PO.CH02.01 · 化学

超低丰度癌症生物标志物发现:具有阿托摩尔灵敏度的多重蛋白质谱分析

Ultra-low-abundance cancer biomarker discovery: Multiplexed protein profiling with attomolar sensitivity

海报缩略图:超低丰度癌症生物标志物发现:具有阿托摩尔灵敏度的多重蛋白质谱分析
编号 7678 展板 2 时间 4/22 09:00–12:00 区域 Section 39 主讲 Malcolm MacKenzie, MBA
分会场 Proteomics: Biomarker Discovery and Signaling Networks
查看 PDF 下载 PDF 🔒 查看 / 下载完整 PDF 需登录并开通下载套餐 · 查看套餐 / 开通 AACR 官方页面

作者与单位 Authors & Affiliations

Malcolm MacKenzie1, Ilya Alexandrov2, Matthew Preimesberger2

1ActivSignal, Natick, MA,2ActivSignal, NATICK, MA

摘要 Abstract

中文摘要
引言:在肿瘤学研究的众多应用中,利用超低丰度生物标志物具有巨大潜力。这些生物标志物,包括许多癌症相关信号蛋白及其翻译后修饰(PTM)异构体,可能提供关键的生物学指标,但在技术上仍难以测量,尤其是在多重检测中。市场上领先的发现平台缺乏可靠检测亚fM级生物标志物所需的灵敏度,因此其检测板中不包含PTM异构体。根据已发表的第三方评估,1000+重平台在给定样本中可能对其检测板中超过一半的靶标返回未检出结果,这是由于灵敏度不足所致。方法与结果:我们开发并验证了一种多重蛋白质谱分析技术BlueSCAI™(Background Lowering using Serial-Capture, Adapter-Insertion,串联捕获-接头插入降低背景),可将技术灵敏度提高至阿托摩尔水平。BlueSCAI是一个基于邻近的平台,具有捕获-释放-再捕获机制。我们与一个业界领先的邻近谱分析平台进行了正面比较,涵盖21个随机选择的生物标志物的重叠,对于这些标志物:i. 其他商业平台已有发表的LOD;ii. 所需试剂,以及iii. 靶抗原,均可从经过审核的供应商处便捷获得。在众多蛋白靶标上,BlueSCAI展示了比高重蛋白平台低数个数量级的检测限,代表分析灵敏度的实质性提升。此外,在使用相同抗体对与商业ELISA检测的比较中,BlueSCAI对多个生物标志物展示了低近1000倍的LOD。例如,BlueSCAI整合的CA19-9生物标志物相比在领先临床实验室平台上测量的CA19-9灵敏度提升约3个数量级(<0.0001 U/mL vs 0.6 U/mL)。剂量-反应曲线分析表明,近一半的靶标检测板表现出4个以上数量级的线性动态范围,同等比例的靶标显示高于背景的最大信号大于10000。交叉反应性(1-信号特异性)采用留一混合抗原池方法测量。在3/4的靶标检测板中信号特异性超过99.9%,在其余25%的靶标上超过98%特异。结论:BlueSCAI的特异性、高灵敏度、多重检测在分析新的肿瘤学相关、具有生物学信息的超低丰度生物标志物方面显示出巨大前景,这些标志物包括癌症信号蛋白、PTM异构体和细胞外囊泡货物,可应用于多样的癌症研究领域。
查看英文原文 English abstract
Introduction: There is a great potential for utilizing ultra-low-abundance biomarkers in numerous applications across oncology research. These biomarkers, including many cancer-related signaling proteins and their post-translationally modified (PTM) isoforms, may provide key biological indicators, yet remain technically challenging to measure, particularly in multiplex. The leading discovery platforms available in the market lack the necessary sensitivity to reliably detect sub-fM biomarkers, and, therefore, do not include PTM isoforms in their panels. Based on published third-party assessments, 1,000+ plex platforms can return non-detects on over half of the targets in their panels for a given sample, due to insufficient sensitivity. Methods and Results: We have developed and validated a multiplex protein profiling technology, BlueSCAI™ ( B ackground L owering u sing S erial- C apture, A dapter- I nsertion), which can increase technical sensitivity down to the attomolar level. BlueSCAI is a proximity-based platform with a capture-release-recapture mechanism. We conducted a head-to-head comparison with an industry leading proximity profiling platform, encompassing an overlap of 21 randomly selected biomarkers, for which there were i. published LODs available for other commercial platform; and ii. the required reagents, and iii. the target antigens, were readily available from vetted vendors . Across numerous protein targets, BlueSCAI demonstrated limits of detection that are several logs lower than those of high plex protein platforms, representing a substantial improvement in analytical sensitivity. In addition, in comparisons with commercial ELISA assays, using the same antibody pairs, BlueSCAI demonstrated LODs almost 1,000 fold lower for multiple biomarkers. For example, BlueSCAI's integrated CA19-9 biomarker has an improved sensitivity of ~ 3 logs compared to CA19-9 measured using a leading clinical lab platform (<0.0001 U/mL vs 0.6 U/mL). Analysis of dose-response curves indicated that almost half of the target panel exhibited 4+ logs of linear dynamic range, with an equal fraction showing maximal signal above background of greater than 10,000. Cross-reactivity (1-signal specificity) was measured with a leave-out mixed antigen pool approach. Signal specificities exceeded 99.9% across ¾ of the target panel, and over 98% specific on the remaining 25% of targets. Conclusion: BlueSCAI's specific, high sensitivity, multiplex detection shows great promise for profiling new oncology-related, biologically informative, ultra-low-abundance biomarkers, which includes cancer signaling proteins, PTM isoforms, and extracellular vesicle cargo, across diverse cancer research applications.
利益披露 Disclosure
M. MacKenzie, None.. I. Alexandrov, None.. M. Preimesberger, None.

← 返回 AACR 2026 检索