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，在有限的资源环境下开发一个完整的“样本-答案”解决方案来诊断卡波西肉瘤(KS)。卡波西肉瘤是撒哈拉以南非洲男性的头号癌症和女性的第二大癌症。KS很难与其他血管增生性疾病区分开来，特别是在非洲，在那里，只有少数几家医院才能找到训练有素的病理学家，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，基于聚合酶链式反应的皮肤活检组织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检测系统结合了我们的(1)用于活检提取和样本处理的“注射器上实验室”技术，(2)用于极低功率核酸扩增的光热聚合酶链式反应，以及(3)用于结果量化的基于纳米颗粒的比色智能手机分析。该系统专为野战护士设计，可在低资源设置的情况下解决卡波西肉瘤诊断的诸多挑战，包括：现场采集和处理活组织标本的能力，通过使用太阳光驱动热循环过程，一次电池充电可执行的诊断反应数量至少增加10倍，以及消除对只需智能手机和镜头的专门仪器的依赖，从而使操作员能够在现场修复系统。我们已经演示了KS检测系统中使用的三种技术。R21的目标是在将每项技术集成到工作流中的同时优化每项技术，并使用人类样本执行一系列系统级验证实验。在临床实施之前，这种临床前优化是至关重要的。

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.