An Epigenetic Mitotic Score Tracks the Proliferative History and Capacity of CLL Samples at Diagnosis and Is Associated with Clinical Outcome

Background: DNA methylation has been extensively described to be related with gene regulation. However, recent data indicate that DNA methylation changes in repressed regions accumulate in every cell division, and thus, they can reflect the proliferative history of the cell. The evaluation of this epigenetic feature in cancer cells may provide information regarding the tumor cell biological evolution and may assist to predict the outcome of the patients.

Aims: The global aim of this study was to develop a DNA methylation-based proliferative history score and determine its possible prognostic value in chronic lymphocytic leukemia (CLL).

Methods: We used 450k methylation arrays from normal B cells subpopulations and CLLs at diagnosis. To analyze DNA methylation changes specifically in leukemic cells, we performed stringent data quality checks and corrections including FACS sorting and in silico purification of DNA methylation. Thus, we retained 67 normal B cells and 477 CLLs, comprising 140 naive-like CLLs (nCLL), 106 intermediate CLLs (iCLL) and 231 memory-like CLLs (mCLL) based on a recent epigenetic classification of cellular origin. We mapped CpGs falling in repressive regions using ChIP-Seq data of 6 histone marks from healthy B cell subpopulations and CLL patients. With the methylation levels of CpGs in repressive chromatin, we built one score per each sample which we termed Epigenetic Mitotic History (epiMH, ranging from 0 to 1). The epiMH was integrated with whole genome sequencing (WGS) and microarray expression data of the very same CLL patients (n=126). Finally, we analyzed whether epiMH was related to clinical behavior.

Results: We showed that epiMH is widely variable in normal B cells, with more advanced differentiation stages displaying the highest epiMH, presumably due to their greater accumulated proliferative history. Then, we calculated the epiMH in CLLs with different cellular origins, namely, nCLL, iCLL and mCLL, and we correlated it with different biological features. Using mutational signatures from WGS data of the same samples, we identified significant correlations of epiMH with signatures 1, 5 and 9, that have been reported to various cell division related mutational processes. Next, differential gene expression analysis between CLLs with high epiMH as compared to those with low epiMH revealed an enrichment in gene signatures related to active proliferation. Collectively, these results support the concept that the epiMH may reflect the past and present proliferative history of the cell. Finally, we postulated that the epiMH may be related with future proliferative capacity and clinical behavior. To test this, we analyzed the clinical impact of epiMH in patients from each epigenetic subgroup. An univariate analysis with epiMH as quantitative variable revealed that the higher the epiMH the worse clinical behavior. Additionally, we performed a multivariate Cox regression model for both overall survival (OS) and time to first treatment (TTT) including epiMH together with other well established prognostic factors for CLL, including age, epigenetic subgroups and the number of driver alterations. We showed that epiMH was an independent significant variable for both OS (HR=1.40, pvalue=0.03) and TTT (HR=1.41, pvalue<0.001) (HRs corresponding to 0.1 epiMH increments).

Conclusions: We have developed a proliferative history score (named epiMH) for CLL based on DNA methylation dynamics in repressed chromatin. Our data suggest that the epiMH of patients within each CLL epigenetic subgroup at diagnosis may reflect their proliferative history and capacity, and represents an independent prognostic factor.