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Global DNA methylation analysis of chronic lymphocytic leukemia and acute myeloid leukemia reveals distinct clinically relevant biological subtypes

Giacopelli, Brian John
http://rave.ohiolink.edu/etdc/view?acc_num=osu1591114255694166

Abstract Details

2020, Doctor of Philosophy, Ohio State University, Molecular, Cellular and Developmental Biology.
Epigenetic gene regulation enables multicellular organisms to develop from a single cell. Epigenetic modifications refer to stable, yet reversable, changes to the genome that do not alter the DNA sequence. These function to control the accessibility of the genome to transcriptional machinery. DNA methylation is an epigenetic modification critical for control of development and defects are common in diseases such as cancer. Chronic lymphocytic leukemia (CLL) and acute myeloid leukemia (AML) are two of the most common leukemias in adults. Both display a high degree of clinical heterogeneity, and global DNA methylation patterns have identified distinct biological subtypes in each disease. Identification of these patterns requires methods that interrogate the methylation from across the genome. However, because these methods are often too costly and require complex data analysis to process and interpret the results making it difficult to analyze large sample cohorts, I developed a novel method, the Methylation-iPLEX (Me-iPLEX), for analyzing DNA methylation from multiple regions of the genome in a high-resolution and high throughput manner. The epigenetic subtypes observed in CLL largely reflect the natural history of the cell of origin. The efficient nature of the Me-iPLEX enabled me to interrogate the epigenetic subtypes of 1286 CLL patients and examine the prognostic significance of the epigenetic subtype across disease stages and with multiple therapies. The large sample size also enabled me to identify several biological traits associated with the subtypes as well as determining that epigenetic subtypes retained prognostic significance after stratifying by biologically related biomarkers. Past studies analyzing DNA methylation patterns in AML identified patterns associated with common genetic aberrations. These aberrations currently form the basis of our understanding of disease mechanisms and are used to predict treatment response. I analyzed Illlumina genome-wide DNA methylation arrays from 649 AMLs patients and, using an unsupervised analysis, identified a pattern that separated the AML patients into 13 distinct epigenetic subtypes. While most DNA methylation subtypes were associated with a certain recurrent mutation (or a specific combination of mutations) in the majority of patients, some subtypes were largely independent of mutations. Detailed analyses of DNA methylation patterns found common mechanisms of developmental blockage and that each subtype associated with discrete stages of myeloid differentiation. These methylation patterns also identified pathogenic mechanisms in each subtype. For example, subtypes most associated with a more stem-cell like pattern have inferior survival and upregulation of inflammatory signaling pathways. I also identified a secondary DNA methylation signature associated with FLT3-ITD mutations involving STAT motifs that identifies additional patients that utilize inflammatory signaling. The epigenetic subtype is stable at relapse in a majority of cases and those that change subtype, do so with evidence of genetic evolution. To further examine the prognostic utility of the epigenetic signature in AML, I developed Me-iPLEX assays capable of classifying the 13 subtypes and distinguishing samples with the STAT hypomethylation signature. Using these assays, I interrogated a cohort of 1377 AML patients who received similar therapy. This large cohort identified enrichment for additional genetic aberrations within the subtypes as well as evaluate the predictive power of these epigenetic classifications. I was able to identify several cases where genetic annotations fail to effectively predict patient outcomes. Through this work I analyzed global DNA methylation patterns to gain a better understanding of disease biology. I developed a novel technique for measuring DNA methylation enabling complex patterns to be interrogated in a high throughput and cost-effective manner. I utilized the Me-iPLEX to further evaluate to prognostic impact of epigenetic subtypes in CLL. I also analyzed global DNA methylation patterns in AML and identified epigenetic subtypes associated with diverse stages of development. A detailed analysis of the methylation patterns combined with gene expression analysis identified diverse disease driving mechanisms. I then again utilized the Me-iPLEX to interrogate these AML signatures in a large patient cohort to evaluate to prognostic impact of epigenetic subtypes in AML. I demonstrate in both diseases’ situations where Me-iPLEX derived epigenetic biomarkers more accurately predict outcomes after stratifying for other prognostic markers. These results highlight that DNA methylation-based markers can be used alongside current markers to improve risk stratification.
Christopher Oakes, PhD (Advisor)
John Byrd, MD (Advisor)
Ramiro Garzon, MD (Committee Member)
Kevin Coombes, PhD (Committee Member)
200 p.
Bioinformatics; Biology; Genetics; Molecular Biology; Oncology
Epigenetics; CLL; Chronic lymphocytic leukemia; AML; Acute myeloid leukemia

Recommended Citations

Citations

  • Giacopelli, B. J. (2020). Global DNA methylation analysis of chronic lymphocytic leukemia and acute myeloid leukemia reveals distinct clinically relevant biological subtypes [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1591114255694166

    APA Style (7th edition)

  • Giacopelli, Brian. Global DNA methylation analysis of chronic lymphocytic leukemia and acute myeloid leukemia reveals distinct clinically relevant biological subtypes. 2020. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1591114255694166.

    MLA Style (8th edition)

  • Giacopelli, Brian. "Global DNA methylation analysis of chronic lymphocytic leukemia and acute myeloid leukemia reveals distinct clinically relevant biological subtypes." Doctoral dissertation, Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1591114255694166

    Chicago Manual of Style (17th edition)

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This open access ETD is published by The Ohio State University and OhioLINK.