scholarly journals Next Generation Sequencing Identifies DNA Methylation Patterns Indicative of Disease Progression in Ph+ CML

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 4526-4526
Author(s):  
Gerwin Heller ◽  
Thais Topakian ◽  
Corinna Altenberger ◽  
Sabine Cerny-Reiterer ◽  
Barbara Ziegler ◽  
...  

Abstract Ph+ chronic myeloid leukemia (CML) is a stem cell malignancy characterized by the BCR-ABL1 oncoprotein and leukemic expansion of myeloid progenitor cells. In the chronic phase (CP) of CML, clonal cells undergo myeloid differentiation and respond well to BCR-ABL1 inhibitors. In the accelerated phase (AP) and blast phase (BP) of CML, however, neoplastic cells are immature and often resistant against most BCR-ABL1-targeting drugs which is a challenge in clinical hematology. So far, little is known about molecular mechanisms underlying disease progression in CML. Methylation of CG sites around the transcriptional start site of various cancer-related genes including diverse tumor suppressor genes (referred to as methylation) is a frequently occurring epigenetic feature in neoplastic cells resulting in silencing of these genes. Although methylation is considered a critical factor in the pathogenesis of various malignant diseases including myeloid neoplasms, no comprehensive studies on the impact of methylation in the pathogenesis of CML have been conducted so far. We hypothesized that methylation may be an important mechanism regulating the transcriptional gene activity in CML cells during disease progression. Therefore, we investigated the methylome and the transcriptome of neoplastic cells in patients with CML in various phases of the disease (CP, n=15; AP, n=5; BP, n=7). Genome-wide methylation and gene expression patterns were analysed by next generation sequencing approaches using bone marrow (BM) or peripheral blood (PB) mononuclear cells (MNC) obtained from patients with CML and BM or PB MNC from control individuals. Methylation was analysed by reduced representation bisulfite sequencing (RRBS), and mRNA expression was determined by RNA-sequencing (RNA-seq). By comparing the methylome of patients who were initially diagnosed with CP-CML and who relapsed several months later (AP-CML, n=1; BC-CML, n=3), we identified a large number of genes which were methylated around their transcriptional start site in leukemic cells in patients at the time of progression compared to the time of CP-CML (range in the 4 patients: 423-1209 genes, adjusted p<0.05). These methylated genes were found to be less methylated or not methylated in BM or PB MNC of control individuals. When the methylome of all patients in all cohorts was examined and compared, more genes were found to be methylated in AP-CML and BC-CML compared to CP-CML (CP-CML, n=200; AP-CML, n=311; BC-CML, n=570). In addition, we identified several genes that were less methylated or not methylated in AP-CML and BC-CML cells compared to cells in CP-CML samples (range: 16-541 genes). Moreover, we analysed and compared the transcriptome of CP-CML, AP-CML and BC-CML samples and identified a large number of genes whose expression is downregulated in AP-CML and BC-CML samples compared to CP-CML (range: 187-382 genes). By correlating RRBS results and RNA-seq data, we found that expression of >100 of the methylated genes is downregulated in AP-CML/BC-CML compared to CP-CML suggesting that these genes may be regulated by methylation. Expression of the majority of these genes was detected in BM or PB MNC of control individuals. In silico pathway analyses and gene network analyses revealed that some methylated genes are involved in the regulation of apoptosis (e.g. CYP1B1, ZBTB16), negative regulation of cell proliferation (e.g. BTG3, VSX2) or regulation of Wnt signalling (e.g. SFRP1). Currently, a large number of CML patients are analysed gene-specifically for methylation by methylation-sensitive high resolution melting PCR and for expression of selected genes by RT-PCR in order to define prognostic patterns in CML. In summary, our results demonstrate that methylation changes are frequent events accompanying disease progression in patients with CML. These results may contribute to the identification of clinically relevant methylation patterns in CML and thus may improve prognostication. In addition, our data may reveal new epigenetic targets of therapy and may help to develop new treatment strategies for high risk or relapsing patients with CML. Disclosures Valent: Novartis: Honoraria; Pfizer: Honoraria; Ariad: Honoraria; BMS: Honoraria.

2014 ◽  
Vol 32 (11) ◽  
pp. 1166-1166 ◽  
Author(s):  
Sheng Li ◽  
Scott W Tighe ◽  
Charles M Nicolet ◽  
Deborah Grove ◽  
Shawn Levy ◽  
...  

2021 ◽  
Vol 11 ◽  
Author(s):  
Vincenza Precone ◽  
Rossella Cannarella ◽  
Stefano Paolacci ◽  
Gian Maria Busetto ◽  
Tommaso Beccari ◽  
...  

BackgroundInfertility affects about 7% of the general male population. The underlying cause of male infertility is undefined in about 50% of cases (idiopathic infertility). The number of genes involved in human spermatogenesis is over two thousand. Therefore, it is essential to analyze a large number of genes that may be involved in male infertility. This study aimed to test idiopathic male infertile patients negative for a validated panel of “diagnostic” genes, for a wide panel of genes that we have defined as “pre-diagnostic.”MethodsWe developed a next-generation sequencing (NGS) gene panel including 65 pre-diagnostic genes that were used in 12 patients who were negative to a diagnostic genetic test for male infertility disorders, including primary spermatogenic failure and central hypogonadism, consisting of 110 genes.ResultsAfter NGS sequencing, variants in pre-diagnostic genes were identified in 10/12 patients who were negative to a diagnostic test for primary spermatogenic failure (n = 9) or central hypogonadism (n = 1) due to mutations of single genes. Two pathogenic variants of DNAH5 and CFTR genes and three uncertain significance variants of DNAI1, DNAH11, and CCDC40 genes were found. Moreover, three variants with high impact were found in AMELY, CATSPER 2, and ADCY10 genes.ConclusionThis study suggests that searching for pre-diagnostic genes may be of relevance to find the cause of infertility in patients with apparently idiopathic primary spermatogenic failure due to mutations of single genes and central hypogonadism.


Blood ◽  
2011 ◽  
Vol 118 (7) ◽  
pp. 1903-1911 ◽  
Author(s):  
Luca Cecchetti ◽  
Neal D. Tolley ◽  
Noemi Michetti ◽  
Loredana Bury ◽  
Andrew S. Weyrich ◽  
...  

Abstract Megakaryocytes transfer a diverse and functional transcriptome to platelets during the final stages of thrombopoiesis. In platelets, these transcripts reflect the expression of their corresponding proteins and, in some cases, serve as a template for translation. It is not known, however, if megakaryocytes differentially sort mRNAs into platelets. Given their critical role in vascular remodeling and inflammation, we determined whether megakaryocytes selectively dispense transcripts for matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs) into platelets. Next-generation sequencing (RNA-Seq) revealed that megakaryocytes express mRNA for 10 of the 24 human MMP family members. mRNA for all of these MMPs are present in platelets with the exception of MMP-2, 14, and 15. Megakaryocytes and platelets also express mRNA for TIMPs 1-3, but not TIMP-4. mRNA expression patterns predicted the presence and, in most cases, the abundance of each corresponding protein. Nonetheless, exceptions were observed: MMP-2 protein is present in platelets but not its transcript. In contrast, quiescent platelets express TIMP-2 mRNA but only traces of TIMP-2 protein. In response to activating signals, however, platelets synthesize significant amounts of TIMP-2 protein. These results demonstrate that megakaryocytes differentially express mRNAs for MMPs and TIMPs and selectively transfer a subset of these into platelets. Among the platelet messages, TIMP-2 serves as a template for signal-dependent translation.


PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e66902 ◽  
Author(s):  
Darragh G. McArt ◽  
Philip D. Dunne ◽  
Jaine K. Blayney ◽  
Manuel Salto-Tellez ◽  
Sandra Van Schaeybroeck ◽  
...  

2020 ◽  
Author(s):  
Estela Sánchez-Herrero ◽  
Roberto Serna-Blasco ◽  
Vadym Ivanchuk ◽  
Rosario García-Campelo ◽  
Manuel Dómine ◽  
...  

Abstract Background: Despite impressive and durable responses, patients treated with ALK inhibitors (ALK-Is) ultimately progress. We investigated potential resistance mechanisms in a series of ALK-positive non-small cell lung cancer (NSCLC) patients progressing on different types of ALK-Is.Methods: 26 plasma and 2 cerebrospinal fluid samples collected upon disease progression to an ALK-I, from 24 advanced ALK-positive NSCLC patients, were analyzed by next-generation sequencing (NGS). A tool to retrieve variants at the ALK locus was developed. Results: 61 somatic mutations were detected in 14 genes: TP53, ALK, PIK3CA, SMAD4, MAP2K1 (MEK1) FGFR2, FGFR3, BRAF, EGFR, IDH2, MYC, MET, CCND3 and CCND1. Overall, We identified at least one mutation in ALK locus in 10 (38.5%) plasma samples, being the G1269A and G1202R mutations the most prevalent among patients progressing to first- and second-generation ALK-I treatment, respectively. An exon 19 deletion in EGFR was identified in a patient showing primary resistance to ALK-I. Likewise, the G466V mutation in BRAF and the F129L mutation in MAP2K1 (MEK1) were identified as the underlying mechanism of resistance in three patients who gained no or little benefit from second-line treatment with an ALK-I. Putative ALK-I resistance mutations were also found in PIK3CA and IDH2. Finally, a c-MYC gain, along with a loss of CCND1 and a FGFR3, were detected in a patient progressing on a first-line treatment with crizotinib. Conclusions: NGS analysis of liquid biopsies upon disease progression identified putative ALK-I resistance mutations in most cases, being a valuable approach to devise therapeutic strategies upon ALK-I failure.


2018 ◽  
Author(s):  
Khaled Moustafa ◽  
Joanna M. Cross

The assessment of gene expression levels is an important step toward elucidating gene functions temporally and spatially. Decades ago, typical studies were focusing on a few genes individually, whereas now researchers are able to examine whole genomes at once. The upgrade of throughput levels aided the introduction of systems biology approaches whereby cell functional networks can be scrutinized in their entireties to unravel potential functional interacting components. The birth of systems biology goes hand-in-hand with huge technological advancements and enables a fairly rapid detection of all transcripts in studied biological samples. Even so, earlier technologies that were restricted to probing single genes or a subset of genes still have their place in research laboratories. The objective here is to highlight key approaches used in gene expression analysis in plant responses to environmental stresses, or, more generally, any other condition of interest. Northern blots, RNase protection assays, and qPCR are described for their targeted detection of one or a few transcripts at a once. Differential display and serial analysis of gene expression represent non-targeted methods to evaluate expression changes of a significant number of gene transcripts. Finally, microarrays and RNA-seq (next-generation sequencing) contribute to the ultimate goal of identifying and quantifying all transcripts in a cell under conditions or stages of study. Recent examples of applications as well as principles, advantages, and drawbacks of each method are contrasted. We also suggest replacing the term "Next-Generation Sequencing (NGS)" with another less confusing synonym such as "RNA-seq", "high throughput sequencing", or "massively parallel sequencing" to avoid confusion with any future sequencing technologies.


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