{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zhong S"],"funding":["National Natural Science Foundation of China","Young Talents Program of Jiangsu Cancer Hospital","Huai‘an Natural Science Research Plan"],"pagination":["e11561"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8183431"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9"],"pubmed_abstract":["N6-methyladenosine (m<sup>6</sup>A) modification has been shown to participate in tumorigenesis and metastasis of human cancers. The present study aimed to investigate the roles of m<sup>6</sup>A RNA methylation regulators in breast cancer. We used LASSO regression to identify m<sup>6</sup>A-related gene signature predicting breast cancer survival with the datasets downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA). RNA-Seq data of 3409 breast cancer patients from GSE96058 and 1097 from TCGA were used in present study. A 10 m<sup>6</sup>A-related gene signature associated with prognosis was identified from 22 m<sup>6</sup>A RNA methylation regulators. The signature divided patients into low- and high-risk group. High-risk patients had a worse prognosis than the low-"],"journal":["PeerJ"],"pubmed_title":["The m<sup>6</sup>A-related gene signature for predicting the prognosis of breast cancer."],"pmcid":["PMC8183431"],"funding_grant_id":["81602551","HAB201816","QL201810"],"pubmed_authors":["Feng J","Zhong S","Zhou S","Lin Z","Chen H","Mao L"],"additional_accession":[]},"is_claimable":false,"name":"The m<sup>6</sup>A-related gene signature for predicting the prognosis of breast cancer.","description":"N6-methyladenosine (m<sup>6</sup>A) modification has been shown to participate in tumorigenesis and metastasis of human cancers. The present study aimed to investigate the roles of m<sup>6</sup>A RNA methylation regulators in breast cancer. We used LASSO regression to identify m<sup>6</sup>A-related gene signature predicting breast cancer survival with the datasets downloaded from Gene Expression Omnibus and The Cancer Genome Atlas (TCGA). RNA-Seq data of 3409 breast cancer patients from GSE96058 and 1097 from TCGA were used in present study. A 10 m<sup>6</sup>A-related gene signature associated with prognosis was identified from 22 m<sup>6</sup>A RNA methylation regulators. The signature divided patients into low- and high-risk group. High-risk patients had a worse prognosis than the low-","dates":{"release":"2021-01-01T00:00:00Z","publication":"2021","modification":"2026-05-08T00:19:46.559Z","creation":"2022-02-10T15:42:36.329Z"},"accession":"S-EPMC8183431","cross_references":{"pubmed":["34141492"],"doi":["10.7717/peerj.11561"]}}