scholarly journals Multiple m6A RNA methylation modulators promote the malignant progression of hepatocellular carcinoma and affect its clinical prognosis

2019 ◽  
Author(s):  
Nanfang Qu ◽  
Haixing Jiang ◽  
Sanyu Qin ◽  
Xuemei Zhang ◽  
Zhengchun Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cancer Genome ◽  
Malignant Progression ◽  
World Health ◽  
Pathological Grade ◽  
Clinical Prognosis ◽  
Rna Methylation ◽  
Expression Levels ◽  
Normal Tissues ◽  
M6a Rna Methylation

Abstract Background: Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death in the world. N 6 -methyladenosine (m 6 A) RNA methylation is dynamically regulated by m 6 A RNA methylation modulators (“writer,” “eraser,” and “reader” proteins), which are associated with cancer occurrence and development. The purpose of this study was to explore the relationships between m 6 A RNA methylation modulators and HCC. Methods: First, using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we compared the expression levels of 13 major m6A RNA methylation modulators between HCC and normal tissues. Second, we applied consensus clustering to the expression data on the m 6 A RNA methylation modulators to divide the HCC tissues into two subgroups (clusters 1 and 2), and we compared the clusters in terms of overall survival (OS), World Health Organization (WHO) stage, and pathological grade. Third, using least absolute shrinkage and selection operator (LASSO) regression, we constructed a risk signature involving the m 6 A RNA methylation modulators that affected OS in TCGA and ICGC analyses. Results: We found that the expression levels of 12 major m6A RNA methylation modulators were significantly different between HCC and normal tissues. After dividing the HCC tissues into clusters 1 and 2, we found that cluster 2 had poorer OS, higher WHO stage, and higher pathological grade. Four m 6 A RNA methylation modulators (YTHDF1, YTHDF2, METTL3, and KIAA1429) affecting OS in the TCGA and ICGC analyses were selected to construct a risk signature, which was significantly associated with WHO stage and was also an independent prognostic marker of OS. Conclusions: In summary, m 6 A RNA methylation modulators are key participants in the malignant progression of HCC and have potential value in prognostication and treatment decisions.

scholarly journals Multiple m6A RNA methylation modulators promote the malignant progression of hepatocellular carcinoma and affect its clinical prognosis

2020 ◽  
Author(s):  
Nanfang Qu ◽  
Sanyu Qin ◽  
Xuemei Zhang ◽  
Xiaotong Bo ◽  
Zhengchun Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cancer Genome ◽  
Malignant Progression ◽  
World Health ◽  
Pathological Grade ◽  
Clinical Prognosis ◽  
Rna Methylation ◽  
Expression Levels ◽  
Normal Tissues ◽  
M6a Rna Methylation

Abstract Background: Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death in the world. N 6 -methyladenosine (m 6 A) RNA methylation is dynamically regulated by m 6 A RNA methylation modulators (“writer,” “eraser,” and “reader” proteins), which are associated with cancer occurrence and development. The purpose of this study was to explore the relationships between m 6 A RNA methylation modulators and HCC. Methods: First, using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we compared the expression levels of 13 major m6A RNA methylation modulators between HCC and normal tissues. Second, we applied consensus clustering to the expression data on the m 6 A RNA methylation modulators to divide the HCC tissues into two subgroups (clusters 1 and 2), and we compared the clusters in terms of overall survival (OS), World Health Organization (WHO) stage, and pathological grade. Third, using least absolute shrinkage and selection operator (LASSO) regression, we constructed a risk signature involving the m 6 A RNA methylation modulators that affected OS in TCGA and ICGC analyses. Results: We found that the expression levels of 12 major m6A RNA methylation modulators were significantly different between HCC and normal tissues. After dividing the HCC tissues into clusters 1 and 2, we found that cluster 2 had poorer OS, higher WHO stage, and higher pathological grade. Four m 6 A RNA methylation modulators (YTHDF1, YTHDF2, METTL3, and KIAA1429) affecting OS in the TCGA and ICGC analyses were selected to construct a risk signature, which was significantly associated with WHO stage and was also an independent prognostic marker of OS. Conclusions: In summary, m 6 A RNA methylation modulators are key participants in the malignant progression of HCC and have potential value in prognostication and treatment decisions.

scholarly journals Multiple m6A RNA methylation modulators promote the malignant progression of hepatocellular carcinoma and affect its clinical prognosis

2020 ◽  
Author(s):  
Nanfang Qu ◽  
Sanyu Qin ◽  
Xuemei Zhang ◽  
Xiaotong Bo ◽  
Zhengchun Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cancer Genome ◽  
Malignant Progression ◽  
World Health ◽  
Pathological Grade ◽  
Clinical Prognosis ◽  
Rna Methylation ◽  
Expression Levels ◽  
Normal Tissues ◽  
M6a Rna Methylation

Abstract Background: Hepatocellular carcinoma (HCC) is the second most common cause of cancer-related death in the world. N 6 -methyladenosine (m 6 A) RNA methylation is dynamically regulated by m 6 A RNA methylation modulators (“writer,” “eraser,” and “reader” proteins), which are associated with cancer occurrence and development. The purpose of this study was to explore the relationships between m 6 A RNA methylation modulators and HCC. Methods: First, using data from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we compared the expression levels of 13 major m6A RNA methylation modulators between HCC and normal tissues. Second, we applied consensus clustering to the expression data on the m 6 A RNA methylation modulators to divide the HCC tissues into two subgroups (clusters 1 and 2), and we compared the clusters in terms of overall survival (OS), World Health Organization (WHO) stage, and pathological grade. Third, using least absolute shrinkage and selection operator (LASSO) regression, we constructed a risk signature involving the m 6 A RNA methylation modulators that affected OS in TCGA and ICGC analyses. Results: We found that the expression levels of 12 major m6A RNA methylation modulators were significantly different between HCC and normal tissues. After dividing the HCC tissues into clusters 1 and 2, we found that cluster 2 had poorer OS, higher WHO stage, and higher pathological grade. Four m 6 A RNA methylation modulators (YTHDF1, YTHDF2, METTL3, and KIAA1429) affecting OS in the TCGA and ICGC analyses were selected to construct a risk signature, which was significantly associated with WHO stage and was also an independent prognostic marker of OS. Conclusions: In summary, m 6 A RNA methylation modulators are key participants in the malignant progression of HCC and have potential value in prognostication and treatment decisions.

scholarly journals N6-methyladenosine (m6A) RNA methylation regulators are associated with clinical prognosis in hepatocellular carcinoma

2020 ◽  
Vol 9 (1) ◽  
pp. 323-334
Author(s):  
Gao Li ◽  
Yue Zhang ◽  
Xiaowei Du ◽  
Wanjun Li ◽  
Yanming Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clinical Prognosis ◽  
Rna Methylation ◽  
M6a Rna Methylation

scholarly journals m6A RNA Methylation Regulators Elicit Malignant Progression and Predict Clinical Outcome in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenli Li ◽  
Jun Liu ◽  
Zhanzhong Ma ◽  
Xiaofeng Zhai ◽  
Binbin Cheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cell ◽  
Clinical Outcome ◽  
Cox Regression ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Rna Methylation ◽  
M6a Rna Methylation

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, and N6-methyladenosine (m6A) is a predominant internal modification of RNA in various cancers. We obtained the expression profiles of m6A-related genes for HCC patients from the International Cancer Genome Consortium and The Cancer Genome Atlas datasets. Most of the m6A RNA methylation regulators were confirmed to be differentially expressed among groups stratified by clinical characteristics and tissues. The clinical factors (including stage, grade, and gender) were correlated with the two subgroups (cluster 1/2). We identified an m6A RNA methylation regulator-based signature (including METTL3, YTHDC2, and YTHDF2) that could effectively stratify a high-risk subset of these patients by univariate and LASSO Cox regression, and receiver operating characteristic (ROC) analysis indicated that the signature had a powerful predictive ability. Immune cell analysis revealed that the genes in the signature were correlated with B cell, CD4 T cell, CD8 T cell, dendritic cell, macrophage, and neutrophil. Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to HCC. Moreover, the nomogram was established based on the signature integrated with clinicopathological features. The calibration curve and the area under ROC also demonstrated the good performance of the nomogram in predicting 3- and 5-year OS in the ICGC and TCGA cohorts. In summary, we demonstrated the vital role of m6A RNA methylation regulators in the initial presentation and progression of HCC and constructed a nomogram which would predict the clinical outcome and provide a basis for individualized therapy.

scholarly journals N6-methyladenosine (m6A) RNA methylation regulator SNRPC is a prognostic biomarker and is correlated with immunotherapy in hepatocellular carcinoma

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jihao Cai ◽  
Minglei Zhou ◽  
Jianxin Xu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Specific Protein ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Rna Methylation ◽  
Gene Set ◽  
Normal Tissues ◽  
Small Nuclear Ribonucleoprotein ◽  
Protein Components ◽  
Nuclear Ribonucleoprotein

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, and due to its complex pathogenic factors, its prognosis is poor. N6-methyladenosine (m6A) RNA methylation plays an important role in the tumorigenesis, progression, and prognosis of many tumors. The m6A RNA methylation regulator small nuclear ribonucleoprotein polypeptide C (SNRPC), which encodes one of the specific protein components of the U1 small nuclear ribonucleoprotein (snRNP) particle, has been proven to be related to the prognosis of patients with HCC. However, the effect of SNRPC on the tumor microenvironment and immunotherapy in HCC remains unclear. Case presentation The HCC RNA-seq profiles in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, including 421 LIHC and 440 LIRI-JP samples, respectively, were used in this study. Both the expression of SNRPC in HCC was upregulated in the TCGA and ICGC databases compared to normal tissues. Next, the expression of SNRPC was validated as a risk factor for prognosis by Kaplan-Meier analysis and employed to establish a nomogram with T pathologic stage. By gene set variation (GSVA) analysis and gene set enrichment (GSEA) analysis, we found that SNRPC was mainly related to protein metabolism and the immune process. Furthermore, the estimation of stromal and immune cells in malignant tumor tissues using expression (ESTIMATE), microenvironment cell population counter (MCP-counter), and single sample GSEA (ssGSEA) algorithms revealed that the high-SNRPC group had a lower stromal score, lower abundance of endothelial cells and fibroblasts, and lower immune infiltration. Ultimately, a tumor immune dysfunction and exclusion (TIDE) analysis revealed that patients in the low-SNRPC group may be more sensitive to immune checkpoint inhibitor therapy. Conclusion SNRPC could serve as a promising prognostic and immunotherapeutic marker in HCC and might contribute to new directions and strategies for HCC treatment.

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 Machine Learning for Building Immune Genetic Model in Hepatocellular Carcinoma Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jun Liu ◽  
Zheng Chen ◽  
Wenli Li
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Score ◽  
Risk Model ◽  
Cox Model ◽  
Cancer Genome ◽  
Algorithm Analysis ◽  
Immune Genes ◽  
Normal Tissues ◽  
Model Based ◽  
Tumor Stages

Background. Hepatocellular carcinoma (HCC) is the leading liver cancer with special immune microenvironment, which played vital roles in tumor relapse and poor drug responses. In this study, we aimed to explore the prognostic immune signatures in HCC and tried to construct an immune-risk model for patient evaluation. Methods. RNA sequencing profiles of HCC patients were collected from the cancer genome Atlas (TCGA), international cancer genome consortium (ICGC), and gene expression omnibus (GEO) databases (GSE14520). Differentially expressed immune genes, derived from ImmPort database and MSigDB signaling pathway lists, between tumor and normal tissues were analyzed with Limma package in R environment. Univariate Cox regression was performed to find survival-related immune genes in TCGA dataset, and in further random forest algorithm analysis, significantly changed immune genes were used to generate a multivariate Cox model to calculate the corresponding immune-risk score. The model was examined in the other two datasets with recipient operation curve (ROC) and survival analysis. Risk effects of immune-risk score and clinical characteristics of patients were individually evaluated, and significant factors were then used to generate a nomogram. Results. There were 52 downregulated and 259 upregulated immune genes between tumor and relatively normal tissues, and the final immune-risk model (based on SPP1, BRD8, NDRG1, KITLG, HSPA4, TRAF3, ITGAV and MAP4K2) can better differentiate patients into high and low immune-risk subpopulations, in which high score patients showed worse outcomes after resection ( p < 0.05 ). The differentially enriched pathways between the two groups were mainly about cell proliferation and cytokine production, and calculated immune-risk score was also highly correlated with immune infiltration levels. The nomogram, constructed with immune-risk score and tumor stages, showed high accuracy and clinical benefits in prediction of 1-, 3- and 5-year overall survival, which is useful in clinical practice. Conclusion. The immune-risk model, based on expression of SPP1, BRD8, NDRG1, KITLG, HSPA4, TRAF3, ITGAV, and MAP4K2, can better differentiate patients into high and low immune-risk groups. Combined nomogram, using immune-risk score and tumor stages, could make accurate prediction of 1-, 3- and 5-year survival in HCC patients.

scholarly journals Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Xiaofei Wang ◽  
Jie Qiao ◽  
Rongqi Wang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Risk Score ◽  
Expression Profiles ◽  
Univariate Analysis ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Good Prediction ◽  
Expression Levels

Abstract The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

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