Postoperative Complications and Survival Rate of Esophageal Cancer: Two-period Analysis

Moral, Gregorio Isaías Moral; Miguel, Mar Viana; Doce, Oscar Vidal; Castro, Rosa Martínez; López, Romina Parra; Luquero, Alberto Palomo; Díez, Marta Bueno; Pedrique, Isabel Sánchez; González, Jorge Santos; Palacios, Jesús Zanfaño

doi:10.1016/j.cireng.2018.09.012

Cited by 3 publications

(1 citation statement)

References 35 publications

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“…Esophageal cancer is usually divided into squamous cell carcinoma and adenocarcinoma according to histopathological characteristics, and ESCC accounts for about 90% of cases in China ( 1 ). Despite continuous improvements in the diagnosis and treatment of ESCC, the prognosis of patients remains very poor, and the 5-year survival rate is only 15–34% ( 2 ). A previous study has reported that the survival rate of patients with ESCC is mainly negatively correlated with tumor invasiveness and the presence of lymph node and distant metastases.…”

Section: Introductionmentioning

confidence: 99%

PTMA binds to HMGB1 to regulate mitochondrial oxidative phosphorylation and thus affect the malignant progression of esophageal squamous cell carcinoma

Chen¹,

He²,

Lin³

et al. 2023

J Thorac Dis

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Background: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor of the digestive tract with complex pathogenesis. There is a pressing need to search for ESCC targeted therapy sites and explore its pathogenesis. Prothymosin alpha (PTMA) is abnormally expressed in numerous tumors and has a significant regulatory effect on tumor malignant progression. However, the regulatory role and mechanism of PTMA in ESCC have not yet been reported. Methods: We first detected the PTMA expression in ESCC patients, subcutaneous tumor xenograft models of ESCC, and ESCC cells. Subsequently, PTMA expression in ESCC cells was inhibited by cell transfection, and cell proliferation and apoptosis were detected by Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU) staining, flow cytometry, and Western blot. A dichloro-dihydro-fluorescein diacetate (DCFH-DA) assay was used to detect reactive oxygen species (ROS) level in cells, and MitoSOX fluorescent probe, 5,5',6,6'-tetrachloro-1,1',3,3'-tetraethyl-benzimidazolyl carbocyanine iodide (JC-1) staining, mitochondrial complex kit, and Western blot were used to detect the expression of mitochondrial oxidative phosphorylation. Next, the combination between PTMA and high mobility group box 1 (HMGB1) was detected using Co-immunoprecipitation (co-IP) and immunofluorescence (IF) techniques. Finally, the expression of PTMA was inhibited and the expression of HMGB1 was overexpressed in cells via cell transfection, and the regulatory effect of PTMA and HMGB1 binding on mitochondrial oxidative phosphorylation in ESCC was determined through related experiments. Results: The expression of PTMA in ESCC was abnormally elevated. The inhibition of PTMA expression in ESCC cells significantly decreased the activity of ESCC cells and increased their apoptosis. Moreover, interference with PTMA can induce ROS aggregation in ESCC cells by inhibiting mitochondrial oxidative phosphorylation, which may be achieved by binding to HMGB1. Conclusions: PTMA binds to HMGB1 to regulate mitochondrial oxidative phosphorylation, thereby affecting the malignant progression of ESCC.

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Section: Introductionmentioning

confidence: 99%

PTMA binds to HMGB1 to regulate mitochondrial oxidative phosphorylation and thus affect the malignant progression of esophageal squamous cell carcinoma

Chen¹,

He²,

Lin³

et al. 2023

J Thorac Dis

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Risk factors and therapeutic measures for postoperative complications associated with esophagectomy

Ahmadinejad

Soltanian

Maghsoudi

2020

Annals of Medicine and Surgery

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Fuzzy Data Mining and Bioinformatics Analysis in Methylation Analysis of M6A Gene Promoter Region in Esophageal Cancer

Yang

Qiu

et al. 2022

Journal of Sensors

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This work was aimed at analyzing the correlation between the methylation level of the M6A gene in esophageal cancer (EC) and the prognosis of patients based on bioinformatics technology and evaluating the prognostic predictive values of different data mining models. 80 EC patients and 80 healthy people were selected, and the serum of the patients was collected to detect the level of DNA methyltransferase. During the radical resection of EC, tumor tissues and adjacent normal tissues were collected from patients to detect the methylation level of the M6A gene. COX regression analysis was employed to analyze the independent risk factors (IRFs) of M6A gene methylation and other treatments affecting the prognosis of EC patients. The particle swarm optimization (PSO) algorithm was introduced to improve the fuzzy C -means clustering (FCM) algorithm. The differences in the prognostic prediction efficiency of logistic regression analysis (LRA), decision tree (DT) C5.0, artificial neural network (ANN), support vector machine (SVM), and improved FCM (IFCM) models were compared. The levels of DNA methyltransferase and human histone deacetylase 1 (HSD-1) in EC patients were increased greatly ( P < 0.05 ). The methylation rates and methylation levels of M6A methylation regulators (ALKBH5, HNRNPC, METTL3, WTAP, RBM15, YTHDC1, YTHDF1, and FTO) in EC tissues were obviously higher ( P < 0.05 ). The survival time of high-risk EC patients was much shorter than that of low-risk patients ( P < 0.05 ). Univariate and multivariate COX regression analysis showed that gender, tumor grade, TNM grade, degree of infiltration, and methylation of ALKBH5, HNRNPC, and METTL3 genes were IRFs for the prognosis of EC patients ( P < 0.05 ). The areas under the ROC curve (AUCs) of LRA, DT C5.0, ANN, SVM, and IFCM algorithms for predicting the prognosis of patients were 0.813, 0.857, 0.895, 0.926, and 0.958, respectively, and the IFCM model had the best diagnostic effect. In conclusion, the detection of bioinformatics technology showed no obvious DNA methylation in EC patients, and the elevated levels of M6A methylation regulators in patients were an IRF affecting the prognosis of patients. In addition, the fuzzy data mining model can be undertaken as the preferred method for prognosis prediction of EC patients.

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Postoperative Complications and Survival Rate of Esophageal Cancer: Two-period Analysis

Cited by 3 publications

References 35 publications

PTMA binds to HMGB1 to regulate mitochondrial oxidative phosphorylation and thus affect the malignant progression of esophageal squamous cell carcinoma

PTMA binds to HMGB1 to regulate mitochondrial oxidative phosphorylation and thus affect the malignant progression of esophageal squamous cell carcinoma

Risk factors and therapeutic measures for postoperative complications associated with esophagectomy

Fuzzy Data Mining and Bioinformatics Analysis in Methylation Analysis of M6A Gene Promoter Region in Esophageal Cancer

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