Gene Risk Signature of m6A Regulators, KIAA1429, YTHDF1, YTHDF2, METTL3 and Its Relationship with Immune Infiltration in Hepatocellular Carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is a tumor of the digestive system with high mortality. N6-methyladenosine (m6A) is one of the most common forms of mRNA modification. Tumor neoantigens play an important role in anti-tumor immune response and predict the clinical response of immunotherapy. There are few studies on the relationship between m6A regulators and immune infiltrating cells. The objective of this study was to determine the gene expression and prognostic value of m6A regulators in hepatocellular carcinoma. Further, we explored the relationship between m6A regulators and immune-infiltrating cells.Methods: 13 m6A regulators expressions in 374 cancer tissues and 50 normal tissues were analyzed using RNA-seq data and clinical information in the TCGA database. Survival package was used to analyze the survival of patients in the two groups, and the corresponding clinical characteristics and gene expression were analyzed using univariate and multivariate Cox regression. We evaluated the expression of KIAA1429, YTHDF1, YTHDF2, and METTL3 in HCC and its correlation with TIICs using TIMER and CIBERSORT.Results: Most m6A regulators had higher expression levels in 374 cancer tissues. We confirmed two groups of HCC patients using a consensus clustering method. The prognosis of the cluster 1 group was poor compared with that of the cluster 2 group. The m6A regulators, KIAA1429, YTHDF1, YTHDF2, and METTL3 are highly expressed in the high-risk group of HCC. Furthermore, it was found that four m6A regulators (KIAA1429, YTHDF1, YTHDF2, and METTL3) are closely related to the clinicopathological characteristics and poor prognostic marker of hepatocellular carcinoma. We analyzed the correlation between KIAA1429, YTHDF1, YTHDF2, and METTL3 expression and the level of immune invasion of HCC.Conclusion: KIAA1429, YTHDF1, YTHDF2, and METTL3 as m6A regulators may regulate the tumor microenvironment through tumor immune infiltration cells to exert immune anti-tumor effects. KIAA1429, YTHDF1, YTHDF2, and METTL3 as molecular markers providing a new target for therapy of HCC in the further.

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Ferroptosis regulator genes are a favorable biomarker for hepatocellular carcinoma

10.21203/rs.3.rs-139865/v1 ◽

2021 ◽

Author(s):

Yongfei He ◽

Shuqi Zhao ◽

Zhongliu Wei ◽

Xin Zhou ◽

Tianyi Liang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

High Risk ◽

Cox Regression ◽

Risk Group ◽

Clinical Information ◽

High Risk Group ◽

Low Risk ◽

The Cancer Genome Atlas ◽

Regulator Genes ◽

The Relationship

Abstract BackgroundIn this study, we comprehensively analyzed the relationship between ferroptosis regulator genes (FRGs) and prognosis of hepatocellular carcinoma (HCC), determined the prognostics value of FRGs, established a prediction model, and explored the relationship with immunotherapy for HCC.MethodsThe mRNA transcriptional levels and clinical information of HCC were obtained from The Cancer Genome Atlas (TCGA) database. The 24 FRGs were combined with the differential expression genes (DEGs) of HCC for further analysis. The prognostics values of differential FRGs via the construction of model and validation by the Cox regression analysis.ResultThere were three genes (CARS1, FANCD2, and SLC7A11) were identified as independent risk factors for HCC, and a predictive model was constructed based on CARS1, FANCD2, and SLC7A11. The model showed that the low-risk group HCC patients with a more prolonged overall survival (OS) than the high-risk group (P=0.001). The high-risk group with higher expression of FRGs than the low-risk group. Finally, the relations between FGEs and immune infiltration showed that CARS1, FANCD2, and SLC7A11 had a positive relationship with macrophage infiltration. From these, three genes might be the potential therapeutic targets.ConclusionOur study indicated that CARS1, FANCD2, and SLC7A11 might have potential value for therapeutic strategies as practical and reliable prognostic tools for HCC.

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The diagnostic and prognostic value of H2AFY in hepatocellular carcinoma

10.21203/rs.3.rs-17889/v2 ◽

2020 ◽

Author(s):

xuyang ma ◽

Ying Ding ◽

Li Zeng

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Prognostic Value ◽

Clinical Characteristics ◽

Cox Regression ◽

Normal Liver ◽

Diagnostic Value ◽

The Relationship ◽

Diagnostic And Prognostic Value

Abstract Background: The potential correlation between H2AFY (also known as MacroH2A1) and the clinical characteristics of hepatocellular carcinoma (HCC) patients was analysed through gene expression profiles and clinical data in The Cancer Genome Atlas (TCGA) database, and the diagnostic and prognostic value of H2AFY in HCC was discussed. Methods: The gene expression data of HCC and the corresponding clinical characteristics of HCC patients were downloaded from the TCGA database. The differences in H2AFY in normal liver tissues and HCC were analysed. The relationship between H2AFY and clinical characteristics was analysed by Wilcoxon signed-rank test, logistic regression and Kruskal-Wallis test. The Kaplan-Meier method and the Cox regression method were used to analyse the relationship between overall survival and clinical characteristics of the patients. An ROC curve was used to predict the diagnostic value of H2AFY in HCC. Gene set enrichment analysis (GSEA) was used to analyse the pathway enrichment of H2AFY. Result: Compared with normal liver tissues, H2AFY was significantly highly expressed in HCC. H2AFY was positively correlated with the age, clinical stage, G stage (grade) and T stage (tumor stage) of liver cancer patients. Higher H2AFY expression predicted a poor prognosis in HCC patients. Cox regression analysis suggested that H2AFY was an independent risk factor for the prognosis of HCC patients. The ROC curve suggested that H2AFY had certain diagnostic value in HCC. GSEA suggested that H2AFY was correlated with lipid metabolism and a variety of tumour pathways. Conclusion: Our study showed that H2AFY was significantly overexpressed in HCC. H2AFY may be a potential diagnostic and prognostic marker for HCC, and high expression of H2AFY predicts a poor prognosis in patients with HCC.

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Identification of CDC20 As an Immune Infiltration-Correlated Prognostic Biomarker in Hepatocellular Carcinoma

10.21203/rs.3.rs-400598/v1 ◽

2021 ◽

Author(s):

Chen Xiong ◽

Zhihuai Wang ◽

Guifu Wang ◽

Chi Zhang ◽

Shengjie Jin ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

T Cells ◽

Poor Prognosis ◽

Prognostic Value ◽

Cox Regression ◽

Cancer Genome ◽

Regression Analyses ◽

Ubiquitin Protein Ligase ◽

Immune Infiltration

Abstract Hepatocellular carcinoma (HCC) is a malignancy with a poor prognosis. Some E3 ubiquitin-protein ligases play essential roles in HCC development. We aimed to explore a hub E3 ubiquitin-protein ligase gene and verify its association with prognosis and immune cell infiltration in HCC. We identified cell division cycle 20 (CDC20) as a hub E3 ubiquitin-protein ligase in HCC by determining the intersecting genes in a protein-protein interaction (PPI) network of differentially expressed genes (DEGs) in HCC data from the International Cancer Genome Consortium (ICGC) and 919 E3 ubiquitin-protein ligase genes from the Integrated annotations for Ubiquitin and Ubiquitin-like Conjugation Database (IUUCD). DEGs and their correlations with clinicopathological features were explored in The Cancer Genome Atlas (TCGA), ICGC, and Gene Expression Omnibus (GEO) databases via the Wilcoxon signed-rank test. The prognostic value of CDC20 was illustrated by Kaplan-Meier (K-M) curves and Cox regression analyses. Subsequently, the correlation between CDC20 and immune infiltration was demonstrated via the Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA). CDC20 expression was significantly higher in HCC than in normal tissues (all P < 0.05). K-M curves and Cox regression analyses showed that high CDC20 expression predicted a poor prognosis and might be an independent risk factor for HCC prognosis (P < 0.05). Additionally, the TIMER and GEPIA results indicated that CDC20 is correlated with the immune infiltration of CD8 + T cells, T cells (general), monocytes, and exhausted T cells. This research revealed the potential prognostic value of CDC20 in HCC and demonstrated that CDC20 might be an immune-associated therapeutic target in HCC because of its correlation with immune infiltration.

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Development of a Novel Autophagy-Related Prognostic Signature and Nomogram for Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2020.591356 ◽

2020 ◽

Vol 10 ◽

Author(s):

Qiongxuan Fang ◽

Hongsong Chen

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

High Risk ◽

Cox Regression ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Regression Analyses ◽

Gene Model

BackgroundHepatocellular carcinoma (HCC) is the seventh most common malignancy and the second most common cause of cancer-related deaths. Autophagy plays a crucial role in the development and progression of HCC.MethodsUnivariate and Lasso Cox regression analyses were performed to determine a gene model that was optimal for overall survival (OS) prediction. Patients in the GSE14520 and GSE54236 datasets of the Cancer Genome Atlas (TCGA) were divided into the high-risk and low-risk groups according to established ATG models. Univariate and multivariate Cox regression analyses were used to identify risk factors for OS for the purpose of constructing nomograms. Calibration and receiver operating characteristic (ROC) curves were used to evaluate model performance. Real-time PCR was used to validate the effects of the presence or absence of an autophagy inhibitor on gene expression in HepG2 and Huh7 cell lines.ResultsOS in the high-risk group was significantly shorter than that in the low-risk group. Gene set enrichment analysis (GSEA) indicated that the association between the low-risk group and autophagy- as well as immune-related pathways was significant. ULK2, PPP3CC, and NAFTC1 may play vital roles in preventing HCC progression. Furthermore, tumor environment analysis via ESTIMATION indicated that the low-risk group was associated with high immune and stromal scores. Based on EPIC prediction, CD8+ T and B cell fractions in the TCGA and GSE54236 datasets were significantly higher in the low-risk group than those in the high-risk group. Finally, based on the results of univariate and multivariate analyses three variables were selected for nomogram development. The calibration plots showed good agreement between nomogram prediction and actual observations. Inhibition of autophagy resulted in the overexpression of genes constituting the gene model in HepG2 and Huh7 cells.ConclusionsThe current study determined the role played by autophagy-related genes (ATGs) in the progression of HCC and constructed a novel nomogram that predicts OS in HCC patients, through a combined analysis of TCGA and gene expression omnibus (GEO) databases.

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The diagnostic and prognostic value of H2AFY in hepatocellular carcinoma

BMC Cancer ◽

10.1186/s12885-021-08161-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xuyang Ma ◽

Ying Ding ◽

Li Zeng

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Prognostic Value ◽

Clinical Characteristics ◽

Cox Regression ◽

Normal Liver ◽

Diagnostic Value ◽

The Relationship ◽

Diagnostic And Prognostic Value

Abstract Background The potential correlation between H2AFY (also known as MacroH2A1) and the clinical characteristics of hepatocellular carcinoma (HCC) patients was analysed through gene expression profiles and clinical data in The Cancer Genome Atlas (TCGA) database, and the diagnostic and prognostic value of H2AFY in HCC was discussed. Methods The gene expression data of HCC and the corresponding clinical characteristics of HCC patients were downloaded from the TCGA database. The differences in H2AFY in normal liver tissues and HCC were analysed. The relationship between H2AFY and clinical characteristics was analysed by Wilcoxon signed-rank test, logistic regression and Kruskal-Wallis test. The Kaplan-Meier method and the Cox regression method were used to analyse the relationship between overall survival and clinical characteristics of the patients. An ROC curve was used to predict the diagnostic value of H2AFY in HCC. Gene set enrichment analysis (GSEA) was used to analyse the pathway enrichment of H2AFY. Result Compared with normal liver tissues, H2AFY was significantly highly expressed in HCC. H2AFY was positively correlated with the age, clinical stage, G stage (grade) and T stage (tumor stage) of liver cancer patients. Higher H2AFY expression predicted a poor prognosis in HCC patients. Cox regression analysis suggested that H2AFY was an independent risk factor for the prognosis of HCC patients. The ROC curve suggested that H2AFY had certain diagnostic value in HCC. GSEA suggested that H2AFY was correlated with lipid metabolism and a variety of tumour pathways. Conclusion Our study showed that H2AFY was significantly overexpressed in HCC. H2AFY may be a potential diagnostic and prognostic marker for HCC, and high expression of H2AFY predicts a poor prognosis in patients with HCC.

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Identification of Hub Genes Associated With Immune Infiltration and Predict Prognosis in Hepatocellular Carcinoma via Bioinformatics Approaches

Frontiers in Genetics ◽

10.3389/fgene.2020.575762 ◽

2021 ◽

Vol 11 ◽

Author(s):

Huaping Chen ◽

Junrong Wu ◽

Liuyi Lu ◽

Zuojian Hu ◽

Xi Li ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Cell Division ◽

Immune Cell ◽

Cox Regression ◽

Close Association ◽

Functional Enrichment ◽

Microtubule Assembly ◽

Hub Genes ◽

Immune Infiltration

AimsIn the cancer-related research field, there is currently a major need for a greater number of valuable biomarkers to predict the prognosis of hepatocellular carcinoma (HCC). In this study, we aimed to screen hub genes related to immune cell infiltration and explore their prognostic value for HCC.MethodsWe analyzed five datasets (GSE46408, GSE57957, GSE74656, GSE76427, and GSE87630) from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). A protein–protein interaction network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes; then, the hub genes were identified. Functional enrichment of the genes was performed on the Metascape website. Next, the expression of these hub genes was validated in several databases, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Human Protein Atlas. We explored the correlations between the hub genes and infiltrated immune cells in the TIMER2.0 database. The survival curves were generated in GEPIA2, and the univariate and multivariate Cox regression analyses were performed using TIMER2.0.ResultsThe top ten hub genes [DNA topoisomerase II alpha (TOP2A), cyclin B2 (CCNB2), protein regulator of cytokinesis 1 (PRC1), Rac GTPase-activating protein 1 (RACGAP1), aurora kinase A (AURKA), cyclin-dependent kinase inhibitor 3 (CDKN3), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle-associated 5 (CDCA5), abnormal spindle microtubule assembly (ASPM), and non-SMC condensin I complex subunit G (NCAPG)] were identified in subsequent analysis. These genes are most markedly enriched in cell division, suggesting their close association with tumorigenesis. Multi-database analyses validated that the hub genes were upregulated in HCC tissues. All hub genes positively correlated with several types of immune infiltration, including B cells, CD4+ T cells, macrophages, and dendritic cells. Furthermore, these hub genes served as independent prognostic factors, and the expression of these hub genes combing with the macrophage levels could help predict an unfavorable prognosis of HCC.ConclusionIn sum, these hub genes (TOP2A, CCNB2, PRC1, RACGAP1, AURKA, CDKN3, NUSAP1, CDCA5, ASPM, and NCAPG) may be pivotal markers for prognostic prediction as well as potentially work as targets for immune-based intervention strategies in HCC.

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The diagnostic and prognostic value of H2AFY in hepatocellular carcinoma

10.21203/rs.3.rs-17889/v1 ◽

2020 ◽

Author(s):

xuyang ma ◽

Ying Ding ◽

Li Zeng

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Poor Prognosis ◽

Prognostic Value ◽

Clinical Characteristics ◽

Cox Regression ◽

Normal Liver ◽

Diagnostic Value ◽

The Relationship ◽

Diagnostic And Prognostic Value

Abstract Background The potential correlation between H2AFY (also known as MacroH2A1) and the clinical characteristics of hepatocellular carcinoma (HCC) patients was analysed through gene expression profiles and clinical data in The Cancer Genome Atlas (TCGA) database, and the diagnostic and prognostic value of H2AFY in HCC was discussed. Methods The gene expression data of HCC and the corresponding clinical characteristics of HCC patients were downloaded from the TCGA database. The differences in H2AFY in normal liver tissues and HCC were analysed. The relationship between H2AFY and clinical characteristics was analysed by Wilcoxon signed-rank test, logistic regression and Kruskal-Wallis test. The Kaplan-Meier method and the Cox regression method were used to analyse the relationship between overall survival and clinical characteristics of the patients. An ROC curve was used to predict the diagnostic value of H2AFY in HCC. Gene set enrichment analysis (GSEA) was used to analyse the pathway enrichment of H2AFY. Result Compared with normal liver tissues, H2AFY was significantly highly expressed in HCC. H2AFY was positively correlated with the age, clinical stage, G stage and T stage of liver cancer patients. Higher H2AFY expression predicted a poor prognosis in HCC patients. Cox regression analysis suggested that H2AFY was an independent risk factor for the prognosis of HCC patients. The ROC curve suggested that H2AFY had certain diagnostic value in HCC. GSEA suggested that H2AFY was correlated with lipid metabolism and a variety of tumour pathways. Conclusion Our study showed that H2AFY was significantly overexpressed in HCC. H2AFY may be a potential diagnostic and prognostic marker for HCC, and high expression of H2AFY predicts a poor prognosis in patients with HCC.

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Identification of ferroptosis-related genes for overall survival prediction in hepatocellular carcinoma

10.21203/rs.3.rs-523396/v1 ◽

2021 ◽

Author(s):

Lianxiang Luo ◽

Xinyue Yao ◽

Fangfang Huang ◽

Hui Luo

Keyword(s):

Hepatocellular Carcinoma ◽

Target Genes ◽

Cox Regression ◽

Clinical Information ◽

Gene Signature ◽

High Risk Group ◽

Differentially Expressed ◽

Survival Prediction ◽

Potential Index ◽

Tumor Tissues

Abstract Ferroptosis is a novel type of cell death depending on iron, which has been confirmed strongly related with the development of tumor. Hepatocellular carcinoma (HCC) is a malignancy with high incidence. Despite some reports demonstrated the relation between ferroptosis-related genes and HCC, more details have not been excavated. In present study, we analyzed ferroptosis-related genes with their clinical information from TCGA-LIHC project to find out prognostic genes in HCC. And four genes (GPX2, MT3, PRDX1 and SRXN1) were established as a prognostic model after differentially expressed analysis, Cox regression analyses and LASSO approach. High-risk group separating by cutoff value with poor prognosis was proved, and risk score regarded as an independent prognostic factor. Subsequently, enrichment analyses were processed to the differentially expressed genes, we found that genes generally enriched in ferroptosis-related functions and pathways, also in some immune cells and functions with different immune status. Eventually, we constructed ferroptosis potential index (FPI) to reveal the functional roles of ferroptosis in tumor tissues. The immunohistochemistry performed prognostic genes expression in normal and tumor tissues. In conclusion, these results demonstrated the four-gene signature can be a biomarker for predicting HCC prognosis and its members can be drug target genes for HCC treatment.

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A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

BMC Cancer ◽

10.1186/s12885-021-07916-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Dongdong Zhou ◽

Xiaoli Liu ◽

Xinhui Wang ◽

Fengna Yan ◽

Peng Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Surgical Therapy ◽

Calibration Curve ◽

Cox Regression ◽

Validation Cohort ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Alpha Fetoprotein ◽

Clinicopathologic Characteristics

Abstract Background Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC. Methods A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort. Results The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively. Conclusions Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

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NDRG3 overexpression is associated with a poor prognosis in patients with hepatocellular carcinoma

Bioscience Reports ◽

10.1042/bsr20180907 ◽

2018 ◽

Vol 38 (6) ◽

Cited By ~ 1

Author(s):

Ji-sheng Jing ◽

Hongbo Li ◽

Shun-cai Wang ◽

Jiu-ming Ma ◽

La-qing Yu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Survival Curve ◽

Disease Free Survival ◽

Prognostic Indicator ◽

Clinicopathological Characteristics ◽

Pcr Analysis ◽

Kaplan Meier ◽

Tumor Tissues ◽

The Relationship

N-myc downstream-regulated gene 3 (NDRG3), an important member of the NDRG family, is involved in cell proliferation, differentiation, and other biological processes. The present study analyzed NDRG3 expression in hepatocellular carcinoma (HCC) and explored the relationship between expression of NDRG3 in HCC patients and their clinicopathological characteristics. We performed quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry (IHC) analyses on HCC tissues to elucidate NDRG3 expression characteristics in HCC patients. Kaplan–Meier survival curve and Cox regression analyses were used to evaluate the prognoses of 102 patients with HCC. The results revealed that compared with non-tumor tissues, HCC tissues showed significantly higher NDRG3 expression. In addition, our analyses showed that NDRG3 expression was statistically associated with tumor size (P=0.048) and pathological grade (P=0.001). Survival analysis and Kaplan–Meier curves revealed that NDRG3 expression is an independent prognostic indicator for disease-free survival (P=0.002) and overall survival (P=0.005) in HCC patients. The data indicate that NDRG3 expression may be considered as a oncogenic biomarker and a novel predictor for HCC prognosis.

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