The Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia

Abstract 5

The impact of clonal heterogeneity on cancer progression in chronic lymphocytic leukemia (CLL) is not well understood. We hypothesized that the evolutionary dynamics of subclonal mutations contribute to the variations in disease tempo and response to therapy that characterize CLL. We therefore carried out a large-scale analysis of subclonal and clonal point mutations and copy-number alterations in 149 CLLs, detected by whole exome sequencing (WES) and SNP arrays.

We utilized a novel computational approach, which integrates purity and local ploidy information, to infer the cancer cell fraction (CCF) of each mutation from WES data, and to classify mutations as clonal or subclonal. Subclonal mutations were detected in 146/149 CLLs and were enriched with putative cancer driver events (P=0.001). Furthermore, higher numbers of subclonal mutations were associated with prior anti-leukemia therapy (P=0.017). Together, these results suggest that a strong extrinsic selection pressure, such as cytotoxic treatment, promotes the expansion of fitter subclones, driving them to above our detection threshold (CCF of ∼0.10).

The order of mutation acquisition may be inferred from the aggregate frequencies at which driver events are clonal or subclonal, as clonal mutations represent earlier events and subclonal later events. Of the 149 samples, we found 3 drivers (MYD88, trisomy 12, and del(13q)) that were clonal in 80–100% of samples harboring these alterations –significantly higher than other driver events (q<0.1), suggesting that they arise earlier in typical CLL development. Other drivers (e.g., ATM, TP53 and SF3B1) were often observed at subclonal frequencies, indicating that they often arise later in leukemic development.

We directly assessed the evolution of somatic mutations in 18 patients, in which data from two distant timepoints were available. Clonal evolution was observed in 11 of 18 patients (10 of 12 who received intervening treatment, but only 1 of 6 without intervening treatment, P=0.012) and confirmed that subclonal mutations (e.g., del(11q), SF3B1 and TP53) shifted towards clonality over time. Indeed, expanding subclonal mutations were enriched in putative drivers (P=0.021), suggesting that these mutations not only mark genetic evolution but also provide the fitness advantage driving it. Changes in the genetic composition of CLL cells with clonal evolution were associated with network level changes in gene expression.

If treatment-associated genetic evolution leads to expansion of a fitter subclone, we would predict a shorter time to relapse in these individuals. Indeed, presence of a detectable subclonal driver mutation was associated with a shorter time to retreatment in these 18 samples (P=0.04), indicating that the presence of subclonal drivers adversely impacts clinical outcome. In the analysis of the full cohort of 149 samples, we observed that CLLs with subclonal driver mutations were associated with shorter times from diagnosis to first therapy (P=0.001) and between sample collection to treatment (P<0.001). Moreover, in the subset of 67 of 149 patients who were treated after sampling, presence of subclonal driver mutations evident in the pre-treatment sample was associated with earlier retreatment (P=0.003). Regression models adjusting for CLL prognostic factors (IGHV status, prior therapy and high risk cytogenetics) demonstrated that the presence of a subclonal driver was an independent risk factor for earlier retreatment (adjusted hazard ratio of 4.61 (CI 1.59–13.34), P=0.005). Thus, the detection of subclonal drivers(indicative of an active evolutionary process) is associated with shorter duration of remission.

In conclusion, the analysis of clonal heterogeneity in CLL provides a glimpse into the past, present and future of a patient's disease. Through the cross-sectional analysis of 149 samples, we derived the number and genetic composition of clonal and subclonal mutations and thus uncovered footprints of the past history of CLL. Furthermore, we inferred a temporal order of genetic events implicated in CLL. Finally, our combined longitudinal and cross-sectional analyses revealed that knowledge of subclonal mutations anticipates the genetic composition of the future relapsing leukemia as well as the rapidity with which it will occur. These data challenge us to therapeutically address not only genetic targets but also their dynamic evolutionary landscape.