• Fan Zhang, Yawei Zhang, Tingting Hou, Fangtao Ren, Xi Liu, Runan Zhao, and Xinhong Zhang.
• Henan Key Laboratory of Big Data Analysis and Processing, Henan University, Kaifeng 475004, China; School of Computer and Information Engineering, Henan University, Kaifeng 475004, China.
• Am. J. Med. Sci. 2022 Sep 1; 364 (3): 333342333-342.

BackgroundEarly screening is the most effective way to control breast cancer. Due to the lack of accurate biomarkers, early diagnosis of breast cancer is still very difficult. Therefore, it is necessary to discover new candidate genes of breast cancer and improve the early diagnosis and prognosis.MethodsA DO-UniBIC gene screening method was proposed. First, Disease Ontology (DO) analysis was used to screen out breast cancer related genes from differentially expressed genes, and then the UniBIC algorithm was used to find all gene clusters with the same changing trend based on the longest common subsequence. In addition, an eight-gene prognostic model was constructed to assess the prognostic risk of breast cancer patients.ResultsThe prognostic analysis of the candidate genomes based on multivariate Cox proportional regression model revealed eight genes that were significantly related to prognosis. The eight genes were ACSL1, CD24, EMP1, JPH3, CAMK4, JUN, S100B and TP53AIP1. Among them, ACSL1 was a new potential breast cancer related gene screened by the DO-UniBIC method.ConclusionsMore comprehensive cancer-related genes can be screened based on the DO-UniBIC method, which can be used as the candidate gene set for prognostic analysis.Copyright © 2022 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

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