Why methylation is not a marker predictive of response to hypomethylating agents (original) (raw)
Related papers
King's College London, 2020
Myeloproliferative neoplasms (MPNs), which includes polycythaemia vera (PV) and essential thrombocythaemia (ET), are bone marrow disorders that give rise to a high production of red blood cells and platelets leading to thrombosis and haemorrhage. Hydroxyurea (HU), is the first line treatment for high-risk PV and ET patients since it effectively reduces the haematocrit, platelets and white blood cells counts. Mechanistically, HU acts by inhibiting the ribonucleotide reductase enzyme, blocking the cell cycle which can lead to cell death. However, additional effects of HU have also been observed which are unlikely related to this mechanism. Therefore, I hypothesize that HU has an influence on the epigenome, causing changes in gene expression which contribute to its therapeutic effects. For this, I assayed and analysed DNA methylation and gene expression from two differentially developed and clinically relevant cells types from MPN patients and a MPN mouse model, comparing samples prior to and following HU treatment. I observed that HU mainly changes gene expression and specifically affects DNA methylation at the stem cell level. Interestingly, several genes encoding transcription factors involved in haematopoiesis were also identified as potential mediators of HU effects in both species. Moreover, SPI1 was found to be upregulated and differentially methylated following HU treatment. In addition, several differentially expressed genes and differentially methylated sites were enriched for SPI1 binding sites. Thus, I propose that SPI1 is involved in the pathogenesis of the disease and in the therapeutic effect of HU. Finally, I also provide a list of candidate genes to be further investigated for their role in the therapeutic effect of HU. I would like to first thank to my supervisor Professor Rebecca Oakey for the support and trust to carry out this project. Thanks to my second supervisor Dr Reiner Schulz for the patience to teach me bioinformatics and for the critical input towards the project. Thank you to Matt, Sam and Pro for helping me in the lab. Many thanks to Professor Claire Harrison for being always helpful and supportive in the clinical aspects of this project. Thank you to the clinical team especially Samah, Claire, Yvonne and Natalia, for helping me with the patients. Thank you to all the patients that participated and made this project meaningful. I am also grateful to the funding received from Becas Chile (CONICYT) to undertake my PhD. Thank you to the funding bodies-King's Heatlh Partners and NIHR BRC at Guy's and St Thomas' NHS Foundation Trust-that supported the experimental work of this study. Thanks to the Genetic Society and King's College London for their support when presenting my work at international conferences. I greatly appreciate the support received through the collaborative work undertaken with Dr Ann Mullally at Harvard Medical School, Boston (USA). Thank you to Ann for your advice and constructive comments towards the project. Thank you to Ann's research group that helped me during my studies in Boston, especially Azu and Will that taught me everything that I needed to perform my experiments. I gratefully acknowledge the funding received from the European Hematology Association that made this study in Boston possible.
Leukemia Research, 2017
We evaluated the association of mutations in 34 candidate genes and response to azacitidine in 84 patients with myelodysplastic syndrome (MDS), with 217 somatic mutations identified by next-generation sequencing. Most patients (93%) had ≥1 mutation (mean=2.6/patient). The overall response rate to azacitidine was 42%. No clinical characteristic was associated with response to azacitidine. However, total number of mutations/patient was negatively associated with overall drug response (odds ratio [OR]: 0.56, 95% confidence interval [CI]: 0.33-0.94; p=0.028), and a positive association was found for having ≥1 mutation in a DNA methylation-related gene: TET2, DNMT3A, IDH1 and/or IDH2 (OR: 4.76, 95%CI: 1.31-17.27; p=0.017). Mutations in TP53 (hazard ratio [HR]: 3.88; 95%CI: 1.94-7.75) and EZH2 (HR: 2.50; 95%CI: 1.23-5.09) were associated with shorter overall survival. Meta-analysis of 6 studies plus present data (n=815 patients) allowed assessment of the association of drug response with mutations in 9 candidate genes: ASXL1,
2007
Promoter DNA hypermethylation and hence silencing of e.g. tumour suppressor genes is considered to be an important step in carcinogenesis and has been associated with poor outcome in patients with myelodysplastic syndromes (MDS). In contrast to many other chemotherapeutic agents, the DNA hypomethylating compound 5-azacytidine has a positive therapeutic effect in patients with high-risk myelodysplastic syndromes (MDS), however, the lack of knowledge about its mechanism of action hampers clinical development of the drug. The first aim of the thesis was to assess the pharmocodynamic properties of 5-azacytidine, and the mechanism of 5-azacytidine-induced apoptosis as well as its link with DNA methylation. Secondly, we investigated the role of gene-specific methylation status for the outcome of induction chemotherapy in a cohort of patients high-risk MDS and MDS-AML, and assessed global and gene-specific (p15INK4B) methylation patterns in another cohort of patients with low and intermedi...
The Genetic Basis of Haematological Cancers
The Genetic Basis of Haematological Cancers, 2016
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Oncotarget, 2016
Although hypomethylating therapy (HMT) is the first line therapy in higherrisk myelodysplastic syndromes (MDS), predicting response to HMT remains an unresolved issue. We aimed to identify mutations associated with response to HMT and survival in MDS. A total of 107 Korean patients with MDS who underwent HMT (57 responders and 50 non-responders) were enrolled. Targeted deep sequencing (median depth of coverage 1,623X) was performed for 26 candidate MDS genes. In multivariate analysis, no mutation was significantly associated with response to HMT, but a lower hemoglobin level (<10g/dL, OR 3.56, 95% CI 1.22-10.33) and low platelet count (<50,000/μL, OR 2.49, 95% CI 1.05-5.93) were independent markers of poor response to HMT. In the subgroup analysis by type of HMT agents, U2AF1 mutation was significantly associated with non-response to azacitidine, which was consistent in multivariate analysis (OR 14.96, 95% CI 1.67-134.18). Regarding overall survival, mutations in DNMT1 (P=0.031), DNMT3A (P=0.006), RAS (P=0.043), and TP53 (P=0.008), and two clinical variables (male-gender, P=0.002; IPSS-R H/ VH, P=0.026) were independent predicting factors of poor prognosis. For AML-free survival, mutations in DNMT3A (P<0.001), RAS (P=0.001), and TP53 (P=0.047), and two clinical variables (male-gender, P=0.024; IPSS-R H/VH, P=0.005) were independent predicting factors of poor prognosis. By combining these mutations and clinical predictors, we developed a quantitative scoring model for response to azacitidine, overall-and AML-free survival. Response to azacitidine and survival rates became worse significantly with increasing risk-scores. This scoring model can make prognosis prediction more reliable and clinically applicable.