Lead Investigators: Suzanne George, MD; Katherine Janeway, MD
Institution: Dana-Farber Cancer Institute, Broad Institute
Clinical Challenge
- Leiomyosarcoma is a rare, aggressive smooth-muscle cancer with limited datasets, slowing discovery of biomarkers and targeted therapies.
- Traditional LMS research has been challenged by small cohorts and fragmented clinical data. The Count Me In LMS project (lmsproject.org) addresses this by collecting patient samples and aggregating clinical, genomic, molecular, and patient-reported data.
LMS Project Overview & Methodology
- Nationwide enrollment of LMS patients across the U.S. and Canada completed.
- Participants provided medical history, saliva/blood (liquid biopsy) samples, and tumor tissue with matched normal when available.
- Whole-exome sequencing (WES) and other genomic analyses ongoing on tumor and matched germline tissue.
- De-identified data shared globally to accelerate discovery and collaboration.
Proposed DFF-Funded Contribution
- Support biospecimen coordination, history annotation, and genomic analysis.
- Integrate genomic and molecular data with clinical and patient-reported outcomes.
- Extend the dataset by including plasma samples for ctDNA and methylation profiling.
- Translate findings into early detection, prognostic, and monitoring tools for uterine sarcomas.
Impact
- Builds the largest, most comprehensive LMS dataset for sarcoma research.
- Enables identification of genomic drivers, therapeutic targets, and molecular subtypes.
- Provides a model for studying uterine sarcomas that arise from or mimic fibroids.
- Accelerates progress from patient-partnered data collection to clinical application.
Join DFF in Partnering for Early Detection and Discovery
- Supporting biospecimen analysis, advanced molecular profiling and data sharing.
- Enabling the integration of fibroid history/uterine tumor biology into LMS research.
- Advancing early detection and personalized care for women with uterine sarcomas.
