Optimizing the Approach to Identify Cancer-Associated Myositis

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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.