IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i5p2936-d762893.html
   My bibliography  Save this article

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

Author

Listed:
  • Guangtao Chang

    (College of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China)

  • Dongli Xie

    (College of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China)

  • Jianchen Hu

    (College of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China)

  • Tong Wu

    (Shanghai Jing Rui Yang Industrial Co., Ltd., Shanghai 200122, China)

  • Kangli Cao

    (Shanghai Institute of Spacecraft Equipment, Shanghai 200240, China)

  • Xiaogang Luo

    (College of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China)

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.

Suggested Citation

  • Guangtao Chang & Dongli Xie & Jianchen Hu & Tong Wu & Kangli Cao & Xiaogang Luo, 2022. "Identification of Candidate lncRNA and Pseudogene Biomarkers Associated with Carbon-Nanotube-Induced Malignant Transformation of Lung Cells and Prediction of Potential Preventive Drugs," IJERPH, MDPI, vol. 19(5), pages 1-26, March.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:5:p:2936-:d:762893
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/5/2936/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/5/2936/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:5:p:2936-:d:762893. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.