据一项新的研究报道,对从肺部周围液体中获取的细胞进行物理检测可对早期癌症诊断有助。这种诊断可用一种自动化的技术完成,这种方法比细胞分析的黄金标准——细胞学检查更快,而细胞学检查需要专家来筛检细胞。
由Henry Tse及其同事研发的一种新的微芯片装置可通过将细胞挤入充满液体的微通道并追踪它们将如何改变形状来发现恶性细胞。细胞的变形能力长期以来就一直与疾病挂钩,但科学家们常常一次只能研究一个细胞--这是一个艰苦的过程。
这种新的装置使用一种叫做“惯性聚焦”的技术来将细胞按特定路线前往准确的位置,这样它们便能在与流体壁相撞时被均匀地拉伸。当一个细胞变形时,它所经受的压缩量可揭示其组成或结构,如它的膜的弹性如何或细胞内的DNA及蛋白的粘性性质等。例如,癌性的细胞往往会有更多的变形或与正常细胞相比显得较大。这一压缩过程发生在一个有着微小、透明通道(大约为人毛发直径的一半)的芯片上,这些通道能被一个高速摄像机在每秒钟对数千个改变形状的细胞进行摄像。用这种技术所产生的大量的摄像数据能让研究人员对细胞变形创建特征性档案。他们用该档案来确定病人是否有恶性肿瘤或只是良性的情况。
这些结果表明,细胞的变形能力能被用来作为一种诊断癌症的新型物理性生物标记,而体液中有癌细胞的一小组病人可在早期获得诊断。(生物谷Bioon.com)
生物谷推荐的英文摘要
Science DOI: 10.1126/scitranslmed.3006559
Quantitative Diagnosis of Malignant Pleural Effusions by Single-Cell Mechanophenotyping
Henry T. K. Tse1,2,3, Daniel R. Gossett1,2,3, Yo Sup Moon4, Mahdokht Masaeli1, Marie Sohsman5, Yong Ying5, Kimberly Mislick5, Ryan P. Adams6, Jianyu Rao3,5,7,* and Dino Di Carlo
Biophysical characteristics of cells are attractive as potential diagnostic markers for cancer. Transformation of cell state or phenotype and the accompanying epigenetic, nuclear, and cytoplasmic modifications lead to measureable changes in cellular architecture. We recently introduced a technique called deformability cytometry (DC) that enables rapid mechanophenotyping of single cells in suspension at rates of 1000 cells/s—a throughput that is comparable to traditional flow cytometry. We applied this technique to diagnose malignant pleural effusions, in which disseminated tumor cells can be difficult to accurately identify by traditional cytology. An algorithmic diagnostic scoring system was developed on the basis of quantitative features of two-dimensional distributions of single-cell mechanophenotypes from 119 samples. The DC scoring system classified 63% of the samples into two high-confidence regimes with 100% positive predictive value or 100% negative predictive value, and achieved an area under the curve of 0.86. This performance is suitable for a prescreening role to focus cytopathologist analysis time on a smaller fraction of difficult samples. Diagnosis of samples that present a challenge to cytology was also improved. Samples labeled as “atypical cells,” which require additional time and follow-up, were classified in high-confidence regimes in 8 of 15 cases. Further, 10 of 17 cytology-negative samples corresponding to patients with concurrent cancer were correctly classified as malignant or negative, in agreement with 6-month outcomes. This study lays the groundwork for broader validation of label-free quantitative biophysical markers for clinical diagnoses of cancer and inflammation, which could help to reduce laboratory workload and improve clinical decision-making.