scholarly journals Study on the expression of TOP2A in hepatocellular carcinoma and its relationship with patient prognosis

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Jiali Meng ◽  
Yuanchao Wei ◽  
Qing Deng ◽  
Ling Li ◽  
Xiaolong Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Differential Expression ◽  
Interaction Analysis ◽  
Clinical Sample ◽  
Primary Liver Cancer ◽  
Data Set ◽  
Hub Gene ◽  
Kegg Pathways ◽  
Normal Tissues ◽  
Top2a Gene

Abstract Background Hepatocellular carcinoma (HCC) is a primary liver cancer with a high mortality rate. However, the molecular mechanism of HCC formation remains to be explored and studied. Objective To investigate the expression of TOP2A in hepatocellular carcinoma (HCC) and its prognosis. Methods The data set of hepatocellular carcinoma was downloaded from GEO database for differential gene analysis, and hub gene was identified by Cytoscape. GEPIA was used to verify the expression of HUB gene and evaluate its prognostic value. Then TOP2A was selected as the research object of this paper by combining literature and clinical sample results. Firstly, TIMER database was used to study TOP2A, and the differential expression of TOP2A gene between normal tissues and cancer tissues was analyzed, as well as the correlation between TOP2A gene expression and immune infiltration of HCC cells. Then, the expression of top2a-related antibodies was analyzed using the Human Protein Atlas database, and the differential expression of TOP2A was verified by immunohistochemistry. Then, SRTING database and Cytoscape were used to establish PPI network for TOP2A and protein–protein interaction analysis was performed. The Oncomine database and cBioPortal were used to express and identify TOP2A mutation-related analyses. The expression differences of TOP2A gene were identified by LinkedOmics, and the GO and KEGG pathways were analyzed in combination with related genes. Finally, Kaplan–Meier survival analysis was performed to analyze the clinical and prognosis of HCC patients. Results TOP2A may be a new biomarker and therapeutic target for hepatocellular carcinoma.

scholarly journals Long Noncoding RNA FOXP4-AS1 Predicts Unfavourable Prognosis and Regulates Proliferation and Invasion in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Jingchen Liang ◽  
Duo Wang ◽  
Guanhua Qiu ◽  
Xiaoqi Zhu ◽  
Junjie Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Biological Function ◽  
Biological Effects ◽  
Primary Liver Cancer ◽  
Training Group ◽  
Normal Tissues ◽  
High Level ◽  
Proliferation And Invasion

Background. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer that has a high level of morbidity and mortality. Long noncoding RNA (lncRNA) is a novel regulatory factor of tumour proliferation, apoptosis, and metastasis. Our previous studies indicated that lncRNA FOXP4-AS1 is a functional oncogene in HCC; thus, this study is aimed at further evaluating the clinical and biological function of FOXP4-AS1 in HCC. Material and Methods. First, we detected the expression of FOXP4-AS1 in HCC tissues and paracarcinoma normal tissues by qRT-PCR. Second, the prognostic effects of FOXP4-AS1 in patients with HCC were analysed in a training group and a verification group. Subsequently, to investigate the biological effects of FOXP4-AS1 on HCC cells, downexpression tests were further conducted. Results. The expression of FOXP4-AS1 was higher in HCC tissues than adjacent nontumourous tissues, whereas the low expression of FOXP4-AS1 was correlated with optimistic treatment outcomes, which suggested that FOXP4-AS1 may be an independent prognostic biomarker for HCC. Moreover, the downregulation of FOXP4-AS1 significantly reduced the cell proliferation and clonal abilities and inhibited the invasion, migration, and angiogenesis of hepatoma cells ( P < 0.05 ). Conclusion. These results revealed the clinical significance and biological function of FOXP4-AS1 in HCC development, which may provide a new direction for finding therapeutic targets and potential prognostic biomarkers of HCC.

Differential expression of hDAB2IPA and hDAB2IPB in normal tissues and promoter methylation of hDAB2IPA in hepatocellular carcinoma

2007 ◽  
Vol 46 (4) ◽  
pp. 655-663 ◽  
Author(s):  
Guo-Hua Qiu ◽  
Huangming Xie ◽  
Nicholas Wheelhouse ◽  
David Harrison ◽  
George G. Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Differential Expression ◽  
Promoter Methylation ◽  
Normal Tissues

scholarly journals MiR-942-3p Promotes the Proliferation and Invasion of Hepatocellular Carcinoma Cells by Targeting MBL2

2019 ◽  
Vol 26 (1) ◽  
pp. 107327481984659 ◽  
Author(s):  
Chun-Yang Xu ◽  
Jun-Feng Dong ◽  
Zi-Qi Chen ◽  
Guo-Shan Ding ◽  
Zhi-Ren Fu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Ectopic Expression ◽  
Bioinformatic Analysis ◽  
Clinicopathological Characteristics ◽  
The Cancer Genome Atlas ◽  
Data Set ◽  
Small Noncoding Rnas ◽  
Normal Tissues ◽  
Potential Marker ◽  
Hcc Cells

MicroRNAs (miRNAs), a subgroup of small noncoding RNAs, play critical roles in tumor growth and metastasis. Accumulating evidence shows that the dysregulation of miRNAs is associated with the progression of hepatocellular carcinoma (HCC). However, the molecular mechanism by which miR-942-3p contributes to HCC remains undocumented. The association between miR-942-3p expression and the clinicopathological characteristics in HCC patients was analyzed by The Cancer Genome Atlas data set. The targets of miR-942-3p were identified by bioinformatic analysis and dual luciferase report assay. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and Transwell assays were performed to assess the functional role of miR-942-3p in HCC cells. Consequently, we found that miR-942-3p expression level was elevated in HCC tissues and cell lines as compared with the normal tissues and was associated with the pathological stage and tumor node metastasis (TNM) stage, acting as an independent prognostic factor of poor survival in patients with HCC. Ectopic expression of miR-942-3p enhanced the proliferation and invasive potential of HCC cells, but inhibition of miR-942-3p expression had the opposite effects. Mannose-binding lectin 2 (MBL2) was further identified as a direct target of miR-942-3p and possessed a negative correlation with miR-942-3p expression and unfavorable survival in patients with HCC. Restoration of MBL2 inhibited the progression of HCC cells and attenuated the tumor-promoting effects induced by miR-942-3p. In conclusion, miR-942-3p may act as an oncogenic factor in HCC cells by targeting MBL2 and provide a potential marker for patients with HCC.

scholarly journals Integrated profiling identifies ITGB3BP as prognostic biomarker for hepatocellular carcinoma

2021 ◽  
Author(s):  
Qiuli Liang ◽  
Chao Tan ◽  
Feifei Xiao ◽  
Fuqiang Yin ◽  
Meiliang Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cox Regression ◽  
Interaction Analysis ◽  
Characteristic Curve ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
T Stage

Hepatocellular carcinoma (HCC) is a highly malignant tumor. In this study, we sought to identify a novel biomarker for HCC by analyzing transcriptome and clinical data. The R software was used to analyze the differentially expressed genes (DEGs) in the datasets GSE74656 and GSE84598 downloaded from the Gene Expression Omnibus database, followed by a functional annotation. A total of 138 shared DEGs were screened from two datasets. They were mainly enriched in the “Metabolic pathways” pathway (Padj=8.21E-08) and involved in the carboxylic acid metabolic process (Padj=0.0004). The top 10 hub genes were found by protein-protein interaction analysis and were up-regulated in HCC tissues compared to normal tissues in The Cancer Genome Atlas (TCGA) database. Survival analysis distinguished 8 hub genes CENPE, SPDL1, HMMR, RACGAP1, TRIP13, CKAP2, CKAP5, and ITGB3BP were considered as prognostic hub genes. Multivariate cox regression analysis indicated that all the prognostic hub genes were independent prognostic factors for HCC. Furthermore, the receiver operating characteristic curve revealed that the 8-hub genes model had better prediction performance for overall survival compared to the T stage (p=0.008) and significantly improved the prediction value of the T stage (p=0.002). The Human Protein Atlas showed that the protein expression of ITGB3BP was up-regulated in HCC, so the expression of ITGB3BP was further verified in our cohort. The results showed that ITGB3BP was up-regulated in HCC tissues and was significantly associated with lymph node metastasis.

scholarly journals Effects Which M6A RNA Methylation Regulation Exerts on the Prognosis of Hepatocellular Carcinoma

2020 ◽  
Author(s):  
Baoxue Jia ◽  
Xiaojian Pei ◽  
Yue Sun ◽  
Yaming Xing ◽  
Jinna Hu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Cancer ◽  
Human Cancer ◽  
Primary Liver Cancer ◽  
Lasso Regression ◽  
Rna Methylation ◽  
Normal Tissues ◽  
Liver Cancers ◽  
M6a Rna Methylation ◽  
The Relationship

Abstract Background: Hepatocellular carcinoma (HCC) ,which has been known as the most common subtype in the range of primary liver cancer . Besides, it hails as one of China ’s common cancers , giving rise to the major cancer death cause in men. N6 methyladenosine (m6A) RNA methylation is under the regulation of m6A RNA methylation regulators in dynamic way (the proteins of "writer" "eraser"; "reader"). More and more evidences show that the m6A modification level is connected with self-renewal of tumor stem cells, the growth, proliferation, anti chemotherapy and radiosensitivity of tumor cells. The relationship between m6A RNA and human cancer types has been confirmed in a variety of cancers. This research aims to investigate the relationship betwixt m6A RNA methylation regulators and liver cancer. Methods: firstly, the comparison of the expression levels harbored by 13 major m6A RNA methylation regulators in liver cancer with normal tissues was conducted by means of the data of TCGA database. Secondly, we cluster the presentation data of m6A RNA methylated regulator uniformly and dissect HCC tissue into two subgroups (group 1 and 2) by comparing these subgroups according to the overall survival rate (OS), WHO phase and pathological level . Thirdly, based on the combination of least absolute contraction with selection operator (lasso) regression, the risk characteristics of m6A RNA methylation regulators was constructed , which affected OS in TCGA analysis. Results: there were significant differences in the presentation degrades held by 12 major m6A RNA methylation regulators in liver cancers and normal tissues. The primary liver cancer was divided into 1 and 2 groups. It was found that the OS of 1 subgroup was poor, the WHO stage was high and the pathological grade was high. In TCGA analysis, five m6A methylation regulators (YTHDF1, ZC3H13, YTHDF2, METTL3 and KIAA1429) were selected to affect OS, and a risk marker significantly related to who staging was constructed, which was also an independent prognostic marker of OS. Conclusion: m6A RNA methylation regulator is a key player in the progression of HCC and has potential value in the prediction and treatment of HCC.

scholarly journals An Autophagy-Related Gene-Based Prognostic Risk Signature for Hepatocellular Carcinoma: Construction and Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Rui Feng ◽  
Jian Li ◽  
Weiling Xuan ◽  
Hanbo Liu ◽  
Dexin Cheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Differential Expression ◽  
Prognostic Model ◽  
Risk Model ◽  
Cox Regression ◽  
Primary Liver Cancer ◽  
Univariate Analysis ◽  
Differential Expression Analysis ◽  
Cox Regression Analysis

Background. Hepatocellular carcinoma (HCC) is a prevalent primary liver cancer. Treatment is dramatically difficult due to its high complexity and poor prognosis. Due to the disclosed dual functions of autophagy in cancer development, understanding autophagy-related genes devotes into novel biomarkers for HCC. Methods. Differential expression of genes in normal and tumor groups was analyzed to acquire autophagy-related genes in HCC. These genes were subjected to GO and KEGG pathway analyses. Genes were then screened by univariate regression analysis. The screened genes were subjected to multivariate Cox regression analysis to build a prognostic model. The model was validated by the ICGC validation set. Results. To sum up, 42 differential genes relevant to autophagy were screened by differential expression analysis. Enrichment analysis showed that they were mainly enriched in pathways including regulation of autophagy and cell apoptosis. Genes were screened by univariate analysis and multivariate Cox regression analysis to build a prognostic model. The model constituted 6 feature genes: EIF2S1, BIRC5, SQSTM1, ATG7, HDAC1, and FKBP1A. Validation confirmed the accuracy and independence of this model in predicting the HCC patient’s prognosis. Conclusion. A total of 6 feature genes were identified to build a prognostic risk model. This model is conducive to investigating interplay between autophagy-related genes and HCC prognosis.

scholarly journals Construction and Comprehensive Analysis of a Stratification System Based on AGTRAP in Patients with Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Li Wang ◽  
Wenjun Zhang ◽  
Tao Yang ◽  
Le He ◽  
Yunmei Liao ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regression Analysis ◽  
Differential Expression ◽  
Topological Degree ◽  
Cox Regression ◽  
Ppi Network ◽  
Hub Gene ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Stratification System

Background. With the development of sequencing technology, several signatures have been reported for the prediction of prognosis in patients with hepatocellular carcinoma (HCC). However, the above signatures are characterized by cumbersome application. Therefore, the study is aimed at screening out a robust stratification system based on only one gene to guide treatment. Methods. Firstly, we used the limma package for performing differential expression analysis on 374 HCC samples, followed by Cox regression analysis on overall survival (OS) and disease-free interval (PFI). Subsequently, hub prognostic genes were found at the intersection of the above three groups. In addition, the topological degree inside the PPI network was used to screen for a unique hub gene. The rms package was used to construct two visual stratification systems for OS and PFI, and Kaplan-Meier analysis was utilized to investigate survival differences in clinical subgroups. The ssGSEA algorithm was then used to reveal the relationship between the hub gene and immune cells, immunological function, and checkpoints. In addition, we also used function annotation to explore into putative biological functions. Finally, for preliminary validation, the hub gene was knocked down in the HCC cell line. Results. We discovered 6 prognostic genes (SKA1, CDC20, AGTRAP, BIRC5, NEIL3, and CDC25C) for constructing a PPI network after investigating survival and differential expression genes. According to the topological degree, AGTRAP was chosen as the basis for the stratification system, and it was revealed to be a risk factor with an independent prognostic value in Kaplan-Meier analysis and Cox regression analysis ( P < 0.05 ). In addition, we constructed two visualized nomograms based on AGTRAP. The novel stratification system had a robust predictive value for PFI and OS in ROC analysis and calibration curve ( P < 0.05 ). Meanwhile, AGTRAP upregulation was associated with T staging, N staging, M staging, pathological stage, grade, and vascular invasion ( P < 0.05 ). Notably, AGTRAP was overexpressed in tumor tissues in all pancancers with paired samples ( P < 0.05 ). Furthermore, AGTRAP was associated with immune response and may change immune microenvironment in HCC ( P < 0.05 ). Next, gene enrichment analysis suggested that AGTRAP may be involved in the biological process, such as cotranslational protein targeting to the membrane. Finally, we identified the oncogenic effect of AGTRAP by qRT-PCR, colony formation, western blot, and CCK-8 assay ( P < 0.05 ). Conclusion. We provided robust evidences that a stratification system based on AGTRAP can guide survival prediction for HCC patients.

scholarly journals The Clinical Significance of RMI2 in Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110454
Author(s):  
Bin Zheng, MS ◽  
Heng Wang, MS ◽  
Jin-xue Wang, MS ◽  
Zheng-hong Liu, MS ◽  
Pu Zhang, MD ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Genome Instability ◽  
Primary Liver Cancer ◽  
Histological Grade ◽  
Prognostic Indicator ◽  
Multivariate Regression Analysis ◽  
Prognostic Indicators ◽  
Normal Tissues ◽  
Diagnosis And Prognosis ◽  
Dismal Prognosis

Background: Hepatocellular carcinoma (HCC), which is the most common type of primary liver cancer, often presents at advanced stage with a dismal prognosis. Novel tumor biomarkers are needed to aid in HCC early detection and prognostication. Methods: Immunohistochemical staining for RecQ-mediated genome instability protein 2 (RMI2) was performed in 330 surgically resected HCC specimens and 190 adjacent normal tissues. Univariate and multivariate regression analysis were applied to identify prognostic indicators of HCC outcomes. Patient's survival was assessed with the Kaplan–Meier method. Results: RMI2 in HCC tissue was significantly higher than that in adjacent normal tissues, and was positively correlated with HCC histological grade and stage ( P < .05) but negatively correlated with the survival period. RIM2 was identified to be an independent prognostic indicator for HCC. Conclusion: The abnormal expression of RMI2 may be related to the occurrence and development of HCC. RIM2 could potentially serve as a novel tumor-specific biomarker for HCC diagnosis and prognosis prediction.

Biomarker Identification for Liver Hepatocellular Carcinoma and Cholangiocarcinoma Based on Gene Regulatory Network Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Qiuyan Huo ◽  
Yuying Ma ◽  
Yu Yin ◽  
Guimin Qin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Networks ◽  
Primary Liver Cancer ◽  
Endocrine Resistance ◽  
Molecular Characteristics ◽  
Network Clustering ◽  
Resistance Pathway ◽  
Gene Regulatory ◽  
Tf Gene ◽  
Liver Hepatocellular Carcinoma

Aims: We aimed to find common and distinct molecular characteristics between LIHC and CHOL based on miRNA-TF-gene FFL. Background: Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are two main histological subtypes of primary liver cancer with a unified molecular landscape, and feed-forward loops (FFLs) have been shown to be relevant in these complex diseases. Objective: To date, there has been no comparative analysis of the pathogenesis of LIHC and CHOL based on regulatory relationships. Therefore, we investigated the common and distinct regulatory properties of LIHC and CHOL in terms of gene regulatory networks. Method: Based on identified FFLs and an analysis of pathway enrichment, we constructed pathway-specific co-expression networks and further predicted biomarkers for these cancers by network clustering. Resul: We identified 20 and 36 candidate genes for LIHC and CHOL, respectively. The literature from PubMed supports the reliability of our results. Conclusion: Our results indicated that the hsa01522-Endocrine resistance pathway was associated with both LIHC and CHOL. Additionally, six genes (SPARC, CTHRC1, COL4A1, EDIL3, LAMA4 and OLFML2B) were predicted to be highly associated with both cancers, of which SPARC was significantly highly ranked. Other: In addition, we inferred that the Collagen gene family, which appeared more frequently in our overall prediction results, might be closely related to cancer development.

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