The genetic and epigenetic etiology of progression from the precursor state to chronic lymphocytic leukemia (CLL)

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the United States and still remains incurable. Due to its impaired immune response, CLL has high number of morbidity and mortality complications including increased risk of infections and second cancers. Therefore, identifying individuals who are at markedly higher risk of developing this disease may enable future prevention strategies. Monoclonal B-cell lymphocytosis (MBL) is the precursor state to CLL. The prevalence of MBL increases with age and is found in almost a third of Caucasians older than 60 years. Although all individuals with CLL pass through the MBL precursor state, the reason why some individuals with MBL progress to CLL yet many do not is unclear. Therefore, there is a need to identify biomarkers that differentiate those MBL who will progress versus those who will remain asymptomatic. The overall goal of this application is to address this knowledge gap by evaluating genetic and epigenetic factors associated with risk of progression to CLL among an established cohort of 1,729 individuals with MBL. In Aim 1 we will analyze the polygenetic risk score (PRS) comprised of a weighted average of 41 inherited single nucleotide polymorphisms (SNPs) that have been previously identified through genome wide association studies (GWAS) of CLL with risk of progression to CLL. In Aim 2 we will perform deep targeted sequencing of 59 putative CLL driver genes to investigate if individual genes with high-impact mutations or the aggregate number of mutated genes leads to an increased risk of progression from MBL to CLL. Finally, in Aim 3 we will evaluate whether methylation signatures that classify MBL individuals into low-, intermediate-, and high-risk predict progression to CLL. At the completion of this application, we will have identified three complementary yet independent genetic and epigenetic factors that we hypothesize will be strong predictors of progression to CLL among a cohort of individuals with MBLs. Our preliminary data support our hypotheses. We have the largest cohort of individuals with MBL collected in US, putting us in an unsurpassed situation to prospectively evaluate the effect of known CLL risk factors at the precancer phase. Our integrative predictive model of all three biomarkers may change current practice guidelines and ultimately improve quality of life by reducing anxiety and distress for individuals in pre-malignant phase.