scholarly journals Systematic Analyses of the Role of the Reader Protein of N6-Methyladenosine RNA Methylation, YTH Domain Family 2, in Liver Hepatocellular Carcinoma

2020 ◽  
Vol 7 ◽  
Author(s):  
Xiang-yang Shao ◽  
Jin Dong ◽  
Han Zhang ◽  
Ying-song Wu ◽  
Lei Zheng
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Domain Family ◽  
Rna Methylation ◽  
Yth Domain ◽  
Liver Hepatocellular Carcinoma

BackgroundYTH domain family (YTHDF) 2 acts as a “reader” protein for RNA methylation, which is important in tumor regulation. However, the effect of YTHDF2 in liver hepatocellular carcinoma (LIHC) has yet to be elucidated.MethodsWe explored the role of YTHDF2 in LIHC based on publicly available datasets [The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO)]. A bioinformatics approach was employed to analyze YTHDF2. Logistic regression analyses were applied to analyze the correlation between YTHDF2 expression and clinical characteristics. To evaluate the effect of YTHDF2 on the prognosis of LIHC patients, we used Kaplan–Meier (K–M) curves. Gene set enrichment analysis (GSEA) was undertaken using TCGA dataset. Univariate and multivariate Cox analyses were used to ascertain the correlations between YTHDF2 expression and clinicopathologic characteristics with survival. Genes co-expressed with YTHDF2 were identified and detected using publicly available datasets [LinkedOmics, University of California, Santa Cruz (UCSC), Gene Expression Profiling Interactive Analysis (GEPIA), and GEO]. Correlations between YTHDF2 and infiltration of immune cells were investigated by Tumor Immune Estimation Resource (TIMER) and GEPIA.ResultsmRNA and protein expression of YTHDF2 was significantly higher in LIHC tissues than in non-cancerous tissues. High YTHDF2 expression in LIHC was associated with poor prognostic clinical factors (high stage, grade, and T classification). K–M analyses indicated that high YTHDF2 expression was correlated with an unfavorable prognosis. Univariate and multivariate Cox analyses revealed that YTHDF2 was an independent factor for a poor prognosis in LIHC patients. GSEA revealed that the high-expression phenotype of YTHDF2 was consistent with the molecular pathways implicated in LIHC carcinogenesis. Analyses of receiver operating characteristic curves showed that YTHDF2 might have a diagnostic value in LIHC patients. YTHDF2 expression was associated positively with SF3A3 expression, which implied that they may cooperate in LIHC progression. YTHDF2 expression was associated with infiltration of immune cells and their marker genes. YTHDF2 had the potential to regulate polarization of tumor-associated macrophages, induce T-cell exhaustion, and activate T-regulatory cells.ConclusionYTHDF2 may be a promising biomarker for the diagnosis and prognosis of LIHC and may provide new directions and strategies for LIHC treatment.

scholarly journals Prognostic value of an immune long non-coding RNA signature in liver hepatocellular carcinoma

2019 ◽  
Author(s):  
rui kong ◽  
Nan Wang ◽  
Wei Han ◽  
Yuejuan Zheng ◽  
Jie Lu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Liver Hepatocellular Carcinoma ◽  
Long Non Coding Rna

Abstract Background: In recent years, long non-coding RNAs (lncRNAs) are emerging as crucial regulators in the immunological process of liver hepatocellular carcinoma (LIHC). Increasing studies have found that some lncRNAs could be used as a diagnostic or therapeutic target for clinical management, but little research has investigated the role of immune-related lncRNA in tumor prognosis. In this study, we aimed to develop an immune lncRNA signature for the precise diagnosis and prognosis of liver hepatocellular carcinoma. Methods: Gene expression profiles of LIHC samples obtained from TCGA were screened for immune-related genes using two reference gene sets. The optimal immune-related lncRNA signature was built via correlational analysis, univariate and multivariate cox analysis. Then the Kaplan-Meier plot, ROC curve, clinical analysis, gene set enrichment analysis, and principal component analysis were carried out to evaluate the capability of immune lncRNA signature as a prognostic indicator. Results: Six long non-coding RNA MSC−AS1, AC009005.1, AL117336.3, AL031985.3, AL365203.2, AC099850.3 were identified via correlation analysis and cox regression analysis considering their interactions with immune genes. Next, tumor samples were separated into two risk groups by the signature with different clinical outcomes. Stratification analysis showed the prognostic ability of this signature acted as an independent factor. The AUC value of ROC curve was 0.779. The Kaplan-Meier method was used in survival analysis and results showed a statistical difference between the two risk groups. The predictive performance of this signature was validated by principal component analysis (PCA). Data from gene set enrichment analysis (GSEA) further unveiled several potential biological processes of these biomarkers may involve in. Conclusion: In summary, the study demonstrated the potential role of the six-lncRNA signature served as an independent prognostic factor for LIHC patients.

scholarly journals Identification and Validation of the N6-Methyladenosine RNA Methylation Regulator YTHDF1 as a Novel Prognostic Marker and Potential Target for Hepatocellular Carcinoma

2020 ◽  
Vol 7 ◽  
Author(s):  
Saiyan Bian ◽  
Wenkai Ni ◽  
Mengqi Zhu ◽  
Qianqian Song ◽  
Jianping Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Biological Activities ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Cell Counting ◽  
Migration And Invasion ◽  
Mesenchymal Transition ◽  
Rna Methylation ◽  
Hcc Cells

Purpose: N6-methyladenosine (m6A) RNA methylation has been implicated in various malignancies. This study aimed to identify the m6A methylation regulator-based prognostic signature for hepatocellular carcinoma (HCC) as well as provide candidate targets for HCC treatment.Methods: The least absolute shrinkage and selection operator (LASSO) analyses were performed to identify a risk signature in The Cancer Genome Atlas (TCGA) datasets. The risk signature was further validated in International Cancer Genome Consortium (ICGC) and Pan-Cancer Analysis of Whole Genomes (PCAWG) datasets. Following transfection of short hairpin RNA (shRNA) targeting YTHDF1, the biological activities of HCC cells were evaluated by Cell Counting Kit-8 (CCK-8), wound-healing, Transwell, flow cytometry, and xenograft tumor assays, respectively. The potential mechanisms mediated by YTHDF1 were predicted by overrepresentation enrichment analysis (ORA)/gene set enrichment analysis (GSEA) and validated by Western blotting.Results: Overexpression of m6A RNA methylation regulators was correlated with malignant clinicopathological characteristics of HCC patients. The Cox regression and LASSO analyses identified a risk signature with five m6A methylation regulators (KIAA1429, ZC3H13, YTHDF1, YTHDF2, and METTL3). In accordance with HCC cases in TCGA, the prognostic value of risk signature was also determined in ICGC and PCAWG datasets. Following analyzing the expression and clinical implications in TCGA and Gene Expression Omnibus (GEO), YTHDF1 was chosen for further experimental validation. Knockdown of YTHDF1 significantly inhibited the proliferation, migration, and invasion of HCC cells, as well as enhanced the apoptosis in vitro. Moreover, silencing YTHDF1 repressed the growth of xenograft tumors in vivo. Mechanism investigation indicated that YTHDF1 might promote the aggressive phenotypes by facilitating epithelial–mesenchymal transition (EMT) and activating AKT/glycogen synthase kinase (GSK)-3β/β-catenin signaling.Conclusion: The current study identified a robust risk signature consisting of m6A RNA methylation regulators for HCC prognosis. In addition, YTHDF1 was a potential molecular target for HCC treatment.

scholarly journals MAPK-RAP1A Signaling Enriched in Hepatocellular Carcinoma Is Associated With Favorable Tumor-Infiltrating Immune Cells and Clinical Prognosis

2021 ◽  
Vol 11 ◽  
Author(s):  
Hailin Li ◽  
Guangyu Han ◽  
Xing Li ◽  
Bowen Li ◽  
Bo Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
T Cell ◽  
Immune Cells ◽  
Clinical Characteristics ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Gamma Delta ◽  
Gene Sets ◽  
Prognostic Prediction

BackgroundMAPK-RAP1A signaling, which is involved in cancer progression, remains to be defined. Upregulation of MAPK-RAP1A signaling accounts for most cancers that harbor high incident rate, such as non-small cell lung cancer (NSCLC) and pancreatic cancer, especially in hepatocellular carcinoma (HCC). MAPK-RAP1A signaling plays an important function as clinical diagnosis and prognostic value in cancers, and the role of MAPK-RAP1A signaling related with immune infiltration for HCC should be elucidated.MethodsMicroarray data and patient cohort information from The Cancer Genome Atlas (TCGA; n = 425) and International Cancer Genome Consortium (ICGC; n = 405) were selected for validation. The Cox regression and least absolute shrinkage and selection operator (LASSO) were used to construct a clinical prognostic model in this analysis and validation study. We also tested the area under the curve (AUC) of the risk signature that could reflect the status of predictive power by determining model. MAPK-RAP1A signaling is also associated with tumor-infiltrating immune cells (TICs) as well as clinical parameters in HCC. The GSEA and CIBERSORT were used to calculate the proportion of TICs, which should be beneficial for the clinical characteristics (clinical stage, distant metastasis) and positively correlated with the survival of HCC patients.ResultsHCC patients with enrichment of MAPK-RAP1A signaling were associated with clinical characteristics and favorable T cell gamma delta (Vδ T cells), and STMN1, RAP1A, FLT3, HSPA8, ANGPT2, and PGF were used as candidate biomarkers for risk scores of HCC. To determine the molecular mechanism of this signature gene association, Gene Set Enrichment Analysis (GSEA) was proposed. Cytokine–cytokine receptor interaction, TGF-β signaling pathway, and Intestinal immune network for IgA production gene sets were closely related in MAPK-RAP1A gene sets. Thus, we established a novel prognostic prediction of HCC to deepen learning of MAPK-RAP1A signaling pathways.ConclusionOur findings demonstrated that HCC patients with enrichment of MAPK-RAP1A signaling were associated with clinical characteristics and favorable T cell gamma delta (Vδ T cells), which may be a novel prognostic prediction of HCC.

scholarly journals Novel Biomarker NEDD1 and Its Analysis in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xiaopeng Ding ◽  
Jiahao Yu ◽  
Xin Shi ◽  
Kangwei Li ◽  
Shuoyi Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
External Validation ◽  
Enrichment Analysis ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Related Data ◽  
Significant Difference

Abstract Background: NEDD1 (NEDD1 Gamma-Tubulin Ring Complex Targeting Factor) plays a crucial impact in regulating cell cycle and the development of scirrhous gastric cancer. However, the role of NEDD1 hasn’t been reported in hepatocellular carcinoma (HCC) so far. The aim of this research is to explore the role of NEDD1 on the development and prognosis of HCC. Methods: HCC-related data were download from The Cancer Genome Atlas (TCGA) database. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA) were conducted by the LinkedOmics database. Results: The expression of NEDD1 has significant difference between tumor and adjacent normal tissues in HCC (P＜0.01). We also found that NEDD1 was an independent risk factor in HCC patients (HR 1.643, 95%CI 1.125–2.398; P = 0.01). The study also demonstrated that NEDD1 expression was significantly relevant to the expression of several immune checkpoint genes, including CTLA-4, PD-L1 and PD-1. GSEA revealed that Cell cycle, MicroRNAs in cancer and Ribosome pathways were significantly enriched in NEDD1 overexpression phenotype. By integrating NEDD1 with other relevant factors, we constructed the prognostic nomogram to help the improvement of the prognosis for patients with HCC. The data from the International Cancer Genome Consortium (ICGC) database were used as an independent external validation of our prognostic model. Conclusion: The expression level of NEDD1 was negatively correlated to the prognosis of HCC patients and it may be a promising therapeutic target of HCC, which probably be able to predict the efficacy of immunotherapy for HCC patients.

scholarly journals Construction and Validation of an Immune Cell Signature Score to Evaluate Prognosis and Therapeutic Efficacy in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Linfeng Xu ◽  
Xingxing Jian ◽  
Zhenhao Liu ◽  
Jingjing Zhao ◽  
Siwen Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Immune Cell ◽  
Expression Profiles ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Marker Genes ◽  
High Morbidity ◽  
Therapeutic Benefits

Background: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with high morbidity and mortality worldwide. Tumor immune microenvironment (TIME) plays a pivotal role in the outcome and treatment of HCC. However, the effect of immune cell signatures (ICSs) representing the characteristics of TIME on the prognosis and therapeutic benefit of HCC patients remains to be further studied.Materials and methods: In total, the gene expression profiles of 1,447 HCC patients from several databases, i.e., The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium, and Gene Expression Omnibus, were obtained and applied. Based on a comprehensive collection of marker genes, 182 ICSs were evaluated by single sample gene set enrichment analysis. Then, by performing univariate and multivariate Cox analysis and random forest modeling, four significant signatures were selected to fit an immune cell signature score (ICSscore).Results: In this study, an ICSscore-based prognostic model was constructed to stratify HCC patients into high-risk and low-risk groups in the TCGA-LIHC cohort, which was successfully validated in two independent cohorts. Moreover, the ICSscore values were found to positively correlate with the current American Joint Committee on Cancer staging system, indicating that ICSscore could act as a comparable biomarker for HCC risk stratification. In addition, when setting the four ICSs and ICSscores as features, the classifiers can significantly distinguish treatment-responding and non-responding samples in HCC. Also, in melanoma and breast cancer, the unified ICSscore could verify samples with therapeutic benefits.Conclusion: Overall, we simplified the tedious ICS to develop the ICSscore, which can be applied successfully for prognostic stratification and therapeutic evaluation in HCC. This study provides an insight into the therapeutic predictive efficacy of prognostic ICS, and a novel ICSscore was constructed to allow future expanded application.

scholarly journals The YTH Domain Family of N6-Methyladenosine “Readers” in the Diagnosis and Prognosis of Colonic Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Dian Xu ◽  
Jun Shao ◽  
Huan Song ◽  
Jianming Wang
Keyword(s):  
Cox Regression ◽  
Expression Patterns ◽  
Prognostic Significance ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Rank Test ◽  
Colonic Adenocarcinoma ◽  
Domain Family ◽  
Rna Methylation ◽  
Yth Domain

To profile the landscape of methylation N6 adenosine (m6A) RNA regulators in colonic adenocarcinoma (COAD) and to explore potential diagnostic and prognostic biomarkers, we assessed the differential expression patterns of m6A RNA methylation regulators between 418 COAD patients and 41 controls based on profiling from The Cancer Genome Atlas (TCGA) database. We plotted the receiver operating characteristic (ROC) curves and calculated the area under the curve (AUC) values to estimate the discrimination ability. The relationship between the expression of m6A RNA methylation regulators and clinicopathological characteristics was explored. Kaplan-Meier plotter, log-rank test, and Cox regression were used and a nomogram was created to explore the prognostic significance of m6A-related genes in overall survival at the mRNA level. Pathway analysis was performed by gene set enrichment analysis (GSEA) using TCGA dataset, and a coexpression network was built based on the STRING database. We observed that YTHDF1, METTL3, and KIAA1429 were significantly upregulated, while YTHDF3, YTHDC2, METTL14, and ALKBH5 were significantly downregulated in COAD samples compared to normal samples. YTHDF1 had the highest diagnostic value. Low expression of YTHDF3 predicted a poor survival rate in COAD patients. YTHDC2 was related to sex and showed a downward trend as clinical stage increased. Our results indicate that the YT521-B homology (YTH) domain family (“readers”), especially YTHDF1, YTHDF3, and YTHDC2, might play a significant role in the detection, progression, and prognosis of COAD, indicating that they are promising cancer biomarkers.

BUB1 Predicts Poor Prognosis and Immune Status in Liver Hepatocellular Carcinoma

2021 ◽  
Author(s):  
wenbo qi ◽  
Yuping Bai ◽  
Le Liu ◽  
Hao Chen
Keyword(s):  
Hepatocellular Carcinoma ◽  
Family Member ◽  
Western Blotting ◽  
Immune Status ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Cell Counting ◽  
Immune Microenvironment ◽  
Hub Genes ◽  
Liver Hepatocellular Carcinoma

Abstract Background: Accurate assessment of the tumour immune microenvironment helps develop individualised immunotherapy regimens and screen dominant populations suitable for immunotherapy. Therefore, potential molecular markers were investigated to make an overall assessment of the immune microenvironment status of liver hepatocellular carcinoma (LIHC). Methods: Differentially expressed genes (DEGs) in LIHC were extracted from the International Cancer Genome Consortium and The Cancer Genome Atlas databases. Gene set enrichment analysis was employed to assess the function of DEGs. Hub genes were identified using the STRING tool. The prognostic value of the hub genes was evaluated through Kaplan–Meier analysis and Cox regression. The correlation between genes and immunity was analysed using the TIMER tool. Further, tissue samples from 42 LIHC patients were collected for immunohistochemistry. HuH7 and SKP1 cells were analysed via western blotting, Cell Counting kit-8 assay, and Transwell assay. Results: A total of 121 DEGs were identified, and DEGs were enriched in the epithelial-mesenchymal transition, hypoxia, myogenesis, and p53 pathways. A total of 20 hub genes were selected and a strong correlation was identified between these hub genes and prognosis. The expression of budding uninhibited by benzimidazoles 1 (BUB1), which is known to play a role in cancer progression, was found to be upregulated in LIHC (compared to normal tissues). Furthermore, BUB1 expression was strongly related to immune cells and immune checkpoint molecule expression. Immunohistochemistry indicated that BUB1 expression was higher in LIHC tissues than in normal liver tissues. Western blotting showed that BUB1 expression was the highest in HuH7 and SKP1 cells. BUB1 knockdown resulted in reduced proliferation and vertical migration ability of LIHC cells, and reduced the expression of phospho-SMAD family member 2 and phospho-SMAD family member 3 proteins. Immunohistochemistry showed that BUB1 expression was accompanied by immune cell infiltration into LIHC tissues.Conclusions: These results suggest that BUB1 may serve as a potential prognostic biomarker for LIHC and as an indicator of its immune status.

Signatures of gene expression, DNA methylation and microRNAs of hepatocellular carcinoma with vascular invasion

2019 ◽  
Vol 15 (22) ◽  
pp. 2603-2617 ◽  
Author(s):  
Siti A Sulaiman ◽  
Nadiah Abu ◽  
Nurul-Syakima Ab-Mutalib ◽  
Teck Yew Low ◽  
Rahman Jamal
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Vascular Invasion ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Methylated Genes ◽  
Cancer Genome Atlas ◽  
Poor Outcomes ◽  
Liver Hepatocellular Carcinoma ◽  
Genome Atlas

Aim: Micro and macro vascular invasion (VI) are known as independent predictors of tumor recurrence and poor survival after surgical treatment of hepatocellular carcinoma (HCC). Here, we aimed to re-analyze The Cancer Genome Atlas of liver hepatocellular carcinoma datasets to identify the VI-expression signatures. Materials & methods: We filtered The Cancer Genome Atlas liver hepatocellular carcinoma (LIHC) datasets into three groups: no VI (NVI = 198); micro VI (MIVI = 89) and macro VI (MAVI = 16). We performed differential gene expression, methylation and microRNA analyses. Results & conclusion: We identified 12 differentially expressed genes and 55 differentially methylated genes in MAVI compared with no VI. The GPD1L gene appeared in all of the comparative analyses. Higher GPD1L expression was associated with VI and poor outcomes in the HCC patients.

scholarly journals Identification of glycolysis related pathways in pancreatic adenocarcinoma and liver hepatocellular carcinoma based on TCGA and GEO datasets

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ji Li ◽  
Chen Zhu ◽  
Peipei Yue ◽  
Tianyu Zheng ◽  
Yan Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Energy Metabolism ◽  
Pancreatic Adenocarcinoma ◽  
Digestive System ◽  
Prognostic Significance ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
System Structure ◽  
Liver Hepatocellular Carcinoma

Abstract Background Abnormal energy metabolism is one of the characteristics of tumor cells, and it is also a research hotspot in recent years. Due to the complexity of digestive system structure, the frequency of tumor is relatively high. We aim to clarify the prognostic significance of energy metabolism in digestive system tumors and the underlying mechanisms. Methods Gene set variance analysis (GSVA) R package was used to establish the metabolic score, and the score was used to represent the metabolic level. The relationship between the metabolism and prognosis of digestive system tumors was explored using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Volcano plots and gene ontology (GO) analyze were used to show different genes and different functions enriched between different glycolysis levels, and GSEA was used to analyze the pathway enrichment. Nomogram was constructed by R package based on gene characteristics and clinical parameters. qPCR and Western Blot were applied to analyze gene expression. All statistical analyses were conducted using SPSS, GraphPad Prism 7, and R software. All validated experiments were performed three times independently. Results High glycolysis metabolism score was significantly associated with poor prognosis in pancreatic adenocarcinoma (PAAD) and liver hepatocellular carcinoma (LIHC). The STAT3 (signal transducer and activator of transcription 3) and YAP1 (Yes1-associated transcriptional regulator) pathways were the most critical signaling pathways in glycolysis modulation in PAAD and LIHC, respectively. Interestingly, elevated glycolysis levels could also enhance STAT3 and YAP1 activity in PAAD and LIHC cells, respectively, forming a positive feedback loop. Conclusions Our results may provide new insights into the indispensable role of glycolysis metabolism in digestive system tumors and guide the direction of future metabolism–signaling target combined therapy.

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