with VSMC senescence. Functional enrichment revealed their involvement in cellular senescence, ECM-receptor interaction, PI3K-Akt and AGE-RAGE signaling pathways. Further analysis of diabetic vascular aging datasets revealed 52 differentially expressed genes, enriched in AMPK signaling, AGE-RAGE signaling, cellular senescence, and VEGF signaling pathways. Machine learning algorithms, including LASSO regression and SVM-RFE, pinpointed six key genes: TFB1M, FOXRED2, LY75, DALRD3, PI4K2B, and NDOR1. Immune cell infiltration analysis demonstrated correlations between diabetic vascular aging, the identified key genes, and infiltration levels of plasma cells, M1 macrophages, CD8+ T cells, eosinophils, and regulatory T cells. In conclusion, this study identified six pivotal genes (TFB1M, FOXRED2, LY75, DALRD3, PI4K2B, and NDOR1) closely associated with diabetic vascular aging through integrative bioinformatics and machine learning approaches. These genes are linked to alterations in the immune microenvironment during diabetic vascular aging. This study provides a reference and basis for molecular mechanism research, biomarker mining, and diagnosis and treatment evaluation of diabetes-related vascular aging.

15 May 2023·BMC medical genomics

The identification of a two-gene prognostic model based on cisplatin resistance-related ceRNA network in small cell lung cancer.

Article

Author: Zhu, Qizhi ; Wang, Wei ; Xu, Ao ; Nie, Jinfu ; Zhang, Yani ; Wang, Hongzhi ; Qi, Jian ; Hong, Bo ; Fu, Meng

BACKGROUNDSmall cell lung cancer (SCLC) is a very malignant tumor with rapid growth and early metastasis. Platinum-based chemo-resistance is the major issue for SCLC treatment failure. Identifying a new prognostic model will help to make an accurate treatment decision for SCLC patients.METHODSUsing the genomics of drug sensitivity in cancer (GDSC) database, we identified cisplatin resistance-related lncRNAs in SCLC cells. Based on the competing endogenous RNA (ceRNA) network, we identified the mRNAs correlated with the lncRNAs. Using Cox and LASSO regression analysis, a prognostic model was established. The survival prediction accuracy was evaluated by receiver operating characteristic (ROC) curve and Kaplan-Meier analysis. GSEA, GO, KEGG and CIBERSORT tools were used for functional enrichment and immune cells infiltration analysis.RESULTSWe first screened out 10 differentially expressed lncRNAs between cisplatin resistant and sensitive SCLC cells from GDSC database. Based on ceRNA network, 31 mRNAs were identified with a correlation with the 10 lncRNAs. Furthermore, two genes (LIMK2 and PI4K2B) were identified by Cox and LASSO regression analysis to construct a prognostic model. Kaplan-Meier analysis indicated that the high-risk group had a poor overall survival compared with the low-risk group. The predicted area under the ROC curve (AUC) was 0.853 in the training set, and the AUC was 0.671 in the validation set. In the meanwhile, the low expression of LIMK2 or the high expression of PI4K2B in SCLC tumors was also significantly associated with poor overall survival in both training and validation sets. Functional enrichment analysis showed that the low-risk group was enriched in the apoptosis pathway and high immune infiltration of T cells. Finally, an apoptosis-related gene Cathepsin D (CTSD) was identified to be up-regulated in the low-risk group, and its higher expression correlated with better overall survival in SCLC.CONCLUSIONWe established a prognostic model and potential biomarkers (LIMK2, PI4K2B and CTSD), which could help to improve the risk stratification of SCLC patients.

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