Chronic lymphocytic leukemia (CLL) is a neoplasm of B-cell lymphocytes. It has a strong genetic component with 45 inherited single nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS). Using these SNPs, we computed a polygenic risk score (PRS), which is a weighted average of the risk alleles across the SNPs with the weights being the log odds ratios from SNP associations, and found that individuals in the upper quintile had a ~3-fold increased risk of CLL compared to the middle quintile (P<0.0001), providing evidence that the combination of known and common CLL susceptibility variants is one of the strongest CLL risk factors. In addition, whole genome and exome sequencing studies have recently identified over 60 recurrent somatic CLL variants or copy number alterations (CNA) and found that 88-90% of CLL cases have at least one putative driver mutation and ~44% have at least three driver mutations. However, little is known about how the inherited genetic variants interact with the tumor (at DNA and RNA level) and their contribution to tumor evolution. This application proposes to address this knowledge gap. In preliminary data from our CLL GWAS, we have evidence that a number of the CLL GWAS-discovered SNPs influence the expression levels of genes in cis (within 1-Mb window around the SNP) using RNA from whole blood or lymphoblastoid cell lines (LCL). However, because whole blood is a composition of multiple cell types, of which B-cells make up ~5-10%, B-cell specific signals are most likely missed, and gene expression from cell lines may be altered by the Epstein Barr Virus transformation used to generate LCL.
Aim 1 proposes to overcome these limitations by using RNA from sorted tumor B-cells, sorted B-cells of healthy controls, and sorted clonal B-cells from individuals with the precursor condition to CLL, monoclonal B-cell lymphocytosis (MBL), to perform expression quantitative trait locus (eQTL) analyses. Validation and experimental in vitro studies will be performed to confirm and evaluate the functional relevance of variants of interest. Next, little is known about the extent of inherited germline variants in the individuals with somatic driver mutations.
Aim 2 will address this gap to assess the relationship between germline and tumor DNA variants and to assess their effect on CLL outcomes. Finally, CLL is a heterogeneous disease with ~20% of CLL cases having a 5-year overall survival of 15-19%. There are a number of somatic variants that drive aggressive CLL disease, yet little is known about the role of inherited variants.
Aim 3 will address this gap by identifying novel inherited variants associated with CLL aggressiveness. Upon completion, we will have identified gene targets of the known CLL susceptibility SNPs, will have characterized those CLL cases with high or low burden of genomic variants and assessed the effects on CLL outcomes, and will have gained insight into the genetic contribution to aggressive CLL. Our results may provide the potential discovery of novel biomarkers for targeted therapies, reveal novel ways to subclassify CLL, and develop potential genetic counseling strategies for family members.
Project Relevance to Public Health: Inherited and acquired variants have been identified for Chronic Lymphocytic Leukemia (CLL) that predispose men and women to increased risk of CLL. This application proposes to evaluate the interaction between these inherited and acquired variants. These results will improve our understanding of the underlying biology of CLL risk and ultimately may enable identification of patients who will benefit from early screening or prevention strategies.
