School of Interdisciplinary Science and Technology, Jamia Hamdard, New Delhi, India.
ICAR-Indian Institute of Farming System Research, Modipuram, Meerut, 250110, India.
Sci Rep. 2023 Aug 22;13(1):13729. doi: 10.1038/s41598-023-40684-7.
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.
鉴定关键调控因子是发现参与乳腺癌的生物标志物的关键步骤。使用乳腺癌患者的基因表达数据集构建了一个网络，以识别乳腺癌中的关键调控因子。使用 BioXpress 鉴定过表达基因，然后使用已整理的基因构建乳腺癌互作网络。通过从 BC 网络中选择具有最高度数的基因并对其进行追踪，鉴定出其中三个为新的关键调控因子，因为它们参与了所有网络层次，因此作为骨干。文献中有一些证据表明这些基因与乳腺癌有关。为了治疗乳腺癌，同时与多个靶点相互作用的药物具有广阔的前景。与单靶点药物相比，多靶点药物具有更高的疗效、改善的安全性和更易给药的特点。FN1 基因的单体型和 LD 研究表明，鉴定出的变异 rs6707530 和 rs1250248 可能分别导致结核病和子宫内膜异位症。SNP 和单体型频率的种间差异可能解释了关联研究中的不可预测性，并有助于使用 FN1 预测药物的药代动力学和药效学。
