scholarly journals PTEN loss promotes oncogenic function of STMN1 via PI3K/AKT pathway in lung cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guangsu Xun ◽  
Wei Hu ◽  
Bing Li
Keyword(s):  
Lung Cancer ◽  
Cell Growth ◽  
Molecular Mechanism ◽  
Drug Sensitivity ◽  
Survival Rates ◽  
Akt Pathway ◽  
Migration And Invasion ◽  
Pten Loss ◽  
Lung Cancer Patients ◽  
Oncogenic Function

AbstractAmong all cancer types, lung cancer has already become the leading cause of cancer-related death around the world. The molecular mechanism understanding this development is still needed to be improved to treat lung cancer. Stathmin (STMN1) was initially identified as a cytoplasmic protein phosphorylated responding to cell signal and controlled cell physiological processes. The dysregulation of STMN1 is found in various kinds of tumors. However, the molecular mechanism of STMN1 regulating lung cancer is still unclear. Here, we found that STMN1 was overexpressed in lung cancer tissues and associated with worse survival rates of lung cancer patients. Inhibition of STMN1 suppressed lung cancer cell growth, migration and invasion, and promoted drug sensitivity. Moreover, PTEN loss promoted STMN1 expression via PI3K/AKT pathway. PTEN loss ameliorated the inhibition of cell growth, migration and invasion, and drug sensitivity induced by STMN1 knockdown in lung cancer. The high expression of STMN1 was negatively correlated with the low expression of PTEN in lung cancer specimens. Overall, our work demonstrated that PTEN regulated the oncogenic function of STMN1 in lung cancer.

scholarly journals Long non-coding RNA AFAP1-AS1 accelerates lung cancer cells migration and invasion by interacting with SNIP1 to upregulate c-Myc

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yu Zhong ◽  
Liting Yang ◽  
Fang Xiong ◽  
Yi He ◽  
Yanyan Tang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Cells ◽  
Cancer Patients ◽  
Cancer Metastasis ◽  
Lung Cancer Cells ◽  
Migration And Invasion ◽  
Lung Cancer Patients ◽  
Lung Cancer Metastasis ◽  
Non Coding Rna ◽  
Long Non Coding Rna

AbstractActin filament associated protein 1 antisense RNA 1 (named AFAP1-AS1) is a long non-coding RNA and overexpressed in many cancers. This study aimed to identify the role and mechanism of AFAP1-AS1 in lung cancer. The AFAP1-AS1 expression was firstly assessed in 187 paraffin-embedded lung cancer and 36 normal lung epithelial tissues by in situ hybridization. The migration and invasion abilities of AFAP1-AS1 were investigated in lung cancer cells. To uncover the molecular mechanism about AFAP1-AS1 function in lung cancer, we screened proteins that interact with AFAP1-AS1 by RNA pull down and the mass spectrometry analyses. AFAP1-AS1 was highly expressed in lung cancer clinical tissues and its expression was positively correlated with lung cancer patients’ poor prognosis. In vivo experiments confirmed that AFAP1-AS1 could promote lung cancer metastasis. AFAP1-AS1 promoted lung cancer cells migration and invasion through interacting with Smad nuclear interacting protein 1 (named SNIP1), which inhibited ubiquitination and degradation of c-Myc protein. Upregulation of c-Myc molecule in turn promoted the expression of ZEB1, ZEB2, and SNAIL gene, which ultimately enhanced epithelial to mesenchymal transition (EMT) and lung cancer metastasis. Understanding the molecular mechanism by which AFAP1-AS1 promotes lung cancer’s migration and invasion may provide novel therapeutic targets for lung cancer patients’ early diagnosis and therapy.

scholarly journals MicroRNA‐4286 promotes cell proliferation, migration, and invasion via PTEN regulation of the PI3K/Akt pathway in non‐small cell lung cancer

2019 ◽  
Vol 8 (7) ◽  
pp. 3520-3531 ◽  
Author(s):  
Chunhua Ling ◽  
Xueting Wang ◽  
Jianjie Zhu ◽  
Haicheng Tang ◽  
Wenwen Du ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cell Proliferation ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Akt Pathway ◽  
Migration And Invasion ◽  
Small Cell Lung

scholarly journals P2.16-14 Survival Rates in Non-Small Cell Lung Cancer Patients in the Brazilian Private Health System: A Cohort Study

2019 ◽  
Vol 14 (10) ◽  
pp. S870
Author(s):  
E. Cerqueira ◽  
C.G. Ferreira ◽  
R. Buzzatti Peixoto ◽  
P. Mendoça Batista ◽  
M. Datz Abadi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cohort Study ◽  
Health System ◽  
Small Cell Lung Cancer ◽  
Cancer Patients ◽  
Survival Rates ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Patients ◽  
System A

scholarly journals Epigallocatechin-3-Gallate (EGCG) Suppresses Pancreatic Cancer Cell Growth, Invasion, and Migration partly through the Inhibition of Akt Pathway and Epithelial–Mesenchymal Transition: Enhanced Efficacy when Combined with Gemcitabine

Nutrients ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1856 ◽  
Author(s):  
Wei ◽  
Penso ◽  
Hackman ◽  
Wang ◽  
Mackenzie
Keyword(s):  
Pancreatic Cancer ◽  
Cell Growth ◽  
Cancer Cell ◽  
Pancreatic Cancer Cell ◽  
Epithelial Mesenchymal Transition ◽  
Akt Pathway ◽  
Migration And Invasion ◽  
Cancer Cell Migration ◽  
Cancer Cell Growth ◽  
Mesenchymal Transition

Most pancreatic cancers are usually diagnosed at an advanced stage when they have already metastasized. Epigallocatechin-3-gallate (EGCG), a major polyphenolic constituent of green tea, has been shown to reduce pancreatic cancer growth, but its effect on metastasis remains elusive. This study evaluated the capacity of EGCG to inhibit pancreatic cancer cell migration and invasion and the underlying mechanisms. EGCG reduced pancreatic cancer cell growth, migration, and invasion in vitro and in vivo. EGCG prevented “Cadherin switch” and decreased the expression level of TCF8/ZEB1, β-Catenin, and Vimentin. Mechanistically, EGCG inhibited the Akt pathway in a time-dependent manner, by suppressing IGFR phosphorylation and inducing Akt degradation. Co-treatment with catalase or N-Acetyl-L-cysteine did not abrogate EGCG’s effect on the Akt pathway or cell growth. Moreover, EGCG synergized with gemcitabine to suppress pancreatic cancer cell growth, migration, and invasion, through modulating epithelial–mesenchymal transition markers and inhibiting Akt pathway. In summary, EGCG may prove beneficial to improve gemcitabine sensitivity in inhibiting pancreatic cancer cell migration and invasion, to some extent through the inhibition of Akt pathway and epithelial–mesenchymal transition.

Survival Rates in Lung Cancer Patients with and without Bronchial Asthma

1993 ◽  
Vol 32 (5) ◽  
pp. 517-520 ◽  
Author(s):  
Erkki Vesterinen ◽  
Sakari Karjalainen ◽  
Tuomo Timonen ◽  
Eero Pukkala ◽  
Timo Hakulinen
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Bronchial Asthma ◽  
Survival Rates ◽  
Lung Cancer Patients

scholarly journals MicroRNA-196b Inhibits Cell Growth and Metastasis of Lung Cancer Cells by Targeting Runx2

2017 ◽  
Vol 43 (2) ◽  
pp. 757-767 ◽  
Author(s):  
Xiaoxue Bai ◽  
Lin Meng ◽  
Huijie Sun ◽  
Zhuo Li ◽  
Xiufang Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cell Growth ◽  
Cell Viability ◽  
Cancer Cells ◽  
Cell Lines ◽  
Lung Cancer Cells ◽  
Human Lung Cancer ◽  
Migration And Invasion ◽  
Mesenchymal Transition

Background/Aims: Lung cancer is one of the most common causes of cancer related deaths worldwide. The role of several microRNAs (miRNAs) including miR-196b in different cancers has already been established. The study was aimed to explore the role of miR-196b in lung cancer and its possible underlying mechanism. Methods: Human lung cancer cell line A549 was transfected with miR-196b mimic, miR-196b inhibitor and corresponding controls. Then cell viability, migration, invasion, and apoptosis of A549 lung cancer cells either with overexpression or with suppression of miR-196b were estimated sequentially. Next, dual luciferase activity assay was performed to clarify whether Runx2 was a direct target of miR-196b. Finally, the expressions of main factors associated with epithelial mesenchymal transition (EMT), PI3K/AKT/GSK3β, Smad, and JNK pathways were detected by western blot. Results: MiR-196b expression was significantly decreased in A549, H1650 and H1299 cell lines compared with in WI-38 and HEL-1 cell lines. Overexpression of miR-196b suppressed cell viability, migration, invasion, and induced apoptosis as well as inhibited TGF-β induced EMT process in A549 cells. In addition, Runx2 was a putative target of miR-196b, and Runx2 silence remarkably increased cell apoptosis and abolished the promotive effects of miR-196b suppression on cell viability, migration and invasion. Finally, miR-196b also mediated its action by inactivation of PI3K/AKT/GSK3β, Smad, and JNK pathways by down-regulation of Runx2. Conclusion: MiR-196b functions as a tumor suppressor that inhibited cell growth and metastasis of lung cancer cells by targeting Runx2. These findings provided further evidences for treatment of lung cancer.

scholarly journals Personalized drug-response prediction model for lung cancer patients using machine learning

2020 ◽  
Author(s):  
Rizwan Qureshi
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Targeted Therapies ◽  
Drug Response ◽  
Kinase Inhibitors ◽  
Binding Free Energy ◽  
Survival Rates ◽  
Drug Binding ◽  
Geometrical Properties ◽  
Lung Cancer Patients

Lung cancer caused by mutations in the epidermal growth factor receptor (EGFR) is a major cause of cancer deaths worldwide. EGFR Tyrosine kinase inhibitors (TKIs) have been developed, and have shown increased survival rates and quality of life in clinical studies. However, drug resistance is a major issue, and treatment efficacy is lost after about an year. Therefore, predicting the response to targeted therapies for lung cancer patients is a significant research problem. In this work, we address this issue and propose a personalized model to predict the drug-response of lung cancer patients. This model uses clinical information, geometrical properties of the drug binding site, and the binding free energy of the drug-protein complex. The proposed model achieves state of the art performance with 97.5% accuracy, 100% recall, 95% precision, and 96.3% F1-score with a random forest classifier. This model can also be tested on other types of cancer and diseases, and we believe that it may help in taking optimal clinical decisions for treating patients with targeted therapies

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