Desmoid Tumor Research Foundation RFP Grant

Desmoid Tumor Research Foundation RFP Grant

Status: ACTIVE
Funder: The Desmoid Tumor Research Foundation
Amount: US $65,000
Last Updated: March 27, 2026

Summary

The Desmoid Tumor Research Foundation invites proposals for research into the spontaneous regression of desmoid tumors, which exhibit unpredictable behaviors. This RFP encourages cross-disciplinary collaborations to explore various aspects such as molecular changes, immune system involvement, and biomarkers associated with tumor behavior. By understanding these factors, the aim is to enhance clinical interventions and develop novel therapeutic strategies. Proposals should focus on innovative methods to investigate these critical issues within tumor biology.

Overview

Background Desmoid tumors (also known as aggressive fibromatosis) are locally invasive soft tissue tumors characterized by unpredictable clinical behavior. While some tumors demonstrate aggressive growth requiring surgical or medical intervention, others remain stable or undergo spontaneous regression without therapy. The basis for this regression remains poorly understood. Understanding the mechanisms underlying spontaneous regression could provide critical insights into tumor biology, improve nomination for clinical intervention, and can lead to novel therapeutic strategies that mimic or induce this process. Purpose This RFP invites proposals that seek to investigate the factors contributing to spontaneous regression in desmoid tumors. Proposals that foster cross-disciplinary teams are strongly encouraged. The proposals can focus on any discipline, and as examples proposals could explore: Molecular or cellular changes associated with regression or stable diseaseImmune system and stroma involvement in tumor behaviorTranscriptional and epigenetic profiles of regressing versus progressing tumorsBiomarkers predictive of regression or progressionDevelopment of preclinical models to study spontaneous regressionSystems biology or computational approaches to model regressionLongitudinal clinical or imaging data to identify features of spontaneous regression, with a clear link to underlying biologyHost/tumor interactions

Eligibility

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