Search

Your search keyword '"Tongjing Xing"' showing total 3 results
Start Over Author "Tongjing Xing" Topic hepatocellular carcinoma
3 results on '"Tongjing Xing"'

2. High expression of nectin-1 indicates a poor prognosis and promotes metastasis in hepatocellular carcinoma

Author

Xuequan Wang, Ziming Xing, Huazhong Chen, Haihua Yang, Qiupeng Wang, and Tongjing Xing

Subjects
hepatocellular carcinoma, nectin-1, prognostic, cell proliferation, metastasis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

ObjectivesNectins are a new class of cell-adhesion molecules that play an important role in tumorigenesis and disease progression. The aim of this study was to investigate the prognostic and pathogenetic roles of nectins in hepatocellular carcinoma (HCC).MethodsThe expression levels of the nectin family in HCC and their role in prognosis were analyzed by bioinformatics analysis based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma database. The correlations between nectins and immune cells were analyzed using TIMER. The functional enrichment of the nectin-1 coexpression network was evaluated in TCGA cohort, and the expression levels of nectin-1 were detected by immunohistochemistry and Western blot analysis. A Transwell kit was used for cell migration experiments. Cell proliferation was analyzed using Cell Counting Kit-8.ResultsThe expression levels of nectin-1 protein in the cancer tissues of 28 patients with HCC were higher than those in paracancerous tissues. The Kaplan–Meier plotter analysis showed that the high expression of all nectin family numbers was related to the poor prognosis of HCC patients. The abnormal expression of nectin-1 effectively distinguished the prognosis at different stages and grades of HCC. The high expression of 17 methylation sites of the nectin-1 gene was related to the high overall survival of HCC patients. Kyoto Encyclopedia of Genes and Genomes analysis of genes negatively correlated with nectin-1, revealing their close relation to the regulation of the immune-effector process. Pearson’s correlation analysis showed that nectin-1 was significantly positively correlated with multiple immune genes and B cells, CD4+ T cells, macrophages, neutrophils, and dendritic cell infiltration. Cell proliferation of the knockdown (KD) group decreased significantly compared to the NC-KD group. The number of metastatic cells in the KD group decreased significantly compared to that in the NC-KD group.ConclusionsAbnormal expression of nectins and multiple methylation sites closely correlates with poor prognosis in HCC patients. Nectins are related to immune cell infiltration and immune-related genes. In particular, nectin-1 can promote the proliferation and migration of liver cancer cells and distinguish the prognosis at different stages and grades of HCC. Nectin-1 might be a new potential molecular marker for prognostic evaluation and also a therapeutic target for HCC.

Published
2022
Full Text
View/download PDF

3. Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma

Author

Tongjing Xing, Huihui Xu, Ziming Xing, Xuequan Wang, and Haihua Yang

Subjects
epithelial cell transformation, Oncology, Aging, medicine.medical_specialty, Carcinoma, Hepatocellular, Epithelial-Mesenchymal Transition, Kaplan-Meier Estimate, Cohort Studies, Lymphocytes, Tumor-Infiltrating, Risk Factors, Cell Line, Tumor, Internal medicine, Databases, Genetic, Humans, Medicine, Protein Interaction Maps, KEGG, Survival analysis, Proportional Hazards Models, Univariate analysis, Framingham Risk Score, Receiver operating characteristic, business.industry, Proportional hazards model, Gene Expression Profiling, Liver Neoplasms, Genetic Variation, Reproducibility of Results, hepatocellular carcinoma, Cell Biology, DNA Methylation, Nomogram, Prognosis, medicine.disease, Gene Expression Regulation, Neoplastic, Nomograms, ROC Curve, Hepatocellular carcinoma, Multivariate Analysis, business, Research Paper
Abstract

Epithelial cell transformation (EMT) plays an important role in the pathogenesis and metastasis of hepatocellular carcinoma (HCC). We aimed to establish a genetic risk model to evaluate HCC prognosis based on the expression levels of EMT-related genes. The data of HCC patients were collected from TCGA and ICGC databases. Gene expression differential analysis, univariate analysis, and lasso combined with stepwise Cox regression were used to construct the prognostic model. Kaplan–Meier curve, receiver operating characteristic (ROC) curve, calibration analysis, Harrell’s concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the predictive ability of the risk model or nomogram. GO and KEGG were used to analyze differently expressed EMT genes, or genes that directly or indirectly interact with the risk-associated genes. A 10-gene signature, including TSC2, ACTA2, SLC2A1, PGF, MYCN, PIK3R1, EOMES, BDNF, ZNF746, and TFDP3, was identified. Kaplan–Meier survival analysis showed a significant prognostic difference between high- and low-risk groups of patients. ROC curve analysis showed that the risk score model could effectively predict the 1-, 3-, and 5-year overall survival rates of patients with HCC. The nomogram showed a stronger predictive effect than clinical indicators. C-index, DCA, and calibration analysis demonstrated that the risk score and nomogram had high accuracy. The single sample gene set enrichment analysis results confirmed significant differences in the types of infiltrating immune cells between patients in the high- and low-risk groups. This study established a new prediction model of risk gene signature for predicting prognosis in patients with HCC, and provides a new molecular tool for the clinical evaluation of HCC prognosis.

Published
2021
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results