乳腺癌干细胞（BCSC）在高耐药率、复发率和转移率中发挥着重要作用。 BCSC的精确生物标志物可以有效帮助识别癌症、评估预后、诊断和监测治疗。本研究的目的是为预测 BCSC 的特定生物标志物提供完整的分析。我们在这项工作中汇总了概况数据集，以揭示 BCSC 的潜在关键基因和途径。我们从基因表达综合 (GEO) 数据库中通过阵列数据集（GSE7513 和 GSE7515）获得了两个表达谱，以识别 BCSC 中的生物标志物。 Enrichr用于进行功能分析，包括基因本体（GO）和反应组途径。此外，使用 Cytoscape 以及用于检索相互作用基因 (STRING) 的搜索工具，可以可视化这些差异表达基因 (DEG) 的蛋白质-蛋白质相互作用 (PPI)。选择PPI网络中的中心基因进行进一步研究。我们鉴定了65个上调和190个下调的DEG，GO富集分析显示这些DEG在与肿瘤发生和干性相关的生物过程中富集，包括改变细胞外基质的理化特性、细胞骨架重组、粘附、运动、迁移、生长和存活。 Reactome 分析表明，这些 DEG 还参与调节 ECM 功能，调节癌症代谢和血管生成、肿瘤生长、增殖和转移。我们的生物信息学研究表明，FYN、INADL、OCLN、F11R 和 TOP2A 是潜在的生物标志物组来自分泌组的 BCSC。

Breast cancer stem cells (BCSCs) play a role in the high rates of resistance, recurrence, and metastasis. The precise biomarkers of BCSCs can assist effectively in identifying cancer, assessing prognosis, diagnosing, and monitoring therapy. The aim of this study was to give a complete analysis for predicting specific biomarkers of BCSCs.We aggregated profile datasets in this work to shed light on the underlying critical genes and pathways of BCSCs. We obtained two expression profiling by array datasets (GSE7513 and GSE7515) from the Gene Expression Omnibus (GEO) database to identify biomarkers in BCSCs. Enrichr was used to do functional analysis, including gene ontology (GO) and reactome pathway. Furthermore, the protein-protein interaction (PPI) of these differential expression genes (DEGs) was visualized using Cytoscape with the search tool for the retrieval of interacting genes (STRING). The hub genes in the PPI network were chosen for further investigation.We identified 65 up-regulated and 190 down- regulated DEGs and the GO enrichment analysis revealed that these DEGs were enriched in biological process related to tumorigenesis and stemness, including alter the extracellular matrix's physicochemical properties, cytoskeletal reorganisation, adhesion, motility, migration, growth, and survival. The Reactome analysis indicated that these DEGs were also involved in modulating function of ECM, regulation cancer metabolism and angiogenesis, tumor growth, proliferation, and metastasis.Our bioinformatic study revealed that FYN, INADL, OCLN, F11R, and TOP2A were potential biomarker panel of BCSCs from secretome.