Systemic Expression Analysis Reveals Prognostic Significance of WIPI3 in Hepatocellular Carcinoma

Liang, Taotao; Shao, Qi; Deng, Zhichao; Wang, Ting; Kang, Qiaozhen

doi:10.3389/fgene.2020.00847

Cited by 5 publications

(2 citation statements)

References 51 publications

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“…The eukaryotic translation initiation factor 4A3 (eIF4A3) is known to be involved in the stimulation of ALYREF expression (21), and eIF4A3 is also a core component of the exon junction complex (22). Importantly, eIF4A3 is also a key mediator of RNA splicing and spliced mRNA nuclear export (23) and has been shown to be involved with the coordination and regulation of the HCC cell cycle (24). However, specific mechanisms and interactions between ALYREF and eIF4A3 are currently unknown, so determining whether ALYREF and eIF4A3 interact in HCC is of great interest.…”

Section: Introductionmentioning

confidence: 99%

Multi-Omic Analyses of the m5C Regulator ALYREF Reveal Its Essential Roles in Hepatocellular Carcinoma

Xue

Zhao

et al. 2021

Front. Oncol.

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The ALYREF protein acts as a crucial epigenetic regulator in several cancers. However, the specific expression levels and functional roles of ALYREF in cancers are largely unknown, including for hepatocellular carcinoma (HCC). In a pan-cancer tissue analysis that included HCC, we assessed the expression of ALYREF compared to normal tissues using The Cancer Genome Atlas database. Associations between ALYREF gene expression and the clinical characteristics of HCC patient samples were assessed using the UALCAN database. Kaplan-Meier plots were performed to assess HCC patient prognosis, and the TIMER database was used to explore associations between ALYREF expression and immune-cell infiltrations. The same methods were used to assess eIF4A3 expression in HCC patient samples. In addition, ALYREF- and elF4A3-related differentially expressed genes (DEGs) were determined using LinkedOmics, associated protein functionalities were predicted for positively associated DEGs, and both the TargetScan and miRDB databases were used to predict potential upstream miRNAs for control of ALYREF and eIF4A3 expression. We found that ALYREF gene expression was dysregulated in several cancers and was significantly elevated in HCC patient tissue samples and HCC cell lines. The overexpression of ALYREF was significantly related to both advanced tumor-node-metastasis stages and poor HCC prognosis. Furthermore, we found that eIF4A3 expression was significantly correlated with ALYREF expression, and that upregulated eIF4A3 was significantly associated with poor HCC patient outcomes. In the protein-protein interaction network, we identified eight hub genes based on the positively associated DEGs in common between ALYREF and eIF4A3, and the high expression levels of these hub genes were positively associated with patient clinical outcomes. In addition, we identified miR-4666a-5p and miR-6124 as potential regulators of ALYREF and eIF4A3 expression. These findings suggest that increased ALYREF expression may function as a novel biomarker for both HCC diagnosis and prognosis predictions.

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Section: Introductionmentioning

confidence: 99%

Multi-Omic Analyses of the m5C Regulator ALYREF Reveal Its Essential Roles in Hepatocellular Carcinoma

Xue

Zhao

et al. 2021

Front. Oncol.

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“…TCGA data-based survival analysis was carried out using the GEPIA (Tang et al 2017) (http://gepia2.cancerpku.cn/#survival). The TCGA cancer datasets used in the analysis include LIHC (hepatocellular carcinoma), PRAD (Prostate adenocarcinoma), CESC (cervical squamous carcinoma) and COAD (colorectal adenocarcinoma) (Liang et al 2020).…”

Section: Analysis Of Clinical Data Samplesmentioning

confidence: 99%

Target Validation and Structure-Based Virtual Screening to Discover Potential Lead Molecules against the oncogenic NSD1 histone methyltransferase

Bhat

Gahlawat

Kumar

et al. 2023

Preprint

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The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. TCGA clinical data, molecular expression techniques were used to validate the target and structure-based virtual screening was performed to design hits against NSD1. Clinical data analysis suggests the role of NSD1 in metastasis, prognosis and influence on overall survival in various malignancies. Furthermore, the mRNA and protein expression profile of NSD1 was evaluated in various cell lines. NSD1 was exploited as a target protein for in silico design of inhibitors using two major databases including ZINC15 and ChemDiv by structure-based virtual screening approach. Virtual screening was performed using the pharmacophore hypothesis designed with a protein complex S-adenosyl-l-methionine (SAM) as an endogenous ligand. Subsequently, a combined score was used to distinguish the top 10 compounds from the docking screened compounds having high performance in all four scores (docking score, XP, Gscore, PhaseScreenScore, and MMGBSA delta G Bind). Finally, the top three Zinc compounds were subjected to molecular dynamic simulation. The binding MMGBSA data suggests that ZINC000257261703 and ZINC000012405780 can be taken for in vitro and in vivo studies as they have lesser MMGBSA energy towards the cofactor binding site of NSD1 than the sinefungin. Our data validates NSD1 as a cancer drug target and provides promising structures that can be utilized for further lead optimization and rational drug design to open new gateways in the field of cancer therapeutics.

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Target validation and structure-based virtual screening to Discover potential lead molecules against the oncogenic NSD1 histone methyltransferase

Bhat

Gahlawat

Kumar

et al. 2023

In Silico Pharmacol.

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The aim of the study was to validate Nuclear receptor-binding SET Domain NSD1 as a cancer drug target followed by the design of lead molecules against NSD1. TCGA clinical data, molecular expression techniques were used to validate the target and structure-based virtual screening was performed to design hits against NSD1. Clinical data analysis suggests the role of NSD1 in metastasis, prognosis and in uence on overall survival in various malignancies.Furthermore, the mRNA and protein expression pro le of NSD1 was evaluated in various cell lines. NSD1 was exploited as a target protein for in silico design of inhibitors using two major databases including ZINC15 and ChemDiv by structure-based virtual screening approach. Virtual screening was performed using the pharmacophore hypothesis designed with a protein complex S-adenosyl-l-methionine (SAM) as an endogenous ligand. Subsequently, a combined score was used to distinguish the top 10 compounds from the docking screened compounds having high performance in all four scores (docking score, XP, Gscore, PhaseScreenScore, and MMGBSA delta G Bind). Finally, the top three Zinc compounds were subjected to molecular dynamic simulation. The binding MMGBSA data suggests that ZINC000257261703 and ZINC000012405780 can be taken for in vitro and in vivo studies as they have lesser MMGBSA energy towards the cofactor binding site of NSD1 than the sinefungin. Our data validates NSD1 as a cancer drug target and provides promising structures that can be utilized for further lead optimization and rational drug design to open new gateways in the eld of cancer therapeutics.

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Systemic Expression Analysis Reveals Prognostic Significance of WIPI3 in Hepatocellular Carcinoma

Cited by 5 publications

References 51 publications

Multi-Omic Analyses of the m5C Regulator ALYREF Reveal Its Essential Roles in Hepatocellular Carcinoma

Multi-Omic Analyses of the m5C Regulator ALYREF Reveal Its Essential Roles in Hepatocellular Carcinoma

Target Validation and Structure-Based Virtual Screening to Discover Potential Lead Molecules against the oncogenic NSD1 histone methyltransferase

Target validation and structure-based virtual screening to Discover potential lead molecules against the oncogenic NSD1 histone methyltransferase

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