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

描述（由申请人提供）：该项目的目标是通过开发我们的KS检测系统，在资源有限的情况下，为卡波西肉瘤（KS）的诊断开发一个完整的“样本-答案-输出”解决方案。卡波西氏肉瘤是撒哈拉以南非洲地区男性的主要癌症，也是女性的第二大癌症。KS很难与其他血管增生性疾病区分开来，特别是在非洲，训练有素的病理学家仅限于少数几家医院，免疫组织化学几乎不存在。多项研究表明，在没有免疫组织化学的情况下，基于PCR的皮肤活检中卡波西肉瘤疱疹病毒（KSHV）的核酸鉴定是进行明确诊断的最佳方法。KS-Detect系统结合了我们的(1)“注射器实验室”技术，用于活检提取和样品处理，(2)太阳能热PCR，用于极低功率核酸扩增，(3)基于纳米颗粒的智能手机比色测定，用于结果定量。该系统旨在供现场护士使用，并解决了卡波西肉瘤诊断资源不足的一些挑战，包括：在现场采集和处理活检样本的能力，提供了至少10倍的诊断反应数量，可以通过使用阳光驱动热循环过程进行一次电池充电，并且消除了对专用仪器的依赖，只需要一个智能手机和一个镜头，从而使系统能够由操作员在现场固定。我们已经演示了KS-Detect系统中使用的三种技术中的每一种。这项R21工作的目的是优化每一项技术，同时将它们集成到工作流程中，并使用人类样本执行一系列系统级验证实验。这种临床前优化在临床实施之前是至关重要的。

DESCRIPTION (provided by applicant): 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 herpes virus (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.