Last update 01 Nov 2024

YWHAZ

Last update 01 Nov 2024

Basic Info

Synonyms

14-3-3 protein zeta/delta, 14-3-3-zeta, KCIP-1

+ [4]

Introduction

Adapter protein implicated in the regulation of a large spectrum of both general and specialized signaling pathways (PubMed:14578935, PubMed:15071501, PubMed:15644438, PubMed:16376338, PubMed:16959763, PubMed:31024343, PubMed:9360956). Binds to a large number of partners, usually by recognition of a phosphoserine or phosphothreonine motif (PubMed:35662396). Binding generally results in the modulation of the activity of the binding partner (PubMed:35662396). Promotes cytosolic retention and inactivation of TFEB transcription factor by binding to phosphorylated TFEB (PubMed:35662396). Induces ARHGEF7 activity on RAC1 as well as lamellipodia and membrane ruffle formation (PubMed:16959763). In neurons, regulates spine maturation through the modulation of ARHGEF7 activity (By similarity).

Drugs associated with YWHAZ

CN115838436

Patent Mining

Target

YWHAZ

Mechanism-

Active Org.

The First Hospital Of China Medical University

Originator Org.

The First Hospital Of China Medical University

Active Indication

Neoplasms

Inactive Indication-

Drug Highest PhaseDiscovery

First Approval Ctry. / Loc.-

First Approval Date20 Jan 1800

100 Clinical Results associated with YWHAZ

100 Translational Medicine associated with YWHAZ

0 Patents (Medical) associated with YWHAZ

619

Literatures (Medical) associated with YWHAZ

01 Dec 2024·Molecular Biology Reports

Comprehensive evaluation and validation of optimal reference genes for normalization of qPCR data in different caprine tissues

Article

Author: Vasu, Mahanthi ; Arora, Reena ; Sharma, Rekha ; Mir, M A ; Singh, Manoj Kumar ; Choudhary, Vikas ; Ahlawat, Sonika

BACKGROUNDQuantitative real-time PCR (qPCR) is a highly reliable method for validating gene expression data in molecular studies due to its sensitivity, specificity, and efficiency. To ensure accurate qPCR results, it's essential to normalize the expression data using stable reference genes.METHODSThis study aimed to identify suitable reference genes for qPCR studies in goats by evaluating 18 candidate reference genes (ACTB, BACH1, B2M, GAPDH, HMBS, HPRT1, PGK1, PPIA, PPIB, RPLP0, RPL19, RPS9, RPS15, RPS28, SDHA, TBP, UXT, and YWHAZ) in 10 different caprine tissues (heart, intestine, kidney, liver, lung, muscle, rumen, skin, spleen, and testis). An integrated tool called RefFinder, which incorporates various algorithms like NormFinder, GeNorm, BestKeeper, and ΔCt, was used to assess the stability of expression among these genes.RESULTSAfter thorough analysis, ACTB, PPIB, and B2M emerged as the most stable reference genes, while RPL19, RPS15, and RPS9 were found to be the least stable. The suitability of the selected internal control genes was further validated through target gene analysis, confirming their efficacy in ensuring accurate gene expression profiling in goats.CONCLUSIONThe study determined that the geometric average of ACTB, PPIB, and B2M creates an appropriate normalization factor for gene expression studies in goat tissues.

01 Dec 2024·International Immunopharmacology

Bioinformatics data combined with single-cell analysis reveals patterns of immunoinflammatory infiltration and cell death in melanoma

Article

Author: Cui, Fan ; Liu, Yangying ; Rang, Zhen ; Yang, Ge ; Jin, Li

BACKGRUONDMelanoma is a common cancer in dermatology, but its molecular mechanisms remain poorly explained.AIMUtilizing single-cell analytics and bioinformatics, the work sought to discover the immunological infiltration and cellular molecular mechanisms of melanoma.METHODSMelanoma genes databases were downloaded from GeneCards, and gene expression profiles were chosen from the Gene Expression Omnibus (GSE244889). Establishing and analyzing protein-protein interaction networks for functional enrichment made use of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. The process assesses the immunological cell infiltration variations between normal and malignant samples by Immune Cell AI software program. Different cell type differences were clarified by cell quality control, filtration, removal of batch effects and cell clustering analysis using single cell analysis techniques.RESULTSUsing a variety of machine learning techniques, 20 differentially expressed hub genes were found; among these, TP53, HSP90AB1, HSPA4, RHOA, CCND1, CYCS, PPARG, NFKBIA, CAV1, ANXA5, ENO1, ITGAM, YWHAZ, RELA, SOD1, and VDAC1 were found to be significantly significant. The results of enrichment analysis demonstrated that immune response and inflammatory response were strongly associated with melanoma. Animal mitophagy, ferroptosis, the PI3K-Akt signaling pathway, and the HIF-1 signaling pathway were the primary signaling pathways implicated. Cells of immunity, T-cells, lymphocytes, B-cells, NK-cells, monocytes, and macrophages were shown to be significantly infiltrated in melanoma patients, according to analysis. Single cell analysis also demonstrated that ferroptosis is a significant mechanism of cell death that contributes to the advancement of melanoma and that macrophages are important in the disease.CONCLUSIONIn summary, different immune cell infiltrations-particularly macrophages-have a significant impact on the onset and course of melanoma, and our findings may help direct future investigations into melanoma macrophages.

16 Sep 2024·Proteomics

Matrix stiffness regulates the protein profile of extracellular vesicles of pancreatic cancer cell lines.

Article

Author: Simanic, Isidora ; Cohen, José ; Gazeau, Florence ; Bourgoin-Voillard, Sandrine ; Cascone, Ilaria ; Habert, Damien ; Courty, José ; Vallée, Benoit ; Ferrara, Benedetta ; Nicolas-Boluda, Alba ; Vingert, Benoit ; Seve, Michel ; Castellano, Flavia

The fibrotic stroma characterizing pancreatic ductal adenocarcinoma (PDAC) derives from a progressive tissue rigidification, which induces epithelial mesenchymal transition and metastatic dissemination. The aim of this study was to investigate the influence of matrix stiffness on PDAC progression by analyzing the proteome of PDAC-derived extracellular vesicles (EVs). PDAC cell lines (mPDAC and KPC) were grown on synthetic supports with a stiffness close to non-tumor (NT) or tumor tissue (T), and the protein expression levels in cell-derived EVs were analyzed by a quantitative MS^E label-free mass spectrometry approach. Our analysis figured out 15 differentially expressed proteins (DEPs) in mPDAC-EVs and 20 DEPs in KPC-EVs in response to matrix rigidification. Up-regulated proteins participate to the processes of metabolism, matrix remodeling, and immune response, altogether hallmarks of PDAC progression. A multimodal network analysis revealed that the majority of DEPs are strongly related to pancreatic cancer. Interestingly, among DEPs, 11 related genes (ACTB/ANXA7/C3/IGSF8/LAMC1/LGALS3/PCD6IP/SFN/TPM3/VARS/YWHAZ) for mPDAC-EVs and 9 (ACTB/ALDH2/GAPDH/HNRNPA2B/ITGA2/NEXN/PKM/RPN1/S100A6) for KPC-EVs were significantly overexpressed in tumor tissues according to gene expression profiling interaction analysis (GEPIA). Concerning the potential clinical relevance of these data, the cluster of ACTB, ITGA2, GAPDH and PKM genes displayed an adverse effect (p < 0.05) on the overall survival of PDAC patients.

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YWHAZ

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