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

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.

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

10.21203/rs.3.rs-832380/v1 ◽

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.

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Identification of Key Genes Associated with Progression and Prognosis of Bladder Cancer through Integrated Bioinformatics Analysis

Cancers ◽

10.3390/cancers13235931 ◽

2021 ◽

Vol 13 (23) ◽

pp. 5931

Author(s):

Shiv Verma ◽

Eswar Shankar ◽

Spencer Lin ◽

Vaibhav Singh ◽

E. Ricky Chan ◽

...

Keyword(s):

Bladder Cancer ◽

Cancer Progression ◽

Univariate Analysis ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Kaplan Meier ◽

Human Protein Atlas ◽

Validation Set ◽

Muscle Invasive

Bladder cancer prognosis remains dismal due to lack of appropriate biomarkers that can predict its progression. The study aims to identify novel prognostic biomarkers associated with the progression of bladder cancer by utilizing three Gene Expression Omnibus (GEO) datasets to screen differentially expressed genes (DEGs). A total of 1516 DEGs were identified between non-muscle invasive and muscle invasive bladder cancer specimens. To identify genes of prognostic value, we performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. A total of seven genes, including CDKN2A, CDC20, CTSV, FOXM1, MAGEA6, KRT23, and S100A9 were confirmed with strong prognostic values in bladder cancer and validated by qRT-PCR conducted in various human bladder cancer cells representing stage-specific disease progression. ULCAN, human protein atlas and The Cancer Genome Atlas datasets were used to confirm the predictive value of these genes in bladder cancer progression. Moreover, Kaplan–Meier analysis and Cox hazard ratio analysis were performed to determine the prognostic role of these genes. Univariate analysis performed on a validation set identified a 3-panel gene set viz. CDKN2A, CTSV and FOXM1 with 95.5% sensitivity and 100% specificity in predicting bladder cancer progression. In summary, our study screened and confirmed a 3-panel biomarker that could accurately predict the progression and prognosis of bladder cancer.

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MP34-06 DEVELOPMENT AND EXTERNAL VALIDATION OF A NOVEL 12-GENE SIGNATURE ON MUSCLE-INVASIVE BLADDER CANCER FOR PREDICTION OF OVERALL SURVIVAL: LINKAGE TO DATA FROM THE CANCER GENOME ATLAS

The Journal of Urology ◽

10.1016/j.juro.2017.02.1023 ◽

2017 ◽

Vol 197 (4S) ◽

Author(s):

Huyang Xie ◽

Fangning Wan ◽

Beihe Wang ◽

Yiping Zhu ◽

Yijun Shen ◽

...

Keyword(s):

Overall Survival ◽

Bladder Cancer ◽

External Validation ◽

Gene Signature ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Muscle Invasive Bladder Cancer ◽

Cancer Genome Atlas ◽

Muscle Invasive ◽

Genome Atlas

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Identification of the Role and Clinical Prognostic Value of Target Genes of m6A RNA Methylation Regulators in Glioma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.709022 ◽

2021 ◽

Vol 9 ◽

Author(s):

Peilin Cong ◽

Tingmei Wu ◽

Xinwei Huang ◽

Huazheng Liang ◽

Xiaofei Gao ◽

...

Keyword(s):

Prognostic Value ◽

Target Genes ◽

Cox Regression ◽

Notch Pathway ◽

Gene Signature ◽

Rna Methylation ◽

Prognostic Gene ◽

Cell Experiment ◽

M6a Rna Methylation ◽

Genome Atlas

m6A RNA methylation regulators can regulate the growth, progression, and invasion of glioma cells by regulating their target genes, which provides a reliable support for the m6A regulator–target axes as the novel therapeutic targets and clinical prognostic signature in glioma. This study aimed to explore the role and prognostic value of m6A RNA methylation regulators and their targets. Expression profiles and clinicopathological data were obtained from the Chinese Glioma Genome Atlas (CGGA), The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Clinical Proteome Tumor Analysis Consortium (CPTAC) datasets. Differential expression and correlation analyses were performed between normal and glioma tissues at mRNA and protein levels. Univariate Cox regression, survival, and Lasso Cox regression analyses were conducted to identify and establish the prognostic gene signature. Kaplan–Meier curve, multivariate Cox regression analysis, and ROC were utilized to evaluate the prognostic capacity of the prognostic gene signature. The correlation analysis, systematic bioinformatics analysis, and cell experiment were performed to further understand the potential underlying molecular mechanisms and drug sensitivity. Our results suggested that IGF2BP2, KIAA1429, METTL16, and METTL3, as well as 208 targets are involved in the occurrence of glioma, GBM, and LGG. YTHDF1 and 78 targets involved the occurrence of glioma and GBM, not LGG, among which 181 genes were associated with overall survival. From other findings and our cell experiment results, we demonstrated that METTL3 can activate Notch pathway and facilitate glioma occurrence through regulating its direct targets NOTCH3, DLL3, and HES1, and Notch pathway genes may serve as the potential treatment targets for glioma. Our study established and validated a seven-gene signature comprising METTL3, COL18A1, NASP, PHLPP2, TIMP1, U2AF2, and VEGFA, with a good capability for predicting glioma survival, which may guide therapeutic customization and clinical decision-making. These genes were identified to influence 81 anticancer drug responses, which further contributes to the early phase clinical trials of drug development.

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LCK and CD3E Orchestrate the Tumor Microenvironment and Promote Immunotherapy Response and Survival of Muscle-Invasive Bladder Cancer Patients

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.748280 ◽

2021 ◽

Vol 9 ◽

Author(s):

Xiaonan Zheng ◽

Xinyang Liao ◽

Ling Nie ◽

Tianhai Lin ◽

Hang Xu ◽

...

Keyword(s):

Overall Survival ◽

Bladder Cancer ◽

Prognostic Value ◽

The Cancer Genome Atlas ◽

Invasive Bladder Cancer ◽

Immune Checkpoints ◽

Muscle Invasive Bladder Cancer ◽

Gene Correlation ◽

Multiple Biomarkers ◽

Muscle Invasive

Background: Studies have demonstrated the significance of multiple biomarkers for bladder cancer. Here, we attempt to present biomarkers potentially predictive of the prognosis and immunotherapy response of muscle-invasive bladder cancer (MIBC).Method: Immune and stromal scores were calculated for MIBC patients from The Cancer Genome Atlas (TCGA). Core differential expression genes (DEGs) with prognostic value were identified and validated using an independent dataset GSE31684. The clinical implications of prognostic genes and the inter-gene correlation were presented. The distribution of tumor-infiltrating immune cells (TICs), the correlation with tumor mutation burden (TMB), and the expression of eight immune checkpoint–relevant genes and CD39 were accordingly compared. Two bladder cancer cohorts (GSE176307 and IMvigor210) receiving immunotherapy were recruited to validate the prognostic value of LCK and CD3E for immunotherapy.Results: 361 MIBC samples from TCGA revealed a worse overall survival for higher stromal infiltration (p = 0.009) but a better overall survival for higher immune infiltration (p = 0.042). CD3E and LCK were independently validated by TCGA and GSE31684 to be prognostic for MIBC. CD3E was the most correlative gene of LCK, with a coefficient of r = 0.86 (p < 0.001). CD8+ T cells and macrophage M1 are more abundant in favor of a higher expression of CD3E and LCK in MIBC and across pan-cancers. Immune checkpoints like CTLA4, CD274 (PD-1), and PDCD1 (PD-L1) were highly expressed in high-CD3E and high-LCK groups for MIBC and also for pan-cancers, except for thymoma. LCK and CD3E had a moderate positive correlation with CD39 expression. Importantly, high-LCK and high-CD3E groups had a higher percentage of responders than the low-expression groups both in GSE176307 (LCK: 22.73vs. 13.64%, CD3E: 22.00 vs. 13.16%) and IMvigor210 cohorts (LCK: 28.19 vs. 17.45%, CD3E: 25.50 vs. 20.13%).Conclusion: CD3E and LCK were potential biomarkers of MIBC. CD3E and LCK were positively correlated with several regular immunotherapy biomarkers, which is supported by real-world outcomes from two immunotherapy cohorts.

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Assessment of prognostic implication of a panel of oncogenes in bladder cancer and identification of a 3-gene signature associated with recurrence and progression risk in non-muscle-invasive bladder cancer

Scientific Reports ◽

10.1038/s41598-020-73642-8 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Constance Le Goux ◽

Sophie Vacher ◽

Anne Schnitzler ◽

Nicolas Barry Delongchamps ◽

Marc Zerbib ◽

...

Keyword(s):

Bladder Cancer ◽

Multivariate Analysis ◽

Gene Signature ◽

Invasive Disease ◽

The Cancer Genome Atlas ◽

Molecular Signature ◽

Invasive Bladder Cancer ◽

Muscle Invasive Bladder Cancer ◽

Cancer Genome Atlas ◽

Muscle Invasive

Abstract This study evaluated the prognostic value of a panel of 29 oncogenes derived from the analysis of The Cancer Genome Atlas (TCGA data) or from the recent literature on bladder tumors on a well-characterized series of muscle-invasive bladder cancer (MIBC) and non-MIBC (NMIBC) samples and tried to identify molecular prognostic markers. Mutations of HRAS, FGFR3, PIK3CA and TERT were found in 2.9%, 27.2%, 14.9% and 76.7% of tumor samples, respectively. Concerning NMIBC, on multivariate analysis, RXRA and FGFR3 levels were associated with recurrence-free survival (RFS) (p = 0.0022 and p = 0.0069) and RXRA level was associated with progression to muscle-invasive disease (p = 0.0068). We identified a 3-gene molecular signature associated with NMIBC prognosis. FGFR3 overexpression was associated with reduced response to Bacillus Calmette–Guerin treatment (p = 0.037). As regards MIBC, on multivariate analysis, ERCC2 overexpression was associated with RFS (p = 0.0011) and E2F3 and EGFR overexpression were associated with overall survival (p = 0.014 and p = 0.035). RT-PCR findings were confirmed by IHC for FGFR3. Genomic alterations in MIBC revealed in TCGA data also concern NMIBC and seem to be associated with prognosis in terms of recurrence and progression. Correcting these alterations by targeted therapies seems a promising pharmacological approach.

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Bioinformatic identification of prognostic indicators in bladder cancer

Biomarkers in Medicine ◽

10.2217/bmm-2020-0316 ◽

2020 ◽

Vol 14 (13) ◽

pp. 1243-1254

Author(s):

Jing Quan ◽

Weiyi Zhang ◽

Chong Yu ◽

Yuchen Bai ◽

Jianxin Cui ◽

...

Keyword(s):

Bladder Cancer ◽

Cox Regression ◽

Tumor Stage ◽

Gene Signature ◽

Tumor Burden ◽

The Cancer Genome Atlas ◽

Prognostic Indicators ◽

Prognostic Signature ◽

Additional Information ◽

Immune Related Genes

Aim: Bladder cancer (BC) is one of the most common malignancies with poor prognosis. We aimed to identify a genetic signature for predicting the prognosis of BC. Materials & methods: Kaplan–Meier survival and Cox regression analyses were used to construct a prognostic signature using data from The Cancer Genome Atlas. Results: Fifty four upregulated and 47 downregulated immune-related genes (IRGs) were identified in BC. A prognostic signature based on the expression of five IRGs was determined, which was moderately accurate in the prognosis of tumors. The prognostic signature was correlated with tumor stage, tumor burden and lymph node metastasis. The expression of IRGs were associated with immune infiltration. Conclusion: We determined a five gene signature, which correlates with the prognosis of BC patients, providing additional information for effective treatment.

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