Optimizing the Approach to Identify Cancer-Associated Myositis

项目摘要 虽然特发性炎性肌病（IIM）的发病机制在很大程度上是未知的， 描述了癌症和IIM发病之间的关系。在IIM患者的一个子集中，存在增加的 在肌炎发作时，癌症的风险被称为癌症相关性肌炎（CAM）。几 肌炎特异性自身抗体已被证明可用于IIM患者的临床表型，包括 与癌症有关。然而，哪些患者患癌症的风险最高， 风险，癌症类型和最佳癌症检测策略都是未知的。我们的初步 数据表明，这些肌炎特异性自身抗体可以在定义能力方面发挥有用的作用 关于癌症风险的亚组，并提供对患者可能处于的癌症类型的洞察力 风险最高的。此外，我们证明，尽管广泛使用的各种癌症- 在美国，临床医生采用的筛查试验中，并非所有的试验在IIM患者中具有相同的价值。的 拟议的研究将利用世界上最大的IIM患者队列之一来定义和验证 与癌症风险增加相关的自身抗体，并评估其在定量癌症风险中的效用， 发病在目标1中，我们将确定癌症相关性肌炎相对于普通人群的风险 在我们的队列总体和不同的自身抗体亚组中。我们将证明癌症的风险和类型 与IIM相关的相对于一般人群的抗体将基于患者产生的自身抗体而变化。 目标2将提供IIM中进行的癌症评估的当前标准的有用性数据 患者，并产生一个更有选择性，更少伤害的检测策略的论点。最后，在目标3中， 推导出一种预测工具，用于为临床决策提供信息，以获得评估IIM的最佳策略 恶性肿瘤患者。这项工作将使临床相关和循证的发展 在IIM发作时检测癌症的方法，并确定通过自身抗体定义IIM患者的作用 子集

PROJECT SUMMARY Although the pathogenesis of idiopathic inflammatory myopathies (IIM) is largely unknown, data has emerged describing a relationship between cancer and IIM onset. In a subset of IIM patients, there exists an increased risk of cancer around the time of myositis onset, referred to as cancer-associated myositis (CAM). Several myositis-specific autoantibodies have proven useful in the clinical phenotyping of patients with IIM, including associating with cancer. However, which patients are at highest risk for developing cancer, the magnitude of the risk, the type of cancer, and the optimal cancer detection strategy are all unknown. Our preliminary data demonstrate that these myositis-specific autoantibodies can serve a useful role in the ability to define subgroups with regards to cancer risk as well as provide insight into the type of cancer a patient may be at highest risk for. Furthermore, we demonstrate that despite the widespread use of a large variety of cancer- screening tests employed by clinicians in the United States, not all tests have equal value in IIM patients. The proposed studies will utilize one of the largest cohorts of IIM patients in the world to define and validate autoantibodies associated with increased cancer risk and to assess their utility in quantifying the cancer risk at disease onset. In Aim 1 we will determine the risk of cancer-associated myositis relative to the general population in our cohort overall and in distinct autoantibody subgroups. We will demonstrate that the risk and type of cancer associated with IIM relative to the general population will vary based on the autoantibody the patient produces. Aim 2 will provide data on the usefulness of the current standard of cancer assessment that is performed in IIM patients, and generate an argument for a more selective, less harmful detection strategy. Lastly, in Aim 3 we will derive a predictive tool that will be used to inform clinical decision-making for optimal strategies to assess IIM patients for malignancy. This work will allow the development of a clinically relevant and evidence-based approach to cancer detection at IIM onset and establish the role for defining IIM patients by autoantibody subsets.