Research ArticleCancer

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

See allHide authors and affiliations

Science Translational Medicine  05 Aug 2020:
Vol. 12, Issue 555, eaaz9746
DOI: 10.1126/scitranslmed.aaz9746

You are currently viewing the abstract.

View Full Text

Log in to view the full text

Log in through your institution

Log in through your institution

Panning for diagnostic gold

Accurate and timely diagnosis and categorization of cancer are not always simple even under optimal conditions, and it can be near impossible in the developing world, where the necessary specialists and equipment may not be available and biopsy results can take months to return. To address this diagnostic bottleneck, Min et al. devised an automated image cytometry system named CytoPAN, which can correctly detect breast cancer and identify its subtype in 1 hour using samples obtained by fine needle aspiration, a less invasive technique than core biopsy. The system is relatively affordable and requires minimal training, which should decrease the barriers to access in low-resource areas.

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.

View Full Text

Stay Connected to Science Translational Medicine