SBIR Phase I: CANCER DIAGNOSTIC TOOL USING CANCER GENOMIC SIGNATURES TO DETERMINE CANCER TYPE

SBIR 第一阶段：使用癌症基因组特征确定癌症类型的癌症诊断工具

• 批准号: 2051900
• 负责人: Zurab Kakushadze
• 金额: $ 25.6万
• 依托单位: VYNANCE TECHNOLOGIES, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051900&HistoricalAwards=false
• 关键词: SBIR; Phase; CANCER; DIAGNOSTIC; TOOL

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop a data analytic tool to predict and identify the organ of origin from early cancer screening blood tests. This will allow noninvasive detection of cancer at early stages, when it can be treated with potentially improved outcomes and in a less costly manner. Second, a complementary application of the proposed technology is to address an unmet need in identifying cancer organ of origin in metastatic cancers of unknown primary, where not knowing the organ of origin hampers designing an effective treatment plan in 30,000+ cases/yr in the U.S.This Small Business Innovation Research (SBIR) Phase I project will accomplish internal development, and external validation of the proposed data analytic technology so it is ready to be validated on circulating tumor DNA data from blood, and can be used for metastatic tumors of unknown primary origin. The proposed technology addresses the problem of the unknown primary by analyzing whole genome or large subsets using predictive tools. Different cancer (sub)types have different patterns or signatures of somatic single nucleotide variations in the cancer genome. A library of these signatures is built using a large number of whole genome data samples with a broad cross-section of known cancer (sub)types. The unknown cancer organ of origin of a new data sample is identified by comparing its somatic mutational patterns to the signatures in the library. A key research objective is to identify the minimum subset of whole genome required to determine the cancer organ of origin to facilitate its application in blood tests.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是开发一种数据分析工具，以预测和识别早期癌症筛查血液检测的起源器官。这将允许在早期阶段对癌症进行非侵入性检测，此时可以以更低成本的方式治疗可能改善的结果。 其次，所提出的技术的补充应用是解决在原发性未知的转移性癌症中识别癌症起源器官的未满足的需求，其中不知道起源器官阻碍了在美国设计30，000多例/年的有效治疗计划。以及所提出的数据分析技术的外部验证，因此其准备好在来自血液的循环肿瘤DNA数据上进行验证，并且可以用于未知原发来源的转移性肿瘤。 所提出的技术通过使用预测工具分析全基因组或大子集来解决未知主要的问题。不同的癌症（子）类型在癌症基因组中具有不同的体细胞单核苷酸变异模式或特征。这些特征的文库使用具有已知癌症（子）类型的广泛横截面的大量全基因组数据样本来构建。通过将其体细胞突变模式与文库中的签名进行比较来识别新数据样本的未知癌症起源器官。一个关键的研究目标是确定确定癌症起源器官所需的全基因组的最小子集，以促进其在血液检测中的应用。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。