Department of Chemistry, University of Massachusetts, Amherst, Massachusetts, United States.
ACS Nano. 2012 Sep 25;6(9):8233-40. doi: 10.1021/nn302917e. Epub 2012 Sep 4.
Rapid and sensitive methods of discriminating between healthy tissue and metastases are critical for predicting disease course and designing therapeutic strategies. We report here the use of an array of gold nanoparticle-green fluorescent protein elements to rapidly detect metastatic cancer cells (in minutes), as well as to discriminate between organ-specific metastases and their corresponding normal tissues through their overall intracellular proteome signatures. Metastases established in a new preclinical non-small-cell lung cancer metastasis model in athymic mice were used to provide a challenging and realistic testbed for clinical cancer diagnosis. Full differentiation between the analyte cell/tissue was achieved with as little as 200 ng of intracellular protein (~1000 cells) for each nanoparticle, indicating high sensitivity of this sensor array. Notably, the sensor created a distinct fingerprint pattern for the normal and metastatic tumor tissues. Moreover, this array-based approach is unbiased, precluding the requirement of a priori knowledge of the disease biomarkers. Taken together, these studies demonstrate the utility of this sensor for creating fingerprints of cells and tissues in different states and present a generalizable platform for rapid screening amenable to microbiopsy samples.
快速而敏感的区分健康组织和转移灶的方法对于预测疾病进程和制定治疗策略至关重要。我们在这里报告了使用一系列金纳米粒子-绿色荧光蛋白元件来快速检测转移性癌细胞(在几分钟内),并通过其整体细胞内蛋白质组特征来区分特定器官的转移灶及其相应的正常组织。在无胸腺小鼠的新临床前非小细胞肺癌转移模型中建立的转移灶为临床癌症诊断提供了具有挑战性和现实意义的测试平台。对于每个纳米粒子,只需 200ng 的细胞内蛋白质(~1000 个细胞)即可实现对分析物细胞/组织的完全区分,表明该传感器阵列具有很高的灵敏度。值得注意的是,该传感器为正常和转移性肿瘤组织创建了一个独特的指纹图谱。此外,这种基于阵列的方法是无偏的,不需要事先了解疾病生物标志物的知识。总之,这些研究表明该传感器可用于创建不同状态下的细胞和组织指纹,并为快速筛选提供了一种可适用于微生物活检样本的通用平台。