DOCK4

Last update 23 Jan 2025

Basic Info

Synonyms

dedicator of cytokinesis 4, Dedicator of cytokinesis protein 4, DOCK4

+ [2]

Introduction

Functions as a guanine nucleotide exchange factor (GEF) that promotes the exchange of GDP to GTP, converting inactive GDP-bound small GTPases into their active GTP-bound form (PubMed:12628187, PubMed:16464467). Involved in regulation of adherens junction between cells (PubMed:12628187). Plays a role in cell migration (PubMed:20679435). Has a higher guanine nucleotide exchange factor activity compared to other isoforms.

100 Clinical Results associated with DOCK4

100 Translational Medicine associated with DOCK4

0 Patents (Medical) associated with DOCK4

106

Literatures (Medical) associated with DOCK4

31 Dec 2025·Annals of Medicine

Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer

Article

Author: Chen, Min ; Zhang, Lisha ; Wang, Meifang ; Huang, Litao ; Zhang, Xiaoqiao ; Wang, Dandan ; Chen, Yong ; Chen, Yanhui ; Sun, Junjun ; Chen, Yanliang ; Zhou, Chan

BACKGROUNDNon-small cell lung cancer (NSCLC) is a fatal disease, and radioresistance is an important factor leading to treatment failure and disease progression. The objective of this research was to detect radioresistance-related genes (RRRGs) with prognostic value in NSCLC.METHODSThe weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) analysis were performed to identify RRRGs using expression profiles from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO) regression and random survival forest (RSF) were used to screen for prognostically relevant RRRGs. Multivariate Cox regression was used to construct a risk score model. Then, Immune landscape and drug sensitivity were evaluated. The biological functions exerted by the key gene LBH were verified by in vitro experiments.RESULTSNinety-nine RRRGs were screened by intersecting the results of DEGs and WGCNA, then 11 hub RRRGs associated with survival were identified using machine learning algorithms (LASSO and RSF). Subsequently, an eight-gene (APOBEC3B, DOCK4, IER5L, LBH, LY6K, RERG, RMDN2 and TSPAN2) risk score model was established and demonstrated to be an independent prognostic factor in NSCLC on the basis of Cox regression analysis. The immune landscape and sensitivity to anti-tumour drugs showed significant disparities between patients categorized into different risk score subgroups. In vitro experiments indicated that overexpression of LBH enhanced the radiosensitivity of A549 cells, and knockdown LBH reversed the cytotoxicity induced by X-rays.CONCLUSIONOur study developed an eight-gene risk score model with potential clinical value that can be adopted for choice of drug treatment and prognostic prediction. Its clinical routine use may assist clinicians in selecting more rational practices for individuals, which is important for improving the prognosis of NSCLC patients. These findings also provide references for the development of potential therapeutic targets.

01 Jan 2025·Anticancer Research

Gene Expression Profiles in Ovarian Cancer Tissues as a Potential Tool to Predict Platinum-based Chemotherapy Resistance

Review

Author: Talijanovic, Melanija ; Høgdall, Estrid V ; Lopacinska-Jørgensen, Joanna

BACKGROUND/AIMOvarian cancer (OC) is one of the leading gynecological causes of death among women. The current standard treatment for OC is debulking surgery followed by platinum-based chemotherapy treatments; however, despite initial success to treatment many patients experience relapses. Currently, there are no available tests to predict sensitivity or resistance to chemotherapy. The aim of this review is to investigate the literature regarding prediction of chemotherapy resistance in patients with OC using gene expression patterns.MATERIALS AND METHODSThe literature research on PubMed resulted in a total of 490 articles published from November 20^th, 2018, to November 20^th, 2024. We selected only the original studies that described the comparison of mRNA profiles between platinum-sensitive and -resistant OC patients. Studies were included if mRNA expression was measured in human tissue by gene expression microarray, RNA sequencing and quantitative real-time PCR.RESULTSForty-four articles were included covering data from discovery cohorts obtained from hospitals and universities, as well as additional data obtained from online datasets from Gene Expression Omnibus and The Cancer Genome Atlas Program that provided either single- or multiple mRNA signatures that could discriminate between chemotherapy-sensitive and chemotherapy-resistant OC patients. OCs at all stages and histological subtypes were used but most articles included exclusively high-grade serous OC patients.CONCLUSIONmRNA-based biomarkers to predict chemotherapy resistance in patients have not yet been clinically implemented, but many differentially expressed genes between chemotherapy-resistant and -sensitive patients have been reported, such as ABCG2, DOCK4, DUSP1, DUSP4, DUSP5, GADD45B, HELQ, HOXA9, KLF4, and NR4A1, which could be compelling biomarker candidates for further studies.

01 Nov 2024·Journal of Lipid Research

The two major splice variants of scavenger receptor BI differ by their interactions with lipoproteins and cellular localization in endothelial cells

Article

Author: Schlumpf, Eveline ; von Eckardstein, Arnold ; Frey, Kathrin ; Potapenko, Anton ; Robert, Jérôme ; Rohrer, Lucia ; Wollscheid, Bernd

The scavenger receptor BI (SR-BI) facilitates the transport of both HDL and LDL through endothelial cells. Its two splice variants, SR-BI_var1 and SR-BI_var2, differ in their carboxy terminal domains. Only SR-BI_var1 contains the putative binding sites for the adapter proteins PDZ domain containing protein 1 (PDZK1) and dedicator of cytokinesis 4 (DOCK4), which limit the cell surface abundance and internalization of the receptor. To investigate the cellular localization of the SR-BI variants and their interaction with lipoproteins in endothelial cells, EA.hy926 cells were stably transfected with vectors encoding untagged, GFP- or mCherry-tagged constructs of the two SR-BI variants. Additionally, the cells were transfected with shRNAs against PDZK1 or DOCK4. Microscopy investigation showed that SR-BI_var1 was predominantly localized on the cell surface together with clathrin whereas SR-BI_var2 was absent from the cell surface but retrieved in endosomes and lysosomes. Accordingly, only SR-BI_var1 increased lipoprotein binding to endothelial while HDL and LDL uptake were enhanced by both variants. Silencing of PDZK1 or DOCK4 only reduced HDL association in SR-BI_var2 overexpressing cells while LDL association was reduced both in WT and SR-BI_var2 overexpressing cells. In conclusion, either SR-BI variant facilitates the uptake of HDL and LDL into endothelial cells, however by different mechanisms and trafficking routes. This dual role may explain why the loss of DOCK4 or PDZK1 differently affects the uptake of HDL and LDL in different endothelial cells.

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