Epigenetic dysregulation in myeloid malignancies

Blood ◽  
2021 ◽  
Author(s):  
Hsuan-Ting Huang ◽  
Maria Eugenia Figueroa

Epigenetic deregulation is now a well-recognized -though not yet fully understood- mechanism that contributes to the development and progression of myeloid malignancies. In the past 15 years, next generation sequencing studies have revealed patterns of aberrant DNA methylation, altered chromatin states, and mutations in chromatin modifiers across the spectrum of myeloid malignancies. Studies into the mechanisms that drive these diseases through mouse modeling have helped identify new avenues for therapeutic interventions, from initial treatment to resistant, relapsed disease. This is particularly significant when chemotherapy with cytotoxic agents remains the general standard of care. In this review, we will discuss some of the recent findings of epigenetic mechanisms and how these are informing the development of more targeted strategies for therapeutic intervention in myeloid malignancies.

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3848-3848
Author(s):  
Suzanne Kamel-Reid ◽  
Mariam Thomas ◽  
Mahadeo A. Sukhai ◽  
Dwayne L. Barber ◽  
Swati Garg ◽  
...  

Abstract Introduction. Recent genome profiling studies have increased our understanding of the mutation landscapes of myeloid malignancies. Molecular testing of AMLs (NPM1, FLT3-ITD, KIT) and MPNs (JAK2, CALR) constitute current diagnostic standard-of-care. Evidence for the diagnostic, prognostic and/or therapeutic impact of a growing set of genes and variants in myeloid malignancies allows for more accurate patient stratification and enhanced patient management. This has led to consideration of next-generation sequencing (NGS) approaches to simultaneously detect multiple variants in myeloid malignancies for use in the clinical diagnostic setting, to supplant single-gene molecular assays. We designed the Princess Margaret Advanced Genomics in Leukemia (AGILE) trial to prospectively assess the utility of NGS molecular profiling in the management of patients with myeloid malignancies. Methods. Patients for the AGILE trial are consented at the time of diagnosis using an REB approved written consent. Bone marrow or peripheral blood samples are collected at consent, accessioned within CoPath, and DNA extracted for NGS testing. NGS molecular profiling was performed using the TruSight Myeloid Sequencing Panel (TMSP; Illumina) on the MiSeq benchtop genome sequencer (Illumina) by the University Health Network Advanced Molecular Diagnostics Laboratory. The TMSP enables profiling of 54 genes (39 hotspot region; 15 complete coding region coverage) using amplicon-based library preparation and sequencing by synthesis. The TMSP detects the CALR 52 base pair deletion relevant to myelofibrosis, but not FLT3 internal tandem duplications greater than 30 base pair in size. Data were analyzed by NextGENe (v.2.3.1, SoftGenetics) and MiSeq Reporter v2.4.60. A specific script enabling alignment and calling of CALR deletions was added to the analysis to ensure there were no false negative calls. Additional testing and verification of CEBPA variants was performed by Sanger sequencing. Variants were interpreted according to Sukhai et al (Genetics in Medicine, 2015), reviewed by lab directors and reported in the Electronic Patient Record. Impact on patient care was defined as: potential for post-consolidation clinical trials; changes to frequency of monitoring; and, changes to transplant management. Cases were discussed in an interdisciplinary Genomic Tumor Board setting, at which NGS profiling data were reviewed in the context of all other diagnostic information for the patient, to determine impact on patient care. Results. Between February 11 and July 24, 2015, 162 patients were consented for AGILE; 148/162 were profiled by NGS, and to date 124/148 have been reviewed and interpreted. 62/124 (50%) of interpreted cases had a diagnosis of acute myeloid leukemia (AML); 21/124 (20%) with myeloproliferative neoplasms (MPNs); 13/124 (10%) with myelodysplastic syndromes (MDS); 6/124 (5%) with MDS/MPN; and, 15% with other hematologic malignancies. 90% of all cases profiled were informative for at least one variant (range 1-9 variants, average 3.1 variants/case). AML, MDS and MDS/MPN cases exhibited slightly more variants (3.4-4.4 variants/case) than did MPN cases (2.6 variants/case). Overall, 69% of variants were potentially actionable (Sukhai et al, 2015: 23% class 1; 8% class 2; 38% class 3), with a large fraction of cases (90/124, 72.6%) demonstrating at least one class 1 or class 3 variant. Additionally, 73/124 (58.9%) of patients exhibited actionable, class 1, variants not currently being identified by routine molecular diagnostics. In AMLs and MPNs, 88-90% of cases exhibited at least one potentially actionable variant; NGS profiling was more informative in AMLs (62% of cases exhibiting potentially actionable variants not profiled in standard of care testing, compared to 12% of MPN cases). Conclusions. We report the results of a prospective analysis of integrated NGS profiling in the context of diagnosis and management of patients with myeloid malignancies. Using a targeted NGS panel, molecular profiling of patients yielded significant information benefit over current standard approaches in 58.9% of cases analyzed, enabling potential impact on patient management. These data highlight the utility of NGS profiling to complement the initial diagnostic evaluation of myeloid malignancies. Disclosures Gupta: Incyte: Honoraria, Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees.


Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2722
Author(s):  
Greta Brezgyte ◽  
Vinay Shah ◽  
Daria Jach ◽  
Tatjana Crnogorac-Jurcevic

Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010—August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved.


2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Ryan J. Sullivan ◽  
Keith T. Flaherty

Since the initial discovery that a subset of patients with cutaneous melanoma harbor BRAF mutations, substantial research has been focused on determining the pathologic consequences of BRAF mutations, optimizing diagnostic techniques to identify these mutations, and developing therapeutic interventions to inhibit the function of this target in mutation-bearing tumors. Recently, advances have been made which are revolutionizing the standard of care for patients with BRAF mutant melanoma. This paper provides an overview on the pathogenic ramifications of mutant BRAF signaling, the latest molecular testing methods to detect BRAF mutations, and the most recent clinical data of BRAF pathway inhibitors in patients with melanoma and BRAF mutations. Finally, emerging mechanisms of resistance to BRAF inhibitors and ways of overcoming this resistance are discussed.


2018 ◽  
Vol 56 (9) ◽  
Author(s):  
Patricia J. Simner ◽  
Heather B. Miller ◽  
Florian P. Breitwieser ◽  
Gabriel Pinilla Monsalve ◽  
Carlos A. Pardo ◽  
...  

ABSTRACT The purpose of this study was to develop and optimize different processing, extraction, amplification, and sequencing methods for metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) specimens. We applied mNGS to 10 CSF samples with known standard-of-care testing (SoC) results (8 positive and 2 negative). Each sample was subjected to nine different methods by varying the sample processing protocols (supernatant, pellet, neat CSF), sample pretreatment (with or without bead beating), and the requirement of nucleic acid amplification steps using DNA sequencing (DNASeq) (with or without whole-genome amplification [WGA]) and RNA sequencing (RNASeq) methods. Negative extraction controls (NECs) were used for each method variation (4/CSF sample). Host depletion (HD) was performed on a subset of samples. We correctly determined the pathogen in 7 of 8 positive samples by mNGS compared to SoC. The two negative samples were correctly interpreted as negative. The processing protocol applied to neat CSF specimens was found to be the most successful technique for all pathogen types. While bead beating introduced bias, we found it increased the detection yield of certain organism groups. WGA prior to DNASeq was beneficial for defining pathogens at the positive threshold, and a combined DNA and RNA approach yielded results with a higher confidence when detected by both methods. HD was required for detection of a low-level-positive enterovirus sample. We demonstrate that NECs are required for interpretation of these complex results and that it is important to understand the common contaminants introduced during mNGS. Optimizing mNGS requires the use of a combination of techniques to achieve the most sensitive, agnostic approach that nonetheless may be less sensitive than SoC tools.


2016 ◽  
Author(s):  
Peizhou Liao ◽  
Glen A. Satten ◽  
Yi-juan Hu

ABSTRACTA fundamental challenge in analyzing next-generation sequencing data is to determine an individual’s genotype correctly as the accuracy of the inferred genotype is essential to downstream analyses. Some genotype callers, such as GATK and SAMtools, directly calculate the base-calling error rates from phred scores or recalibrated base quality scores. Others, such as SeqEM, estimate error rates from the read data without using any quality scores. It is also a common quality control procedure to filter out reads with low phred scores. However, choosing an appropriate phred score threshold is problematic as a too-high threshold may lose data while a too-low threshold may introduce errors. We propose a new likelihood-based genotype-calling approach that exploits all reads and estimates the per-base error rates by incorporating phred scores through a logistic regression model. The algorithm, which we call PhredEM, uses the Expectation-Maximization (EM) algorithm to obtain consistent estimates of genotype frequencies and logistic regression parameters. We also develop a simple, computationally efficient screening algorithm to identify loci that are estimated to be monomorphic, so that only loci estimated to be non-monomorphic require application of the EM algorithm. We evaluate the performance of PhredEM using both simulated data and real sequencing data from the UK10K project. The results demonstrate that PhredEM is an improved, robust and widely applicable genotype-calling approach for next-generation sequencing studies. The relevant software is freely available.


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