Inflammatory cytokine interleukin-17 (IL-17) has been associated with the risk of progressive cancers including lung cancer. However, it remains unclear how IL-17 may contribute to the invasion and development of these inflammation-associated malignancies. Here we aimed to investigate the role of IL-17 in lung cancer cell development. Epithelial-mesenchymal transition (EMT) has been recently proposed as a developmental process which plays an important role in cancer progression and metastases. Here we show that IL-17 might promote EMT in lung cancer cells by inducing the transcriptional repressor ZEB1. Exposure to IL-17 upregulated the signature EMT phenotypic markers vimentin and E-cadherin in lung cancer cells, and compared with controls, increased cell migration was observed in IL-17-treated lung cancer cells. ZEB1 mRNA and protein expression was induced by IL-17, and IL-17 stimulated nuclear localization of phosphorylated ZEB1. Conversely, suppressing ZEB1 expression by ZEB1 siRNA abrogated IL-17-stimulated vimentin expression and cell migration. Moreover, the phosphorylation of IκBα was required for IL-17-induced expression of ZEB1, suggesting the involvement of canonical NF-κB signaling. To check this hypothesis, we used IKK inhibitor BAY 11-7028 to block NF-κB activity. We found that BAY 11-7028 abrogated IL-17-induced ZEB1 expression, cell migration, and EMT, thus confirming that NF-κB is required for IL-17 to induce these aggressive phenotypes in lung cancer cells. Taken together, our data support the idea that IL-17-induced EMT promotes lung cancer cell migration and invasion via NF-κB-mediated upregulation of ZEB1. This study reveals a new signaling axis through which the tumor microenvironment causes ZEB1 expression to promote cancer metastasis. We suggest that targeting IL-17-induced ZEB1 expression may offer an effective therapeutic strategy for lung cancer treatment.
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Lancet Reg Health West Pac
January 2025
Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
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Knight Foundation School of Computing and Information Sciences, Florida International University, Miami, USA.
Lung cancer remains a predominant cause of cancer-related deaths, with notable disparities in incidence and outcomes across racial and gender groups. This study addresses these disparities by developing a computational framework leveraging explainable artificial intelligence (XAI) to identify both patient- and cohort-specific biomarker genes in lung cancer. Specifically, we focus on two lung cancer subtypes, Lung Adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC), examining distinct racial and sex-specific cohorts: African American males (AAMs) and European American males (EAMs).
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Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin 300052, China.
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View Article and Find Full Text PDFFront Public Health
January 2025
School of Public Health, Gansu University of Chinese Medicine, Lanzhou, China.
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