# Prediction and Significance of Cancer in Idiopathic Inflammatory Myositis

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2024 · $575,021

## Abstract

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.

## Key facts

- **NIH application ID:** 10855717
- **Project number:** 1R01AR083912-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Christopher Mecoli
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $575,021
- **Award type:** 1
- **Project period:** 2024-09-01 → 2029-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10855717

## Citation

> US National Institutes of Health, RePORTER application 10855717, Prediction and Significance of Cancer in Idiopathic Inflammatory Myositis (1R01AR083912-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10855717. Licensed CC0.

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