Predicting molecular mechanisms, pathways, and health outcomes induced by Juul e-cigarette aerosol chemicals using the Comparative Toxicogenomics Database

Grondin, Cynthia; Davis, Allan Peter; Wiegers, Jolene; Wiegers, Thomas C.; Sciaky, Daniela; Johnson, Robin J.; Mattingly, Carolyn J.

doi:10.1016/j.crtox.2021.08.001

Cited by 51 publications

(34 citation statements)

References 46 publications

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“…To predict potential drugs that may prevent and treat CNT-induced lung cancer, the Comparative Toxicogenomics Database (CTD, ; accessed on 12 October 2021) [ 32 ] was searched to obtain the chemical interactions of hub lncRNAs and pseudogenes associated with CNT exposure. Only chemical drugs that reversed the expression levels of lncRNAs and pseudogenes and involved in cancer initiation and development were screened (that is, if the lncRNA was upregulated, we selected the drugs that decreased its expression levels).…”

Section: Methodsmentioning

confidence: 99%

Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs

Chang

Xie

et al. 2022

IJERPH

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Mounting evidence has linked carbon nanotube (CNT) exposure with malignant transformation of lungs. Long non-coding RNAs (lncRNAs) and pseudogenes are important regulators to mediate the pathogenesis of diseases, representing potential biomarkers for surveillance of lung carcinogenesis in workers exposed to CNTs and possible targets to develop preventive strategies. The aim of this study was to screen crucial lncRNAs and pseudogenes and predict preventive drugs. GSE41178 (small airway epithelial cells exposed to single- or multi-walled CNTs or dispersant control) and GSE56104 (lung epithelial cells exposed to single-walled CNTs or dispersant control) datasets were downloaded from the Gene Expression Omnibus database. Weighted correlation network analysis was performed for these two datasets, and the turquoise module was preserved and associated with CNT-induced malignant phenotypes. In total, 24 lncRNAs and 112 pseudogenes in this module were identified as differentially expressed in CNT-exposed cells compared with controls. Four lncRNAs (MEG3, ARHGAP5-AS1, LINC00174 and PVT1) and five pseudogenes (MT1JP, MT1L, RPL23AP64, ZNF826P and TMEM198B) were predicted to function by competing endogenous RNA (MEG3/RPL23AP64-hsa-miR-942-5p-CPEB2/PHF21A/BAMBI; ZNF826P-hsa-miR-23a-3p-SYNGAP1, TMEM198B-hsa-miR-15b-5p-SYNGAP1/CLU; PVT1-hsa-miR-423-5p-PSME3) or co-expression (MEG3/MT1L/ZNF826P/MT1JP-ATM; ARHGAP5-AS1-TMED10, LINC00174-NEDD4L, ARHGAP5-AS1/PVT1-NIP7; MT1L/MT1JP-SYNGAP1; MT1L/MT1JP-CLU) mechanisms. The expression levels and prognosis of all genes in the above interaction pairs were validated using lung cancer patient samples. The receiver operating characteristic curve analysis showed the combination of four lncRNAs, five pseudogenes or lncRNAs + pseudogenes were all effective for predicting lung cancer (accuracy >0.8). The comparative toxicogenomics database suggested schizandrin A, folic acid, zinc or gamma-linolenic acid may be preventive drugs by reversing the expression levels of lncRNAs or pseudogenes. In conclusion, this study highlights lncRNAs and pseudogenes as candidate diagnostic biomarkers and drug targets for CNT-induced lung cancer.

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Section: Methodsmentioning

confidence: 99%

Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs

Chang

Xie

et al. 2022

IJERPH

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“…SwissTargetPrediction allows us to estimate the most probable macromolecular targets of a small molecule [ 25 , 26 ]. The CTD was used to screen for genes associated with UC [ 27 ]. For further confirmation, AutoDock Vina, a widely cited open-source molecular docking software [ 28 ] was used, and the final docking results suggested that PKC-θ might be the target protein of anemonin.…”

Section: Discussionmentioning

confidence: 99%

Anti-inflammatory effects of anemonin on acute ulcerative colitis via targeted regulation of protein kinase C-θ

et al. 2022

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Background Ulcerative colitis (UC) is an inflammatory bowel disease that causes continuous mucosal inflammation. Anemonin is a natural molecule from the Ranunculaceae and Gramineae plants that exerts anti-inflammatory properties. This study aimed to explore the effects and mechanisms of anemonin on UC. Methods C57BL/6 mice were administered dextran sulphate sodium (DSS; 3% [w/v]) to establish an animal model of UC. Mice were treated with an intraperitoneal injection of anemonin. Body weight and the disease activity index (DAI) were recorded. Haematoxylin and eosin staining, RT-qPCR, ELISA, and western blotting were performed to evaluate the histopathological changes and tissue inflammation. HT-29 cells were treated with lipopolysaccharide (LPS) and anemonin. Cell inflammation was evaluated using RT-qPCR and western blotting. The target proteins of anemonin were predicted using bioinformatics analysis and confirmed in vitro and in vivo. Results Anemonin improved DSS-induced body weight loss, shortened colon length, increased DAI, and induced pathological changes in the colon tissue of mice. Anemonin inhibited DSS-induced colon tissue inflammation as the release of IL-1β, TNF-α, and IL-6 was significantly suppressed. Additionally, anemonin attenuated LPS-induced cytokine production in HT-29 cells. PKC-θ was predicted as a target protein of anemonin. Anemonin did not affect PRKCQ gene transcription, but inhibited its translation. PRKCQ overexpression partially reversed the protective effects of anemonin on HT-29 cells. Adeno-associated virus delivery of the PRKCQ vector significantly reversed the protective effects of anemonin on the mouse colon. Conclusions Anemonin has the potential to treat UC. The anti-inflammatory effects of anemonin may be mediated through targeting PKC-θ.

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“…The NetworkAnalyst is used to construct a protein–chemical interaction network. The protein–chemical interaction comes from the Comparative Toxicogenomics Database ( 26 ), which contains the interactions between chemical substances and genes in the literature.…”

Section: Methodsmentioning

confidence: 99%

LPIN1 Is a Regulatory Factor Associated With Immune Response and Inflammation in Sepsis

et al. 2022

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ObjectivesSepsis is a clinical disease that is typically treated in the intensive care unit, and the complex pathophysiology under this disease has not been thoroughly understood. While ferroptosis is involved in inflammation and infection, its effect in sepsis is still unknown. The study aimed to identify ferroptosis-related genes in sepsis, providing translational potential therapeutic targets.MethodsThe dataset GSE65682 was used to download the sample source from the Gene Expression Omnibus (GEO) database. Consensus weighted gene co-expression network analysis (WGCNA) was performed to find suspected modules of sepsis. The differentially expressed genes (DEGs) most significantly associated with mortality were intersected with those altered by lipopolysaccharide (LPS) treatment and were further analyzed for the identification of main pathways of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The related pathway markers were further verified by qPCR.ResultsA total of 802 blood samples with sepsis were included for WGCNA, which identified 21 modules. Intersected with ferroptosis databases and LPS treatment groups, we identified two ferroptosis-related genes: PEBP1 and LPIN1. Only LPIN1 contributes to a poor outcome. Then, 205 DEGs were further identified according to the high or low LPIN1 expression. Among them, we constructed a gene regulatory network with several transcriptional factors using the NetworkAnalyst online tool and identified that these genes mostly correlate with inflammation and immune response. The immune infiltration analysis showed that lower expression of LPIN1 was related to macrophage infiltration and could be an independent predictor factor of the survival status in sepsis patients. Meanwhile, the multivariate Cox analysis showed that LPIN1 had a significant correlation with survival that was further verified by in vitro and in vivo experiments.ConclusionIn conclusion, LPIN1 could become a reliable biomarker for patient survival in sepsis, which is associated with immune and inflammation status.

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Predicting molecular mechanisms, pathways, and health outcomes induced by Juul e-cigarette aerosol chemicals using the Comparative Toxicogenomics Database

Abstract: Graphical abstract

Cited by 51 publications

References 46 publications

Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs

Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs

Anti-inflammatory effects of anemonin on acute ulcerative colitis via targeted regulation of protein kinase C-θ

LPIN1 Is a Regulatory Factor Associated With Immune Response and Inflammation in Sepsis

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