This Project Grant award from the National Institute of Dental and Craniofacial Research (NIDCR), under the Oral Diseases and Disorders Research program (CFDA 93.121), will fund research to develop a machine learning-based model that can accurately predict the presence of aggressive tissue phenotypes in head and neck squamous cell carcinoma (HNSCC). The $168,610 award, effective from April 2025 to March 2028, will be led by Dr. Yingci Liu at Rutgers, The State University of New Jersey. The project aims to utilize large-scale molecular data, including from the Cancer Genome Atlas (TCGA) and Database of Genotypes and Phenotypes (dbGaP), as well as a multi-institutional patient cohort, to train an algorithm capable of identifying adverse prognostic factors that may lead to disease recurrence and decreased survival in HNSCC patients. The goal is to develop a more objective tool to stratify patients into high-risk and low-risk groups for disease progression, ultimately informing treatment strategies. The project will also explore the underlying molecular pathways driving different HNSCC tissue phenotypes, potentially opening new avenues for targeted therapeutic interventions.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $168.6k | 4/7/25 |