{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Pei J"],"funding":["Chen Xiao-ping Foundation for the Development of Science and Techonology of Hubei Province","Wu Jieping medical foundation"],"pagination":["30067"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11615351"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(1)"],"pubmed_abstract":["Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, which can seriously harm the health of cancer patients. However, there is currently a lack of effective and reliable biomarkers for the early diagnosis of TIC in clinical practice. Therefore, we screened the TIC candidate diagnostic gene solute carrier family 6 member 6 (SLC6A6) by combining multi-machine learning algorithm based on bioinformatics. In addition, cross-validation showed that SLC6A6 had a consistent expression trend in multi-data-sets. To further explore the diagnostic capability of SLC6A6 in TIC, we constructed a nomogram diagnostic model based on SLC6A6 expression level, and receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis proved that S"],"journal":["Scientific reports"],"pubmed_title":["Exploring an novel diagnostic gene of trastuzumab-induced cardiotoxicity based on bioinformatics and machine learning."],"pmcid":["PMC11615351"],"funding_grant_id":["No. 320.6750.2023-18-21","No. CXPJJH122011-011"],"pubmed_authors":["Wu Z","Liu Y","Feng L","Wang Q","Pei J","Mu Q","Wang Z"],"additional_accession":[]},"is_claimable":false,"name":"Exploring an novel diagnostic gene of trastuzumab-induced cardiotoxicity based on bioinformatics and machine learning.","description":"Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, which can seriously harm the health of cancer patients. However, there is currently a lack of effective and reliable biomarkers for the early diagnosis of TIC in clinical practice. Therefore, we screened the TIC candidate diagnostic gene solute carrier family 6 member 6 (SLC6A6) by combining multi-machine learning algorithm based on bioinformatics. In addition, cross-validation showed that SLC6A6 had a consistent expression trend in multi-data-sets. To further explore the diagnostic capability of SLC6A6 in TIC, we constructed a nomogram diagnostic model based on SLC6A6 expression level, and receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis proved that S","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Dec","modification":"2026-06-01T20:40:21.69Z","creation":"2025-04-06T17:29:05.083Z"},"accession":"S-EPMC11615351","cross_references":{"pubmed":["39627317"],"doi":["10.1038/s41598-024-81335-9"]}}