Biomarker-Based Prediction Models for Response to Treatment in Systemic Sclerosis-Related Interstitial Lung Disease
Abstract
Topic Area: Scleroderma. Systemic sclerosis (SSc -- also called scleroderma) is a multi-organ, autoimmune disease that is associated with high disease burden. One of main disease manifestations is interstitial lung disease (ILD -- also called pulmonary fibrosis), which leads to thickening of air sac walls in the lung tissue. ILD results in decreased lung volumes and hinders efficient oxygen exchange. Initially, affected patients have only shortness of breath with exertion. As this disease manifestation progresses, they even experience shortness of breath at rest. Thus, advanced ILD can result in substantial limitations during activities of daily living and can severely impair quality of life in persons with SSc. Furthermore, ILD can lead to decreased survival and is the primary cause of disease-related death in SSc. Medications that generally dampen the immune response (immunosuppresive agents) such as cyclophosphamide or mycophenolate mofetil are used for treatment of SSc-related ILD. However, patients respond very differently to these medications. Some show significant improvement in their lung function while others will continue experiencing worsening disease, despite treatment. Furthermore, these medications can be associated with significant side effects such as life-threatening infections or infertility and should be reserved for patients who will be likely responders. The currently available clinical information is not sufficient for predicting response to immunosuppressive agents in patients with SSc-related ILD. Treatment is usually delayed until considerable disease damage has occurred and treatment options cannot be tailored according to the individual patient s treatment needs. Thus, there is a substantial unmet clinical need for identification of novel molecular predictors in SSc-related ILD. Novel molecular techniques like RNA sequencing, microarrays, and multiplex protein profiling are important tools for understanding the molecular basis of diseases. RNA sequencing and microarrays can simultaneously measure levels of thousands of RNA strands in a given tissue. Similarly, protein profiling can determine levels of tens of proteins in a small amount of blood. These technologies represent breakthroughs in medicine that can help researchers and clinicians subgroup patients at the molecular level and identify new targets for development of effective medications. The goal of this proposal is to use these novel technologies in valuable clinical samples for identifying better molecular predictors of response to treatment in SSc-related ILD. Scleroderma Lung Study II is a recently completed, 14-center trial comparing the efficacy of mycophenolate mofetil (MMF) with that of cyclophosphamide (CYC) for treatment of SSc-ILD. This important study investigated for the first time the efficacy of a commonly used medication, MMF, for treatment of SSc-ILD in a randomized controlled trial. The results of this study will be presented at the upcoming American College of Rheumatology Annual Meeting in November 2015. They show that both CYC and MMF are modestly effective in the overall group. However, the treatment effect is highly variable. Approximately, one-third of patients experienced worsening lung function despite treatment with CYC or MMF. The prospective collected biospecimens (blood and skin biopsies) in the Scleroderma Lung Study II is an unparalleled resource because they represent the only currently available patient sample collection in the world in a randomized-controlled trial of SSc-related ILD. This unprecedented resource will enable us to compare the prominent immune abnormalities in SSc with clinical outcomes and determine their predictive significance. The ultimate goal of this proposal is to develop and validate prediction tools for response to treatment in SSc-related ILD. A robust and evidence-driven treatment guide can aid physicians in their clinical decisions and ultima
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 31, 2017
- Source ID
- W81XWH1610296
Entities
People
- Shervin Assassi
Organizations
- United States Army
- University of Texas Health Science Center at Houston