Expression profiles and prognostic roles of m6A writers, erasers and readers in gastric cancer

2021 ◽  
Vol 17 (20) ◽  
pp. 2605-2620
Author(s):  
Jing-Jing Jing ◽  
Xu Zhao ◽  
Hao Li ◽  
Li-ping Sun ◽  
Yuan Yuan
Keyword(s):  
Gastric Cancer ◽  
Expression Profiles ◽  
Tumor Stage ◽  
The Cancer Genome Atlas ◽  
Pathological Stage ◽  
Rna Methylation ◽  
Web Resources ◽  
Cancer Genome Atlas ◽  
M6a Rna Methylation ◽  
Using Data

Aim: To explore the expression profiles of N6-methyladenosine (m6A) enzymes (writers, erasers and readers) and their associations with gastric cancer (GC) prognosis. Methods: Gene expression was analyzed using the UALCAN and Oncomine web resources. The prognostic roles of these genes in GC were analyzed using data from The Cancer Genome Atlas. Results: Thirteen m6A enzymes were found to be upregulated in GC tissues. The expression of m6A writers METTL3, RBM15 and WTAP was associated with pathological stage. The m6A eraser FTO was related to tumor stage and ALKBH5 expression was related to GC prognosis. The m6A reader YTHDF3 expression was associated with tumor stage. YTHDC2 was associated with survival of GC patients. Conclusion: Abnormal changes of key genes involved in m6A RNA methylation may have an important impact on GC development and prognosis.

scholarly journals Tumor microenvironment characterization in stage IV gastric cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Xianxue Zhang ◽  
Feng Yang ◽  
Zhenbao Wang
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Stage Iv ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Stage Iv Gastric Cancer ◽  
Th 17 ◽  
Cancer Genome Atlas

Abstract Immunotherapy is remarkably affected by the immune environment of the principal tumor. Nonetheless, the immune environment’s clinical relevance in stage IV gastric cancer (GC) is largely unknown. The gene expression profiles of 403 stage IV GC patients in the three cohorts: GEO (Gene Expression Omnibus, GSE84437 (n=292) and GSE62254 (n=77), and TCGA (The Cancer Genome Atlas, n=34) were used in the present study. Using four publicly available stage IV GC expression datasets, 29 immune signatures were expression profiled, and on this basis, we classified stage IV GC. The classification was conducted using the hierarchical clustering method. Three stage IV GC subtypes L, M, and H were identified representing low, medium, and high immunity, respectively. Immune correlation analysis of these three types revealed that Immune H exhibited a better prognostic outcome as well as a higher immune score compared with other subtypes. There was a noticeable difference in the three subgroups of HLA genes. Further, on comparing with other subtypes, CD86, CD80, CD274, CTLA4, PDCD1, and PDCD1LG2 had higher expression in the Immunity H subtype. In stage IV GC, potentially positive associations between immune and pathway activities were displayed, due to the enrichment of pathways including TNF signaling, Th-17 cell differentiation, and JAK-STAT signaling pathways in Immunity H vs Immunity L subtypes. External cohorts from TCGA cohort ratified these results. The identification of stage IV GC subtypes has potential clinical implications in stage IV GC treatment.

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 The Cancer Genome Atlas Predicts the Prognosis of Lung Carcinoma Based on Genes Associated with m6A Methylation

2021 ◽  
Author(s):  
Huanqing Liu ◽  
Tingting Li ◽  
Chunsheng Dong ◽  
Jun Lyu
Keyword(s):  
Lung Cancer ◽  
Survival Rate ◽  
Lung Carcinoma ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Predictive Values ◽  
Rna Methylation ◽  
Cancer Genome Atlas ◽  
M6a Rna Methylation ◽  
Genome Atlas

Abstract Lung cancer has become a predominant cause of death in relation with carcinoma worldwide. N6-methylladenosine (m6A) is a common mRNA that is internally modified, which has a pivotal role in mRNA splicing, outputting, localizing, and translating and in identifying stable features. This study evaluated the expression pattern and prognostic value of m6A-related genes in lung cancer. Expression data of lung cancer samples with related clinical information were obtained from The Cancer Genome Atlas (TCGA). Then, R software was used in combination with several corresponding software packages to identify the regulatory factors of m6A RNA methylation with differential expression. Three genes (METTL3, YTHDF1, and FTO) were overexpressed in lung cancer. METTL3 had a low survival rate (P < 0.05). Significant differences in survival rate were observed among the subgroups, which possessed differently expressed m6A levels. Two latent predicting factors (METTL3 and KIAA1429) that met the independent predictive values were selected. M6A RNA methylation modulators may be involved with the malignant progression of lung cancer, and the two selected risk characteristics of m6A RNA methylation regulators may be a potential prognostic biological marker for guiding customized therapies in patients with lung carcinoma.

scholarly journals Development and Validation of a Unique Gignature of Cancer Stemness-related Genes for Predicting the Overall survival of Colorectal Cancer Patients

2020 ◽  
Author(s):  
Ran Wei ◽  
Jichuan Quan ◽  
Shuofeng Li ◽  
Zhao Lu ◽  
Xu Guan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Cancer Stemness ◽  
Poor Overall Survival ◽  
Tissue Samples ◽  
Cox Regression Analysis ◽  
Rna Methylation ◽  
M6a Rna Methylation

Abstract Background: Cancer stem cells (CSCs), which are characterized by self-renewal and plasticity, are highly correlated with tumor metastasis and drug resistance. To fully understand the role of CSCs in colorectal cancer (CRC), we evaluated the stemness traits and prognostic value of stemness-related genes in CRC.Methods: In this study, the data from 616 CRC patients from The Cancer Genome Atlas (TCGA) were assessed and subtyped based on the mRNA expression-based stemness index (mRNAsi). The correlations of cancer stemness with the immune microenvironment, tumor mutational burden (TMB) and N6-methyladenosine (m6A) RNA methylation regulators were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify the crucial stemness-related genes and modules. Furthermore, a prognostic expression signature was constructed using Lasso-penalized Cox regression analysis. The signature was validated via multiplex immunofluorescence staining of tissue samples in an independent cohort of 48 CRC patients.Results: This study suggests that high mRNAsi scores are associated with poor overall survival in stage Ⅳ CRC patients. Moreover, the levels of TMB and m6A RNA methylation regulators were positively correlated with mRNAsi scores, and low mRNAsi scores were characterized by increased immune activity in CRC. The analysis identified 2 key modules and 34 key genes as prognosis-related candidate biomarkers. Finally, a 3-gene prognostic signature (PARPBP, KNSTRN and KIF2C) was explored together with specific clinical features to construct a nomogram, which was successfully validated in an external cohort. Conclusions: There is a unique correlation between CSCs and the prognosis of CRC patients, and the novel biomarkers related to cell stemness could accurately predict the clinical outcomes of these patients.

scholarly journals A Novel m6A Gene Signature Associated With Regulatory Immune Function for Prognosis Prediction in Clear-Cell Renal Cell Carcinoma

2021 ◽  
Vol 8 ◽  
Author(s):  
Siteng Chen ◽  
Ning Zhang ◽  
Encheng Zhang ◽  
Tao Wang ◽  
Liren Jiang ◽  
...  
Keyword(s):  
Risk Score ◽  
Clear Cell ◽  
Area Under The Curve ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Cell Renal Cell Carcinoma ◽  
Training Cohort ◽  
Rna Methylation ◽  
Cancer Genome Atlas ◽  
Genome Atlas

The important role of N6-methyladenosine (m6A) RNA methylation regulator in carcinogenesis and progression of clear-cell renal cell carcinoma (ccRCC) is poorly understood by now. In this study, we performed comprehensive analyses of m6A RNA methylation regulators in 975 ccRCC samples and 332 adjacent normal tissues and identified ccRCC-related m6A regulators. Moreover, the m6A diagnostic score based on ccRCC-related m6A regulators could accurately distinguish ccRCC from normal tissue in the Meta-cohort, which was further validated in the independent GSE-cohort and The Cancer Genome Atlas-cohort, with an area under the curve of 0.924, 0.867, and 0.795, respectively. Effective survival prediction of ccRCC by m6A risk score was also identified in the Cancer Genome Atlas training cohort and verified in the testing cohort and the independent GSE22541 cohort, with hazard ratio values of 3.474, 1.679, and 2.101 in the survival prognosis, respectively. The m6A risk score was identified as a risk factor of overall survival in ccRCC patients by the univariate Cox regression analysis, which was further verified in both the training cohort and the independent validation cohort. The integrated nomogram combining m6A risk score and predictable clinicopathologic factors could accurately predict the survival status of the ccRCC patients, with an area under the curve values of 85.2, 82.4, and 78.3% for the overall survival prediction in 1-, 3- and 5-year, respectively. Weighted gene co-expression network analysis with functional enrichment analysis indicated that m6A RNA methylation might affect clinical prognosis through regulating immune functions in patients with ccRCC.

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 90-Gene Expression Profiling for Tissue Origin Diagnosis of Cancer of Unknown Primary

2021 ◽  
Vol 11 ◽  
Author(s):  
Yi Zhang ◽  
Lei Xia ◽  
Dawei Ma ◽  
Jing Wu ◽  
Xinyu Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Cancer Of Unknown Primary ◽  
The Cancer Genome Atlas ◽  
Unknown Primary ◽  
Gene Expression Assay ◽  
Primary Location ◽  
Cancer Genome Atlas ◽  
Expression Characteristics

Cancer of unknown primary (CUP), in which metastatic diseases exist without an identifiable primary location, accounts for about 3–5% of all cancer diagnoses. Successful diagnosis and treatment of such patients are difficult. This study aimed to assess the expression characteristics of 90 genes as a method of identifying the primary site from CUP samples. We validated a 90-gene expression assay and explored its potential diagnostic utility in 44 patients at Jiangsu Cancer Hospital. For each specimen, the expression of 90 tumor-specific genes in malignant tumors was analyzed, and similarity scores were obtained. The types of malignant tumors predicted were compared with the reference diagnosis to calculate the accuracy. In addition, we verified the consistency of the expression profiles of the 90 genes in CUP secondary malignancies and metastatic malignancies in The Cancer Genome Atlas. We also reported a detailed description of the next-generation coding sequences for CUP patients. For each clinical medical specimen collected, the type of malignant tumor predicted and analyzed by the 90-gene expression assay was compared with its reference diagnosis, and the overall accuracy was 95.4%. In addition, the 90-gene expression profile generally accurately classified CUP into the cluster of its primary tumor. Sequencing of the exome transcriptome containing 556 high-frequency gene mutation oncogenes was not significantly related to the 90 genes analysis. Our results demonstrate that the expression characteristics of these 90 genes can be used as a powerful tool to accurately identify the primary sites of CUP. In the future, the inclusion of the 90-gene expression assay in pathological diagnosis will help oncologists use precise treatments, thereby improving the care and outcomes of CUP patients.

scholarly journals Molecular basis of distinct oestrogen responses in endometrial and breast cancer

2019 ◽  
Vol 26 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Eva Baxter ◽  
Karolina Windloch ◽  
Greg Kelly ◽  
Jason S Lee ◽  
Frank Gannon ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcriptional Activation ◽  
The Cancer Genome Atlas ◽  
Breast Cancers ◽  
Oestrogen Receptor Alpha ◽  
Limited Success ◽  
Cancer Genome Atlas ◽  
Using Data ◽  
Oestrogen Signalling

Up to 80% of endometrial and breast cancers express oestrogen receptor alpha (ERα). Unlike breast cancer, anti-oestrogen therapy has had limited success in endometrial cancer, raising the possibility that oestrogen has different effects in both cancers. We investigated the role of oestrogen in endometrial and breast cancers using data from The Cancer Genome Atlas (TCGA) in conjunction with cell line studies. Using phosphorylation of ERα (ERα-pSer118) as a marker of transcriptional activation of ERα in TCGA datasets, we found that genes associated with ERα-pSer118 were predominantly unique between tumour types and have distinct regulators. We present data on the alternative and novel roles played by SMAD3, CREB-pSer133 and particularly XBP1 in oestrogen signalling in endometrial and breast cancer.

scholarly journals A Prognostic Nomogram Model Based on mRNA Expression of DNA Methylation-Driven Genes for Gastric Cancer

2020 ◽  
Vol 10 ◽  
Author(s):  
Zuhua Chen ◽  
Bo Liu ◽  
Minxiao Yi ◽  
Hong Qiu ◽  
Xianglin Yuan
Keyword(s):  
Gastric Cancer ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Clinicopathological Parameters ◽  
Dna Hypomethylation

PurposeThe exploration and interpretation of DNA methylation-driven genes might contribute to molecular classification, prognostic prediction and therapeutic choice. In this study, we built a prognostic risk model via integrating analysis of the transcriptome and methylation profile for patients with gastric cancer (GC).MethodsThe mRNA expression profiles, DNA methylation profiles and corresponding clinicopathological information of 415 GC patients were downloaded from The Cancer Genome Atlas (TCGA). Differential expression and correlation analysis were performed to identify DNA methylation-driven genes. The candidate genes were selected by univariate Cox regression analyses followed by the least absolute shrinkage and selection operator (LASSO) regression. A prognostic risk nomogram model was then built together with clinicopathological parameters.Results5 DNA methylation-driven genes (CXCL3, F5, GNAI1, GAMT and GHR) were identified by integrated analyses and selected to construct the prognostic risk model with clinicopathological parameters. High expression and low DNA hypermethylation of F5, GNAI1, GAMT and GHR, as well as low expression and high DNA hypomethylation of CXCL3 were significantly associated with poor prognosis rates, respectively. The high-risk group showed a significantly shorter prognosis than the low-risk group in the TCGA dataset (HR = 0.212, 95% CI = 0.139–0.322, P = 2e-15). The final nomogram model showed high predictive efficiency and consistency in the training and validation group.ConclusionWe construct and validate a prognostic nomogram model for GC based on five DNA methylation-driven genes with high performance and stability. This nomogram model might be a powerful tool for prognosis evaluation in the clinic and also provided novel insights into the epigenetics in GC.

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