Multiplexed single-cell analysis of FNA allows accurate diagnosis of salivary gland tumors

FNA 的多重单细胞分析可以准确诊断唾液腺肿瘤

阅读:6
作者:Juhyun Oh, Tae Yeon Yoo, Talia M Saal, Lisa Tsay, William C Faquin, Jonathan C T Carlson, Daniel G Deschler, Sara I Pai, Ralph Weissleder

Abstract

Diagnosing salivary gland tumors (SGTs) through fine-needle aspiration (FNA) biopsies is challenging due to the overlapping cytomorphologic features between benign and malignant tumors. The authors developed an innovative, multiplexed cycling technology for the rapid analyses of single cells obtained from FNA that can facilitate the molecular analyses and diagnosis of SGTs. Antibodies against 29 protein markers associated with 7 SGT subtypes were validated and chemically modified via custom linker-bio-orthogonal probes (FAST). Single-cell homogenates and FNA samples were profiled by FAST cyclic imaging and computational analysis. A prediction model was generated using a training set of 151,926 cells from primary SGTs (N = 26) and validated on a separate cohort (N = 30). Companion biomarker testing, such as neurotrophic tyrosine receptor kinase (NTRK), was also assessed with the FAST technology. The FAST molecular diagnostic assay was able to distinguish between benign and malignant SGTs with an accuracy of 0.86 for single-cell homogenate samples and 0.88 for FNA samples. Profiling of multiple markers as compared to a single marker increased the diagnostic accuracy (0.82 as compared to 0.65-0.74, respectively), independent of the cell number sampled. NTRK expression was also assessed by the FAST assay, highlighting the potential therapeutic application of this technology. Application of the novel multiplexed single-cell technology facilitates rapid biomarker testing from FNA samples at low cost. The customizable and modular FAST-FNA approach has relevance to multiple pathologies and organ systems where cytologic samples are often scarce and/or indeterminate resulting in improved diagnostic workflows and timely therapeutic clinical decision-making.

特别声明

1、本文转载旨在传播信息,不代表本网站观点,亦不对其内容的真实性承担责任。

2、其他媒体、网站或个人若从本网站转载使用,必须保留本网站注明的“来源”,并自行承担包括版权在内的相关法律责任。

3、如作者不希望本文被转载,或需洽谈转载稿费等事宜,请及时与本网站联系。

4、此外,如需投稿,也可通过邮箱info@biocloudy.com与我们取得联系。