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 Development a Prognostic Model Integrating lncRNA/ mRNA novel Biomarkers Identified by Bioinformatics Analysis and Experiments in Breast Cancer

2021 ◽  
Author(s):  
Jinrong Wei ◽  
Qianshu Dou ◽  
Futing Ba ◽  
Guo-Qin Jiang
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
High Risk ◽  
Risk Score ◽  
Risk Group ◽  
Low Risk ◽  
Breast Cancers ◽  
Rt Pcr ◽  
Cerna Network ◽  
Prognosis Model

Abstract Purpose: The purpose of this study is to established a prognosis model based on the expression profiles of lncRNAs and mRNAs for breast cancers.Methods: Single Variable Cox Proportional Risk Regression analysis and difference analysis were applied to screen survival-related and differently expressed lncRNAs and mRNAs between tumor and normal tissues from TCGA data. GO and KEGG analysis were applied for top 30 survival-related genes. LncRNA/mRNA co-expressed network was constructed based on correlation analysis. LASSO analysis and Multivariate Stepwise Cox Regression analysis were applied to establish the prognosis model. RT-PCR experiments were applied to verify the correctness of the analysis results. Relative components of the TME in breast cancers with high and low risk groups were analysed by xCell and Cox proportional risk regression analysis. The ceRNA network was constructed by calculating the Pearson correlation coefficient (PCC) for miRNA-mRNA and miRNA-lncRNA using paired miRNA, mRNA, and lncRNA expression profile data.Results:Venn diagrams showed that there were 60 genes and 54 lncRNAs that were differently expressed and related with survival. Through lncRNA/mRNA co-expressed network construction, 19 lncRNA and 16 mRNA hub genes were gained. The genes were then included in LASSO and multivariate Cox proportional hazard regression analysis, and finally, 3 lncRNAs (LINC01497, LINC02766, LINC02528) and 2 mRNAs (C20orf85, CST1) were selected as prognosis predictive genes. According to the median risk score of the 5 candidates, patients were divided into high-risk group and low-risk group. The results of RT-PCR were consistent with the analysis results. The proportions of Adipocytes, Endothelial cells, HSCs, Fibroblasts were significantly lower in low risk score tissues compared with the high risk score tissues, while the proportions of M1 macrophages, MSCs, Th2 cells were significantly higher. A lncRNA-miRNA-mRNA ceRNA network containing 3 lncRNAs, 2 mRNAs, and 158 miRNAs was finally constructed, preliminarily revealed a proper mechanism of the 5 molecules playing important roles in breast cancer progression and prognosis prediction.Conclusion: We found that LINC01497, LINC02766, LINC02528 and C20orf85, CST1 may serve as a powerful prognostic tool to optimize the prognosis evaluation system of breast cancer.

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 < 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.

scholarly journals m5C-Related lncRNAs Predict Overall Survival of Patients and Regulate the Tumor Immune Microenvironment in Lung Adenocarcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Junfan Pan ◽  
Zhidong Huang ◽  
Yiquan Xu
Keyword(s):  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Immune Cells ◽  
Prognostic Value ◽  
Risk Model ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Rna Methylation

Long non-coding RNAs (lncRNAs), which are involved in the regulation of RNA methylation, can be used to evaluate tumor prognosis. lncRNAs are closely related to the prognosis of patients with lung adenocarcinoma (LUAD); thus, it is crucial to identify RNA methylation-associated lncRNAs with definitive prognostic value. We used Pearson correlation analysis to construct a 5-Methylcytosine (m5C)-related lncRNAs–mRNAs coexpression network. Univariate and multivariate Cox proportional risk analyses were then used to determine a risk model for m5C-associated lncRNAs with prognostic value. The risk model was verified using Kaplan–Meier analysis, univariate and multivariate Cox regression analysis, and receiver operating characteristic curve analysis. We used principal component analysis and gene set enrichment analysis functional annotation to analyze the risk model. We also verified the expression level of m5C-related lncRNAs in vitro. The association between the risk model and tumor-infiltrating immune cells was assessed using the CIBERSORT tool and the TIMER database. Based on these analyses, a total of 14 m5C-related lncRNAs with prognostic value were selected to build the risk model. Patients were divided into high- and low-risk groups according to the median risk score. The prognosis of the high-risk group was worse than that of the low-risk group, suggesting the good sensitivity and specificity of the constructed risk model. In addition, 5 types of immune cells were significantly different in the high-and low-risk groups, and 6 types of immune cells were negatively correlated with the risk score. These results suggested that the risk model based on 14 m5C-related lncRNAs with prognostic value might be a promising prognostic tool for LUAD and might facilitate the management of patients with LUAD.

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 Ferroptosis regulators, especially SQLE, play an important role in prognosis, progression and immune environment of breast cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenqing Tang ◽  
Fangshi Xu ◽  
Meng Zhao ◽  
Shuqun Zhang
Keyword(s):  
Breast Cancer ◽  
Risk Score ◽  
Prognostic Value ◽  
Risk Group ◽  
Immune Checkpoints ◽  
Risk Level ◽  
Lasso Regression ◽  
Luminal A ◽  
Prognostic Assessment

Abstract Background Ferroptosis, a new form of programmed cell death, has great potential for cancer treatment. However, the roles of ferroptosis-related (FR) genes in breast cancer (BC) remain elusive. Materials and methods Using TCGA database, a novel FR risk signature was constructed through the Lasso regression analysis. Meanwhile, its prognostic value was assessed by a series of survival analyses. Besides, a nomogram was constructed to predict the overall survival rate (OSR) of individual at 1,3,5 year. Four validation cohorts (n = 2248), including METABRIC, GSE58812, GSE20685 and ICGC-KR datasets, were employed to test the prognostic value of FR risk signature. The effects of FR risk signature on BC immune microenvironment were explored by CIBERSORT algorithm and ssGSEA method. The histological expressions of FR risk genes were presented by HPA database. The biofunctions of SQLE were determined by qPCR, MTT, wound-healing and Transwell assays. Results We constructed a novel FR risk signature consisting of eight genes. High FR risk led a poor prognosis and was identified as an independent prognostic factor. Besides, A higher proportion of patients with luminal A type was observed in low-risk group (53%), while a higher proportion of patients with basal type in high-risk group (24%). FR risk score could discriminate the prognostic difference of most clinical subgroups, except for M1 stage, HER2 and basal types. Moreover, its prognostic value was successfully validated in other four cohorts. Through immune analyses, we found that the reduced infiltration levels of CD8+ and NK cells, whereas the enhanced activity of antigen presentation process appeared in high FR risk. Then, FR risk score was found to weakly correlate with the expressions of six immune checkpoints. Through the experiments in vitro, we confirmed that overexpression of SQLE could promote, whereas blocking SQLE could inhibit the proliferative, migrative and invasive abilities of BC cells. Conclusions FR risk signature was conducive to BC prognostic assessment. High FR risk level was closely associated with BC immunosuppression, but may not predict ICIs efficacy. Moreover, SQLE was identified as a crucial cancer-promoting gene in BC. Our findings provide new insights into prognostic assessment and molecular mechanism of BC.

scholarly journals A Ferroptosis-Related lncRNAs Signature Predicts Prognosis and Immune Microenvironment for Breast Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Kaiming Zhang ◽  
Liqin Ping ◽  
Tian Du ◽  
Gehao Liang ◽  
Yun Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Prognostic Value ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
High Risk Group ◽  
Breast Cancer Patients ◽  
Immune Microenvironment ◽  
Cox Regression Analysis

Background: Ferroptosis, a regulated cell death which is driven by the iron-dependent peroxidation of lipids, plays an important role in cancer. However, studies about ferroptosis-related Long non-coding RNAs (lncRNAs) in breast cancer (BC) are limited. Besides, the prognostic role of ferroptosis-related lncRNAs and their relationship to immune microenvironment in breast cancer remain unclear. This study aimed to explore the potential prognostic value of ferroptosis-related lncRNAs and their relationship to immune microenvironment in breast cancer.Methods: RNA-sequencing data of female breast cancer patients were downloaded from TCGA database. 937 patients were randomly separated into training or validation cohort in 2:1 ratio. Ferroptosis-related lncRNAs were screened by Pearson correlation analysis with 239 reported ferroptosis-related genes. A ferroptosis-related lncRNAs signature was constructed with univariate and multivariate Cox regression analyses in the training cohort, and its prognostic value was further tested in the validation cohort.Results: An 8-ferroptosis-related-lncRNAs signature was developed by multivariate Cox regression analysis to divide patients into two risk groups. Patients in the high-risk group had worse prognosis than patients in the low-risk group. Multivariate Cox regression analysis showed the risk score was an independent prognostic indicator. Receiver operating characteristic curve (ROC) analysis proved the predictive accuracy of the signature. The area under time-dependent ROC curve (AUC) reached 0.853 at 1 year, 0.802 at 2 years, 0.740 at 5 years in the training cohort and 0.791 at 1 year, 0.778 at 2 years, 0.722 at 5 years in the validation cohort. Further analysis demonstrated that immune-related pathways were significantly enriched in the high-risk group. Analysis of the immune cell infiltration landscape showed that breast cancer in the high-risk group tended be immunologically “cold”.Conclusion: We identified a novel ferroptosis-related lncRNA signature which could precisely predict the prognosis of breast cancer patients. Ferroptosis-related lncRNAs may have a potential role in the process of anti-tumor immunity and serve as therapeutic targets for breast cancer.

scholarly journals Quantification of m6A RNA methylation modulators pattern was a potential biomarker for prognosis and associated with tumor immune microenvironment of pancreatic adenocarcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lianzi Wang ◽  
Shubing Zhang ◽  
Huimin Li ◽  
Yang Xu ◽  
Qiang Wu ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
High Risk ◽  
Pancreatic Adenocarcinoma ◽  
Risk Score ◽  
Gene Set Enrichment Analysis ◽  
Wilcoxon Test ◽  
Rna Methylation ◽  
Potential Biomarker ◽  
Prognosis Model ◽  
M6a Rna Methylation

Abstract Background m6A is the most prevalent and abundant form of mRNA modifications and is closely related to tumor proliferation, differentiation, and tumorigenesis. In this study, we try to conduct an effective prediction model to investigated the function of m6A RNA methylation modulators in pancreatic adenocarcinoma and estimated the potential association between m6A RNA methylation modulators and tumor microenvironment infiltration for optimization of treatment. Methods Expression of 28 m6A RNA methylation modulators and clinical data of patients with pancreatic adenocarcinoma and normal samples were obtained from TCGA and GTEx database. Differences in the expression of 28 m6A RNA methylation modulators between tumour (n = 40) and healthy (n = 167) samples were compared by Wilcoxon test. LASSO Cox regression was used to select m6A RNA methylation modulators to analyze the relationship between expression and clinical characteristics by univariate and multivariate regression. A risk score prognosis model was conducted based on the expression of select m6A RNA methylation modulators. Bioinformatics analysis was used to explore the association between the m6Ascore and the composition of infiltrating immune cells between high and low m6Ascore group by CIBERSORT algorithm. Evaluation of m6Ascore for immunotherapy was analyzed via the IPS and three immunotherapy cohort. Besides, the biological signaling pathways of the m6A RNA methylation modulators were examined by gene set enrichment analysis (GSEA). Results Expression of 28 m6A RNA methylation modulators were upregulated in patients with PAAD except for MTEEL3. An m6Ascore prognosis model was established, including KIAA1429, IGF2BP2, IGF2BP3, METTL3, EIF3H and LRPPRC was used to predict the prognosis of patients with PAAD, the high risk score was an independent prognostic indicator for pancreatic adenocarcinoma, and a high risk score presented a lower overall survival. In addition, m6Ascore was related with the immune cell infiltration of PAAD. Patients with a high m6Ascore had lower infiltration of Tregs and CD8+T cells but a higher resting CD4+ T infiltration. Patients with a low m6Ascore displayed a low abundance of PD-1, CTLA-4 and TIGIT, however, the IPS showed no difference between the two groups. The m6Ascore applied in three immunotherapy cohort (GSE78220, TCGA-SKCM, and IMvigor210) did not exhibit a good prediction for estimating the patients’ response to immunotherapy, so it may need more researches to figure out whether the m6A modulator prognosis model would benefit the prediction of pancreatic patients’ response to immunotherapy. Conclusion Modulators involved in m6A RNA methylation were associated with the development of pancreatic cancer. An m6Ascore based on the expression of IGF2BP2, IGF2BP3, KIAA1429, METTL3, EIF3H and LRPPRC is proposed as an indicator of TME status and is instrumental in predicting the prognosis of pancreatic cancer patients.

scholarly journals Analysis and validation of m6A regulatory network: a novel circBACH2/has-miR-944/HNRNPC axis in breast cancer progression

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wenchang Lv ◽  
Yufang Tan ◽  
Mingchen Xiong ◽  
Chongru Zhao ◽  
Yichen Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Signaling Pathway ◽  
Regulatory Network ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
The Cancer Genome Atlas ◽  
Circular Rnas ◽  
Rna Methylation ◽  
M6a Rna Methylation ◽  
Low Expression

Abstract Background N6-methyladenosine (m6A), the most abundant and reversible modification of mRNAs in eukaryotes, plays pivotal role in breast cancer (BC) tumorigenesis and progression. Circular RNAs (circRNAs) can act as tumor promoters or suppressors by microRNA (miRNA) sponges in BC. However, the underlying mechanism of circRNAs in BC progression via regulating m6A modulators remains unclear. Methods Prognostic m6A RNA methylation regulators were identified in 1065 BC patients from The Cancer Genome Atlas (TCGA) project. Differentially expressed (DE) miRNAs and DE circRNAs were identified between BC and normal samples in TCGA and GSE101123, respectively. MiRNA-mRNA interactive pairs and circRNA-miRNA interactive pairs were verified by MiRDIP and Circular RNA Interactome. GSEA, KEGG, and ssGSEA were executed to explore the potential biological and immune functions between HNRNPC-high and HNRNPC-low expression groups. qRT-PCR and Western blot were used to quantify the expression of HNRNPC and circBACH2 in MCF-7 and MDA-MB-231 cells. The proliferation of BC cells was assessed by CCK-8 and EdU assay. Results 2 m6A RNA methylation regulators with prognostic value, including HNRNPC and YTHDF3, were identified in BC patients. Then, the regulatory network of circRNA-miRNA-m6A modulators was constructed, which consisted of 2 DE m6A modulators (HNRNPC and YTHDF3), 12 DE miRNAs, and 11 DE circRNAs. Notably, BC patients with high expression of HNRNPC and low expression of hsa-miR-944 were correlated with late clinical stages and shorter survival times. Besides, the results from the KEGG inferred that the DE HNRNPC was associated with the MAPK signaling pathway in BC. Moreover, the circBACH2 (hsa_circ_0001625) was confirmed to act as hsa-miR-944 sponge to stimulate HNRNPC expression to promote BC cell proliferation via MAPK signaling pathway, thus constructing a circBACH2/hsa-miR-944/HNRNPC axis in BC. Conclusions Our findings decipher a novel circRNA-based m6A regulatory mechanism involved in BC progression, thus providing attractive diagnostic and therapeutic strategies for combating BC.

scholarly journals A Novel Signature Based on Pyroptosis-Related Genes for Predicting Breast Cancer

2021 ◽  
Author(s):  
Shuang Shen ◽  
Xin Chen ◽  
Rui Qu ◽  
Youming Guo ◽  
Yingying Su ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Independent Predictive Factor ◽  
Tumour Immunity

Abstract Background: Breast cancer (BC) surpassed lung cancer as the most frequent malignant tumour in women. In recent years, pyroptosis has revealed itself as an inflammatory form of programmed cell death. However, it is unclear as to the expression of genes associated with pyroptosis in BC and its relationship to prognosis. Results: In this study, we identified 31 pyroptosis regulators that are differentially expressed between BC and normal breast. The differently expressed genes (DEG) allow BC patients to be divided into three subtypes. Through single-factor and multi-factor COX regression and the application of least absolute contraction and selection operator (LASSO) Cox regression method, the survival prognostic value of each gene related to pyroptosis in The Cancer Genome Atlas (TCGA) cohort was evaluated, and a 4-gene signature was constructed. BC patients of the TCGA cohort are divided into low-risk or high-risk groups by risk score. The survival of the low-risk group was significantly higher than the high-risk group (P <0.001). Using the median risk score from the TCGA cohort, BC patients from the Gene Expression Omnibus (GEO) cohort were divided into two risk sub-groups and similar conclusions were drawn. In combination with clinicopathological characteristics, the risk score is an independent predictive factor of OS in BC patients. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) indicated that the high-risk group's immune genes were enriched and immune status was reduced. Conclusions: In conclusion, pyroptosis-related genes are important for tumour immunity and can be used to predict the prognosis of BC.

scholarly journals A new m6A methylation-related gene signature for prognostic value in patient with urothelial carcinoma of the bladder

2021 ◽  
Author(s):  
Bin Zheng ◽  
Jianwei Wang ◽  
Guiting Zhao ◽  
Xiaoxu Chen ◽  
Zhongshun Yao ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Prognostic Value ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Rna Methylation ◽  
Human Protein Atlas ◽  
Carcinoma Of The Bladder ◽  
M6a Rna Methylation ◽  
Muscle Invasive

Background: Bladder cancer (BC) is one of the most common malignant urological cancer in the world. Because of its characteristic of easy-recurrence and muscle-invasive, advances in our genetic understanding of bladder cancer should be translated into prognostic indicators. Methods: We investigated 16 m6A RNA methylation regulators from The Cancer Genome Atlas (TCGA) database and The Human Protein Atlas (HPA) database. The expression profile, clinical application as well as prognostic value of these genes in UC were investigated. Moreover, we further explored the correlation between RNA methylation genes and biological functions, pathways and immune status. Results: Five m6A-related genes (HNRNPC, YTHDF2, YTHDF1, HNRNPA2B1, METTL3) upregulated in UC tissues, while three regulators (ZC3H13, METTL16, FTO) downregulated in UC. FTO and YTHDF2 show biomarker potential for the prognosis of UC patients. In addition, these identified genes may related with essential functions and core molecular pathways. Conclusions: Our research shows that two m6A RNA methylation regulators can serve as reliable prognostic biomarkers of UC, which might be exerted as potential targets of therapeutic strategies.

Sign in / Sign up

Export Citation Format

Share Document