CytoPAN—Portable cellular analyses for rapid point-of-care cancer diagnosis

Jouha Min, Lip Ket Chin, Juhyun Oh, Christian Landeros, Claudio Vinegoni, Jeeyeon Lee, Soo Jung Lee, Jee Young Park, Ai Qun Liu, Cesar M. Castro, Hakho Lee, Hyungsoon Im, Ralph Weissleder

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Rapid, automated, point-of-care cellular diagnosis of cancer remains difficult in remote settings due to lack of specialists and medical infrastructure. To address the need for same-day diagnosis, we developed an automated image cytometry system (CytoPAN) that allows rapid breast cancer diagnosis of scant cellular specimens obtained by fine needle aspiration (FNA) of palpable mass lesions. The system is devoid of moving parts for stable operations, harnesses optimized antibody kits for multiplexed analysis, and offers a user-friendly interface with automated analysis for rapid diagnoses. Through extensive optimization and validation using cell lines and mouse models, we established breast cancer diagnosis and receptor subtyping in 1 hour using as few as 50 harvested cells. In a prospective patient cohort study (n = 68), we showed that the diagnostic accuracy was 100% for cancer detection and the receptor subtyping accuracy was 96% for human epidermal growth factor receptor 2 and 93% for hormonal receptors (ER/PR), two key biomarkers associated with breast cancer. A combination of FNA and CytoPAN offers faster, less invasive cancer diagnoses than the current standard (core biopsy and histopathology). This approach should enable the ability to more rapidly diagnose breast cancer in global and remote settings.

Original languageEnglish
Article numbereaaz9746
JournalScience Translational Medicine
Volume12
Issue number555
DOIs
StatePublished - 5 Aug 2020

Fingerprint

Dive into the research topics of 'CytoPAN—Portable cellular analyses for rapid point-of-care cancer diagnosis'. Together they form a unique fingerprint.

Cite this