scholarly journals Expression pattern and prognostic value of N6-methyladenosine RNA methylation key regulators in hepatocellular carcinoma

Mutagenesis ◽  
2021 ◽  
Vol 36 (5) ◽  
pp. 369-379
Author(s):  
Min Deng ◽  
Lin Fang ◽  
Shao-Hua Li ◽  
Rong-Ce Zhao ◽  
Jie Mei ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Risk Score ◽  
Critical Role ◽  
Risk Groups ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Hepatocellular carcinoma (HCC) is still one of the most common malignancies worldwide. The accuracy of biomarkers for predicting the prognosis of HCC and the therapeutic effect is not satisfactory. N6-methyladenosine (m6A) methylation regulators play a crucial role in various tumours. Our research aims further to determine the predictive value of m6A methylation regulators and establish a prognostic model for HCC. In this study, the data of HCC from The Cancer Genome Atlas (TCGA) database was obtained, and the expression level of 15 genes and survival was examined. Then we identified two clusters of HCC with different clinical factors, constructed prognostic markers and analysed gene set enrichment, proteins’ interaction and gene co-expression. Three subgroups by consensus clustering according to the expression of the 13 genes were identified. The risk score generated by five genes divided HCC patients into high-risk and low-risk groups. In addition, we developed a prognostic marker that can identify high-risk HCC. Finally, a novel prognostic nomogram was developed to accurately predict HCC patients’ prognosis. The expression levels of 13 m6A RNA methylation regulators were significantly upregulated in HCC samples. The prognosis of cluster 1 and cluster 3 was worse. Patients in the high-risk group show a poor prognosis. Moreover, the risk score was an independent prognostic factor for HCC patients. In conclusion, we reveal the critical role of m6A RNA methylation modification in HCC and develop a predictive model based on the m6A RNA methylation regulators, which can accurately predict HCC patients’ prognosis and provide meaningful guidance for clinical treatment.

scholarly journals The role of m6A RNA methylation-related lncRNAs in the prognosis and tumor immune microenvironment of papillary thyroid carcinoma

2021 ◽  
Author(s):  
WenLong Wang ◽  
Cong Shen ◽  
Yunzhe Zhao ◽  
Botao Sun ◽  
Xiangyuan Qiu ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Consensus Clustering ◽  
Papillary Thyroid ◽  
Immune Microenvironment ◽  
Rna Methylation ◽  
Tumor Immune Microenvironment ◽  
M6a Rna Methylation

Abstract Background: Emerging evidence has indicated that N6-methylandenosine (m6A) RNA methylation plays a critical role in cancer development. However, the function of m6A RNA methylation-related long noncoding RNAs (m6A-lncRNAs) in papillary thyroid carcinoma (PTC) has never been reported. This study aimed to investigate the role of m6A-lncRNAs in the prognosis and tumor immune microenvironment of PTC.Methods: The gene expression data of lncRNAs and 20 m6A methylation regulators with corresponding clinicopathological information download from the Cancer Genome Atlas database. Based on consensus clustering analysis, LASSO Cox regression, nivariate and multivariate Cox regression analysis were used to determine the role of m6A-lncRNA in the prognosis and tumor immune microenvironment of PTC.Results: Three subgroups (clusters 1, 2, and 3) were identified by consensus clustering of 19 prognosis-related m6A-lncRNA regulators，of which cluster 1 preferentially related with unfavorable prognosis, lower immune scores, and distinct immune infiltrate level. A risk-score model was established based on 8 prognosis-related m6A-lncRNAs. Patients with a high-risk score had a worse prognosis and the ROC indicated a reliable prediction performance for patients with PTC (AUC=0.802). As expected, the immune scores, infiltration levels of immune cells and ESTIMATE scores in the low-risk subgroups were notably higher (p < 0.001) compared with those of high-risk subgroups. Furthermore, GSEA analysis showed that tumor associated pathways, hallmarks, and biological processes were remarkably enriched in the high-risk subgroup. Further analysis indicated that the risk score and age were independent prognostic factors for PTC. An integrated nomogram was constructed that accurately predicted the survival status (AUC = 0.963). Moreover, a lncRNA–miRNA–mRNA regulated network was established based on seven prognosis-related m6A-lncRNAs. Additional, 30 clinical samples and different PTC cells were validated. Conclusions: This is the first study to reveal that m6A-lncRNAs play a vital role in the prognosis and TME of PTC. To a certain degree, m6A-lncRNAs can be considered as new, promising prognostic biomarkers and treatment targets.

scholarly journals The Role of m6A RNA Methylation-Related lncRNAs in the Prognosis and Tumor Immune Microenvironment of Papillary Thyroid Carcinoma

2022 ◽  
Vol 9 ◽  
Author(s):  
Wenlong Wang ◽  
Cong Shen ◽  
Yunzhe Zhao ◽  
Botao Sun ◽  
Xiangyuan Qiu ◽  
...  
Keyword(s):  
High Risk ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Risk Score ◽  
Critical Role ◽  
Clinical Samples ◽  
Papillary Thyroid ◽  
Rna Methylation ◽  
M6a Rna Methylation

Emerging evidence has indicated that N6-methylandenosine (m6A) RNA methylation plays a critical role in cancer development. However, the function of m6A RNA methylation-related long noncoding RNAs (m6A-lncRNAs) in papillary thyroid carcinoma (PTC) has never been reported. This study aimed to investigate the role of m6A-lncRNAs in the prognosis and tumor microenvironment (TME) of PTC. Three subgroups (clusters 1, 2, and 3) were identified by consensus clustering of 19 prognosis-related m6A-lncRNA regulators, of which cluster 1 is preferentially related to unfavorable prognosis, lower immune scores, and distinct immune infiltrate level. A risk-score model was established based on 8 prognosis-related m6A-lncRNAs. Patients with a high-risk score showed a worse prognosis, and the ROC indicated a reliable prediction performance for patients with PTC (AUC = 0.802). As expected, the immune scores, the infiltration levels of immune cells, and ESTIMATE scores in the low-risk subgroups were notably higher (p &lt; 0.001) when compared with those in high-risk subgroups. Furthermore, GSEA analysis revealed that tumor associated pathways, hallmarks, and biological processes were remarkably enriched in the high-risk subgroup. Further analysis indicated that the risk score and age were independent prognostic factors for PTC. An integrated nomogram was constructed that accurately predicted the survival status (AUC = 0.963). Moreover, a lncRNA–miRNA–mRNA regulated network was established based on seven prognosis-related m6A-lncRNAs. In addition, 30 clinical samples and different PTC cells were validated. This is the first study to reveal that m6A-lncRNAs plays a vital role in the prognosis and TME of PTC. To a certain degree, m6A-lncRNAs can be considered as new, promising prognostic biomarkers and treatment targets.

scholarly journals Construction of a Prognostic m6A-related lncRNA Signature to Predict Immunotherapy and Chemotherapy Response in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Yiping Zou ◽  
Zhihong Chen ◽  
Hongwei Han ◽  
Qi Lou ◽  
Yuanpeng Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
High Risk ◽  
Noncoding Rna ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Tumor Development ◽  
Risk Groups ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Chemotherapy Response

Abstract Hepatocellular carcinoma (HCC) is one of the main causes of cancer-related deaths worldwide. N6-methyladenosine (m6A) and long noncoding RNA (lncRNA) are two common modifications that affect tumor development and play vital roles in the prognosis of HCC. Therefore, we comprehensively analyzed transcriptome data from the Cancer Genome Atlas (TCGA) and identified lncRNAs related to m6A regulators. Univariate, LASSO, and multivariate Cox regression analyses were used to build a prognostic model. Patients were then divided into low- and high-risk groups according to the optimal cut-off point. The prognosis value of the novel model was evaluated using Kaplan-Meier analysis and the receiver operating characteristic curve. Besides, mutation and immune profiles together with immune checkpoint expressions were further explored to identify the difference in somatic alteration and tumor immune landscape between the two groups. Additionally, a better response to conventional chemotherapy and immunotherapy was found in patients with the high-risk group, but they were more resistant to sorafenib. The m6A-related lncRNAs model might be used to predict the prognosis and drug responses in patients with HCC.

scholarly journals A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Yan ◽  
Wenjiang Zheng ◽  
Boqing Wang ◽  
Baoqian Ye ◽  
Huiyan Luo ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Performance ◽  
Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear. Methods Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset. Results A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours. Conclusion Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

scholarly journals Prognostic Value of A Risk Score Model Constructed By m6A Methylation Regulators In Breast Cancer

2021 ◽  
Author(s):  
Xiaowei Qiu ◽  
Qiaoli Zhang ◽  
Jingnan Xu ◽  
Xin Jiang ◽  
Xuewei Qi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Prognostic Value ◽  
Validation Cohort ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Rna Methylation ◽  
Model Based ◽  
Prognosis Model ◽  
M6a Rna Methylation

Abstract Background: N6-methyladenosine (m6A) methylation modification can affect the tumorigenesis, progression, and metastasis of breast cancer (BC). Up to now, a prognostic model based on m6A methylation regulators for BC is still lacking. This study aimed to construct an accurate prediction prognosis model by m6A methylation regulators for BC patients.Methods: After processing of The Cancer Genome Atlas (TCGA) datasets, the differential expression and correlation analysis of m6A RNA methylation regulators were applied. Next, tumor samples were clustered into different groups and clinicopathologic features in different clusters were explored. By univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) analysis, m6A regulators with prognostic value were identified to develop a prediction model. Furthermore, we constructed and validated a predictive nomogram to predict the prognosis of BC patients.Results: 19 m6A related genes were extracted and 908 BC patients enrolled from TCGA dataset. After univariate Cox and LASSO analysis, 3 m6A RNA methylation regulators (YTHDF3, ZC3H13 and HNRNPC) were selected to establish the prognosis model based on median risk score (RS) in training and validation cohort. With the increasing of RS, the expression levels of YTHDF3 and ZC3H13 were individually elevated, while the HNRNPC expressed decreasingly. By survival analysis and Receiver Operating Characteristic (ROC) curve, we found that the overall survival (OS) of high-risk group was significantly shorter than that of the low-risk group based on Kaplan-Meier (KM) analysis in each cohort. Univariate and multivariate analysis identified the RS, age, and pathological stage are independent prognostic factors. A nomogram was constructed to predict 1- and 3-year OS and the calibration plots validate the performance. The C-index of nomogram reached 0.757 (95% CI:0.7-0.814) in training cohort and 0.749 (95% CI:0.648-0.85) in validation cohort, respectively.Conclusions: We successfully constructed a predictive prognosis model by m6A RNA methylation regulators. These results indicated that the m6A RNA methylation regulators are potential therapeutic targets of BC patients.

scholarly journals Retrospective Comparative Analysis of POPF Using Fistula Risk Score According to Pancreaticoenterostomy Method

2021 ◽  
Vol 105 (1-3) ◽  
pp. 559-563
Author(s):  
Seungmin Lee ◽  
Kwang Yeol Paik
Keyword(s):  
High Risk ◽  
Pancreatic Fistula ◽  
Risk Score ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Postoperative Pancreatic Fistula ◽  
Clinical Risk Score ◽  
Reconstructive Methods ◽  
Fistula Risk Score

Background The aim of this study is to examine whether pancreaticogastrostomy (PG) or pancreaticojejunostomy (PJ) is the better reconstructive method to reduce postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy (PD) according to the fistula risk. Methods An institutional database was reviewed for patients undergoing PD between January 2008 and August 2019. A total of 159 patients were stratified into 4 groups according to the Clinical Risk Score-Pancreatic Fistula. POPF according to 4 risk groups was compared between PJ and PG. Results Of the 159 patients, 82 underwent PG (51.6%) and 77 underwent PJ (48.4%) reconstruction. POPF rate was 17.1% (n = 14) in the PG group and 12.9% (n = 10) in the PJ group (P = 0.51). POPF rates were not different in intermediate, low, and negligible risks between 2 reconstructive methods. In the high-risk group (n = 47), there were 4 POPFs (22.2%) in PJ group and 9 (31.0%) in the PG group, respectively (P = 0.74). Conclusion In PD, there was no superior method of reconstruction with regard to POPF, even in high-risk glands.

Prognostic Value of m6A RNA Methylation Modulators and Potential Clinical Application in Pancreatic Cancer

2020 ◽  
Author(s):  
Lianzi Wang ◽  
Huimin Li ◽  
Tao Li ◽  
Huihui Wang ◽  
Xuemei Li ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
High Risk ◽  
Pancreatic Adenocarcinoma ◽  
Risk Score ◽  
Prognostic Indicator ◽  
Gene Set Enrichment Analysis ◽  
Wilcoxon Test ◽  
Rna Methylation ◽  
Incidence And Mortality ◽  
M6a Rna Methylation

Abstract Background m6A is the most prevalent and abundant form of mRNA modification and plays a dual role in cancer development. The high incidence and mortality of pancreatic cancer are critical obstacles worldwide. In this study, we investigated the function of m6A RNA methylation modulators in pancreatic cancer. Methods Expression of 13 m6A RNA methylation modulators and clinical data from patients with pancreatic adenocarcinoma were obtained from TCGA database. Differences in the expression of 13 m6A RNA methylation modulators between tumour (n = 178) and healthy (n = 4) samples were compared by Wilcoxon test. LASSO Cox regression was used to select m6A RNA methylation modulators for analysis of the relationship between expression and clinical characteristics by univariate and multivariate regression. The pathways of the m6A RNA methylation modulators were examined by gene set enrichment analysis (GSEA) and we found enrichment in chemokine, ribosome, and mTOR signalling pathways. Results WTAP had a low expression in tumour samples compared with healthy samples. Furthermore, our analyses revealed that the m6A RNA methylation modulators YTHDF1, ALKBH5, METTL3, METTL14, and KIAA1429 correlated with high-risk patients, resulting in an elevated risk score and a lower overall survival. High-risk score correlated with clinical characteristic and was an independent prognostic indicator for pancreatic adenocarcinoma. The pathways involved were identified by GSEA to explore the potential mechanism of action. Conclusion Modulators involved in m6A RNA methylation were associated with the development of pancreatic cancer. A risk score based on the expression of YTHDF1, ALKBH5, METTL3, METTL14, and KIAA1429 may be an independent prognostic indicator.

scholarly journals Identification of a Pyroptosis-Related Gene Signature for Predicting Overall Survival and Response to Immunotherapy in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Susu Zheng ◽  
Xiaoying Xie ◽  
Xinkun Guo ◽  
Yanfang Wu ◽  
Guobin Chen ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
High Risk ◽  
Regression Model ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
High Risk Group ◽  
Related Gene

Pyroptosis is a novel kind of cellular necrosis and shown to be involved in cancer progression. However, the diverse expression, prognosis and associations with immune status of pyroptosis-related genes in Hepatocellular carcinoma (HCC) have yet to be analyzed. Herein, the expression profiles and corresponding clinical characteristics of HCC samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Then a pyroptosis-related gene signature was built by applying the least absolute shrinkage and selection operator (LASSO) Cox regression model from the TCGA cohort, while the GEO datasets were applied for verification. Twenty-four pyroptosis-related genes were found to be differentially expressed between HCC and normal samples. A five pyroptosis-related gene signature (GSDME, CASP8, SCAF11, NOD2, CASP6) was constructed according to LASSO Cox regression model. Patients in the low-risk group had better survival rates than those in the high-risk group. The risk score was proved to be an independent prognostic factor for overall survival (OS). The risk score correlated with immune infiltrations and immunotherapy responses. GSEA indicated that endocytosis, ubiquitin mediated proteolysis and regulation of autophagy were enriched in the high-risk group, while drug metabolism cytochrome P450 and tryptophan metabolism were enriched in the low-risk group. In conclusion, our pyroptosis-related gene signature can be used for survival prediction and may also predict the response of immunotherapy.

scholarly journals Identification of prognostic hypoxia-related genes signature on the tumor microenvironment in esophageal cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 7743-7758
Author(s):  
Linlin Tan ◽  
◽  
Dingzhuo Cheng ◽  
Jianbo Wen ◽  
Kefeng Huang ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
High Risk ◽  
Immune Cells ◽  
Immune Cell ◽  
Risk Group ◽  
Roc Curves ◽  
Risk Groups ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas

<abstract> <sec><title>Background</title><p>Hypoxia is a crucial factor in the development of esophageal cancer. The relationship between hypoxia and immune status in the esophageal cancer microenvironment is becoming increasingly important in clinical practice. This study aims to clarify and investigate the possible connection between immunotherapy and hypoxia in esophageal cancer.</p> </sec> <sec><title>Methods</title><p>The Cancer Genome Atlas databases are used to find two types of esophageal cancer cases. Cox regressions analyses are used to screen genes for hypoxia-related traits. After that, the genetic signature is validated by survival analysis and the construction of ROC curves. GSEA is used to compare differences in enrichment in the two groups and is followed by the CIBERSORT tool to investigate a potentially relevant correlation between immune cells and gene signatures.</p> </sec> <sec><title>Results</title><p>We found that the esophageal adenocarcinoma hypoxia model contains 3 genes (PGK1, PGM1, SLC2A3), and the esophageal squamous cell carcinoma hypoxia model contains 2 genes (EGFR, ATF3). The findings demonstrated that the survival rate of patients in the high-risk group is lower than in the lower-risk group. Furthermore, we find that three kinds of immune cells (memory activated CD4+ T cells, activated mast cells, and M2 macrophages) have a marked infiltration in the tissues of patients in the high-risk group. Moreover, we find that PD-L1 and CD244 are highly expressed in high-risk groups.</p> </sec> <sec><title>Conclusions</title><p>Our data demonstrate that oxygen deprivation is correlated with prognosis and the incidence of immune cell infiltration in patients with both types of esophageal cancer, which provides an immunological perspective for the development of personalized therapy.</p> </sec> </abstract>

scholarly journals Prognostic Implication of the m6A RNA Methylation Regulators in Rectal Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Yajie Chen ◽  
Shanshan Wang ◽  
William C. Cho ◽  
Xiang Zhou ◽  
Zhen Zhang
Keyword(s):  
Rectal Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Score ◽  
Prognostic Value ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Functional Difference ◽  
Mesenchymal Transition ◽  
Rna Methylation

N6-methyladenosine (m6A) is a very common and abundant RNA modifications occurring in nearly all types of RNAs. Although the dysregulated expression of m6A regulators is implicated in cancer progression, our understanding of the prognostic value of the m6A regulators in rectal cancer is still quite limited. In this study, we analyzed the RNA expression levels of the 17 m6A regulator genes of 95 rectal cancer and 10 normal rectal samples from the The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) dataset. Lasso regression analysis was conducted to build a prognostic model and calculate the risk score. The rectal cancer patients were then devided into the high-risk and low-risk groups according to the mean risk score. The prognostic value of the identified model was separately evaluated in the TCGA-READ and GSE87211 datasets. GSEA was conducted to analyze the functional difference of high-risk and low-risk rectal cancer patients. Our analysis revealed that rectal cancer patients with lower expression of YTHDC2 and METTL14 had a remarkable worse overall survival (P &lt; 0.05). The prognostic value of the model was validated in GSE87211 datasets, with AUC = 0.612 for OS and AUC = 0.651 for RFS. Furthermore, the m6A modification-based risk score system is associated with activation of distinct signaling pathways, such as DNA repair, epithelial-mesenchymal transition, G2M checkpoint and the MYC pathway, that may contribute to the progression of rectal cancer. In conclusion, our findings demonstrated that the m6A RNA methylation regulators, specifically YTHDC2 and METTL14, were significantly down-regulated and might be potential prognostic biomarkers in rectal cancer.

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