David Frankhouser

Epigenetics Meets Genetics in Acute Myeloid Leukemia: Clinical Impact of a Novel Seven-Gene Score

PURPOSE Molecular risk stratification of acute myeloid leukemia (AML) is largely based on genetic markers. However, epigenetic changes, including DNA methylation, deregulate gene expression and may also have prognostic impact. We evaluated the clinical relevance of integrating DNA methylation and genetic information in AML. METHODS Next-generation sequencing analysis of methylated DNA identified differentially methylated regions (DMRs) associated with prognostic mutations in older (≥ 60 years) cytogenetically normal (CN) patients with AML (n = 134). Genes with promoter DMRs and expression levels significantly associated with outcome were used to compute a prognostic gene expression weighted summary score that was tested and validated in four independent patient sets (n = 355). RESULTS In the training set, we identified seven genes (CD34, RHOC, SCRN1, F2RL1, FAM92A1, MIR155HG, and VWA8) with promoter DMRs and expression associated with overall survival (OS; P ≤ .001). Each gene had high DMR methylation and lower expression, which were associated with better outcome. A weighted summary expression score of the seven gene expression levels was computed. A low score was associated with a higher complete remission (CR) rate and longer disease-free survival and OS (P < .001 for all end points). This was validated in multivariable models and in two younger (< 60 years) and two older independent sets of patients with CN-AML. Considering the seven genes individually, the fewer the genes with high expression, the better the outcome. Younger and older patients with no genes or one gene with high expression had the best outcomes (CR rate, 94% and 87%, respectively; 3-year OS, 80% and 42%, respectively). CONCLUSION A seven-gene score encompassing epigenetic and genetic prognostic information identifies novel AML subsets that are meaningful for treatment guidance.

Methylation-dependent loss of RIP3 expression in cancer represses programmed necrosis in response to chemotherapeutics.

Receptor-interacting protein kinase-3 (RIP3 or RIPK3) is an essential part of the cellular machinery that executes “programmed” or “regulated” necrosis. Here we show that programmed necrosis is activated in response to many chemotherapeutic agents and contributes to chemotherapy-induced cell death. However, we show that RIP3 expression is often silenced in cancer cells due to genomic methylation near its transcriptional start site, thus RIP3-dependent activation of MLKL and downstream programmed necrosis during chemotherapeutic death is largely repressed. Nevertheless, treatment with hypomethylating agents restores RIP3 expression, and thereby promotes sensitivity to chemotherapeutics in a RIP3-dependent manner. RIP3 expression is reduced in tumors compared to normal tissue in 85% of breast cancer patients, suggesting that RIP3 deficiency is positively selected during tumor growth/development. Since hypomethylating agents are reasonably well-tolerated in patients, we propose that RIP3-deficient cancer patients may benefit from receiving hypomethylating agents to induce RIP3 expression prior to treatment with conventional chemotherapeutics.

The dual epigenetic role of PRMT5 in acute myeloid leukemia: gene activation and repression via histone arginine methylation.

Changes in the enzymatic activity of protein arginine methyltransferase (PRMT) 5 have been associated with cancer; however, the protein’s role in acute myeloid leukemia (AML) has not been fully evaluated. Here, we show that increased PRMT5 activity enhanced AML growth in vitro and in vivo while PRMT5 downregulation reduced it. In AML cells, PRMT5 interacted with Sp1 in a transcription repressor complex and silenced miR-29b preferentially via dimethylation of histone 4 arginine residue H4R3. As Sp1 is also a bona fide target of miR-29b, the miR silencing resulted in increased Sp1. This event in turn led to transcription activation of FLT3, a gene that encodes a receptor tyrosine kinase. Inhibition of PRMT5 via sh/siRNA or a first-in-class small-molecule inhibitor (HLCL-61) resulted in significantly increased expression of miR-29b and consequent suppression of Sp1 and FLT3 in AML cells. As a result, significant antileukemic activity was achieved. Collectively, our data support a novel leukemogenic mechanism in AML where PRMT5 mediates both silencing and transcription of genes that participate in a ‘yin-yang’ functional network supporting leukemia growth. As FLT3 is often mutated in AML and pharmacologic inhibition of PRMT5 appears feasible, the PRMT5–miR-29b–FLT3 network should be further explored as a novel therapeutic target for AML.

Methods for high-throughput MethylCap-Seq data analysis

BackgroundAdvances in whole genome profiling have revolutionized the cancer research field, but at the same time have raised new bioinformatics challenges. For next generation sequencing (NGS), these include data storage, computational costs, sequence processing and alignment, delineating appropriate statistical measures, and data visualization. Currently there is a lack of workflows for efficient analysis of large, MethylCap-seq datasets containing multiple sample groups.MethodsThe NGS application MethylCap-seq involves the in vitro capture of methylated DNA and subsequent analysis of enriched fragments by massively parallel sequencing. The workflow we describe performs MethylCap-seq experimental Quality Control (QC), sequence file processing and alignment, differential methylation analysis of multiple biological groups, hierarchical clustering, assessment of genome-wide methylation patterns, and preparation of files for data visualization.ResultsHere, we present a scalable, flexible workflow for MethylCap-seq QC, secondary data analysis, tertiary analysis of multiple experimental groups, and data visualization. We demonstrate the experimental QC procedure with results from a large ovarian cancer study dataset and propose parameters which can identify problematic experiments. Promoter methylation profiling and hierarchical clustering analyses are demonstrated for four groups of acute myeloid leukemia (AML) patients. We propose a Global Methylation Indicator (GMI) function to assess genome-wide changes in methylation patterns between experimental groups. We also show how the workflow facilitates data visualization in a web browser with the application Anno-J.ConclusionsThis workflow and its suite of features will assist biologists in conducting methylation profiling projects and facilitate meaningful biological interpretation.

Prognostic and biologic significance of DNMT3B expression in older patients with cytogenetically normal primary acute myeloid leukemia.

DNMT3B encodes a DNA methyltransferase implicated in aberrant epigenetic changes contributing to leukemogenesis. We tested whether DNMT3B expression, measured by NanoString nCounter assay, associates with outcome, gene and microRNA expression and DNA methylation profiles in 210 older (⩾60 years) adults with primary, cytogenetically normal acute myeloid leukemia (CN-AML). Patients were dichotomized into high versus low expressers using median cut. Outcomes were assessed in the context of known CN-AML prognosticators. Gene and microRNA expression, and DNA methylation profiles were analyzed using microarrays and MethylCap-sequencing, respectively. High DNMT3B expressers had fewer complete remissions (CR; P=0.002) and shorter disease-free (DFS; P=0.02) and overall (OS; P<0.001) survival. In multivariable analyses, high DNMT3B expression remained an independent predictor of lower CR rates (P=0.04) and shorter DFS (P=0.04) and OS (P=0.001). High DNMT3B expression associated with a gene expression profile comprising 363 genes involved in differentiation, proliferation and survival pathways, but with only four differentially expressed microRNAs (miR-133b, miR-148a, miR-122, miR-409-3p) and no differential DNA methylation regions. We conclude that high DNMT3B expression independently associates with adverse outcome in older CN-AML patients. Gene expression analyses suggest that DNMT3B is involved in the modulation of several genes, although the regulatory mechanisms remain to be investigated to devise therapeutic approaches specific for these patients.

Preclinical Investigation of the Novel Histone Deacetylase Inhibitor AR-42 in the Treatment of Cancer-Induced Cachexia

BACKGROUND Cancer cachexia is a debilitating condition that impacts patient morbidity, mortality, and quality of life and for which effective therapies are lacking. The anticachectic activity of the novel HDAC inhibitor AR-42 was investigated in murine models of cancer cachexia. METHODS The effects of AR-42 on classic features of cachexia were evaluated in the C-26 colon adenocarcinoma and Lewis lung carcinoma (LLC) models. Effects on survival in comparison with approved HDAC inhibitors (vorinostat, romidepsin) were determined. The muscle metabolome and transcriptome (by RNA-seq), as well as serum cytokine profile, were evaluated. Data were analyzed using mixed effects models, analysis of variance, or log-rank tests. All statistical tests were two-sided. RESULTS In the C-26 model, orally administered AR-42 preserved body weight (23.9±2.6 grams, AR-42-treated; 20.8±1.3 grams, vehicle-treated; P = .005), prolonged survival (P < .001), prevented reductions in muscle and adipose tissue mass, muscle fiber size, and muscle strength and restored intramuscular mRNA expression of the E3 ligases MuRF1 and Atrogin-1 to basal levels (n = 8). This anticachectic effect, confirmed in the LLC model, was not observed after treatment with vorinostat and romidepsin. AR-42 suppressed tumor-induced changes in inflammatory cytokine production and multiple procachexia drivers (IL-6, IL-6Rα, leukemia inhibitory factor, Foxo1, Atrogin-1, MuRF1, adipose triglyceride lipase, uncoupling protein 3, and myocyte enhancer factor 2c). Metabolomic analysis revealed cachexia-associated changes in glycolysis, glycogen synthesis, and protein degradation in muscle, which were restored by AR-42 to a state characteristic of tumor-free mice. CONCLUSIONS These findings support further investigation of AR-42 as part of a comprehensive therapeutic strategy for cancer cachexia.

Toward personalized therapy in AML: in vivo benefit of targeting aberrant epigenetics in MLL-PTD-associated AML.

Toward personalized therapy in AML: in vivo benefit of targeting aberrant epigenetics in MLL -PTD-associated AML

Enrichment-based DNA methylation analysis using next-generation sequencing: sample exclusion, estimating changes in global methylation, and the contribution of replicate lanes

BackgroundDNA methylation is an important epigenetic mark and dysregulation of DNA methylation is associated with many diseases including cancer. Advances in next-generation sequencing now allow unbiased methylome profiling of entire patient cohorts, greatly facilitating biomarker discovery and presenting new opportunities to understand the biological mechanisms by which changes in methylation contribute to disease. Enrichment-based sequencing assays such as MethylCap-seq are a cost effective solution for genome-wide determination of methylation status, but the technical reliability of methylation reconstruction from raw sequencing data has not been well characterized.MethodsWe analyze three MethylCap-seq data sets and perform two different analyses to assess data quality. First, we investigate how data quality is affected by excluding samples that do not meet quality control cutoff requirements. Second, we consider the effect of additional reads on enrichment score, saturation, and coverage. Lastly, we verify a method for the determination of the global amount of methylation from MethylCap-seq data by comparing to a spiked-in control DNA of known methylation status.ResultsWe show that rejection of samples based on our quality control parameters leads to a significant improvement of methylation calling. Additional reads beyond ~13 million unique aligned reads improved coverage, modestly improved saturation, and did not impact enrichment score. Lastly, we find that a global methylation indicator calculated from MethylCap-seq data correlates well with the global methylation level of a sample as obtained from a spike-in DNA of known methylation level.ConclusionsWe show that with appropriate quality control MethylCap-seq is a reliable tool, suitable for cohorts of hundreds of patients, that provides reproducible methylation information on a feature by feature basis as well as information about the global level of methylation.

Quality Control for RNA-Seq (QuaCRS): An Integrated Quality Control Pipeline

QuaCRS (Quality Control for RNA-Seq) is an integrated, simplified quality control (QC) system for RNA-seq data that allows easy execution of several open-source QC tools, aggregation of their output, and the ability to quickly identify quality issues by performing meta-analyses on QC metrics across large numbers of samples in different studies. It comprises two main sections. First is the QC Pack wrapper, which executes three QC tools: FastQC, RNA-SeQC, and selected functions from RSeQC. Combining these three tools into one wrapper provides increased ease of use and provides a much more complete view of sample data quality than any individual tool. Second is the QC database, which displays the resulting metrics in a user-friendly web interface. It was designed to allow users with less computational experience to easily generate and view QC information for their data, to investigate individual samples and aggregate reports of sample groups, and to sort and search samples based on quality. The structure of the QuaCRS database is designed to enable expansion with additional tools and metrics in the future. The source code for not-for-profit use and a fully functional sample user interface with mock data are available at http://bioserv.mps.ohio-state.edu/QuaCRS/.

Comparison of insertional RNA editing in Myxomycetes.

RNA editing describes the process in which individual or short stretches of nucleotides in a messenger or structural RNA are inserted, deleted, or substituted. A high level of RNA editing has been observed in the mitochondrial genome of Physarum polycephalum. The most frequent editing type in Physarum is the insertion of individual Cs. RNA editing is extremely accurate in Physarum; however, little is known about its mechanism. Here, we demonstrate how analyzing two organisms from the Myxomycetes, namely Physarum polycephalum and Didymium iridis, allows us to test hypotheses about the editing mechanism that can not be tested from a single organism alone. First, we show that using the recently determined full transcriptome information of Physarum dramatically improves the accuracy of computational editing site prediction in Didymium. We use this approach to predict genes in the mitochondrial genome of Didymium and identify six new edited genes as well as one new gene that appears unedited. Next we investigate sequence conservation in the vicinity of editing sites between the two organisms in order to identify sites that harbor the information for the location of editing sites based on increased conservation. Our results imply that the information contained within only nine or ten nucleotides on either side of the editing site (a distance previously suggested through experiments) is not enough to locate the editing sites. Finally, we show that the codon position bias in C insertional RNA editing of these two organisms is correlated with the selection pressure on the respective genes thereby directly testing an evolutionary theory on the origin of this codon bias. Beyond revealing interesting properties of insertional RNA editing in Myxomycetes, our work suggests possible approaches to be used when finding sequence motifs for any biological process fails.