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 N6-Methyladenosine RNA Methylation Regulators Contribute to Malignant Progression and Survival Prediction in Chronic Lymphocytic Leukemia

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1738-1738 ◽  
Author(s):  
Ya Zhang ◽  
Xiaosheng Fang ◽  
Na Chen ◽  
Xiao Lv ◽  
Xueling Ge ◽  
...  
Keyword(s):  
Risk Score ◽  
Cox Regression ◽  
Lymphocytic Leukemia ◽  
Functional Enrichment ◽  
Biological Mechanism ◽  
Regression Analyses ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
M6a Rna Methylation

Introduction N6-methyladenosine (m6A) RNA methylation is the most abundant epitranscriptomic modification, dynamically installed by the m6A methyltransferases (termed as "writers"), reverted by the demethylases (termed as "erasers"), and recognized by m6A binding proteins (termed as "readers"). Emerging evidence suggests that m6A RNA methylation regulates RNA stability, and participates in the pathogenesis of multiple diseases including cancers. Nevertheless, the role of m6A RNA methylation in chronic lymphocytic leukemia (CLL) remains to be unveiled. Herein, we hypothesized that m6A RNA methylation contributed to the tumorigenesis and maintenance of CLL. Moreover, the risk-prediction model integrated with the m6A regulators could serve as a novel and effective prognostic indicator in CLL. This study aimed to identify robust m6A RNA methylation-associated fingerprints for risk stratification in patients with CLL. Methods A total of 714 de novo CLL patients from 4 cohorts (China, Spain, Germany and Italy) were enrolled with informed consents. EpiQuik m6A RNA methylation colorimetric quantification assay was utilized to assess m6A RNA methylation levels. LASSO Cox regression algorithm was performed to calculate m6A RNA methylation-associated risk score (short for "m6A risk score") in R software. Besides, Kaplan-Meier survival analysis with log-rank test, univariate and multivariate Cox regression analyses and ROC curve analysis of overall survival (OS) were conduct to explore the prognostic value of m6A signature in CLL. Furthermore, RNA-seq, MeRIP-seq, Ribo-seq, functional enrichment analyses in silico and preclinical experiments ex vivo were applied to confirm the biological mechanism of the m6A regulators in CLL. Results In the present study, we performed a comprehensive analysis to dissect the role of m6A RNA methylation regulators in CLL. Compared with normal B cells from healthy donors, obvious decreased level of m6A RNA methylation was observed in primary CLL cells (p<0.01; Figure 1A). In addition, down-regulated m6A RNA methylation was also detected in CLL cell lines MEC1 and EHEB (p<0.05; Figure 1A). Then, we further investigated the association of the m6A RNA methylation regulators with clinical outcomes of CLL patients. By LASSO Cox regression analysis in 486 CLL patients, the m6A risk score was established with the coefficients of fourteen m6A regulators at the minimum lambda value of 0.00892 (Figure 1B-C). Based on the median risk score as the cut-off value, a clear distribution pattern was delineated in CLL patients (Figure 1D). Kaplan-Meier curves showed stratified high-risk patients presented significantly shorter OS versus the low-risk group (HR=4.477, p<0.001; Figure 2A). Besides, m6A risk score also predicts inferior prognosis in stable subgroup (HR=3.097, p=0.037; Figure 2B), and progressed/ relapsed subgroup (HR=3.325, p=0.001; Figure 2C). Moreover, univariate, multivariate cox regression analyses and ROC curve confirmed high m6A risk score as an independent survival predictor in CLL patients (p<0.001; Figure 2D-E). Thereafter, the clinicopathological relevance and underlying mechanism of m6A risk score were explored. Significant elevated m6A risk score was detected in patients with unfavorable treatment responses compared with stable status (p<0.001; Figure 3A). Furthermore, CLL patients with advanced Binet stage, positive ZAP-70 and unmutated IGHV present increased m6A risk score (p<0.05; Figure 3B-C). Intriguingly, we also observed the significantly negative correlation between highrisk score and 13q14 deletion, in accordance with patients' inferior outcome (p=0.047; Figure 3D). Moreover, Pearson correlation analysis, STRING interactive network and functional enrichment analyses deciphered that the m6A regulators exerted crucial roles in CLL progression potentially via modulating RNA metabolism and oncogenic pathways (Figure 4A-C). Conclusion To date, our study provides evidence for the first time that reduced m6A RNA methylation contributes to the tumorigenesis of CLL. Distinct m6A risk scoreis demonstrated as an efficient tool facilitating prognosis evaluation in CLL patients. However, validation of the signature in more independent cohorts are warranted. Further interrogations will be elucidated on the biological mechanism of m6A regulators, highlighting insights into pathogenesis and therapy strategy of CLL. Disclosures No relevant conflicts of interest to declare.

scholarly journals Role of ferroptosis-related genes in prognostic prediction and tumor immune microenvironment in colorectal carcinoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11745
Author(s):  
Chao Yang ◽  
Shuoyang Huang ◽  
Fengyu Cao ◽  
Yongbin Zheng
Keyword(s):  
High Risk ◽  
Complete Information ◽  
High Risk Group ◽  
Consensus Clustering ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Risk Patients ◽  
Prognostic Prediction ◽  
Public Datasets

Background and Aim Colorectal cancer (CRC) ranks the second most common cause of cancer-related mortality worldwide. Ferroptosis, a recently discovered form of programmed cell death different from other, raises promising novel opportunities for therapeutic intervention of CRC. This study intended to systematically assess the prognosis value and multiple roles of the ferroptosis-related genes in the tumor immune microenvironment of CRC. Materials and Methods Of 1,192 CRC patients with complete information from the public datasets (TCGA CRC, GEO GSE39582 and GSE17538 cohorts) were selected for analysis. Firstly, K-means consensus clustering was performed to identify ferroptosis-associated subtypes in CRC patients. Subsequently, we constructed a risk signature based on ferroptosis-related genes in TCGA cohort and acquired its validation in two GEO cohorts. Additionally, we established a nomogram integrating the risk signature and clinical factors to improve risk assessment of CRC patients. Results Five molecular subtypes were identified by consensus clustering for ferroptosis-related genes. There were significant differences in the overall survival, immune cells infiltration status and PD1/PD-L1 mRNA among the five clusters. Then, a risk signature based on the ten-gene was constructed which could distinguish effectively high-risk group among CRC patients in both training and validation sets. The high-risk patients were more likely to have an inhibitory immune microenvironment and lower stemness features. A prognostic nomogram integrated risk signature and clinicopathological features could be used as a more accurate prognostic prediction visualization tool than TNM stage alone. Conclusion This ferroptosis risk signature may accurately differentiate between different risk populations and predict the prognosis of CRC. Besides, this study elucidated the crucial role of ferroptosis in tumor immune microenvironment.

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 A Lipid Metabolism-Related Genes Prognosis Biomarker Associated With The Tumor Immune Microenvironment in Colorectal Carcinoma

2021 ◽  
Author(s):  
Chao YANG ◽  
Shuoyang Huang ◽  
Yongbin ZHENG ◽  
Fengyu CAO
Keyword(s):  
Lipid Metabolism ◽  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Expression Profiles ◽  
Low Risk ◽  
Metabolic Reprogramming ◽  
Immune Microenvironment ◽  
Potential Biomarker ◽  
Tumor Immune Microenvironment

Abstract Background: Lipid metabolic reprogramming was considered as a new hallmark of malignant tumors. It has been reported to play a crucial biological role in cell proliferation, energy homeostasis and signal-transduction. However, the important value of lipid metabolism-related genes(LMRGs) in prognostic prediction and the tumor immune microenvironment has not been explored by large sample studies in colorectal cancer(CRC). Methods: In this study, the lipid metabolism status of 1086 CRC samples was analyzed using RNA expression profiles and clinical data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, of which the former was determined as training set and the latter as validation set. The risk signature was constructed by the univariate Cox regression and Least Absolute Shrinkage and Selection Operator(LASSO) COX regression. The patients were stratified into high- and low-risk groups according to the median value of the risk score. Immune and mutation landscape between low- and high-risk CRC patients were also explored. Additionally, we established a nomogram integrating the risk signature and clinical factors to improve risk assessment of CRC patients. Results: A four LMRGs signature, including PROCA1, CCKBR, CPT2 and FDFT1, was constructed to predict the prognosis of CRC. The risk signature as an independent prognostic factor for CRC was associated with a variety of parameters. Survival analysis showed that patients with low risk score had a better prognosis. There were different immune landscapes between low and high-risk CRC patients, especially in monocytes, dendritic cells, M0 and M2-like macrophages. Patients in the low-risk group were more likely to have higher tumor mutation burden, stem cell characteristics and level of PD-L1 expression. In addition, it was found that genes that played crucial biological functions in tumorigenesis (including TP53, PI3K and MUC16) had significant differences in mutation frequency between two groups. Conclusion: A lipid metabolism-related risk signature for predicting the prognosis of CRC was identified in this study. Furthermore, this prognostic signature may be a potential biomarker for predicting the efficacy of chemotherapy and anti-PD-L1 therapy in CRC.

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 Prognostic Modeling of Patients with Metastatic Melanoma Based on Tumor Immune Microenvironment Characteristics

2021 ◽  
Author(s):  
Jing Liu ◽  
Ting Ye ◽  
Xue fang Zhang ◽  
Yong jian Dong ◽  
Wen feng Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Metastatic Melanoma ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Low Risk ◽  
Risk Scores ◽  
Immune Microenvironment ◽  
Immune Infiltration ◽  
Tumor Immune Microenvironment

Abstract Most of the malignant melanomas are already in the middle and advanced stages when they are diagnosed, which is often accompanied by the metastasis and spread of other organs.Besides, the prognosis of patients is bleak. The characteristics of the local immune microenvironment in metastatic melanoma have important implications for both tumor progression and tumor treatment. In this study, data on patients with metastatic melanoma from the TCGA and GEO datasets were selected for immune, stromal, and estimate scores, and overlapping differentially expressed genes (DEGs) were screened. A nine-IRGs prognostic model (ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) was established by univariate COX regression, LASSO and multivariate COX regression. Receiver operating characteristic (ROC) curves were used to test the predictive accuracy of the model. Immune infiltration was analyzed by using CIBERSORT, Xcell and ssGSEA in high-risk and low-risk groups. The immune infiltration of the high-risk group was significantly lower than that of the low-risk group. Immune checkpoint analysis revealed that the expression of PDCD1, CTLA4, TIGIT, CD274, HAVR2 and LAG3 were significantly different in groups with different levels of risk scores. WGCNA analysis found that the yellow-green module contained seven genes (ALOX5AP, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22) from the nine-IRG prognostic model, of which the yellow-green module had the highest correlation with risk scores. The results of GO and KEGG suggested that the genes in the yellow-green module were mainly enriched in immune-related biological processes. Finally, we analyzed the prognostic ability and expression characteristics of ALOX5AP, ARHGAP15, CCL8, FCER1G, GBP4, HCK, MMP9, RARRES2 and TRIM22 in metastatic melanoma. Overall, a prognostic model for metastatic melanoma based on the characteristics of the tumor immune microenvironment was established, which was helpful for further studies.It could function well in helping people to understand the characteristics of the immune microenvironment in metastatic melanoma and to find possible therapeutic targets.

scholarly journals A Ferroptosis-Related Signature Robustly Predicts Clinical Outcomes and Associates With Immune Microenvironment for Thyroid Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Mingqin Ge ◽  
Jie Niu ◽  
Ping Hu ◽  
Aihua Tong ◽  
Yan Dai ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cell ◽  
Cox Regression ◽  
Low Risk ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Microenvironment ◽  
Cox Regression Analysis

Objective: This study aimed to construct a prognostic ferroptosis-related signature for thyroid cancer and probe into the association with tumor immune microenvironment.Methods: Based on the expression profiles of ferroptosis-related genes, a LASSO cox regression model was established for thyroid cancer. Kaplan-Meier survival analysis was presented between high and low risk groups. The predictive performance was assessed by ROC. The predictive independency was validated via multivariate cox regression analysis and stratified analysis. A nomogram was established and verified by calibration curves. The enriched signaling pathways were predicted via GSEA. The association between the signature and immune cell infiltration was analyzed by CIBERSORT. The ferroptosis-related genes were validated in thyroid cancer tissues by immunohistochemistry and RT-qPCR.Results: A ferroptosis-related eight gene model was established for predicting the prognosis of thyroid cancer. Patients with high risk score indicated a poorer prognosis than those with low risk score (p = 1.186e-03). The AUCs for 1-, 2-, and 3-year survival were 0.887, 0.890, and 0.840, respectively. Following adjusting other prognostic factors, the model could independently predict the prognosis (p = 0.015, HR: 1.870, 95%CI: 1.132–3.090). A nomogram combining the signature and age was constructed. The nomogram-predicted probability of 1-, 3-, and 5-year survival approached the actual survival time. Several ferroptosis-related pathways were enriched in the high-risk group. The signature was distinctly associated with the immune cell infiltration. After validation, the eight genes were abnormally expressed between thyroid cancer and control tissues.Conclusion: Our findings established a prognostic ferroptosis-related signature that was associated with the immune microenvironment for thyroid cancer.

scholarly journals Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs

2021 ◽  
Vol 8 ◽  
Author(s):  
Li Zhang ◽  
Xianzhe Tang ◽  
Jia Wan ◽  
Xianghong Zhang ◽  
Tao Zheng ◽  
...  
Keyword(s):  
High Risk ◽  
Soft Tissue ◽  
Cox Regression ◽  
Soft Tissue Sarcomas ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Consensus Clustering ◽  
Immune Microenvironment

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations.Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan–Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature.Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS.Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

scholarly journals m6A RNA methylation regulators can contribute to malignant progression and impact the prognosis of bladder cancer

2019 ◽  
Vol 39 (12) ◽  
Author(s):  
Mei Chen ◽  
Zhen-yu Nie ◽  
Xiao-hong Wen ◽  
Yuan-hui Gao ◽  
Hui Cao ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Malignant Progression ◽  
Low Risk ◽  
Rna Methylation ◽  
M6a Rna Methylation ◽  
Clinicopathological Variables

Abstract N6-methyladenosine (m6A) is the most common form of messenger RNA (mRNA) modification. An increasing number of studies have proven that m6A RNA methylation regulators are overexpressed in many cancers and participate in the development of cancer through the dynamic regulation of m6A RNA methylation regulators. However, the prognostic role of m6A RNA methylation regulators in bladder cancer (BC) is poorly understood. In the present study, we downloaded the mRNA expression data from The Cancer Genome Atlas (TCGA) database and the corresponding clinical and prognostic information. The relationship between m6A RNA methylation regulators and clinicopathological variables of BC patients was assessed by the Kolmogorov–Smirnov test. The expression of the m6A RNA methylation regulators was differentially associated with different clinicopathological variables of BC patients. The least absolute shrinkage and selection operator (LASSO) Cox regression model was then applied to identify three m6A RNA methylation regulators. The risk signature was constructed as follows: 0.164FTO − (0.081YTHDC1+0.032WTAP). Based on the risk signature, the risk score of each patient was calculated, and the patients were divided into a high-risk group and a low-risk group. The overall survival (OS) rate of the high-risk group was significantly lower than that of the low-risk group. The risk signature was not only an independent prognostic marker for BC patients but also a predictor of clinicopathological variables. In conclusion, m6A RNA methylation regulators can participate in the malignant progression of BC, and a risk signature with three selected m6A RNA methylation regulators may be a promising prognostic biomarker to guide personalized treatment for BC patients.

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