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dc.contributor.authorMin, Jouhaen_US
dc.contributor.authorChin, Lip Keten_US
dc.contributor.authorOh, Juhyunen_US
dc.contributor.authorLanderos, Christianen_US
dc.contributor.authorVinegoni, Claudioen_US
dc.contributor.authorLee, Jeeyeonen_US
dc.contributor.authorLee, Soo Jungen_US
dc.contributor.authorPark, Jee Youngen_US
dc.contributor.authorLiu, Ai Qunen_US
dc.contributor.authorCastro, Cesar M.en_US
dc.contributor.authorLee, Hakhoen_US
dc.contributor.authorIm, Hyungsoonen_US
dc.contributor.authorWeissleder, Ralphen_US
dc.identifier.citationMin, J., Chin, L. K., Oh, J., Landeros, C., Vinegoni, C., Lee, J., Lee, S. J., Park, J. Y., Liu, A. Q., Castro, C. M., Lee, H., Im, H. & Weissleder, R. (2020). CytoPAN-Portable cellular analyses for rapid point-of-care cancer diagnosis. Science Translational Medicine, 12(555), eaaz9746-.
dc.description.abstractRapid, 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.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.relation.ispartofScience Translational Medicineen_US
dc.rightsThis is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science Translational Medicine on Vol 12 and 5 August 2020, DOI: 10.1126/scitranslmed.aaz9746en_US
dc.titleCytoPAN-Portable cellular analyses for rapid point-of-care cancer diagnosisen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionAccepted versionen_US
dc.description.acknowledgementWe acknowledge the following grant support: NRFCRP13-2014-01 to A.-Q.Len_US
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