Downregulation of NMI promotes tumor growth and predicts poor prognosis in human lung adenocarcinomas

Abstract

BackgroundN-myc (and STAT) interactor (NMI) plays vital roles in tumor growth, progression, and metastasis. In this study, we identified NMI as a potential tumor suppressor in lung cancer and explored its molecular mechanism involved in lung cancer progression.MethodsHuman lung cancer cell lines and a mouse xenograft model was used to study the effect of NMI on tumor growth. The expression of NMI, COX-2 and relevant signaling proteins were examined by Western blot. Tissue microarray immunohistochemical analysis was performed to assess the correlation between NMI and COX-2 expression in lung cancer patients.ResultsNMI was highly expressed in normal lung cells and tissues, but lowly expressed in lung cancer cells and tissues. Overexpression of NMI induced apoptosis, suppressed lung cancer cell growth and migration, which were mediated by up-regulation of the cleaved caspase-3/9 and down-regulation of phosphorylated PI3K/AKT, MMP2/MMP9, β-cadherin, and COX-2/PGE2. In contrast, knockdown of NMI promoted lung cancer cell colony formation and migration, which were correlated with the increased expression of phosphorylated PI3K/AKT, MMP2/MMP9, β-cadherin and COX-2/PGE2. Further study showed that NMI suppressed COX-2 expression through inhibition of the p50/p65 NF-κB acetylation mediated by p300. The xenograft lung cancer mouse models also confirmed the NMI-mediated suppression of tumor growth by inhibiting COX-2 signaling. Moreover, tissue microarray immunohistochemical analysis of lung adenocarcinomas also demonstrated a negative correlation between NMI and COX-2 expression. Kaplan-Meier analysis indicated that the patients with high level of NMI had a significantly better prognosis.ConclusionsOur study showed that NMI suppressed tumor growth by inhibiting PI3K/AKT, MMP2/MMP9, COX-2/PGE2 signaling pathways and p300-mediated NF-κB acetylation, and predicted a favorable prognosis in human lung adenocarcinomas, suggesting that NMI was a potential tumor suppressor in lung cancer.

N‐myc and STAT interactor correlates with severity and prognosis in acute‐on‐chronic liver failure of hepatitis B virus

“…Recently, some reports show that NMI could be used as an effective biomarker for prognosis evaluating in cancer patients . However, the prognostic value of NMI in HBV‐ACLF patients remains unknown.…”

“…Recently, some reports show that NMI could be used as an effective biomarker for prognosis evaluating in cancer patients. 26 However, the prognostic value of NMI in HBV-ACLF patients remains unknown. As an important mediator involves in development of tumor, elevated NMI is also significantly correlated with poor prognosis in patients with glioblastoma.…”

MiR-629-3p-induced downregulation of SFTPC promotes cell proliferation and predicts poor survival in lung adenocarcinoma

“…In China, it is the most common cancer and the major cause of cancer-related deaths as well [4]. Non-small-cell lung cancer (NSCLC) takes up more than 85% of lung cancer, of which 60% are lung adenocarcinoma (LUAD), being the most frequently diagnosed subtype of NSCLC [5]. Of note, approximately 75% of lung cancer patients are diagnosed in the advanced stages of the disease [3].…”

Dissecting pharmacological effects of chloroquine in cancer treatment: interference with inflammatory signaling pathways

“…214 Hence, CQ can affect metastatic cells in transition and this can explain the statistically significant effect of CQ against metastatic cancer cells in patients. 217,218 As an example, interactions between NF-jB, STAT3, p53, and the glucocorticoid receptor (GR) guide dynamic transitions in the structures and functions of a cells' organelles and the resulting changes in the cells' phenotype. 216 The capacity of CQ to affect cancer cells in transition can also be linked to the interactions between transcription factors that steer cellular metabolism.…”

“…216 The capacity of CQ to affect cancer cells in transition can also be linked to the interactions between transcription factors that steer cellular metabolism. 217,218 As an example, interactions between NF-jB, STAT3, p53, and the glucocorticoid receptor (GR) guide dynamic transitions in the structures and functions of a cells' organelles and the resulting changes in the cells' phenotype. [219][220][221][222] Organelles, in turn, form intracellular networks that control autophagy and cell death.…”