Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), Tianjin Key Laboratory of Cellular and Molecular Immunology, Department of Immunology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Faculty of Medicine, Macau University of Science and Technology, Macau, Macau SAR, China.
Front Endocrinol (Lausanne). 2023 Mar 1;14:1131525. doi: 10.3389/fendo.2023.1131525. eCollection 2023.
The aim of this study was to systematically establish a comprehensive tumour microenvironment (TME)-relevant prognostic gene and target miRNA network for breast cancer patients.
Based on a large-scale screening of TME-relevant prognostic genes (760 genes) for breast cancer patients, the prognostic model was established. The primary TME prognostic genes were selected from the constructing database and verified in the testing database. The internal relationships between the potential TME prognostic genes and the prognosis of breast cancer patients were explored in depth. The associated miRNAs for the TME prognostic genes were generated, and the functions of each primary TME member were investigated in the breast cancer cell line.
Compared with sibling controls, breast cancer patients showed 55 differentially expressed TME prognostic genes, of which 31 were considered as protective genes, while the remaining 24 genes were considered as risk genes. According to the lambda values of the LASSO Cox analysis, the 15 potential TME prognostic genes were as follows: ENPEP, CCDC102B, FEZ1, NOS2, SCG2, RPLP2, RELB, RGS3, EMP1, PDLIM4, EPHA3, PCDH9, VIM, GFI1, and IRF1. Among these, there was a remarkable linear internal relationship for CCDC102B but non-linear relationships for others with breast cancer patient prognosis. Using the siRNA technique, we silenced the expression of each TME prognostic gene. Seven of the 15 TME prognostic genes (NOS2, SCG2, RGS3, EMP1, PDLIM4, PCDH9, and GFI1) were involved in enhancing cell proliferation, destroying cell apoptosis, promoting cell invasion, or migration in breast cancer. Six of them (CCDC102B, RPLP2, RELB, EPHA3, VIM, and IRF1) were favourable for maintaining cell invasion or migration. Only two of them (ENPEP and FEZ1) were favourable for the processes of cell proliferation and apoptosis.
This integrated study hypothesised an innovative TME-associated genetic functional network for breast cancer patients. The external relationships between these TME prognostic genes and the disease were measured. Meanwhile, the internal molecular mechanisms were also investigated.
本研究旨在系统建立一个与乳腺癌患者肿瘤微环境（TME）相关的预后基因和靶 miRNA 网络。
基于对大量与乳腺癌患者 TME 相关的预后基因（760 个基因）的大规模筛选，构建了预后模型。从构建的数据库中选择主要的 TME 预后基因，并在测试数据库中进行验证。深入探讨潜在 TME 预后基因与乳腺癌患者预后之间的内在关系。生成与 TME 预后基因相关的关联 miRNA，并在乳腺癌细胞系中研究每个主要 TME 成员的功能。
与同胞对照组相比，乳腺癌患者表现出 55 个差异表达的 TME 预后基因，其中 31 个被认为是保护性基因，而其余 24 个被认为是风险基因。根据 LASSO Cox 分析的 lambda 值，选择了 15 个潜在的 TME 预后基因，分别是：ENPEP、CCDC102B、FEZ1、NOS2、SCG2、RPLP2、RELB、RGS3、EMP1、PDLIM4、EPHA3、PCDH9、VIM、GFI1 和 IRF1。其中，CCDC102B 具有明显的线性内在关系，而其他基因则与乳腺癌患者的预后呈非线性关系。使用 siRNA 技术，我们沉默了每个 TME 预后基因的表达。在 15 个 TME 预后基因中，有 7 个（NOS2、SCG2、RGS3、EMP1、PDLIM4、PCDH9 和 GFI1）参与增强细胞增殖、破坏细胞凋亡、促进细胞侵袭或迁移，而其中 6 个（CCDC102B、RPLP2、RELB、EPHA3、VIM 和 IRF1）有利于维持细胞侵袭或迁移，只有 2 个（ENPEP 和 FEZ1）有利于细胞增殖和凋亡过程。
本综合研究提出了一个创新性的与乳腺癌患者肿瘤微环境相关的遗传功能网络假说。测量了这些 TME 预后基因与疾病之间的外部关系，同时还研究了内在的分子机制。
