Jiang Fa, Yang Lifeng, Jiao Xiong
College of Biomedical Engineering, Taiyuan University of Technology, Jinzhong, 030600, China.
College of Information and Computer, Taiyuan University of Technology, Jinzhong, 030600, China.
Breast Cancer. 2023 May;30(3):453-465. doi: 10.1007/s12282-023-01438-5. Epub 2023 Feb 18.
The discovery of early warning signs and biomarkers in patients with early breast cancer is crucial for the prevention and treatment of breast cancer. Dynamic Network Biomarker (DNB) is an approach based on nonlinear dynamics theory, which we exploited to identify a set of DNB members and their key genes as early warning signals during breast cancer staging progression.
First, based on the gene expression profile of breast cancer in the TCGA database, the DNB algorithm was used to calculate the composite index (CI) of each gene cluster in the process of breast cancer anatomical staging. Then we calculated gene modules associated with the clinical phenotype stage based on weighted gene co-expression network analysis (WGCNA), combined with DNB membership to identify key genes in the network.
We identified a set of gene clusters with the highest CI in Stage II as DNBs, whose roles in related pathways indicate the emergence of a tipping point and impact on breast cancer development. In addition, analysis of the key gene GPRIN1 showed that high expression of GPRIN1 predicts poor prognosis, and related immune analysis showed that GPRIN1 is involved in the development of breast cancer through immune aspects.
The discovery of DNBs and the key gene GPRIN1 can provide potential biomarkers and therapeutic targets for breast cancer.
发现早期乳腺癌患者的预警信号和生物标志物对于乳腺癌的预防和治疗至关重要。动态网络生物标志物（DNB）是一种基于非线性动力学理论的方法，我们利用该方法在乳腺癌分期进展过程中识别出一组DNB成员及其关键基因作为预警信号。
首先，基于TCGA数据库中乳腺癌的基因表达谱，在乳腺癌解剖分期过程中使用DNB算法计算每个基因簇的综合指数（CI）。然后，我们基于加权基因共表达网络分析（WGCNA）计算与临床表型阶段相关的基因模块，并结合DNB成员身份识别网络中的关键基因。
我们将II期具有最高CI的一组基因簇鉴定为DNB，它们在相关途径中的作用表明了临界点出现并对乳腺癌发展产生影响。此外，对关键基因GPRIN1的分析表明，GPRIN1高表达预示着预后不良，相关免疫分析表明GPRIN1通过免疫方面参与乳腺癌的发展。
DNB和关键基因GPRIN1的发现可为乳腺癌提供潜在的生物标志物和治疗靶点。
