Breast cancer (BC) is the second most frequently diagnosed cancer and accounts for approximately 25% of new cancer cases in Canadian women. Using biomarkers as a less-invasive BC diagnostic method is currently under investigation but is not ready for practical application in clinical settings. During the last decade, extracellular vesicles (EVs) have emerged as a promising source of biomarkers because they contain cancer-derived proteins, RNAs, and metabolites. In this study, EV proteins from small EVs (sEVs) and medium EVs (mEVs) were isolated from BC MDA-MB-231 and MCF7 and non-cancerous breast epithelial MCF10A cell lines and then analyzed by two approaches: global proteomic analysis and enrichment of EV surface proteins by Sulfo-NHS-SS-Biotin labeling. From the first approach, proteomic profiling identified 2459 proteins, which were subjected to comparative analysis and correlation network analysis. Twelve potential biomarker proteins were identified based on cell line-specific expression and filtered by their predicted co-localization with known EV marker proteins, CD63, CD9, and CD81. This approach resulted in the identification of 11 proteins, four of which were further investigated by Western blot analysis. The presence of transmembrane serine protease matriptase (ST14), claudin-3 (CLDN3), and integrin alpha-7 (ITGA7) in each cell line was validated by Western blot, revealing that ST14 and CLDN3 may be further explored as potential EV biomarkers for BC. The surface labeling approach enriched proteins that were not identified using the first approach. Ten potential BC biomarkers (Glutathione S-transferase P1 (GSTP1), Elongation factor 2 (EEF2), DEAD/H box RNA helicase (DDX10), progesterone receptor (PGR), Ras-related C3 botulinum toxin substrate 2 (RAC2), Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), Aconitase 2 (ACO2), UTP20 small subunit processome component (UTP20), NEDD4 binding protein 2 (N4BP2), Programmed cell death 6 (PDCD6)) were selected from surface proteins commonly identified from MDA-MB-231 and MCF7, but not identified in MCF10A EVs. In total, 846 surface proteins were identified from the second approach, of which 11 were already known as BC markers. This study supports the proposition that Evs are a rich source of known and novel biomarkers that may be used for non-invasive detection of BC. Furthermore, the presented datasets could be further explored for the identification of potential biomarkers in BC.
乳腺癌是加拿大女性中第二常见的恶性肿瘤，约占新发癌症病例的25%。目前正在研究将生物标志物作为创伤性更小的乳腺癌诊断方法，但尚未达到临床应用阶段。过去十年间，细胞外囊泡因其含有肿瘤源性蛋白质、RNA和代谢物，已成为极具潜力的生物标志物来源。本研究从乳腺癌MDA-MB-231、MCF7细胞系及非癌性乳腺上皮MCF10A细胞系中分离出小细胞外囊泡和中型细胞外囊泡的蛋白质，并通过两种方法进行分析：全局蛋白质组学分析以及采用磺基-NHS-SS-生物素标记技术富集囊泡表面蛋白。 通过第一种方法，蛋白质组学分析鉴定出2459种蛋白质，并进行了比较分析和相关性网络分析。基于细胞系特异性表达筛选出12种潜在生物标志物蛋白，并通过预测其与已知囊泡标志蛋白（CD63、CD9、CD81）的共定位进行过滤，最终确定11种蛋白质。其中4种蛋白质通过蛋白质印迹法进一步验证，跨膜丝氨酸蛋白酶matriptase（ST14）、claudin-3（CLDN3）和整合素α-7（ITGA7）在各细胞系中的存在得到确认，表明ST14和CLDN3可作为乳腺癌潜在囊泡生物标志物进行深入研究。 表面标记方法富集了第一种方法未检测到的蛋白质。从MDA-MB-231和MCF7共有而MCF10A囊泡中未发现的表面蛋白中，筛选出10种潜在乳腺癌生物标志物：谷胱甘肽S-转移酶P1（GSTP1）、延伸因子2（EEF2）、DEAD/H盒RNA解旋酶（DDX10）、孕激素受体（PGR）、Ras相关C3肉毒毒素底物2（RAC2）、含去整合素和金属蛋白酶结构域蛋白10（ADAM10）、乌头酸酶2（ACO2）、UTP20小亚基加工体组分（UTP20）、NEDD4结合蛋白2（N4BP2）、程序性细胞死亡蛋白6（PDCD6）。第二种方法共鉴定846种表面蛋白，其中11种为已知乳腺癌标志物。 本研究证实细胞外囊泡是已知及新型生物标志物的丰富来源，可用于乳腺癌无创检测。此外，本研究建立的数据集可为进一步探索乳腺癌潜在生物标志物提供重要资源。
Surface Proteome of Extracellular Vesicles and Correlation Analysis Reveal Breast Cancer Biomarkers
肿瘤(癌症)患者之家