RHOD

Last update 08 May 2025

Basic Info

Synonyms

ARHD, ras homolog family member D, Rho

+ [4]

Introduction

Involved in endosome dynamics. May coordinate membrane transport with the function of the cytoskeleton. Involved in the internalization and trafficking of activated tyrosine kinase receptors such as PDGFRB. Participates in the reorganization of actin cytoskeleton; the function seems to involve WHAMM and includes regulation of filopodia formation and actin filament bundling. Can modulate the effect of DAPK3 in reorganization of actin cytoskeleton and focal adhesion dissolution.

100 Clinical Results associated with RHOD

100 Translational Medicine associated with RHOD

0 Patents (Medical) associated with RHOD

117

Literatures (Medical) associated with RHOD

05 Mar 2025·Microbial Genomics

Differential effect of monoterpenes and flavonoids on the transcription of aromatic ring-hydroxylating dioxygenase genes in Rhodococcus opacus C1 and Rhodococcus sp. WAY2

Article

Author: Semerad, Jaroslav ; Uhlik, Ondrej ; Strejcek, Michal ; Tadrosova, Manuela ; Suman, Jachym ; Cajthaml, Tomas ; Zubrova, Andrea ; Pajer, Petr

Aromatic ring-hydroxylating dioxygenases (ARHDs) play a crucial role in the aerobic biodegradation of both natural and anthropogenic aromatic compounds. Although their ability to process contaminants is not entirely understood, it is thought to have evolved from the transformation of structurally similar secondary plant metabolites (SPMs). Hence, to investigate this connection, we tested a variety of SPMs from the monoterpene and flavonoid classes as carbon sources and transcriptional effectors of several phylogenetically distant ARHD genes involved in the degradation of aromatic pollutants. Specifically, we focused on bphA1, nahA1 and phtA1 in Rhodococcus opacus C1, whose genomic analysis is also presented hereinafter, and bphA1a, nahA1-bphA1b and etbA1ab in Rhodococcus sp. WAY2. Whilst induction was only observed with (R)-carvone for bphA1a and nahA1-bphA1b of strain WAY2, and with p-cymene for nahA1 and nahA1-bphA1b of strains C1 and WAY2, respectively, an extensive inhibition by flavonoids was observed for most of the genes in both strains. To the best of our knowledge, our study is the first to report the effect of flavonoids and monoterpenes on the transcription of nahA1, etbA1 and phtA1 genes. In addition, we show that, in contrast to pseudomonads, many flavonoids inhibit the transcription of the ARHD genes in rhodococci. Thus, our work provides a new perspective on flavonoids as the transcriptional effectors of ARHDs, highlighting the significant variability of these enzymes and the divergent responses that they elicit. Moreover, our results contribute to understanding the complex interactions between microorganisms and SPMs and provide insights into the molecular basis of a number of them.

01 Dec 2024·Current Medicinal Chemistry

Identifying Hub Genes for Glaucoma based on Bulk RNA Sequencing Data and Multi-machine Learning Models

Article

Author: Xie, Yangyang ; Yu, Kai

Aims:The aims of this study were to determine hub genes in glaucoma through multiple machine learning algorithms.Background:Glaucoma has afflicted many patients for many years, with excessive pressure in the eye continuously damaging the nervous system and leading to severe blindness. An effective molecular diagnostic method is currently lacking.Objective:The present study attempted to reveal the molecular mechanism and gene regulatory network of hub genes in glaucoma, followed by an attempt to reveal the drug-gene-disease network regulated by hub genes.Methods:A microarray sequencing dataset (GSE9944) was obtained through the Gene Expression Omnibus database. The differentially expressed genes in Glaucoma were identified. Based on these genes, we constructed three machine learning models for feature training, Random Forest model (RF), Least absolute shrinkage and selection operator regression model (LASSO), and Support Vector Machines model (SVM). Meanwhile, Weighted Gene Co-Expression Network Analysis (WGCNA) was performed for GSE9944 expression profiles to identify Glaucoma-related genes. The overlapping genes in the four groups were considered as hub genes of Glaucoma. Based on these genes, we also constructed a molecular diagnostic model of Glaucoma. In this study, we also performed molecular docking analysis to explore the gene-drug network targeting hub genes. In addition, we evaluated the immune cell infiltration landscape in Glaucoma samples and normal samples by applying CIBERSORT method.Results:8 hub genes were determined: ATP6V0D1, PLEC, SLC25A1, HRSP12, PKN1, RHOD, TMEM158 and GSN. The diagnostic model showed excellent diagnostic performance (area under the curve=1). GSN might positively regulate T cell CD4 naïve as well as negatively regulate T cell regulation (Tregs). In addition, we constructed gene-drug networks in an attempt to explore novel therapeutic agents for Glaucoma.Conclusion:Our results systematically determined 8 hub genes and established a molecular diagnostic model that allowed the diagnosis of Glaucoma. Our study provided a basis for future systematic studies of Glaucoma pathogenesis.

01 Aug 2024·Advanced Science

Identification and Characterization of Metastasis‐Initiating Cells in ESCC in a Multi‐Timepoint Pulmonary Metastasis Mouse Model

Article

Author: Lyu, Yingchen ; Guan, Xin-Yuan ; Jiang, Peng ; Qin, Yanru ; Zhang, Yu ; Ru, Beibei ; Lin, Jiarun ; Zhou, Hongyu ; Lee, Victor Ho-Fun ; Wang, Songna ; Wong, Ching Ngar

AbstractMetastasis is the biggest obstacle to esophageal squamous cell carcinoma (ESCC) treatment. Single‐cell RNA sequencing analyses are applied to investigate lung metastatic ESCC cells isolated from pulmonary metastasis mouse model at multiple timepoints to characterize early metastatic microenvironment. A small population of parental KYSE30 cell line (Cluster S) resembling metastasis‐initiating cells (MICs) is identified because they survive and colonize at lung metastatic sites. Differential expression profile comparisons between Cluster S and other subpopulations identified a panel of 7 metastasis‐initiating signature genes (MIS), including CD44 and TACSTD2, to represent MICs in ESCC. Functional studies demonstrated MICs (CD44high) exhibited significantly enhanced cell survival (resistances to oxidative stress and apoptosis), migration, invasion, stemness, and in vivo lung metastasis capabilities, while bioinformatics analyses revealed enhanced organ development, stress responses, and neuron development, potentially remodel early metastasis microenvironment. Meanwhile, early metastasizing cells demonstrate quasi‐epithelial‐mesenchymal phenotype to support both invasion and anchorage. Multiplex immunohistochemistry (mIHC) staining of 4 MISs (CD44, S100A14, RHOD, and TACSTD2) in ESCC clinical samples demonstrated differential MIS expression scores (dMISs) predict lymph node metastasis, overall survival, and risk of carcinothrombosis.

Analysis

Perform a panoramic analysis of this field.

view full example data

AI Agents Built for Biopharma Breakthroughs

Accelerate discovery. Empower decisions. Transform outcomes.

Get started for free today!

Accelerate Strategic R&D decision making with Synapse, PatSnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.

Start your data trial now!

Synapse data is also accessible to external entities via APIs or data packages. Empower better decisions with the latest in pharmaceutical intelligence.

Bio

Bio Sequences Search & Analysis

Chemical

Chemical Structures Search & Analysis

RHOD

Basic Info

Related

Analysis