College of Information Science and Engineering Xinjiang University, Urumqi 830046, China.
College of Software, Xinjiang University, Urumqi 830046, China.
Stud Health Technol Inform. 2023 Nov 23;308:303-312. doi: 10.3233/SHTI230854.
Triple negative breast cancer (TNBC) that has low survival rate and prognosis due to its heterogeneity and lack of reliable molecular targets for effective targeted therapy. Therefore, finding new biomarkers is crucial for the targeted treatment of TNBC. The experimental data from the Cancer Genome Atlas database (TCGA).First, key genes associated with TNBC prognosis were screened and used for survival analysis using a single-factor COX regression analysis combined with three algorithms: LASSO, RF and SVM-RFE. Multi-factor COX regression analysis was then used to construct a TNBC risk prognostic model. Four key genes associated with TNBC prognosis were screened as TENM2, OTOG, LEPR and HLF. Among them, OTOG is a new biomarker. Survival analysis showed a significant effect of four key genes on OS in TNBC patients (P<0.05). The experiment showed that four key genes could provide new ideas for targeting therapy for TNBC patients and improved prognosis and survival.
三阴性乳腺癌（TNBC）由于其异质性和缺乏可靠的分子靶点，导致生存率和预后较差，因此寻找新的生物标志物对于 TNBC 的靶向治疗至关重要。本研究基于癌症基因组图谱数据库（TCGA）的实验数据。首先，筛选与 TNBC 预后相关的关键基因，并使用单因素 COX 回归分析结合 LASSO、RF 和 SVM-RFE 三种算法进行生存分析。然后进行多因素 COX 回归分析构建 TNBC 风险预后模型。筛选出与 TNBC 预后相关的 4 个关键基因，分别为 TENM2、OTOG、LEPR 和 HLF。其中，OTOG 是一个新的生物标志物。生存分析显示，这 4 个关键基因对 TNBC 患者的 OS 有显著影响（P<0.05）。实验表明，这 4 个关键基因可为 TNBC 患者的靶向治疗提供新的思路，改善预后和生存。
