The Roles of Cullin-2 E3 Ubiquitin Ligase Complex in Cancer

Liu, Xijuan; Zurlo, Giada; Zhang, Qing

doi:10.1007/978-981-15-1025-0_11

Cited by 14 publications

(13 citation statements)

References 91 publications

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“…CUL2is one of the seven members of Cullin family. It can participate in the regulation of cell cycle, proliferation, apoptosis, differentiation, gene expression, transcription regulation, signal transmission, damage repair, inflammation and immunity.CUL2 affects the occurrence of renal cell carcinoma by promoting the substrate ubiquitination and degradation ( Liu, Zurlo & Zhang, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis

Zhang

Zhou

Liu

et al. 2022

PeerJ

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Background Glioblastoma (GBM) is the most common malignant tumor in the central system with a poor prognosis. Due to the complexity of its molecular mechanism, the recurrence rate and mortality rate of GBM patients are still high. Therefore, there is an urgent need to screen GBM biomarkers to prove the therapeutic effect and improve the prognosis. Results We extracted data from GBM patients from the Gene Expression Integration Database (GEO), analyzed differentially expressed genes in GEO and identified key modules by weighted gene co-expression network analysis (WGCNA). GSE145128 data was obtained from the GEO database, and the darkturquoise module was determined to be the most relevant to the GBM prognosis by WGCNA (r = − 0.62, p = 0.01). We performed enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to reveal the interaction activity in the selected modules. Then Kaplan-Meier survival curve analysis was used to extract genes closely related to GBM prognosis. We used Kaplan-Meier survival curves to analyze the 139 genes in the darkturquoise module, identified four genes (DARS/GDI2/P4HA2/TRUB1) associated with prognostic GBM. Low expression of DARS/GDI2/TRUB1 and high expression of P4HA2 had a poor prognosis. Finally, we used tumor genome map (TCGA) data, verified the characteristics of hub genes through Co-expression analysis, Drug sensitivity analysis, TIMER database analysis and GSVA analysis. We downloaded the data of GBM from the TCGA database, the results of co-expression analysis showed that DARS/GDI2/P4HA2/TRUB1 could regulate the development of GBM by affecting genes such as CDC73/CDC123/B4GALT1/CUL2. Drug sensitivity analysis showed that genes are involved in many classic Cancer-related pathways including TSC/mTOR, RAS/MAPK.TIMER database analysis showed DARS expression is positively correlated with tumor purity (cor = 0.125, p = 1.07e−02)), P4HA2 expression is negatively correlated with tumor purity (cor =−0.279, p = 6.06e−09). Finally, GSVA analysis found that DARS/GDI2/P4HA2/TRUB1 gene sets are closely related to the occurrence of cancer. Conclusion We used two public databases to identify four valuable biomarkers for GBM prognosis, namely DARS/GDI2/P4HA2/TRUB1, which have potential clinical application value and can be used as prognostic markers for GBM.

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Section: Discussionmentioning

confidence: 99%

Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis

Zhang

Zhou

Liu

et al. 2022

PeerJ

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“…This complex is best known for detecting hypoxia-inducible (HIFs) polyubiquitination and proteasome degeneration [ 59 ]. Under hypoxic conditions, HIF-1 alpha and HIF-2 alpha bind together to form HIF-1beta heterodimers, which then transmit to the nucleus, where they stimulate downstream gene expression, including vascular endothelial growth factor (VEGF) [ 60 ]. The absence of wild VHL promotes incorrect activation of targeted genes, which contributes to tumorigenesis [ 61 ].…”

Section: Reviewmentioning

confidence: 99%

DNA Methylation and Epigenetic Events Underlying Renal Cell Carcinomas

Tanvir¹,

Hassan²,

Albeladi³

2022

Cureus

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Renal cell carcinoma (RCC) refers to a group of tumors that develop from the epithelium of the kidney tubes, including clear cell RCC, papillary RCC, and chromophobe RCC. Most clear cell renal carcinomas have a large histologic subtype, genetic or epigenetic von Hippel-Lindau (VHL). A comprehensive analysis of the genetic modification genome suggested that chromosome 3p loss and chromosome gains 5q and 7 may be significant copy defects in the development of clear RCC. A more potent RCC may develop if chromosome 1p, 4, 9, 13q, or 14q is also lost. Renal carcinogenesis is not associated with chronic inflammation or histological changes. However, if regional hypermethylation of DNA in CpG C-type islands has already accumulated in cancer-free kidney tissue, it implies that the presence of malignant kidney lesions may also be detected by modified DNA methylation. Modification of DNA methylation in cancerous kidney tissue may advance kidney tissue to epigenetic mutations and genes, leading to more serious cancers and even determining a patient's outcome. The genetic and epigenetic profile provides accurate predictors for patients with kidney cancer. New genetic and epigenetic analysis technologies will help to speed up the identification of vital cells for kidney cancer prevention, diagnosis, and treatment.

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“…NEDD8 bound to Cullin proteins also prevents the binding of Cullin-associated and NEDDylation-dissociated protein 1 (CAND1) [22], a protein which facilitates the exchange of substrate receptors from the CRL (reviewed in [23]). For a more detailed description of canonical NEDD8-Cullin interactions, the reader is encouraged to consult a compilation of recently published, in-depth review articles [15,[23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]. The remainder of this article will focus instead on instances where NEDD8 modification has been detected on other proteins and what function this may have in the cell (see Figure 1 for a summary of canonical and non-canonical NEDD8 substrates).…”

Section: Nedd8 Modification Of Cullinsmentioning

confidence: 99%

The Many Potential Fates of Non-Canonical Protein Substrates Subject to NEDDylation

Vijayasimha

Dolan

2021

Cells

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Neuronal precursor cell-expressed developmentally down-regulated protein 8 (NEDD8) is a ubiquitin-like protein (UBL) whose canonical function involves binding to, and thus, activating Cullin–Ring finger Ligases (CRLs), one of the largest family of ubiquitin ligases in the eukaryotic cell. However, in recent years, several non-canonical protein substrates of NEDD8 have been identified. Here we attempt to review the recent literature regarding non-canonical NEDDylation of substrates with a particular focus on how the covalent modification of NEDD8 alters the protein substrate. Like much in the study of ubiquitin and UBLs, there are no clear and all-encompassing explanations to satisfy the textbooks. In some instances, NEDD8 modification appears to alter the substrates localization, particularly during times of stress. NEDDylation may also have conflicting impacts upon a protein’s stability: some reports indicate NEDDylation may protect against degradation whereas others show NEDDylation can promote degradation. We also examine how many of the in vitro studies measuring non-canonical NEDDylation were conducted and compare those conditions to those which may occur in vivo, such as cancer progression. It is likely that the conditions used to study non-canonical NEDDylation are similar to some types of cancers, such as glioblastoma, colon and rectal cancers, and lung adenocarcinomas. Although the full outcomes of non-canonical NEDDylation remain unknown, our review of the literature suggests that researchers keep an open mind to the situations where this modification occurs and determine the functional impacts of NEDD8-modification to the specific substrates which they study.

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The Roles of Cullin-2 E3 Ubiquitin Ligase Complex in Cancer

Cited by 14 publications

References 91 publications

Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis

Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis

DNA Methylation and Epigenetic Events Underlying Renal Cell Carcinomas

The Many Potential Fates of Non-Canonical Protein Substrates Subject to NEDDylation

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