Prediction of survival prognosis of non-small cell lung cancer by APE1 through regulation of epithelial-mesenchymal transition

Wei, Xi; Li, Qing; Liu, Ying; Duan, Wei; Huang, Chongbiao; Zheng, Xiangqian; Sun, Lei; Luo, Jingtao; Wang, Dong; Zhang, Sheng; Xin, Xiaojie; Gao, Ming

doi:10.18632/oncotarget.8660

Cited by 23 publications

(31 citation statements)

References 21 publications

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“…Our previous study indicated that APE1 overexpression was associated with poor prognosis of non-small cell lung cancer and enhanced epithelial-Mesenchymal Transition (EMT) of lung cancer cell in vitro and in vivo 2. Other study also reported that APE1 inhibitor was able to suppress gastric cancer cell migration and invasion in combination with 5-Fu treatment 3.…”

Section: Introductionmentioning

confidence: 96%

Prediction of Lymph Node Metastases in Gastric Cancer by Serum APE1 Expression

Wei¹,

Li²,

Liu³

et al. 2017

J. Cancer

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Aims: To investigate the functional role of serum Human apurinic/apyrimidinic endonuclease 1 (APE1) in prediction of lymph node metastasis in gastric cancer patients.Materials and methods: Serum samples were pre-operational collected from 86 patients with gastric cancer from Tianjin Medical University Cancer Institute and Hospital from March 2016 to August 2016. The serum of APE1 was measured by ELISA development kit and other CA242, CA724, CA199 and CEA levels by electrochemiluminescence assay.Results: The total of 86 patients with gastric cancer was classified into two groups (lymph node positive and negative groups). Using ELISA assay, we found out that the concentration of serum APE1 was higher in lymph node positive group than that of lymph node negative group. The receiver operating characteristic (ROC) curve was performed to analyze, indicating that area under the ROC curve of serum APE1 were better than those of each regular markers (CEA+CA199+CA242+CA724) or combination of these markers. Additionally, the APE1 overexpression was uncovered in tissue of gastric cancer patients with lymph nodes metastases, which is correlation with results of serum APE1.Conclusion: Serum APE1 was identified as a valuable marker for prediction of lymph node metastases in patients with gastric cancer.

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Section: Introductionmentioning

confidence: 96%

Prediction of Lymph Node Metastases in Gastric Cancer by Serum APE1 Expression

Wei¹,

Li²,

Liu³

et al. 2017

J. Cancer

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“…31,32 Studies have shown that radiomic features extracted from CT images can be correlated with pathologic information 33 patient overall survival, 30,32,[34][35][36][37][38][39] gene expression, 30,38,40 cancer staging, 41 and response assessment. 31,[42][43][44][45] Recent research has focused on the role of radiomics toward increasing the performance and stability of feature classifiers for predicting overall survival in head and neck cancer patients. 22,[46][47][48][49] Identification of optimal classification methods and the best radiomic features for prognostic analyses in head and neck cancer patients may indeed broaden the scope of radiomics in precision oncology.…”

Section: Introductionmentioning

confidence: 99%

Application of radiomics for the prediction of HPV status for patients with head and neck cancers

et al. 2020

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Purpose To perform radiomic analysis of primary tumors extracted from pretreatment contrast‐enhanced computed tomography (CE‐CT) images for patients with oropharyngeal cancers to identify discriminant features and construct an optimal classifier for the characterization and prediction of human papilloma virus (HPV) status. Materials and methods One hundred and eighty seven patients with oropharyngeal cancers with known HPV status (confirmed by immunohistochemistry—p16 protein testing) were retrospectively studied as follows: Group A: 95 patients (19HPV− and 76HPV+) from the MICAII grand challenge. Group B: 92 patients (52HPV− and 40HPV+) from our institution. Radiomic features (172) were extracted from pretreatment diagnostic CE‐CT images of the gross tumor volume (GTV). Levene and Kolmogorov–Smirnov's tests with absolute biserial correlation (>0.48) were used to identify the discriminant features between the HPV+ and HPV− groups. The discriminant features were used to train and test eight different classifiers. Area under receiver operating characteristic (AUC), positive predictive and negative predictive values (PPV and NPV, respectively) were used to evaluate the performance of the classifiers. Principal component analysis (PCA) was applied on the discriminant feature set and seven PCs were used to train and test a generalized linear model (GLM) classifier. Results Among 172 radiomic features only 12 radiomic features (from 3 categories) were significantly different (P < 0.05, |BSC| > 0.48) between the HPV+ and HPV− groups. Among the eight classifiers trained and applied for prediction of HPV status, the GLM showed the highest performance for each discriminant feature and the combined 12 features: AUC/PPV/NPV = 0.878/0.834/0.811. The GLM high prediction power was AUC/PPV/NPV = 0.849/0.731/0.788 and AUC/PPV/NPV = 0.869/0.807/0.870 for unseen test datasets for groups A and B, respectively. After eliminating the correlation among discriminant features by applying PCA analysis, the performance of the GLM was improved by 3.3%, 2.2%, and 1.8% for AUC, PPV, and NPV, respectively. Conclusions Results imply that GTV's for HPV+ patients exhibit higher intensities, smaller lesion size, greater sphericity/roundness, and higher spatial intensity‐variation/heterogeneity. Results are suggestive that radiomic features primarily associated with the spatial arrangement and morphological appearance of the tumor on contrast‐enhanced diagnostic CT datasets may be potentially used for classification of HPV status.

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“…Transforming growth factor-β signaling and Wnt/β-catenin have key roles in the regulation of EMT processes. In NSCLC, several genes, including kinesin family member C1 (24), APE1 (25,26) and F-box and WD repeat domain containing 7 (27), were reported to participate in the regulation of EMT. The present study demonstrated that knockdown of TIPRL in A549 cells promoted E-cadherin expression, whereas suppressed twist and vimentin expression was observed.…”

Section: Discussionmentioning

confidence: 99%

Knockdown of TOR signaling pathway regulator suppresses cell migration and invasion in non‑small cell lung cancer via the regulation of epithelial‑to‑mesenchymal transition

Zhu

Yang

et al. 2019

Exp Ther Med

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Non-small cell lung cancer (NSCLC) is one of the most common cancer types worldwide. Previous studies have indicated that TOR signaling pathway regulator (TIPRL) is involved in the progression of NSCLC. However, the underlying mechanisms of the role of TIPRL in regulating NSCLC metastasis have remained largely elusive. In the present study, the expression pattern of TIPRL in NSCLC was analyzed using The Cancer Genome Atlas (TCGA) dataset. Furthermore, Kaplan-Meier curve analysis was performed to evaluate the prognostic value of TIPRL in NSCLC, using the Kaplan-Meier Plotter and TCGA datasets. Loss-of-function assays were performed to determine the effects of TIPRL on cell migration and invasion. The results suggested that TIPRL was upregulated in NSCLC and positively associated with an advanced Tumor-Node-Metastasis stage. A higher expression level of TIPRL was associated with shorter overall and disease-free survival times in patients with NSCLC. To the best of our knowledge, the present study was the first to report that TIPRL acts as a metastasis promoter in NSCLC. Silencing of TIPRL suppressed A549 cell migration and invasion. Mechanistically, the present study indicated that TIPRL knockdown significantly promoted epithelial-cadherin expression, whereas it suppressed twist and vimentin expression in A549 cells. In conclusion, the present analysis suggested that TIPRL may serve as a biomarker for the prognosis of NSCLC and as a future target for its treatment.

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Prediction of survival prognosis of non-small cell lung cancer by APE1 through regulation of epithelial-mesenchymal transition

Cited by 23 publications

References 21 publications

Prediction of Lymph Node Metastases in Gastric Cancer by Serum APE1 Expression

Prediction of Lymph Node Metastases in Gastric Cancer by Serum APE1 Expression

Application of radiomics for the prediction of HPV status for patients with head and neck cancers

Knockdown of TOR signaling pathway regulator suppresses cell migration and invasion in non‑small cell lung cancer via the regulation of epithelial‑to‑mesenchymal transition

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