Research Paper Volume 15, Issue 21 pp 11970—11984
Identification of epithelial-mesenchymal transition-related biomarkers in lung adenocarcinoma using bioinformatics and lab experiments
- 1 Department of Thoracic Surgery, The Second Affiliated Hospital of Soochow University, Suzhou, China
- 2 Department of Cardiothoracic Surgery, People’s Hospital of Chizhou, Chizhou, China
- 3 Department of Operation, The Second Affiliated Hospital of Soochow University, Suzhou, China
- 4 Department of Obstetrics, People’s Hospital of Chizhou, Chizhou, China
- 5 Department of Pathology, The Second Affiliated Hospital of Soochow University, Suzhou, China
Received: August 10, 2023 Accepted: September 27, 2023 Published: October 31, 2023
https://doi.org/10.18632/aging.205159How to Cite
Copyright: © 2023 Cheng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: Lung adenocarcinoma accounts for approximately 40% of lung cancer cases and poses a serious threat to human health. Therefore, there is an urgent need to identify central biomarkers in lung adenocarcinoma.
Methods: We first identified the EMT-associated genes in LUAD based on the TCGA cohort. Then we screened these 90 EMT-associated genes using univariate Cox regression analysis and LASSO regression analysis to develop a prognostic gene signature in the training set. The predictive performance of the gene signature was assessed in the validation set and multiple external test sets using the ROC cure, C index and log-rank tests. RT-PCR, western blot, wound healing assays, and siRNA methods were further used to investigate the role of PLEK2 in tumor behaviors.
Results: Eight genes (CCNB1, PLEK2, DERL3, C1QTNF6, DLGAP5, HMMR, GJB3, and SPOCK1) were eventually selected to develop an eight-gene signature. The 5-year AUC of the gene signature has a robust predictive ability both for predicting overall survival (0.774, 0.756, and 0.669 in the external test sets, respectively), and for progression free survival (0.774, 0.746, and 0.755 in the external test sets, respectively). C-index of the gene signature was 0.961 ± 0.005, 0.916 ± 0.011, and 0.868 ± 0.234 in the external test sets, respectively. Four genes (C1QTNF6, DLGAP5, HMMR, and PLEK2) were identified as key genes in LUAD progression, which were upregulated in the cancerous tissue compared with in the normal tissue (P < 0.001), and correlated with an unwanted prognosis in lung cancer (P < 0.05). PLEK2 was used as an example to explore its effect on LUAD progression in vitro using RT-PCR, western blot, CCK8, si-RNA and wound healing assay. Silencing of PLEK2 was shown to reduce proliferative and migrated ability of lung cancer cells via prohibition of autophagy.
Conclusions: This study developed a novel EMT-related gene signature benefiting precision medicine, and identified four pivotal genes which can serve as therapeutic targets in LUAD. Four key genes can serve as molecular targets for patients with LUAD; silencing of PLEK2 was shown to reduce proliferative and migrated ability of lung cancer cells via prohibition of autophagy.
Abbreviations
CCNB1: Cyclin B1; PLEK2: Pleckstrin 2; DERL3: Derlin 3; C1QTNF6: C1q and TNF related 6; DLGAP5: DLG associated protein 5; HMMR: Hyaluronan mediated motility receptor; GJB3: Gap junction protein beta 3; SPOCK1: SPARC (osteonectin), cwcv and kazal like domains proteoglycan 1.