College of Pharmacy, Zhejiang University of Technology, Hangzhou, Zhejiang, China.
Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, Zhejiang, China.
PLoS One. 2024 Feb 26;19(2):e0299138. doi: 10.1371/journal.pone.0299138. eCollection 2024.
Cuproptosis is a novel copper-dependent mode of cell death that has recently been discovered. The relationship between Cuproptosis-related ncRNAs and breast cancer subtypes, however, remains to be studied.
The aim of this study was to construct a breast cancer subtype prediction model associated with Cuproptosis. This model could be used to determine the subtype of breast cancer patients. To achieve this aim, 21 Cuproptosis-related genes were obtained from published articles and correlation analysis was performed with ncRNAs differentially expressed in breast cancer. Random forest algorithms were subsequently utilized to select important ncRNAs and build breast cancer subtype prediction models.
A total of 94 ncRNAs significantly associated with Cuproptosis were obtained and the top five essential features were chosen to build a predictive model. These five biomarkers were differentially expressed in the five breast cancer subtypes and were closely associated with immune infiltration, RNA modification, and angiogenesis.
The random forest model constructed based on Cuproptosis-related ncRNAs was able to accurately predict breast cancer subtypes, providing a new direction for the study of clinical therapeutic targets.
铜死亡是一种新发现的依赖铜的细胞死亡方式。然而，铜死亡相关 ncRNAs 与乳腺癌亚型之间的关系仍有待研究。
本研究旨在构建与铜死亡相关的乳腺癌亚型预测模型。该模型可用于确定乳腺癌患者的亚型。为了实现这一目标，从已发表的文章中获取了 21 个铜死亡相关基因，并对乳腺癌中差异表达的 ncRNAs 进行了相关性分析。随后，利用随机森林算法选择重要的 ncRNAs 并构建乳腺癌亚型预测模型。
共获得 94 个与铜死亡显著相关的 ncRNAs，选择前五个重要特征来构建预测模型。这五个生物标志物在五种乳腺癌亚型中表达差异，与免疫浸润、RNA 修饰和血管生成密切相关。
基于铜死亡相关 ncRNAs 构建的随机森林模型能够准确预测乳腺癌亚型，为临床治疗靶点的研究提供了新的方向。
