ArticleInternational journal of environmental research and public health2022
Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 7 citations in OpenAlex.
- Pseudogene Coexpression Networks Reveal a Robust Prognostic Signature for Pediatric B-ALL Survival.Cancer research communications · 2026Article
- Pseudogenes in Cancer: State of the Art.Cancers · 2023Review
- In Vitro Cell Transformation Assays: A Valuable Approach for Carcinogenic Potentiality Assessment of Nanomaterials.International journal of molecular sciences · 2023Review
- Inflammatory Genes Associated with Pristine Multi-Walled Carbon Nanotubes-Induced Toxicity in Ocular Cells.International journal of nanomedicine · 2023Article
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6 authors at 2 institutions in 1 country.
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Abstract
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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