Prediction and Significance of Cancer in Idiopathic Inflammatory Myositis

PROJECT SUMMARY Idiopathic inflammatory myopathies (IIM) comprise a heterogeneous group of chronic autoimmune diseases that can lead to severe muscle weakness and chronic disability; however, it is their association with contemporaneous cancer (cancer-associated myositis, CAM), that is responsible for mortality rates approaching

50%. Myositis-specific autoantibodies have emerged as important biomarkers, and are associated with an

increased risk of cancer, but are of limited utility in predicting if cancer will emerge in an individual patient – the majority of patients with the highest-risk antibodies for CAM never have cancer diagnosed. Despite multiple studies focused on the myositis-cancer association, the ability to predict cancer, and the biologic

relationship between cancer and myositis, remain poorly understood. Given the inability to predict cancer, the current standard is that the majority of patients with IIM are aggressively screened for cancer for multiple years following diagnosis, leading to increased cost, radiation, and false positive results. Beyond CAM prediction, the biologic relationship between IIM and cancer has been

historically neglected; specifically, how cancer emergence and elimination impact IIM outcomes is largely unknown. However, insights gained from the careful study of cancer emergence/elimination in IIM can inform research into disease mechanism, particularly given that cancer has been hypothesized to be responsible for

IIM development – so called “cancer-induced autoimmunity”. In this setting, the recent development of highly sensitive, novel cancer detection technologies have enabled the robust study of cancer in IIM cohorts. The overall goals of this proposal are to (i) optimize the prediction of CAM at the individual patient level and

(ii) determine how the emergence and elimination of cancer influence IIM clinical outcomes. In Aim 1, we will utilize three of the largest cohorts of IIM patients in the United States to develop and validate a cancer prediction model to inform clinical decision-making. In Aim 2, the relationship between cancer

emergence, cancer elimination, and IIM outcomes will be determined using novel liquid biopsy cancer detection technologies, providing insights into IIM pathogenesis and improvements in disease monitoring. Understanding the cancer-IIM relationship will ultimately enable development of novel, effective treatment strategies

that are focused on cancer detection/elimination rather than the currently used non-specific immunosuppression approaches.