Department of Anesthesiology, The First Affiliated Hospital, Fujian Medical University, Fuzhou 350005, China.
Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou 350212, China.
Aging (Albany NY). 2023 Aug 18;15(16):8185-8203. doi: 10.18632/aging.204963.
Breast cancer (BC) is a heterogeneous disease characterized by significant differences in prognosis and therapy response. Numerous prognostic tools have been developed for breast cancer. Usually these tools are based on bulk RNA-sequencing (RNA-Seq) and ignore tumor heterogeneity. Consequently, the goal of this study was to construct a single-cell level tool for predicting the prognosis of BC patients. In this study, we constructed a stemness-risk gene score (SGS) model based on single-sample gene set enrichment analysis (ssGSEA). Patients were divided into two groups based on the median SGS. Patients with a high SGS scores had a significantly worse prognosis than those with a low SGS, and these groups exhibited differences in several tumor characteristics, such as immune infiltration, gene mutations, and copy number variants. Our results indicate that the SGS is a reliable tool for predicting prognosis and response to immunotherapy in BC patients.
乳腺癌(BC)是一种异质性疾病,其预后和治疗反应存在显著差异。已经开发了许多用于乳腺癌的预后工具。通常这些工具基于批量 RNA 测序(RNA-Seq),并忽略了肿瘤异质性。因此,本研究的目的是构建一种用于预测 BC 患者预后的单细胞水平工具。在这项研究中,我们基于单样本基因集富集分析(ssGSEA)构建了一个干性风险基因评分(SGS)模型。根据 SGS 的中位数将患者分为两组。SGS 较高的患者预后明显差于 SGS 较低的患者,这些组在免疫浸润、基因突变和拷贝数变异等几个肿瘤特征方面存在差异。我们的结果表明,SGS 是预测 BC 患者预后和免疫治疗反应的可靠工具。