Monoclonal B cell lymphocytosis (MBL) has been shown to be the precursor condition that precedes overt diagnosis of chronic lymphocytic leukemia (CLL). Whereas CLL is classified with greater than or ...equal to 5 × 109/L B lymphocytes in the peripheral blood, MBL is a clonal expansion of B-cells below this threshold. MBL can be further divided into high- or low-count based on whether the B-cell count is above or below 0.5 × 109/L. Approximately 10% of the population over 40 is estimated to have MBL, increasing to >50% over the age of 90. While low-count MBL is unlikely to progress, 1-2% of high-count (HC) MBL individuals progress to CLL requiring therapy per year. It is debatable if all patients with detectable MBL should be classified as an entity requiring monitoring by a hematologist, especially for low-count MBL. In addition, the diagnosis of leukemia is distressing to patients; therefore, it is important to identify HC MBL patients that are more likely to progress to disease requiring treatment and thus should be monitored more closely.
As the majority of MBL cases phenotypically resemble CLL, established prognostic markers including recurrent chromosomal aberrations, beta-2 microglobulin levels, and the mutational status of the Immunoglobulin heavy-chain variable region locus (IGHV) have been shown to predict time to treatment (TTT) and overall survival (OS) in a large retrospective study of MBL1. CLL patients can also be divided into three distinct epigenetic subtypes that reflect progressive DNA methylation changes that occurs during B cell development. These ‘epitypes’ termed low-programmed (LP), intermediate-programmed (IP), and high-programmed (HP) independently predict clinical outcomes irrespective of disease stage and treatment2. LP-CLL patients follow a generally unfavorable clinical course compared to the more indolent HP-CLL patients, while IP CLL patients display an intermediate outcome. Here we sought to determine if epitype forecasts progression to CLL and eventual clinical outcome for individuals with MBL.
We analyzed 66 individuals diagnosed with HC MBL at the Mayo Clinic with a median follow-up of 6.3 years. Developmental epitype was determined using our novel Methylation-iPLEX technique that interrogates 34 CpGs and assigns epitype using a random forest model2. Seventy-seven percent of the MBL cases were assigned to one of the three epitypes: 42.4% HP, 19.7% IP, and 15.2% LP. The residual 23% remained unclassified due to ambiguous (low confidence) epigenetic patterns or insufficient purity (Figure 1A). The overall proportion of HP and IP epitypes in MBL were significantly greater than proportions observed in CLL cohorts (P<0.01). Epitypes remained stable over time as 20/21 cases for which we obtained a high-confidence epitype classification at multiple time points remained unchanged. Epitype significantly predicted MBL individuals progressing to treatment (P=0.001) with LP individuals progressing in a median of 5.6 years (P=0.049 and P=0.0002 versus IP and HP, respectively); median was not reached in HP or IP (Figure 1B). Epitype also predicted overall survival (OS) in MBL (P=0.04), with LP individuals having a significantly shorter OS (median of 11 years versus not reached in IP and HP; P=0.056 and P=0.048 versus IP and HP, respectively).
In this study we evaluated a cohort of 66 HC MBL cases and determined that classification using developmental DNA methylation epitypes can be employed in HC MBL to aid in risk stratification. HC MBL patients classified as LP are more likely to progress to requiring treatment and have a significantly reduced OS. The epigenetic classification may help clinicians decide how closely and frequently a HC MBL individual needs to be monitored.
Figure 1: (A) Breakdown of the epigenetic subtype assigned to 66 HC MBL samples. (B) Kaplan-Meier analysis of time to treatment and (C) overall survival of MBL patients separated by epitype.
1. Parikh, S. A. et al. Outcomes of a large cohort of individuals with clinically ascertained high-count monoclonal B-cell lymphocytosis. Haematologica103, e237-e240 (2018).
2. Giacopelli, B. et al. Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia. Blood blood.2019000490 (2019). doi:10.1182/blood.2019000490
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Byrd:Ohio State University: Patents & Royalties: OSU-2S; Janssen: Consultancy, Other: Travel Expenses, Research Funding, Speakers Bureau; BeiGene: Research Funding; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; TG Therapeutics: Other: Travel Expenses, Research Funding, Speakers Bureau; Genentech: Research Funding; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel Expenses, Speakers Bureau; Ohio State University: Patents & Royalties: OSU-2S; Gilead: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding; Genentech: Research Funding; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Pharmacyclics LLC, an AbbVie Company: Other: Travel Expenses, Research Funding, Speakers Bureau; Acerta: Research Funding. Shanafelt:Patent: Patents & Royalties: US14/292,075 on green tea extract epigallocatechin gallate in combination with chemotherapy for chronic lymphocytic leukemia; Merck: Research Funding; Polyphenon E International: Research Funding; Pharmacyclics: Research Funding; Genentech: Research Funding; Hospira: Research Funding; Glaxo-SmithKline: Research Funding; Abbvie: Research Funding; Cephalon: Research Funding; Celgene: Research Funding. Parikh:Genentech: Honoraria; Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding. Kay:Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board; Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board.
The characteristic clinical heterogeneity observed in chronic lymphocytic leukemia (CLL) reflects its biological diversity and as a consequence, better understanding of the biology of this disease ...has led to the identification of a number of useful prognostic tools. Advances in massively parallel sequencing technologies have unearthed genetic and epigenetic heterogeneity and reinforced the concept that specific genetic lesions and the development of genomic complexity can modulate the pathology of CLL. In addition, DNA methylation profiling has shown that CLL patients can be grouped into at least three clinically relevant epigenetic subgroups with distinct outcomes. However, despite this explosion in knowledge, defining the prognosis of individual CLL patients remains a significant clinical challenge. Consequently, there is a need to identify prognostic tests that can provide reliable personalized risk assessments.
We have recently shown that a subset of CLL patients manifest telomere dysfunction, which drives genomic instability and clonal evolution. We went on to show an association between short, dysfunctional telomeres and ‘high-risk’ genetic lesions1,2. Importantly, longitudinal analysis confirmed that tumor cell telomere length remained remarkably stable throughout the course of the disease suggesting that the telomere length is fixed at an early point in disease pathogenesis making it a reliable predictor of both clinical progression and overall survival (OS) regardless of when the measurement is made. In this study, we generated telomere length profiles in 224 newly diagnosed, early stage CLL patients seen at the Mayo clinic in Rochester using high-throughput single telomere length analysis (HT-STELA). We then tested the ability of telomere length to predict time to treatment (TTT) and OS and compared its predictive power with DNA methylation profiling and CLL-IPI scores.
Patients with a mean telomere length inside the fusogenic range (IFR) had a significantly shorter time to treatment (P<0.0001; HR = 3.2) and OS (P = 0.0027; HR = 2.3) when compared to patients with a mean telomere length outside the fusogenic range (OFR) (Figure 1A and B). When considering epigenetic subgroups, we found a strong association between telomere length and ‘epitype’; high programmed (HP) CLL cells had significantly longer telomeres than intermediate programmed (IP), and low programmed (LP) CLL cells (P = 0.0002 and P<0.0001 respectively). Furthermore, bifurcation of the HP and IP groups into telomere length OFR and IFR subsets identified patients with distinctly different TTT (P = 0.0008; HR = 2.74) and OS (P = 0.004; HR = 2.4). 79/81 (97.5%) of the LP group had short telomere length IFR, but when we divided the LP group above and below the mean telomere length of the fusogenic range (≤/>2.17kb), patients with the shortest telomeres had a significantly worse OS (P = 0.034; HR = 2.83). Telomere length was also strongly associated with CLL-IPI score; the CLL-IPI low-risk group (CLL-IPI 1) had the longest telomeres and the CLL-IPI high-risk group (CLL-IPI 4) had the shortest telomeres (P<0.0001). More heterogeneity in telomere length was observed in the CLL-IPI 1 and 2 groups and patients with telomere length IFR in these ‘low-risk’ groups showed significantly shorter TTT (P<0.0001; HR = 4.24) and overall survival (P<0.0001; HR = 10.1) (Figure 1C and 1D). Finally, multivariate modelling, using Cox proportional hazards with forward selection, revealed that telomere length retained independent prognostic significance when CLL-IPI score was entered in the model for time to treatment (HR = 1.42; P = 0.023) and OS (HR = 1.68; P = 0.008). In conclusion, telomere length analysis provides more accurate prognostic information about the progression and outcome of CLL patients and can augment the prognostic power of the CLL-IPI for early stage CLL.
ReferencesLin TT et al. Blood. 2010;116(11):1899-907.Britt-Compton et al. Leukemia. 2012; 26(4):826-30.
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Norris:Cardiff University: Patents & Royalties: Telomere measurement patent. Shanafelt:GlaxoSmithKline: Research Funding; Genentech: Research Funding; Pharmacyclics: Research Funding; Jansen: Research Funding. Kay:Acerta: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Cytomx Therapeutics: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Infinity Pharm: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees. Fegan:Napp: Honoraria; Gilead Sciences, Inc.: Honoraria; Roche: Honoraria; Abbvie: Honoraria; Janssen: Honoraria. Baird:Cardiff University: Patents & Royalties: Telomere measurement patents. Pepper:Cardiff University: Patents & Royalties: Telomere measurement patents.
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