Department of Clinical Molecular Biology (EpiGen), Akershus University Hospital, Lørenskog, Norway.
Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Norway.
Mol Oncol. 2024 Oct;18(10):2495-2509. doi: 10.1002/1878-0261.13655. Epub 2024 May 16.
Benign breast tumors are a nonthreatening condition defined as abnormal cell growth within the breast without the ability to invade nearby tissue. However, benign lesions hold valuable biological information that can lead us toward better understanding of tumor biology. In this study, we have used two pathway analysis algorithms, Pathifier and gene set variation analysis (GSVA), to identify biological differences between normal breast tissue, benign tumors and malignant tumors in our clinical dataset. Our results revealed that one-third of all pathways that were significantly different between benign and malignant tumors were immune-related pathways, and 227 of them were validated by both methods and in the METABRIC dataset. Furthermore, five of these pathways (all including genes involved in cytokine and interferon signaling) were related to overall survival in cancer patients in both datasets. The cellular moieties that contribute to immune differences in malignant and benign tumors were analyzed using the deconvolution tool, CIBERSORT. The results showed that levels of some immune cells were specifically higher in benign than in malignant tumors, and this was especially the case for resting dendritic cells and follicular T-helper cells. Understanding the distinct immune profiles of benign and malignant breast tumors may aid in developing noninvasive diagnostic methods to differentiate between them in the future.
良性乳腺肿瘤是一种非威胁性疾病,定义为乳腺内异常细胞生长,而无侵犯附近组织的能力。然而,良性病变具有有价值的生物学信息,可以帮助我们更好地了解肿瘤生物学。在这项研究中,我们使用了两种途径分析算法,Pathifier 和基因集变异分析(GSVA),来识别我们临床数据集正常乳腺组织、良性肿瘤和恶性肿瘤之间的生物学差异。我们的结果表明,在良性和恶性肿瘤之间有三分之一显著不同的途径是与免疫相关的途径,其中 227 个途径通过两种方法和 METABRIC 数据集得到了验证。此外,这五个途径中的五个(均包括细胞因子和干扰素信号转导相关的基因)与两个数据集的癌症患者的总生存率相关。使用去卷积工具 CIBERSORT 分析了导致恶性和良性肿瘤免疫差异的细胞成分。结果表明,一些免疫细胞的水平在良性肿瘤中明显高于恶性肿瘤,尤其是静止树突状细胞和滤泡辅助性 T 细胞。了解良性和恶性乳腺肿瘤的不同免疫特征可能有助于未来开发非侵入性的诊断方法来区分它们。