據(jù)一項新的研究報道,，對從肺部周圍液體中獲取的細胞進行物理檢測可對早期癌癥診斷有助,。這種診斷可用一種自動化的技術(shù)完成,，這種方法比細胞分析的黃金標準——細胞學檢查更快,，而細胞學檢查需要專家來篩檢細胞,。
由Henry Tse及其同事研發(fā)的一種新的微芯片裝置可通過將細胞擠入充滿液體的微通道并追蹤它們將如何改變形狀來發(fā)現(xiàn)惡性細胞,。細胞的變形能力長期以來就一直與疾病掛鉤,，但科學家們常常一次只能研究一個細胞--這是一個艱苦的過程。
這種新的裝置使用一種叫做“慣性聚焦”的技術(shù)來將細胞按特定路線前往準確的位置,，這樣它們便能在與流體壁相撞時被均勻地拉伸,。當一個細胞變形時，它所經(jīng)受的壓縮量可揭示其組成或結(jié)構(gòu),，如它的膜的彈性如何或細胞內(nèi)的DNA及蛋白的粘性性質(zhì)等,。例如，癌性的細胞往往會有更多的變形或與正常細胞相比顯得較大,。這一壓縮過程發(fā)生在一個有著微小,、透明通道（大約為人毛發(fā)直徑的一半）的芯片上，這些通道能被一個高速攝像機在每秒鐘對數(shù)千個改變形狀的細胞進行攝像,。用這種技術(shù)所產(chǎn)生的大量的攝像數(shù)據(jù)能讓研究人員對細胞變形創(chuàng)建特征性檔案,。他們用該檔案來確定病人是否有惡性腫瘤或只是良性的情況。
這些結(jié)果表明,，細胞的變形能力能被用來作為一種診斷癌癥的新型物理性生物標記,，而體液中有癌細胞的一小組病人可在早期獲得診斷。（生物谷Bioon.com）
生物谷推薦的英文摘要
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.
