深入研究利用 scRNA-Seq 和 Bulk RNA-Seq 的不同乳腺癌亚型的异质性和预后模型。
Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq.
机构信息
Jiangsu Key Laboratory for Biodiversity and Biotechnology, College of Life Sciences, Nanjing Normal University, Wenyuan Road 1, Nanjing 210023, China.
出版信息
Int J Mol Sci. 2022 Sep 1;23(17):9936. doi: 10.3390/ijms23179936.
BACKGROUND
Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice.
METHODS
Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models.
RESULTS
Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor-ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: , , , and ; protective genes: , , , and ) for luminal BC, seven genes (risk genes: and protective genes: , , , and ) for HER2+ BC, and seven genes (risk genes: , and ; protective genes: , , and ) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis.
CONCLUSIONS
Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.
背景
乳腺癌（BC）是女性中最常见的恶性肿瘤，具有高度异质性。不同 BC 亚型的癌细胞异质性尚未得到彻底表征，临床上仍然没有有效的生物标志物来预测 BC 患者的预后。
方法
使用 inferCNV 算法计算单细胞拷贝数变异来鉴定癌细胞。利用 SCENIC 推断基因调控网络。使用 CellPhoneDB 软件分析不同细胞类型之间的细胞间通讯。生存分析、单因素 Cox、最小绝对收缩和选择算子（LASSO）回归和多因素 Cox 分析用于构建亚型特异性预后模型。
结果
三阴性乳腺癌（TNBC）的癌细胞比例高于 HER2+ BC 和 luminal BC 亚型，并且 TNBC 亚型特异性上调的基因与抗氧化和化学应激抗性有关。三种亚型肿瘤细胞的关键转录因子（TFs）不同，大多数 TF-靶基因在相应的 BC 亚型中特异性上调。不同受体-配体对介导的细胞间通讯导致三种 BC 亚型中炎症反应的程度不同。我们建立了一个包含 10 个基因（风险基因： 、 、 、 和 ；保护基因： 、 、 、 和 ）的 luminal BC 预后模型、7 个基因（风险基因： 和 ；保护基因： 、 、 、 和 ）的 HER2+ BC 预后模型和 7 个基因（风险基因： 、 和 ；保护基因： 、 、 、 和 ）的 TNBC 预后模型。这三个预后模型可以区分高风险患者和低风险患者，准确预测患者的预后。
结论
本研究基于癌症细胞异质性对三种 BC 亚型进行比较分析，对 BC 患者的诊断、预后和靶向治疗具有重要的临床意义。
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