Wang Zhen-Zhen, Li Xu-Hua, Wen Xiao-Ling, Wang Na, Guo Yu, Zhu Xu, Fu Shu-Heng, Xiong Fei-Fan, Bai Jing, Gao Xiao-Ling, Wang Hong-Jiu
Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China.
The Medical Laboratory Center, Hainan General Hospital, Haikou, China.
Front Oncol. 2023 Mar 21;13:1130092. doi: 10.3389/fonc.2023.1130092. eCollection 2023.
Tumor heterogeneity in breast cancer hinders proper diagnosis and treatment, and the identification of molecular subtypes may help enhance the understanding of its heterogeneity. Therefore, we proposed a novel integrated multi-omics approach for breast cancer typing, which led to the identification of a hybrid subtype (Mix_Sub subtype) with a poor survival prognosis. This subtype is characterized by lower levels of the inflammatory response, lower tumor malignancy, lower immune cell infiltration, and higher T-cell dysfunction. Moreover, we found that cell-cell communication mediated by NCAM1-FGFR1 ligand-receptor interaction and cellular functional states, such as cell cycle, DNA damage, and DNA repair, were significantly altered and upregulated in patients with this subtype, and that such patients displayed greater sensitivity to targeted therapies. Subsequently, using differential genes among subtypes as biomarkers, we constructed prognostic risk models and subtype classifiers for the Mix_Sub subtype and validated their generalization ability in external datasets obtained from the GEO database, indicating their potential therapeutic and prognostic significance. These biomarkers also showed significant spatially variable expression in malignant tumor cells. Collectively, the identification of the Mix_Sub breast cancer subtype and its biomarkers, based on the driving relationship between omics, has deepened our understanding of breast cancer heterogeneity and facilitated the development of breast cancer precision therapy.
乳腺癌中的肿瘤异质性阻碍了正确的诊断和治疗，而分子亚型的鉴定可能有助于加深对其异质性的理解。因此，我们提出了一种用于乳腺癌分型的新型综合多组学方法，该方法鉴定出了一种生存预后较差的混合亚型（Mix_Sub亚型）。该亚型的特征是炎症反应水平较低、肿瘤恶性程度较低、免疫细胞浸润较少以及T细胞功能障碍较高。此外，我们发现由NCAM1-FGFR1配体-受体相互作用介导的细胞间通讯以及细胞功能状态，如细胞周期、DNA损伤和DNA修复，在该亚型患者中发生了显著改变且上调，并且这类患者对靶向治疗表现出更高的敏感性。随后，我们将亚型间的差异基因用作生物标志物，构建了Mix_Sub亚型的预后风险模型和亚型分类器，并在从GEO数据库获得的外部数据集中验证了它们的泛化能力，表明了它们潜在的治疗和预后意义。这些生物标志物在恶性肿瘤细胞中也表现出显著的空间可变表达。总体而言，基于组学间的驱动关系鉴定出Mix_Sub乳腺癌亚型及其生物标志物，加深了我们对乳腺癌异质性的理解，并促进了乳腺癌精准治疗的发展。
