{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Su F"],"funding":["Traditional Chinese Medicine (Tibetan Medicine) at the University of Tibetan Medicine","China Postdoctoral Science Foundation","National Nature Science Foundation of China","Postdoctoral Foundation of Hei Long Jiang Province","Natural Science Foundation of Heilongjiang Province"],"pagination":["1931"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9690091"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13(11)"],"pubmed_abstract":["We aimed to identify miRNAs that were closely related to breast cancer (BRCA). By integrating several methods including significance analysis of microarrays, fold change, Pearson's correlation analysis, <i>t</i> test, and receiver operating characteristic analysis, we developed a decision-tree-based scoring algorithm, called Optimized Scoring Mechanism for Primary Synergy MicroRNAs (O-PSM). Five synergy miRNAs (hsa-miR-139-5p, hsa-miR-331-3p, hsa-miR-342-5p, hsa-miR-486-5p, and hsa-miR-654-3p) were identified using O-PSM, which were used to distinguish normal samples from pathological ones, and showed good results in blood data and in multiple sets of tissue data. These five miRNAs showed accurate categorization efficiency in BRCA typing and staging and had better categorization efficiency"],"journal":["Genes"],"pubmed_title":["Integrated Tissue and Blood miRNA Expression Profiles Identify Novel Biomarkers for Accurate Non-Invasive Diagnosis of Breast Cancer: Preliminary Results and Future Clinical Implications."],"pmcid":["PMC9690091"],"funding_grant_id":["LBH-Z18129","61801151","2019M651298","BSDJS-20-07","H2018014","LH2021F053","LBH-Z18187"],"pubmed_authors":["Liu Y","Deng C","Guan L","Cui Y","Zhang Y","Ma X","Gao Z","Zhou G","Liu B","Wang Y","Su F"],"additional_accession":[]},"is_claimable":false,"name":"Integrated Tissue and Blood miRNA Expression Profiles Identify Novel Biomarkers for Accurate Non-Invasive Diagnosis of Breast Cancer: Preliminary Results and Future Clinical Implications.","description":"We aimed to identify miRNAs that were closely related to breast cancer (BRCA). By integrating several methods including significance analysis of microarrays, fold change, Pearson's correlation analysis, <i>t</i> test, and receiver operating characteristic analysis, we developed a decision-tree-based scoring algorithm, called Optimized Scoring Mechanism for Primary Synergy MicroRNAs (O-PSM). Five synergy miRNAs (hsa-miR-139-5p, hsa-miR-331-3p, hsa-miR-342-5p, hsa-miR-486-5p, and hsa-miR-654-3p) were identified using O-PSM, which were used to distinguish normal samples from pathological ones, and showed good results in blood data and in multiple sets of tissue data. These five miRNAs showed accurate categorization efficiency in BRCA typing and staging and had better categorization efficiency","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Oct","modification":"2026-04-08T11:11:19.741Z","creation":"2024-12-04T01:22:36.115Z"},"accession":"S-EPMC9690091","cross_references":{"pubmed":["36360168"],"doi":["10.3390/genes13111931"]}}