INDIVIDUALIZING COLON CANCER THERAPY USING HYBRID RNA AND DNA MOLECULAR SIGNATURE

描述(申请人提供)：预测哪些癌症患者对治疗的反应最好是一个巨大的医疗保健问题。最近有人提出，基于对整个外显子组测序数据的早期阅读，可能只有~12条分子途径驱动癌症的发生和发展。许多实验性疗法现在都针对这些途径。我们认为，基因表达特征可能是判断特定分子途径激活的最好方法之一，因为它提供了许多基因活性的“分子摘要”。此外，我们认为，选择性地增加突变评估可能会提高混合、多分析物(DNA+RNA)测试的分辨率，该测试可用于指导患者选择最有效的药物。我们最近开发了基因表达特征来测量结肠癌中两个最重要的通路，RAS和PI3K的激活，对于这两个通路，有越来越多的通路靶向治疗。由于这些途径的复杂性，对典型的单基因突变的简单分析只识别了一部分(&lt；30%)人群的反应特征。在这里，我们建议从技术上验证现有的RAS和PI3K签名，并通过新的突变评估来提炼它们的活性。多分析物签名/算法将在接受西妥昔单抗治疗的一组结直肠癌患者的CLIA环境中进行临床验证。这种方法将在不久的将来为临床应用准备签名。 公共卫生相关性：这项提案寻求确定一种可靠的方法，为合适的癌症患者确定合适的药物。目前的治疗方法过度治疗许多患者，以帮助未知的少数人，成本和毒性都很大。分子签名在个体化治疗中的应用为个性化癌症治疗、提高应答率、降低毒性和相关成本带来了巨大的希望。在这里，我们将结合RNA基因表达签名和基因突变评估来识别西妥昔单抗治疗的应答者和无效者。

DESCRIPTION (provided by applicant): Predicting which cancer patients will best respond to therapy is an enormous health care issue. It has been recently suggested, based on early reads of whole exome sequencing data, that there may only be ~12 molecular pathways that drive the development and progression of cancer. Many experimental therapies are now targeting these pathways. We believe that gene expression signatures may be one of the best ways to judge the activation of a particular molecular pathway, by providing a "molecular summary" of the activity of many genes. Moreover, we believe that the selective addition of mutational assessment may improve the resolving power of a hybrid, multi-analyte (DNA + RNA) test that may be used to guide patients to the most effective drugs. We have recently developed gene expression signatures to measure the activation of two of the most important pathways in colon cancer, RAS and PI3K, for which there is an increasing availability of pathway targeted therapeutics. Due to the complex nature of these pathways, simple analysis of canonical single gene mutations only identifies the response characteristics of a proportion (<30%) of the population. Here, we propose to technically validate the existing RAS and PI3K signatures and to refine their activity through novel mutational assessment. Multi-analyte signatures/ algorithms will be clinically validated in a CLIA environment with a cohort of colorectal cancer patients treated with cetuximab therapy. This approach will prepare signatures for clinical application in the near future. PUBLIC HEALTH RELEVANCE: This proposal seeks to identify a reliable means to identify the right drugs for the right cancer patients. Current approaches over treat many patients to help an unknown few, with substantial costs and toxicities. The application of molecular signatures to individualize therapy holds significant promise to personalize cancer care, improve response rates, reduces toxicity and associated costs. Here we will combine RNA gene expression signatures with gene mutation assessments to identify responders and non-responders to cetuximab therapy.