Zawadzka Anna M, Schilling Birgit, Cusack Michael P, Sahu Alexandria K, Drake Penelope, Fisher Susan J, Benz Christopher C, Gibson Bradford W
Buck Institute for Research on Aging, 8001 Redwood Blvd., Novato, California 94945;
Mol Cell Proteomics. 2014 Apr;13(4):1034-49. doi: 10.1074/mcp.M113.035485. Epub 2014 Feb 6.
Breast cancer is a heterogeneous disease whose molecular diversity is not well reflected in clinical and pathological markers used for prognosis and treatment selection. As tumor cells secrete proteins into the extracellular environment, some of these proteins reach circulation and could become suitable biomarkers for improving diagnosis or monitoring response to treatment. As many signaling pathways and interaction networks are altered in cancerous tissues by protein phosphorylation, changes in the secretory phosphoproteome of cancer tissues could reflect both disease progression and subtype. To test this hypothesis, we compared the phosphopeptide-enriched fractions obtained from proteins secreted into conditioned media (CM) derived from five luminal and five basal type breast cancer cell lines using label-free quantitative mass spectrometry. Altogether over 5000 phosphosites derived from 1756 phosphoproteins were identified, several of which have the potential to qualify as phosphopeptide plasma biomarker candidates for the more aggressive basal and also the luminal-type breast cancers. The analysis of phosphopeptides from breast cancer patient plasma and controls allowed us to construct a discovery list of phosphosites under rigorous collection conditions, and second to qualify discovery candidates generated from the CM studies. Indeed, a set of basal-specific phosphorylation CM site candidates derived from IBP3, CD44, OPN, FSTL3, LAMB1, and STC2, and luminal-specific candidates derived from CYTC and IBP5 were selected and, based on their presence in plasma, quantified across all cell line CM samples using Skyline MS1 intensity data. Together, this approach allowed us to assemble a set of novel cancer subtype specific phosphopeptide candidates for subsequent biomarker verification and clinical validation.
乳腺癌是一种异质性疾病,其分子多样性在用于预后和治疗选择的临床及病理标志物中未得到很好的体现。由于肿瘤细胞会向细胞外环境分泌蛋白质,其中一些蛋白质会进入循环系统,有可能成为改善诊断或监测治疗反应的合适生物标志物。由于许多信号通路和相互作用网络在癌组织中会因蛋白质磷酸化而发生改变,癌组织分泌性磷酸化蛋白质组的变化可能反映疾病进展和亚型。为了验证这一假设,我们使用无标记定量质谱法比较了从五种腔面型和五种基底型乳腺癌细胞系的条件培养基(CM)中分泌的蛋白质所获得的富含磷酸肽的组分。总共鉴定出了来自1756种磷酸化蛋白质的5000多个磷酸位点,其中一些有潜力成为更具侵袭性的基底型和腔面型乳腺癌磷酸肽血浆生物标志物候选物。对乳腺癌患者血浆和对照的磷酸肽分析使我们能够在严格的收集条件下构建一个磷酸位点发现列表,并对从CM研究中产生的发现候选物进行鉴定。事实上,从IBP3、CD44、OPN、FSTL3、LAMB1和STC2衍生的一组基底特异性磷酸化CM位点候选物以及从CYTC和IBP5衍生的腔面特异性候选物被筛选出来,并根据它们在血浆中的存在情况,使用Skyline MS1强度数据在所有细胞系CM样品中进行定量。总之,这种方法使我们能够组装出一组新的癌症亚型特异性磷酸肽候选物,用于后续的生物标志物验证和临床验证。