KS-Detect: A sample-in, answer-out solution to the Diagnosis of Kaposi's Sarcoma

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Abstract The goal of this project is to develop a complete "sample-in-answer-out" solution to the diagnosis of Kaposi's sarcoma (KS) in limited resource settings through the development of our KS-Detect system. Kaposi's sarcoma is the leading cancer in men and the second leading cancer in women in sub-Saharan Africa. KS is difficult to distinguish from other angioproliferative diseases, particularly in Africa where access to trained pathologists is limited to few hospitals and immunohistochemistry is practically non-existent. Multiple studies have shown that PCR based nucleic acid identification of Kaposi's sarcoma herpesvirus (KSHV) in skin biopsies represents the best method of performing an unambiguous diagnosis in the absence of immunohistochemistry. The KS-Detect system combines our (1) "lab-on-a-syringe" technology for biopsy extraction and sample processing, (2) solar-thermal PCR for extremely low-power nucleic acid amplification, and (3) a nanoparticle based colorimetric smartphone assay for the quantification of the results. The system is designed to be used by a field nurse and addresses a number of challenges with low resource setting diagnosis of Kaposi's sarcoma including: the ability to take and process a biopsy samples in the field, providing at least a 10-fold increase in the number of diagnostic reactions that can be performed on a single battery charge by using sunlight to drive the thermal cycling process, and elimination of the reliance on specialized instrumentation requiring only a smartphone and a lens thereby enabling the system to be fixed in the field by the operator. We have already demonstrated each of the three technologies used in the KS-Detect system. The aims of this R21 effort are to optimize each of the technologies while integrating them into the workflow, and to perform a series of system level validation experiments using human samples. This pre-clinical optimization is critical prior to clinical implementation.