Dataset Information

Identification and validation of m⁶A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.

ABSTRACT:

Background

Papillary thyroid cancer (PTC) is a type of malignant tumor with excellent prognosis, accounting for more than 80% of thyroid cancer. Recently, numerous studies illustrated the importance of N ⁶-methyladenosine (m⁶A) RNA modification to tumorigenesis, but it has never been reported in PTC.

Methods

We downloaded data from The Cancer Genome Atlas (TCGA) and analyzed RNA expression, single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) of 19 m⁶A RNA methylation regulators in PTC. Then we used nonnegative matrix factorization (NMF) to cluster patients into two m⁶A subtypes and compared them in overall survival (OS) and disease-free survival (DFS). The Weighted correlation network analysis (WGCNA) and univariate Cox proportional hazard model (CoxPH) were used to select genes for the construction of a m⁶A-related signature. The accuracy and prognostic value of this signature were validated by using receiver operating characteristic (ROC) curves, K-M (Kaplan-Meier) survival analysis, univariant and multivariant analyses.

Results

CNVs and differential expression of m⁶A regulators were observed in PTC patients. Especially IGF2BP2 (Insulin-like growth factor 2 mRNA binding protein 2), which was most significantly overexpressed in tumor tissue. We chose 4 genes in the m⁶A-related module from WGCNA: IGF2BP2, STT3A, MTHFD1 and GSTM4, and used them to construct a m⁶A-related signature. The prognostic value of this signature was validated, and risk scores provided by the signature was the independent prognostic factor for PTC. A nomogram was also provided for clinical usage.

Conclusions

We performed a comprehensive evaluation of the m⁶A RNA modification landscape of PTC and explored its underlying mechanisms. Our m⁶A-related signature was of great significance in predicting the DFS of patients with PTC. And IGF2BP2 was a gene worthy for further analysis as its strong correlation with DFS and clinical phenotypes of PTC.

SUBMITTER: Wang X

PROVIDER: S-EPMC7260751 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Identification and validation of m<sup>6</sup>A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.

Wang Xinyi X Fu Xiaorui X Zhang Junjia J Xiong Chengfeng C Zhang Shuyong S Lv Yunxia Y

Cancer cell international 20200529

<h4>Background</h4>Papillary thyroid cancer (PTC) is a type of malignant tumor with excellent prognosis, accounting for more than 80% of thyroid cancer. Recently, numerous studies illustrated the importance of <i>N</i> <sup>6</sup>-methyladenosine (m<sup>6</sup>A) RNA modification to tumorigenesis, but it has never been reported in PTC.<h4>Methods</h4>We downloaded data from The Cancer Genome Atlas (TCGA) and analyzed RNA expression, single nucleotide polymorphisms (SNPs) and copy number variati ...[more]

PMID: 32514248

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Project description: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.

Dataset Information

Identification and validation of m⁶A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.

Background

Methods

Results

Conclusions

Publications

Identification and validation of m<sup>6</sup>A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Identification and validation of m6A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.

Background

Methods

Results

Conclusions

Publications

Identification and validation of m<sup>6</sup>A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Identification and validation of m⁶A RNA methylation regulators with clinical prognostic value in Papillary thyroid cancer.