LGL leukemia results from a clonal expansion of cytotoxic T lymphocytes with a terminal effector memory (TEMRA) phenotype. LGL leukemia patients have multiple clinical phenotypes including chronic neutropenia, pure red cell aplasia, and rheumatoid arthritis. The major focus of this proposal is to identify and understand how genomic changes contribute to the pathogenesis of LGL leukemia as well as normal TEMRA biology. Our collaborative group has recently completed whole genome sequencing of matched LGL clone and normal saliva samples from three patients. An additional 48 genome pairs will be sequenced by the time this proposal would be funded. Preliminary analysis of these three genome pairs indicate an average of 8,000 somatic DNA substitutions as well as evidence of copy number variation and other genome structural changes. Our goal is to understand how these genome changes contribute to the genesis and pathological manifestations of LGL leukemia.
In Aim 1, we focus on analyzing the protein coding changes as well as identifying the numerous other genomic changes with less rapidly definable function. In order to gain a more complete understanding of how non-coding genome changes contribute to LGL we will then conduct a series of ENCODE type experiments to identify important genomic regions in LGL (Aim 2). We will then screen our large patient registry to determine the prevalence of these mutations in LGL leukemia and integrate the newly identified interaction data and mutation data into our network model of LGL leukemia survival pathways. In addition, we will correlate mutations with clinical parameters to determine their usefulness in predicting treatment responses to current therapies and individual disease phenotypes (Aim 3).
The proposed study has the potential to impact human health by identifying genomic changes associated with LGL leukemia. Currently there are no curative therapies for LGL leukemia and often multiple therapies must be attempted in order to find an effective therapy. Additionally, these studies represent a unique opportunity to identify critical regulatory interactions in normal CD8+ terminal effector memory cells that are normally difficult to study, but have important functions in the control of viral infections and cancer. We strongly believe that the identification of key mutations in LGL will lead to both predictive markers of treatment response and new targets for therapeutic intervention. The assembled multidisciplinary team is uniquely suited to integrate genomic data (Hardison) with network modeling (Albert) that combined with the extensive knowledge of LGL leukemia biology and an extensive patient registry (Loughran) ensures success for work that is proposed.
