Dataset Information

Identification and functional analysis of N6-methyladenine (m⁶ A)-related lncRNA across 33 cancer types.

ABSTRACT:

Background

N6-methyladenosine (m⁶ A) plays an essential role in tumorigenesis and cancer progression. Long noncoding RNAs (lncRNAs) are discovered to be important targets of m⁶ A modification, and they play fundamental roles in diverse biological processes. However, there is still a lack of knowledge with regards to the association between m⁶ A and lncRNAs in human tumors.

Methods

The relationship between lncRNAs and 21 m⁶ A regulators was comprehensively explored, through the integration of multi-omics data from M6A2Target, m6A-Atlas, and TCGA (The Cancer Genome Atlas). In order to explore the potential roles of m6A-related lncRNAs in human tumors, three applicable methods were introduced, which include the construction of ceRNA networks, drug sensitivity estimation, and survival analysis.

Results

A substantial number of positive correlation events across 33 cancer types were found. Moreover, cancer-specific lncRNAs were associated with tissue specificity, and cancer-common lncRNAs were conserved in cancer-related biological function. In particular, the m⁶ A-related lncRNA FGD5-AS1 was found to be associated with cancer treatment, through its influence on cisplatin resistance in breast cancer patients. Finally, a user-friendly interface Lnc2m6A, which is enriched with various browsing sections resource for the exhibition of relationships and putative biogenesis between lncRNAs and m⁶ A modifications, is offered in http://hainmu-biobigdata.com/Lnc2m6A.

Conclusions

In summary, the results from this paper will provide a valuable resource that guides both mechanistic and therapeutic roles of m⁶ A-related lncRNAs in human tumors.

SUBMITTER: Xu D

PROVIDER: S-EPMC9883401 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification and functional analysis of N6-methyladenine (m<sup>6</sup> A)-related lncRNA across 33 cancer types.

Xu Dahua D Xu Zhizhou Z Bi Xiaoman X Cai Jiale J Cao Meng M Zheng Dehua D Chen Liyang L Li Peihu P Wang Hong H Wu Deng D Yang Jun J Li Kongning K

Cancer medicine 20220704 2

<h4>Background</h4>N6-methyladenosine (m<sup>6</sup> A) plays an essential role in tumorigenesis and cancer progression. Long noncoding RNAs (lncRNAs) are discovered to be important targets of m<sup>6</sup> A modification, and they play fundamental roles in diverse biological processes. However, there is still a lack of knowledge with regards to the association between m<sup>6</sup> A and lncRNAs in human tumors.<h4>Methods</h4>The relationship between lncRNAs and 21 m<sup>6</sup> A regulators w ...[more]

PMID: 35789547

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Project description:Despite recent advances in surgical and multimodal therapies, the overall survival (OS) of advanced colorectal cancer (CRC) patients remains low. Thus, discerning sensitive prognostic biomarkers to give the optimistic treatment for CRC patients is extremely critical. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play an important role in CRC progression. Nonetheless, few studies have focused on the impact of m6A-related lncRNAs on the prognosis, tumor microenvironment (TME) and treatment of CRC. In this study, 1707 m6A-related lncRNAs were identified through Pearson correlation analysis and Weighted co-expression network analysis (WGCNA) using The Cancer Genome Atlas (TCGA) cohort. Then, 28 m6A-related prognostic lncRNAs were screened by univariate Cox regression analysis, followed by identifying two clusters by consensus clustering analysis. A prognostic model consisted of 8 lncRNA signatures was constructed by the least absolute shrinkage and selection operator (LASSO). Kaplan-Meier curve analysis and a nomogram were performed to investigate the prognostic ability of this model. The risk score of prognostic model act as an independent risk factor for OS rate. Functional enrichment analysis indicated that lncRNA signatures related tumor immunity. The low-risk group characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of OS. Moreover, the lncRNA signatures were significantly associated with the cancer stem cell (CSC) index and drug sensitivity. In addition, 3 common immune genes shared by the lncRNA signatures were screened out. We found that these immune genes were widely distributed in 2 cell types of TME. Finally, a ceRNA network was constructed to identify ZEB1-AS1 regulatory axis in CRC. We found that ZEB1-AS1 was significantly overexpressed in tumor tissues, and was related to the metastasis of EMT and the chemoresistance of 5-Fu in CRC. Therefore, our study demonstrated the important role of m6A-related lncRNAs in TME remodeling. Moreover, these results illustrated the levels of ZEB1-AS1 might be valuable for predicting the progression and prognosis of CRC, and further provided a new target for the diagnosis and treatment of CRC patients.

Project description:The N6-methyladenosine (m6A) RNA modification can modify long non-coding RNAs (lncRNAs), thereby affecting the tumorigenesis and progression of tumors. However, the underlying role of m6A-modified lncRNAs in colorectal cancer (CRC) remains largely unknown. Therefore, our aim was to assess the prognostic value of m6A-modified lncRNAs in CRC patients. The gene expression and clinicopathological data of CRC were extracted from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to investigate the m6A-modified lncRNAs. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance of molecular subtypes was identified. The least absolute shrinkage and selection operator analysis (LASSO) was applied to establish a risk signature. Finally, a prognostic nomogram with risk score and clinicopathological variables was established. In total, 29 m6A-modified lncRNAs were identified as prognostic lncRNAs. Two molecular clusters were identified and significant differences were found with respect to clinicopathological features and prognosis. Cluster1 is associated with poor overall survival (OS), down-regulation of Programmed cell death ligand-1 (PD-L1) expression, lower immune score, and less immune cell infiltration. Then, an m6A-modified lncRNA signature for predicting OS was constructed in the TCGA training cohort. The signature demonstrated favorable prediction performance in both training and validation sets. Compared with low-risk patients, patients with high risk showed worse clinical outcomes, lower immune scores, and downregulated PD-L1 expression. Further analysis indicated that the signature was an independent prognostic indicator, and then a prognostic nomogram based on risk score, tumor location, and tumor stage was established. Our study identified a seven m6A-modified lncRNA signature and established a prognostic nomogram that reliably predicts OS in CRC. These findings may improve the understanding of m6A modifications in CRC and provide insights into the prognosis and treatment strategy of CRC.

Dataset Information

Identification and functional analysis of N6-methyladenine (m⁶ A)-related lncRNA across 33 cancer types.

Background

Methods

Results

Conclusions

Publications

Identification and functional analysis of N6-methyladenine (m<sup>6</sup> A)-related lncRNA across 33 cancer types.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Identification and functional analysis of N6-methyladenine (m6 A)-related lncRNA across 33 cancer types.

Background

Methods

Results

Conclusions

Publications

Identification and functional analysis of N6-methyladenine (m<sup>6</sup> A)-related lncRNA across 33 cancer types.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Identification and functional analysis of N6-methyladenine (m⁶ A)-related lncRNA across 33 cancer types.