Desmoid tumors are rare, locally aggressive neoplasms with unpredictable behavior. Although some tumors are indolent, resolving spontaneously, with tamoxifen, or with anti-inflammatory medications, others are prone to local recurrence, leading to significant morbidity, impaired function and poor quality of life for patients. For patients with advanced, refractory tumors, intensive chemotherapy regimens such as methotrexate/vinblastine or doxorubicin/dacarbazine can produce significant radiographic responses and symptomatic improvement. However these therapies are associated with both short and long-term toxicities. The ability to personalize therapy based on a predictive marker from an individual patient’s tumor would allow early treatment of aggressive tumors with chemotherapy, while sparing patients with indolent tumors or those more likely to respond to milder interventions.
Recently, desmoid tumors with particular mutations in CTNNB1, including S45F, have been shown to have a higher risk of recurrence. Additionally, desmoid tumors with S45F mutations were less likely to respond to conservative treatments with imatinib or meloxicam. However, it is unknown whether S45F mutated tumors are more likely to respond to chemotherapy. In this proposal, we will obtain tissue and radiographic imaging for our existing database of desmoid tumor patients, and perform CTNNB1 sequencing to identify specific mutations. Through a collaboration with MD Anderson Cancer Center and Mount Sinai School of Medicine, our combined datasets will then be analyzed to determine whether the presence of S45F mutations correlates with MRI response to various chemotherapy regimens. The ability to use CTNNB1 mutation status to predict behavior of desmoid tumors and to guide therapeutic decisions would have immediate implications for clinical management of these rare yet often aggressive tumors.