Head and neck squamous cell carcinoma (HNSCC) is a debilitating disease with few molecularly-based therapeutics. Recent genomic studies of HNSCC have identified numerous genomic alterations, but the alterations are dominated by tumor suppressor genes and untargetable oncogenes. Nevertheless, we hypothesize that novel molecular therapeutic targets are present in HNSCC and that these targets exist in parts of the data that have not been effectively analyzed. We propose to combine existing genomic data with computational approaches and in vivo pathway analysis to identify novel candidate targets in HNSCC. These candidate targets will be functionally tested in a high-throughput in vivo screening system in HNSCC lines with known genotype. Validated targets will be tested for genotype co-dependencies, and any known drug targets will be tested in preclinical xenograft models. Targets that are not currently druggable will have their pathways computationally and experimentally analyzed for additional targets that will be functionally tested. All experiments wil be performed in vivo in genomically characterized models.
We aim to generate an extensive list of functionally validated novel targets for HNSCC that will be candidates for drug development pipelines.
Head and neck cancer is the sixth most common cancer worldwide and, like all cancers, is caused by genetic alterations and mutations. We begin with knowledge about the genetic causes of this disease and use computational and experimental approaches, including functional screens, to find new ways to treat head and neck cancer. It is hoped that our work will lead to new treatment options that will improve outcomes for head and neck cancer patients.
|Gadhikar, Mayur A; Zhang, Jiexin; Shen, Li et al. (2018) CDKN2A/p16 Deletion in Head and Neck Cancer Cells Is Associated with CDK2 Activation, Replication Stress, and Vulnerability to CHK1 Inhibition. Cancer Res 78:781-797|
|Zhou, Ge; Liu, Zhiyi; Myers, Jeffrey N (2016) TP53 Mutations in Head and Neck Squamous Cell Carcinoma and Their Impact on Disease Progression and Treatment Response. J Cell Biochem 117:2682-2692|
|Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier (2016) COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS. Pac Symp Biocomput 21:21-32|
|Koire, Amanda; Katsonis, Panagiotis; Lichtarge, Olivier (2016) REPURPOSING GERMLINE EXOMES OF THE CANCER GENOME ATLAS DEMANDS A CAUTIOUS APPROACH AND SAMPLE-SPECIFIC VARIANT FILTERING. Pac Symp Biocomput 21:207-18|