Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, Jiangsu, China.
Med Oncol. 2022 May 15;39(5):92. doi: 10.1007/s12032-022-01690-3.
HER2 positive BC is heterogeneous. But few studies discussed the classification of HER2-positive BC based on immune-related signatures. Using three publicly BC genomics datasets, we classified HER2 positive BC based on 33 immune-related signatures and used unsupervised machine learning methods to predict and perform the classification. We grouped three HER2-positive BC subtypes that we called Immune-High (IM-H), Immune-Medium (IM-M), and Immune-Low (IM-L), and manifested this categorization was predictable, duplicable and reliable by analyzing another dataset. Compared to other subtypes, IM-H had a higher immune cell infiltration level and stronger anti-tumor immune activities, as well as better clinical survival outcome. Besides these signatures, there were some cancer-related pathways which were hyperactivated in IM-H, including cytokine-cytokine receptor interactions, antigen processing and presentation pathways, natural killer cell-mediated cytotoxicity, Th1 and Th2 cell differentiation, chemokine signaling pathway, Th17 cell differentiation, B and T cell receptor signaling, NF-kappa B signaling, PD-L1 expression and PD-1 checkpoint pathway in cancer, TNF signaling, IL-17 signaling, NOD-like receptor signaling and Toll-like receptor signaling. By contrast, IM-L showed depressed immune-related signatures and enhanced activation of lycosylphosphatidylinositol-anchor biosynthesis and mismatch repair. Moreover, we discovered a gene co-expression network focused on eight transcription factor genes (EOMES, TBX21, GFI1, IRF4, POU2AF1, CIITA, FOXP3 and TOX) and one tumor suppress gene (PRF1), which were closely related with tumor immune. We identified three HER2-positive BC subtypes based on immune-related signatures, which had potential clinical implications and promoted the optimal stratification of HER2-positive BC responsive to immunotherapy.
HER2 阳性乳腺癌具有异质性。但是，很少有研究基于免疫相关特征讨论 HER2 阳性乳腺癌的分类。使用三个公开的乳腺癌基因组数据集，我们基于 33 个免疫相关特征对 HER2 阳性乳腺癌进行分类，并使用无监督机器学习方法进行预测和分类。我们将三种 HER2 阳性乳腺癌亚型分组，称为免疫高（IM-H）、免疫中（IM-M）和免疫低（IM-L），并通过分析另一个数据集证明这种分类是可预测的、可复制的和可靠的。与其他亚型相比，IM-H 具有更高的免疫细胞浸润水平和更强的抗肿瘤免疫活性，以及更好的临床生存结局。除了这些特征之外，还有一些癌症相关通路在 IM-H 中被过度激活，包括细胞因子-细胞因子受体相互作用、抗原加工和呈递途径、自然杀伤细胞介导的细胞毒性、Th1 和 Th2 细胞分化、趋化因子信号通路、Th17 细胞分化、B 和 T 细胞受体信号、NF-κB 信号、PD-L1 表达和 PD-1 检查点通路在癌症中、TNF 信号、IL-17 信号、NOD 样受体信号和 Toll 样受体信号。相比之下，IM-L 显示出免疫相关特征的抑制和糖基磷脂酰肌醇锚生物合成和错配修复的增强激活。此外，我们发现了一个以八个转录因子基因（EOMES、TBX21、GFI1、IRF4、POU2AF1、CIITA、FOXP3 和 TOX）和一个肿瘤抑制基因（PRF1）为中心的基因共表达网络，它们与肿瘤免疫密切相关。我们基于免疫相关特征鉴定了三种 HER2 阳性乳腺癌亚型，它们具有潜在的临床意义，并促进了针对免疫治疗的 HER2 阳性乳腺癌的最佳分层。
