Christopher D. Willey, MD, PhD
Associate Professor
Director UAB Kinome Core
Department of Radiation Oncology


Glioblastoma (GBM) is the most common and most deadly primary brain malignancy with median survival barely exceeding 1 year. There has been considerable effort to improve upon the dismal outcome through preclinical models, translational (e.g., TCGA) and clinical research. One major research approach has been to generate patient-derived xenografts (PDX), “tumor avatars”, that faithfully replicate patient tumor characteristics, particularly when compared to traditional preclinical research models (e.g., immortalized cell lines grown under very artificial conditions).
We and others have shown that GBM PDX are testable model systems suitable for hypothesis testing and potential clinical decision making. Since 2005, UAB has used collaborative efforts funded by 5 NIH grants/contracts to develop a large GBM PDX panel characterized by biologic, therapeutic, genomic, transcriptomic, and kinomic profiling. Many of these GBM PDX were derived from UAB treated patients with clinical and even clinicogenomic (e.g. STRATA Oncology CLIA-NGS sequencing) metadata available.

However, the large amount of data that has been produced resides in data silos that hampers integrative analyses that could drive a host of translational discovery research. Some of the more novel data types, i.e. kinomics (i.e., global kinase activity profiling), involves less commonly used data tools. Therefore, we seek to build an integrated yet expandable platform that will allow these datasets to be integrated, visualized, queried, transformed, and exported for investigator use at UAB. Since numerous investigators are using similar datasets in other diseases (both cancer and non-cancer), we anticipate successful implementation of such a platform will enhance translational research efforts across the School of Medicine.

Precision Oncology

Scientific background
  • Actionable biomarkers in patient tumors can guide therapy
  • All patients with advanced cancer are eligible for Strata tumor sequencing trial
    • No cost to patient
    • Matches eligible patients with clinical trials (limited)
  • Need computer-assisted identification of eligible patients
    • Currently using UAB i2b2 query
    • Limited data set sent to Strata to populate web-based dashboard
  • Understanding of tumor genomic landscape at UAB can generate avenues of future research
Eddy Yang
Wayne Liang
John Osborne
Alex Zotov
Dale Johnson
Zechen Chong
JC Edberg
RP Kimberly
Department of Medicine
Division of Clinical Immunology and Rheumatology
C Hendrickson
Department of Microbiology
CCTS Informatics

Multiethnics Longitudinal Study in SLE

Scientific background
  • Lupus (SLE) is a systemic autoimmune disease
  • Genetic predisposition plays a role in BOTH disease development AND progression
  • SLE more frequent in women; worse outcomes in minority patient populations
  • UAB PROFILE study (and the ancillary SLE-ESRD study) is a unique multi-ethnic patient cohort that has been studied extensively for clinical phenotype, genomics and epigenetics

The UAB Autoimmunity Data Commons

Autoimmune diseases, such as rheumatoid arthritis (RA), have both genetic and non-genetic risk factors and are variable in their degrees of severity. In RA, a subset of patients has radiographic joint damage which impacts significantly on patient quality of life. There are no robust models to predict radiographic damage in individual patients, which would greatly facilitate precision medicine in RA. To develop a model to predict radiographic joint damage in RA, we will use the following aim:
1. To create a prototype UAB Autoimmunity Data Commons (ADC) using data from the Consortium for the Longitudinal Evaluation of African Americans with Rheumatoid Arthritis (CLEAR) Registry and Repository.

Dongmei Sun
Zongliang Yue
S. Louis Bridges, Jr.