鉴定关键调控因子是发现参与BC的生物标志物的关键步骤。利用乳腺癌患者的基因表达数据集构建网络，鉴定乳腺癌关键调控因子。利用BioXpress鉴定过表达基因，然后使用筛选的基因构建BC相互作用网络。通过从BC网络中选取度数最高的基因并进行追溯，确定其中三个为新的关键调控因子，因为它们参与了网络的所有层级，充当了骨干。文献中有些证据表明这些基因与BC有关。为了治疗BC，能够同时作用于多个靶点的药物非常有前景。与单一靶点药物相比，多靶点药物具有更高的疗效、改善的安全性和更容易使用的特点。对FN1基因的单倍型和LD研究表明，鉴定出的变异rs6707530和rs1250248可能分别导致TB和子宫内膜异位。不同人种间SNP和单倍型频率的差异可能解释了关联研究的不可预测性，并可用于预测使用FN1的药物的药代动力学和药效学。 © 2023. Springer Nature Limited.

Identification of key regulators is a critical step toward discovering biomarker that participate in BC. A gene expression dataset of breast cancer patients was used to construct a network identifying key regulators in breast cancer. Overexpressed genes were identified with BioXpress, and then curated genes were used to construct the BC interactome network. As a result of selecting the genes with the highest degree from the BC network and tracing them, three of them were identified as novel key regulators, since they were involved at all network levels, thus serving as the backbone. There is some evidence in the literature that these genes are associated with BC. In order to treat BC, drugs that can simultaneously interact with multiple targets are promising. When compared with single-target drugs, multi-target drugs have higher efficacy, improved safety profile, and are easier to administer. The haplotype and LD studies of the FN1 gene revealed that the identified variations rs6707530 and rs1250248 may both cause TB, and endometriosis respectively. Interethnic differences in SNP and haplotype frequencies might explain the unpredictability in association studies and may contribute to predicting the pharmacokinetics and pharmacodynamics of drugs using FN1.© 2023. Springer Nature Limited.