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SF3B1 is a highly mutated gene in myelodysplastic syndrome (MDS) patients, related to a specific subtype and parameters of good prognosis in MDS without excess blasts. More than 40% of MDS patients carry at least two myeloid-related gene mutations but little is known about the impact of concurrent mutations on the outcome of MDS patients. In applying next-generation sequencing (NGS) with a 117 myeloid gene custom panel, we analyzed the co-occurrence of SF3B1 with other mutations to reveal their clinical, biological, and prognostic implications in very low/low- and intermediate-risk MDS patients. Mutations in addition to those of SF3B1 were present in 80.4% of patients (median of 2 additional mutations/patient, range 0–5). The most frequently mutated genes were as follows: TET2 (39.2%), DNMT3A (25.5%), SRSF2 (10.8%), CDH23 (5.9%), and ASXL1, CUX1, and KMT2D (4.9% each). The presence of at least two mutations concomitant with that of SF3B1 had an adverse impact on survival compared with those with the SF3B1 mutation and fewer than two additional mutations (median of 54 vs. 87 months, respectively: p = 0.007). The co-occurrence of SF3B1 mutations with specific genes is also linked to a dismal prognosis: SRSF2 mutations were associated with shorter overall survival (OS) than SRSF2wt (median, 27 vs. 75 months, respectively; p = 0.001), concomitant IDH2 mutations (median OS, 11 [mut] vs. 75 [wt] months; p = 0.001), BCOR mutations (median OS, 11 [mut] vs. 71 [wt] months; p = 0.036), and NUP98 and STAG2 mutations (median OS, 27 and 11 vs. 71 months, respectively; p = 0.008 and p = 0.002). Mutations in CHIP genes (TET2, DNMT3A) did not significantly affect the clinical features or outcome. Our results suggest that a more comprehensive NGS study in low-risk MDS SF3B1mut patients is essential for a better prognostic evaluation.

NGS Establishment in Multidisciplinary Healthcare (NEMHESYS) is an Erasmus+ programme with the purpose of providing qualified staff with the essential technical and bioinformatic knowledge and skills on next-generation sequencing (NGS) to be able to carry out NGS studies and perform some of the most common types of analyses. The clinical application of NGS has become easier with advancements in technologies.1 However, the investment needed to bring NGS into medical practice remains significant, with the scale of knowledge required being unprecedented at most hospitals. In addition, these novel technologies bring new challenges in translating NGS to clinical practice, at both technical and regulatory level, in terms of data management, interpretation of the results, and genetic counseling.2,3 All these aspects justify the consideration of what will be the precise role of NGS in diagnosis, risk assessment, response prediction, and treatment monitoring, today and tomorrow. Thus, to evaluate the implementation of NGS in European healthcare/research centers, a mapping survey was carried out, based on previous NGS mapping studies.

Myelodysplastic syndromes (MDS) are hematological disorders at high risk of progression to secondary acute myeloid leukemia (sAML). However, the mutational dynamics and clonal evolution underlying disease progression are poorly understood at present. To elucidate the mutational dynamics of pathways and genes occurring during the evolution to sAML, next generation sequencing was performed on 84 serially paired samples of MDS patients who developed sAML (discovery cohort) and 14 paired samples from MDS patients who did not progress to sAML during follow-up (control cohort). Results were validated in an independent series of 388 MDS patients (validation cohort). We used an integrative analysis to identify how mutations, alone or in combination, contribute to leukemic transformation. The study showed that MDS progression to sAML is characterized by greater genomic instability and the presence of several types of mutational dynamics, highlighting increasing (STAG2) and newly-acquired (NRAS and FLT3) mutations. Moreover, we observed cooperation between genes involved in the cohesin and Ras pathways in 15-20% of MDS patients who evolved to sAML, as well as a high proportion of newly acquired or increasing mutations in the chromatin-modifier genes in MDS patients receiving a disease-modifying therapy before their progression to sAML.

The iron chelator deferasirox is widely used in patients with iron overload. Patients with low-grade myelodysplastic syndromes (MDS) get transfusion dependency and need to be treated with deferasirox to avoid iron overload. Moreover, in some patients an increase in both erythroid and platelets have been observed after deferasirox therapy. However, the mechanisms involved in these clinical findings are poorly understood. The aim of this work was to analyze, in patients treated with deferasirox, the changes in the gene-expression profile after receiving the treatment. A total of 15 patients with the diagnosis of low-grade MDS were studied. Microarrays were carried out in RNA from peripheral blood before and after 14 weeks of deferasirox therapy. Changes in 1457 genes and 54 miRNAs were observed: deferasirox induced the downregulation of genes related to the Nf kB pathway leading of an overall inactivation of this pathway. In addition, the iron chelator also downregulated gamma interferon. Altogether these changes could be related to the improvement of erythroid response observed in these patients after therapy. Moreover, the inhibition of NFE2L2/NRF2, which was predicted in silico, could be playing a critical role in the reduction of reactive oxygen species (ROS). Of note, miR-125b, overexpressed after deferasirox treatment, could be involved in the reduced inflammation and increased hematopoiesis observed in the patients after treatment. In summary this study shows, for the first time, the mechanisms that could be governing deferasirox impact in vivo.

The landscape of medical sequencing has rapidly changed with the evolution of next generation sequencing (NGS). These technologies have contributed to the molecular characterization of the myelodysplastic syndromes (MDS) and chronic myelomonocytic leukaemia (CMML), through the identification of recurrent gene mutations, which are present in >80% of patients. These mutations contribute to a better classification and risk stratification of the patients. Currently, clinical laboratories include NGS genomic analyses in their routine clinical practice, in an effort to personalize the diagnosis, prognosis and treatment of MDS and CMML. NGS technologies have reduced the cost of large‐scale sequencing, but there are additional challenges involving the clinical validation of these technologies, as continuous advances are constantly being made. In this context, it is of major importance to standardize the generation, analysis, clinical interpretation and reporting of NGS data. To that end, the Spanish MDS Group (GESMD) has expanded the present set of guidelines, aiming to establish common quality standards for the adequate implementation of NGS and clinical interpretation of the results, hoping that this effort will ultimately contribute to the benefit of patients with myeloid malignancies.

Over the past few years, several large-scale studies using next-generation sequencing (NGS) of whole-genomes (WGS) and whole-exomes (WES) have defined the mutational landscape of chronic lymphocytic leukemia (CLL) [1,2,3,4]. NGS studies have also revealed the clonal heterogeneity in CLL and showed that clonal evolution contributes to the variability in clinical course among CLL patients [3]. Clonal evolution is considered a key condition in CLL progression and relapse after treatment. Most CLL cases are diagnosed during the inactive disease phase, genetic aberrations’ underlying progress in CLL activity leading to the need for therapy are poorly understood and should be explored. A large number of frequently mutated genes have been identified and several putative driver mutations likely to confer selective growth advantage to CLL tumor cells have been proposed [1,2,3]. In addition, clonal shifts between paired treatment-naïve and relapsed CLL samples have been reported due to pre-existing subclone expansion under therapeutic pressure, demonstrating that clonal evolution likely underlies CLL relapse [3, 5]. Nevertheless, there are still a limited amount of longitudinal WES studies analyzing consecutive CLL samples before treatment intervegntion [6]. The acquisition of driver mutations accompanied by selectively neutral passenger changes during disease prior to therapy influence is therefore poorly documented. Here, WES was performed on consecutive treatment-naïve samples of CLL patients from three groups with different disease course: Active disease (AD) group: patients with an active disease before the second analyzed time-point (TP2); Stable disease (SD) group: cases with a period of stable phase after diagnosis followed by progression within 3 years after; and Indolent disease (ID) group: those with a long-term stable indolent disease. Moreover, we applied a novel integrative bioinformatics tool called “Cancer Genome Interpreter” to identify driver mutations [7].

Somatic mutations in patients with myelodysplastic syndromes (MDS) undergoing allogeneic hematopoietic stem cell transplantation (HSTC) are associated with adverse outcome, but the role of chronic graft-versus-host disease (cGVHD) in this subset of patients remains unknown. We analyzed bone marrow samples from 115 patients with MDS collected prior to HSCT using next-generation sequencing. Seventy-one patients (61%) had at least one mutated gene. We found that patients with a higher number of mutated genes (more than 2) had a worse outcome (2 years overall survival [OS] 54.8% vs. 31.1%, p = 0.035). The only two significant variables in the multivariate analysis for OS were TET2 mutations (p = 0.046) and the development of cGVHD, considered as a time-dependent variable (p < 0.001), correlated with a worse and a better outcome, respectively. TP53 mutations also demonstrated impact on the cumulative incidence of relapse (CIR) (1 year CIR 47.1% vs. 9.8%, p = 0.006) and were related with complex karyotype (p = 0.003). cGVHD improved the outcome even among patients with more than 2 mutated genes (1-year OS 88.9% at 1 year vs. 31.3%, p = 0.02) and patients with TP53 mutations (1-year CIR 20% vs. 42.9%, p = 0.553). These results confirm that cGVHD could ameliorate the adverse impact of somatic mutations in patients with MDS with HSCT.

Our study aimed to analyze the presence of mutations in SF3B1 and other spliceosome-related genes in myelodysplastic syndromes with ringed sideroblasts (MDS-RS) by combining conventional Sanger and next-generation sequencing (NGS) methods, and to determine the feasibility of this approach in a clinical setting. 122 bone marrow samples from MDS-RS patients were studied. Initially, exons 14 and 15 of the SF3B1 gene were analyzed by Sanger sequencing. Secondly, they were studied by NGS covering besides SF3B1, SRSF2, U2AF1 and ZRSR2 genes. An 86% of all patients showed mutations in the SF3B1 gene. Six of them, which were not identifiable by conventional sequencing in the first diagnostic step, were revealed by NGS. In addition, 19.5% of cases showed mutations in other splicing genes: SRSF2, U2AF1, and ZRSR2. Furthermore, 8.7% of patients had two mutations in SF3B1, SF3B1 and SRSF2, and SF3B1 and U2AF1, while 5.7% showed no mutations in the four spliceosome-related genes analyzed. The combined use of conventional Sanger and NGS allows the identification of mutations in spliceosome-related genes in almost all MDS patients with RS. This two-step approach is affordable and could be useful as a complementary technique in cases with an unclear diagnosis.

[Background]: In B-cell precursor acute lymphoblastic leukaemia (B-ALL), the identification of additional genetic alterations associated with poor prognosis is still of importance. We determined the frequency and prognostic impact of somatic mutations in children and adult cases with B-ALL treated with Spanish PETHEMA and SEHOP protocols. [Methods]: Mutational status of hotspot regions of TP53, JAK2, PAX5, LEF1, CRLF2 and IL7R genes was determined by next-generation deep sequencing in 340 B-ALL patients (211 children and 129 adults). The associations between mutation status and clinicopathological features at the time of diagnosis, treatment outcome and survival were assessed. Univariate and multivariate survival analyses were performed to identify independent prognostic factors associated with overall survival (OS), event-free survival (EFS) and relapse rate (RR). [Results]: A mutation rate of 12.4% was identified. The frequency of adult mutations was higher (20.2% vs 7.6%, P=0.001). TP53 was the most frequently mutated gene (4.1%), followed by JAK2 (3.8%), CRLF2 (2.9%), PAX5 (2.4%), LEF1 (0.6%) and IL7R (0.3%). All mutations were observed in B-ALL without ETV6-RUNX1 (P=0.047) or BCR-ABL1 fusions (P<0.0001). In children, TP53mut was associated with lower OS (5-year OS: 50% vs 86%, P=0.002) and EFS rates (5-year EFS: 50% vs 78.3%, P=0.009) and higher RR (5-year RR: 33.3% vs 18.6% P=0.037), and was independently associated with higher RR (hazard ratio (HR)=4.5; P=0.04). In adults, TP53mut was associated with a lower OS (5-year OS: 0% vs 43.3%, P=0.019) and a higher RR (5-year RR: 100% vs 61.4%, P=0.029), whereas JAK2mut was associated with a lower EFS (5-year EFS: 0% vs 30.6%, P=0.035) and a higher RR (5-year RR: 100% vs 60.4%, P=0.002). TP53mut was an independent risk factor for shorter OS (HR=2.3; P=0.035) and, together with JAK2mut, also were independent markers of poor prognosis for RR (TP53mut: HR=5.9; P=0.027 and JAK2mut: HR=5.6; P=0.036). [Conclusions]: TP53mu

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, CBL, EZH2, SF3B1, SRSF2, TET2, DNMT3A, IDH1/2 and TP53. TET2 mutations predicted a more favorable drug response compared with 'wild-type' peers (pooled OR: 1.67, 95%CI: 1.14-2.44; p=0.01). In conclusion, mutations in the DNA methylation pathway, especially TET2 mutations, and low number of total mutations are associated with a better response to azacitidine.

[Background]: In the study of complex diseases using genome-wide expression data from clinical samples, a difficult case is the identification and mapping of the gene signatures associated to the stages that occur in the progression of a disease. The stages usually correspond to different subtypes or classes of the disease, and the difficulty to identify them often comes from patient heterogeneity and sample variability that can hide the biomedical relevant changes that characterize each stage, making standard differential analysis inadequate or inefficient. [Results]: We propose a methodology to study diseases or disease stages ordered in a sequential manner (e.g. from early stages with good prognosis to more acute or serious stages associated to poor prognosis). The methodology is applied to diseases that have been studied obtaining genome-wide expression profiling of cohorts of patients at different stages. The approach allows searching for consistent expression patterns along the progression of the disease through two major steps: (i) identifying genes with increasing or decreasing trends in the progression of the disease; (ii) clustering the increasing/decreasing gene expression patterns using an unsupervised approach to reveal whether there are consistent patterns and find genes altered at specific disease stages. The first step is carried out using Gamma rank correlation to identify genes whose expression correlates with a categorical variable that represents the stages of the disease. The second step is done using a Self Organizing Map (SOM) to cluster the genes according to their progressive profiles and identify specific patterns. Both steps are done after normalization of the genomic data to allow the integration of multiple independent datasets. In order to validate the results and evaluate their consistency and biological relevance, the methodology is applied to datasets of three different diseases: myelodysplastic syndrome, colorectal cancer and Alzhei

Identifying additional genetic alterations associated with poor prognosis in acute lymphoblastic leukemia (ALL) is still a challenge. Aims: To characterize the presence of additional DNA copy number alterations (CNAs) in children and adults with ALL by whole-genome oligonucleotide array (aCGH) analysis, and to identify their associations with clinical features and outcome. Array-CGH was carried out in 265 newly diagnosed ALLs (142 children and 123 adults). The NimbleGen CGH 12x135K array (Roche) was used to analyze genetic gains and losses. CNAs were analyzed with GISTIC and aCGHweb software. Clinical and biological variables were analyzed. Three of the patients showed chromothripsis (cth6, cth14q and cth15q). CNAs were associated with age, phenotype, genetic subtype and overall survival (OS). In the whole cohort of children, the losses on 14q32.33 (p = 0.019) and 15q13.2 (p = 0.04) were related to shorter OS. In the group of children without good- or poor-risk cytogenetics, the gain on 1p36.11 was a prognostic marker independently associated with shorter OS. In adults, the gains on 19q13.2 (p = 0.001) and Xp21.1 (p = 0.029), and the loss of 17p (p = 0.014) were independent markers of poor prognosis with respect to OS. In summary, CNAs are frequent in ALL and are associated with clinical parameters and survival. Genome-wide DNA copy number analysis allows the identification of genetic markers that predict clinical outcome, suggesting that detection of these genetic lesions will be useful in the management of patients newly diagnosed with ALL.

To explore novel genetic abnormalities occurring in myelodysplastic syndromes (MDS) through an integrative study combining array-based comparative genomic hybridization (aCGH) and next-generation sequencing (NGS) in a series of MDS and MDS/myeloproliferative neoplasms (MPN) patients. 301 patients diagnosed with MDS (n = 240) or MDS/MPN (n = 61) were studied at the time of diagnosis. A genome-wide analysis of DNA copy number abnormalities was performed. In addition, a mutational analysis of DNMT3A, TET2, RUNX1, TP53 and BCOR genes was performed by NGS in selected cases. 285 abnormalities were identified in 71 patients (23.6%). Three high-risk MDS cases (1.2%) displayed chromothripsis involving exclusively chromosome 13 and affecting some cancer genes: FLT3, BRCA2 and RB1. All three cases carried TP53 mutations as revealed by NGS. Moreover, in the whole series, the integrative analysis of aCGH and NGS enabled the identification of cryptic recurrent deletions in 2p23.3 (DNMT3A; n = 2.8%), 4q24 (TET2; n = 10%) 17p13 (TP53; n = 8.5%), 21q22 (RUNX1; n = 7%), and Xp11.4 (BCOR; n = 2.8%), while mutations in the non-deleted allele where found only in DNMT3A (n = 1), TET2 (n = 3), and TP53 (n = 4). These cryptic abnormalities were detected mainly in patients with normal (45%) or non-informative (15%) karyotype by conventional cytogenetics, except for those with TP53 deletion and mutation (15%), which had a complex karyotype. In addition to wellknown copy number defects, the presence of chromothripsis involving chromosome 13 was a novel recurrent change in high-risk MDS patients. Array CGH analysis revealed thepresence of cryptic abnormalities in genomic regions where MDS-related genes, such as TET2, DNMT3A, RUNX1 and BCOR, are located.

The presence of SF3B1 gene mutations is a hallmark of refractory anemia with ring sideroblasts (RARS). However, the mechanisms responsible for iron accumulation that characterize the Myelodysplastic Syndrome with ring sideroblasts (MDS-RS) are not completely understood. In order to gain insight in the molecular basis of MDS-RS, an integrative study of the expression and mutational status of genes related to iron and mitochondrial metabolism was carried out. A total of 231 low-risk MDS patients and 81 controls were studied. Gene expression analysis revealed that iron metabolism and mitochondrial function had the highest number of genes deregulated in RARS patients compared to controls and the refractory cytopenias with unilineage dysplasia (RCUD). Thus mitochondrial transporters SLC25 (SLC25A37 and SLC25A38) and ALAD genes were over-expressed in RARS. Moreover, significant differences were observed between patients with SF3B1 mutations and patients without the mutations. The deregulation of genes involved in iron and mitochondrial metabolism provides new insights in our knowledge of MDS-RS. New variants that could be involved in the pathogenesis of these diseases have been identified.

There are currently different techniques, such as CGH arrays, to study genetic variations in patients. CGH arrays analyze gains and losses in different regions in the chromosome. Regions with gains or losses in pathologies are important for selecting relevant genes or CNVs (copy-number variations) associated with the variations detected within chromosomes. Information corresponding to mutations, genes, proteins, variations, CNVs, and diseases can be found in different databases and it would be of interest to incorporate information of different sources to extract relevant information. This work proposes a multiagent system to manage the information of aCGH arrays, with the aim of providing an intuitive and extensible system to analyze and interpret the results. The agent roles integrate statistical techniques to select relevant variations and visualization techniques for the interpretation of the final results and to extract relevant information from different sources of information by applying a CBR system.