Getting More from Less: Multi-omic Capture and Analysis from Patient Samples

事半功倍：从患者样本中进行多组学捕获和分析

• 批准号: 9545010
• 负责人: Scott M Berry
• 金额: $ 53.38万
• 依托单位: SALUS DISCOVERY, LLC
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9545010
• 关键词: Address; Adopted; Advanced Malignant Neoplasm; Agreement; Androgen Receptor; Automation; Biological Assay; Biological Markers; Biological Models; Blood; CLIA certified; Cancer Center; Cancer Diagnostics; Cancer Patient; Caring; Cell Nucleus; Cells; Cellular Assay; Clinic; Clinical; Clinical Trials; Companions; Complement; Cyclic GMP; Cytoplasm; DNA; Data; Development; Devices; Diagnosis; Disease; Documentation; Drug Targeting; Exclusion; Foundations; Funding; Gene Expression; Genetic Transcription; Genomics; Glean; Goals; Image; Industrialization; Industry; Laboratories; Letters; Licensing; Ligand Binding; Malignant Neoplasms; Malignant neoplasm of prostate; Manuals; Measurement; Measures; Medicine; Messenger RNA; Methods; Modeling; Monitor; Mutation; Neoplasm Circulating Cells; Nuclear Translocation; Nucleic Acids; Patients; Pharmaceutical Preparations; Phase; Population; Positioning Attribute; Precision therapeutics; Preparation; Progressive Disease; Protein translocation; Proteins; RNA; RNA Splicing; Receptor Signaling; Recovery; Regulation; Resistance; Resistance development; Resources; Sampling; Small Business Innovation Research Grant; Stains; TACSTD1 gene; Techniques; Technology; Testing; Time; Tube; Universities; Validation; Variant; Wisconsin; abiraterone; base; cancer therapy; carbonate dehydratase; clinical diagnostics; clinical efficacy; clinical practice; clinically actionable; cohort; commercialization; design; effective therapy; improved; individual patient; inhibitor/antagonist; innovation; instrumentation; manufacturability; molecular marker; multiple omics; next generation sequencing; patient biomarkers; personalized medicine; predictive marker; prevent; programs; prospective; protein function; public health relevance; resistance mechanism; success; targeted treatment; therapy resistant; treatment choice; tumorigenesis

 DESCRIPTION (provided by applicant): Personalized medicine is predicated on having sufficient patient specific information to provide a diagnosis specific to that patient. Genomics (e.g. next generation sequencing) is now being adopted into clinical practice and is enabling improvements in patient specific care particularly in cancer. However, sequence information alone will not be sufficient to realize the full potential of personalized medicine. If we examine prostate cancer, more than half of patients do not benefit from new anti-cancer therapies such as Abiraterone and Enzalutamide and nearly all patients who initially benefit develop resistance within 1-2 years. Yet, for the clinician the treatment decisions are largely guesswork as he/she has little quantitative mechanistic data to guide treatment choices. Importantly, prostate cancer is driven in large part by the Androgen Receptor (AR) including ligand binding and translocation from the cytoplasm to the nucleus activating a transcriptional program critical to tumorigenesis. Multiple drugs are currently available that prevent nuclear translocation of the AR via different mechanisms, but sequencing alone will be insufficient to accurately guide therapy choice and to monitor the development of resistance (similar scenarios exist in other cancers and other diseases). Predicting and monitoring targeted therapies requires orthogonal multi-omic (i.e., protein, genomic, gene expression) endpoints. Circulating tumor cells (CTCs) have great potential as an accessible sample and many technologies are being developed for CTC analysis, but none have the ability to perform multi-omic analysis from a single sample. This proposal addresses these issues by leveraging and advancing Exclusion-based Sample Preparation (ESP) to enable the rapid and efficient isolation of multiple analytes (cells, proteins RNA, DNA) from a single precious sample with high recovery and purity. To efficiently move this platform into the clinic, we have signed licensing agreements with Gilson and Foundation Medicine (recently acquired by Roche) industry leaders in instrumentation/manufacturing, and advanced cancer diagnostics/clinical laboratory test development respectively. Additionally our clinical collaborator, Dr. Lang (University of Wisconsin), will enable us to directly demonstrate the clinical efficacy of our multi-omic approach during the SBIR proposal period, using advanced prostate cancer as a clinical model. As illustrated by the AR model system, assays capable of measuring multi-omic biomarkers would enable clinicians to make more informed decisions about what type of therapy to use and when to use it for patients with progressive disease, informing both choice of initial treatment as well as when to switch therapy as resistance occurs. We have chosen to submit a Fast-Track SBIR Proposal and have addressed the Fast-Track requirements of clear Phase I goals and clear evidence (e.g. letters) of additional funding & resource commitments that significantly enhance the likelihood of successful commercialization.

 描述（由申请人提供）：个性化医疗的前提是拥有足够的患者特定信息，以提供针对该患者的诊断。基因组学（例如，下一代测序）现在正被应用于临床实践，并且能够改善患者的特定护理，特别是癌症。然而，仅仅序列信息不足以实现个性化医疗的全部潜力。如果我们检查前列腺癌，超过一半的患者没有从新的抗癌治疗中获益，如阿比特龙和恩杂鲁胺，几乎所有最初获益的患者在1-2年内都会产生耐药性。然而，对于临床医生来说，治疗决策在很大程度上是猜测，因为他/她几乎没有定量的机械数据来指导治疗选择。重要的是，前列腺癌在很大程度上是由雄激素受体（AR）驱动的，包括配体结合和从细胞质到细胞核的易位激活对肿瘤发生至关重要的转录程序。目前有多种药物可以通过不同的机制防止AR的核转位，但单独的测序不足以准确指导治疗选择和监测耐药性的发展（其他癌症和其他疾病也存在类似的情况）。预测和监测靶向治疗需要正交多组学（即，蛋白质、基因组、基因表达）终点。循环肿瘤细胞（CTC）作为可获得的样品具有巨大的潜力，并且正在开发用于CTC分析的许多技术，但是没有一种技术具有从单个样品进行多组学分析的能力。该提案通过利用和推进基于排除的样品制备（ESP）来解决这些问题，从而能够以高回收率和纯度从单个珍贵样品中快速有效地分离多种分析物（细胞、蛋白质RNA、DNA）。为了有效地将该平台应用于临床，我们与Gilson和Foundation Medicine（最近被罗氏收购）分别在仪器/制造和先进癌症诊断/临床实验室测试开发方面的行业领导者签署了许可协议。此外，我们的临床合作者Lang博士（威斯康星州大学）将使我们能够在SBIR提案期间使用晚期前列腺癌作为临床模型直接证明我们的多组学方法的临床疗效。如AR模型系统所示，能够测量多组学生物标志物的测定将使临床医生能够做出更明智的决定，决定使用何种类型的治疗以及何时将其用于患有进展性疾病的患者，从而告知初始治疗的选择以及当出现耐药性时何时转换治疗。我们选择提交一份快速通道SBIR提案，并解决了明确的第一阶段目标和明确的额外资金和资源承诺的快速通道要求（例如信件），这些承诺显著提高了成功商业化的可能性。