SBIR Phase I: High multiplex visual mapping of heterogeneity in FFPE biospecimen

这个SBIR一期项目将通过活检的高级分析来解决癌症患者的耐药性问题。不仅每个病人都是独一无二的，而且他们的肿瘤也包含着高度的基因多样性。忽视患者肿瘤内的多样性可能导致治疗不充分，从而获得耐药性，并且也被证明可以预测对某些药物的治疗反应。该技术能够提取肿瘤基因表达谱，并将其与活检的空间信息和成像相关联，从而构建遗传多样性的物理图谱。这种方法的最初应用将是在免疫肿瘤学中，免疫细胞对抗癌症的空间位置已被证明可以预测对治疗的反应。下一步将是阐明标本中通常被常规诊断所忽略的所有细胞类型，并利用这些信息确定治疗组合，以影响该肿瘤中发现的所有类型的恶性细胞。这直接解决了癌症登月计划（Cancer Moonshot Initiative）对个性化药物联合治疗的关注。该方法的成功商业化将导致药物生物标志物发现服务，对患者的精确筛选，以及研究人员使用该工具调查各种疾病的生物学基础发现。这个SBIR一期项目的技术创新是将基因组分析与空间信息相关联，从而创建整个标本的基因表达原位图的能力。成像和大基因组数据（如测序）一直是相互排斥的，能够将它们联系起来，以便在标本中可视化遗传多样性，将为筛选和研究提供信息。该项目的目标是展示从存档的活组织检查中创建基因表达可视化热图的能力，并表明该表达图识别标准分析方法无法识别的遗传多样性。这种多样性的量化和肿瘤中偏离的位置将是未来药物反应性筛查的基础，也是对各种疾病的病因和治疗进行基础研究的基础。

This SBIR Phase I project will address drug resistance in cancer patients through the advanced analysis of biopsies. Not only is each patient unique but their tumor contains a high level of genetic diversity as well. Overlooked diversity within patient tumors can lead to inadequate treatment and consequently acquired drug resistance, and has also been shown to predict therapeutic response to certain drugs. The proposed technology is capable of extracting and correlating tumor gene expression profiles to the spatial information and imaging of a biopsy so that a physical map of genetic diversity can be constructed. The initial application of this method will be in immuno-oncology where the spatial locations of immune cells fighting cancer have been shown to predict response to treatment. The next step will be to elucidate all cell types in the specimen that are usually overlooked with conventional diagnostics and use this information for determining treatment combinations that would affect all types of malignant cells found in this tumor. This directly addresses the Cancer Moonshot Initiative's focus on combination treatments for personalized medicine. Successful commercialization of this method will result in drug biomarker discovery services, precision screening for patients, and fundamental discoveries in biology by researchers using this tool to investigate various diseases. The technical innovation in this SBIR Phase I Project is the ability to correlate genomic analysis with spatial information to create an in-situ map of gene expression across the specimen. Imaging and big genomic data such as sequencing have been mutually exclusive, and the ability to correlate them in order to visualize genetic diversity within a specimen would be informative for both screening and research. The goals of this project are to demonstrate the ability to create a visual heat map of gene expression from archived biopsies and to show that this expression map identifies genetic diversity that standard analysis methods do not. Quantification of this diversity and the locations of deviations in the tumor will be the basis of future screenings for drug responsiveness as well as basic research into the causes and treatments of various diseases.