Добірка наукової літератури з теми "NGS, exome, Leukemia"

Abstract Background Recent development in sequencing technologies with deep coverage for mutation analysis has enabled the identification of clonal architecture in some cancers. RAS mutations are observed in a large proportion of MLL leukemias. Our hypothesis is that determination of RAS mutation status in MLL leukemias should provide insights into the clonal make up of this disease and clues about the nature of clones that overcome therapy. Methods We combined exome and transcriptome sequencing in 32 adult MLL leukemias and results were compared to our cohort of 48 normal karyotype (NK) AML. Exome capture and paired-end sequencing (2 x 100bp, Illumina HiSeq 2000) were performed using TruSeq (Illumina) protocols. Mean coverage was 165X for transcriptome and 42X for exome. Initial analysis was focused on 25 known AML-associated genes and excluded all other novel mutations. Average transcriptome and exome coverage for N/KRAS alleles was 287X (25-846) and 42X (9-151), respectively. Clones were defined based on the identification of N/KRAS mutations in at least 1% of the reads. Results Figure 1 shows mutation status, MLL partners and FAB classification for each MLL leukemia. No mutations were observed in NPM1, FLT3 (ITD), CEBPA (biallelic), RUNX1, DNMT3A, IDH1, KIT, BCOR, SF3B1, U2AF1 or RAD21. On average, 1 mutated gene (range: 0-4) per sample was found compared to 3 (range 0-5) in NK-AML (p < 0.0001). We observed that 13/32 MLL leukemias (which include 2 paired samples) harbored N/KRAS mutations. There were no association between RAS mutation status and MLL partner, FAB classification, age, white blood cell count and overall survival. RAS mutations were found in 15% of NK-AML which contained on average 2.3 additional mutations in leukemia-associated genes compared to only 0.3 (p<0.0001) in MLL leukemias. Excluding 2 paired relapse specimens, a total of 24 N/KRAS mutated clones were identified in 11 of the 30 MLL leukemias. The first sample included 5 clones each containing different NRAS mutations (e.g. G13R, G13D, etc.) contributing to 17, 9, 4, 2 and 2 % of the reads. Since RAS mutations are mostly heterozygous, we estimated that the contribution of each clones varied between 34 (i.e. 17% x 2) to 4%. A similar analysis revealed 4 clones in another specimen, contributing to 22, 12, 12 and 4 % of the cells. In 4 additional samples, the proportions of N/KRAS mutated clones were 1) 42, 38 and 8% 2) 92, 4 and 2 %, 3) 78 and 12% and 4) 52 and 32%, establishing that 20% (6/30) of these MLL leukemias were oligo- to polyclonal. In comparison, our NK-AML cohort of 48 patients included 7 specimens mutated for N/KRAS in which a total of 10 different clones were identified for an average of 0.2 RAS mutated clones per NK-AML versus 0.8 in MLL leukemias (p=0.007). This result further strengthens the hypothesis that RAS and MLL-fusion genes are strong collaborators in human AML. Grossmann et al recently showed that RAS mutated clones can be lost at relapse (Leukemia, 2013), possibly suggesting that other genes are at play in collaborating with MLL-fusions and causing drug resistance. To identify such genes, we further analyzed paired diagnosis and relapse samples in 2 patients. In the first patient, the KRAS mutation that was found in 66% of the cells at diagnosis was identified in all cells at relapse. In the second patient, while KRAS G12V and G12D mutations were found in 78% and 12 % of the cells at diagnosis, only the G12V clone was detected in 100% of the cells at relapse indicating in vivo clonal selection in both cases. We then performed a comparative analysis of mutated/wild type allele ratios for other coding genes. This analysis enabled us to identify a subset of mutations in candidate genes that are present at relapse in the dominant clone but that were undetectable or at lower frequency at presentation, indicating they might be specifically involved into occurrence of relapse (i.e. drug resistance). Conclusion NRAS and KRAS are mutated in 37% of MLL leukemias in this cohort. In contrast to NK-AML, these leukemias are frequently oligo- to polyclonal and contain few additional mutations suggesting that RAS activation may be sufficient to induce AML in the presence of MLL fusions. Evidence from our limited number of relapse patients, and that of others, suggests that RAS does not confer drug resistance which could be explained by novel mutations in genes that were specifically detected in the dominant clones at relapse. Disclosures: No relevant conflicts of interest to declare.

Abstract INTRODUCTION: Atypical Chronic Myeloid Leukemia (aCML) is a heterogeneous disorder belonging to the group of myelodysplastic/myeloproliferative syndromes, characterized by a poor prognosis with a median survival time of 37 months. In 2013, by applying Next Generation Sequencing (NGS) technologies on 8 aCML cases, we demonstrated the presence of a recurrent somatic mutations in the SETBP1 gene (Piazza et al, Nat Gen 2013). SETBP1 mutations were identified in approximately 30% of aCML cases. AIM: To further characterize the molecular pathogenesis of aCML and to possibly identify other recurrent lesions responsible for SETBP1 unmutated cases, we extended our initial NGS effort: we applied whole-exome and transcriptome sequencing to a total of 16 matched samples taken at onset of the disease. MATERIAL and METHODS: Whole-exome and transcriptome sequencing data were generated using an Illumina Genome Analyzer IIx following standard library-preparation protocols. Alignment to the reference GRCh37/hg19 genome was performed using BWA. Alignment data were processed using Samtools. Single nucleotide and small indel detection was performed using in-house software. Copy number analyses from whole-exome data were generated using CEQer (Piazza et al, PLoS One 2013) and gene fusions transcriptome data were screened using FusionAnalyser (Piazza et al, Nucleic Acids Res. 2012). RESULTS: The application of NGS techniques to the cohort of aCML cases led to the identification of a somatic, non-synonymous single-nucleotide mutation (chr4:g.55599321A>T) in the KIT gene in 1/16 (6%) cases. At protein level this mutation translated into the D816V variant that has been already described in several clonal disorders, such as systemic mastocytosis, gastrointestinal stromal tumors and acute myeloid leukemia. To assess whether the mutation identified by NGS was recurrent, we extended our analysis by targeted resequencing on a larger cohort of 68 aCML cases. This analysis revealed the presence of KIT mutations in 3 additional patients, thus confirming the recurrence of KIT variants in aCML. All the KIT mutations identified correspond to the D816V that is responsible for the constitutive activation of the tyrosine kinase. This finding suggests that the activation of the KIT tyrosine kinase signaling may play an important role in this subset of aCML patients. It is known from the literature that KIT D816V is highly sensitive to the tyrosine kinase inhibitor dasatinib (Schittenhelm MM, Cancer Res 2006). To test whether dasatinib is able to affect the growth of the leukemic clone in KIT mutated aCML cases, we performed ex vivo tritiated thymidine proliferation assays on bone marrow (BM) cells from one of the KIT D816V positive aCML patients in presence of either dasatinib, imatinib or vehicle alone: the proliferation assay showed that dasatinib was able to inhibit the proliferation of the leukemic clone with an IC50 of 1nM, while, as expected, neither imatinib nor vehicle alone were able to significantly impair cell growth. In line with these data, western blot with an anti- Phospho-KIT antibody on KIT+ lysates after treatment with increasing concentration of dasatinib showed that the drug was highly effective in inhibiting KIT autophosphorylation. To further confirm the inhibitory activity of dasatinib, we performed a colony assay on peripheral blood cells from a KIT D816V positive aCML patient grown in presence of increasing concentrations of the drug: treatment with 100nM dasatinib was able to completely inhibit cell growth, leading to a virtually complete absence of colonies in the D816V-positive plates. CONCLUSION: These data indicate that KIT D816V is a pro-oncogenic lesion recurrently present in aCML, albeit with low frequency (5/84, 6%) and that aCML cells bearing this mutation are highly sensitive to dasatinib, at least ex vivo. Given the very poor prognosis of this disorder, these findings suggest a new, highly efficient targeted treatment for a subset of aCML patients. Disclosures Schnittger: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Meggendorfer:MLL Munich Leukemia Laboratory: Employment.

The characterization of the landscape of genetic lesions that underlie cancer has been significantly advanced with the recent application of next-generation sequencing (NGS) technology. To define the genomic landscapes of 21 different pediatric cancer subtypes of brain tumors, solid tumors and leukemias, we analyzed >1,000 pediatric cancers and matched control tissue by whole-genome, whole-exome or transcriptome sequencing as part of the St Jude Children’s Research Hospital – Washington University Pediatric Cancer Genome Project (PCGP). Novel bioinformatics methods for integrative analysis of single-nucleotide variation (SNV), small insertion/deletion (indel), copy number alteration (CNA) and structural variation (SV) have been developed to ensure high sensitivity and accuracy, which is critical for the discovery of highly recurrent somatic lesions that have the potential for developing new cancer therapy. For example, our fusion transcript detection method CICERO has played a key role in identifying recurrent kinase fusions in 90% of Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL), a subgroup characterized by a gene expression profile similar to BCR-ABL1-positive ALL. To evaluate whether NGS is able to identify germline and somatic lesions reported by molecular diagnostic assay, we carried out a pilot clinical sequencing study that employed whole-genome, whole-exome and transcriptome sequencing of matched tumor/normal samples from 78 pediatric cancer patients. We implemented an analysis pipeline that integrates the genetic lesions from all three NGS platforms as well as a data portal that supports classification of somatic and germline lesions. We present a comparison of the sensitivity and accuracy of single-platform analysis with that of integrative multi-platform analysis in identifying somatic and germline SNVs/indels, translocation, gene fusion, CNAs, karyotype, and loss of heterozygosity. Our experience provides informative insight for the design of clinical sequencing of pediatric cancer. Disclosures No relevant conflicts of interest to declare.

Abstract INTRODUCTION: Although allogeneic Hematopoietic Stem Cell Transplantation (allo-HSCT) can accomplish apparent leukemia eradication in most patients, residual tumor cells can persist over time and eventually outgrow, resulting in clinical relapse. The genetic landscape of relapsing leukemia is often markedly different from its counterpart at diagnosis, due to clonal evolution (Ding et al, Nature, 2012) and selection of treatment-resistant variants (Vago et al, N Engl J Med, 2009). A potential solution to treat, or even prevent, relapse is to identify and specifically target mutations occurring very early in the leukemic transformation process, and thus putative hallmarks of cancer progenitors. Next-Generation Sequencing (NGS) provides the opportunity to track disease subclones during the clinical history of patients, pinpoint founder alterations and identify the mechanisms by which leukemia evades elimination. METHODS: In the present study, we combined immunogenetic analyses and NGS to detail the complex clinical history of a patient with therapy-related myelodysplasia (t-MDS), diagnosed years after sequential intensive chemotherapy for B cell Acute Lymphoblastic Leukemia (B-ALL). Leukemic cells collected at serial time-points during the patient disease history (initial diagnosis of B-ALL, first presentation of t-MDS, relapse after first allo-HSCT, relapse after second allo-HSCT) were characterized by means of genomic HLA typing, HLA allele-specific quantitative PCR and whole exome sequencing, with a minimum depth of coverage of 70x. Patient fibroblasts and peripheral blood mononuclear cells (PBMCs) collected before the occurrence of t-MDS, as well as PBMCs from the two allogeneic HSC donors, served as controls and reference exomes. Targeted resequencing of mutations of interest was performed using the Fluidigm Access Array system. Gene segments encompassing newly-identified mutations in TP53, NHEJ1 and BTNL8and their respective wild-type counterparts were cloned into plasmids, and used to design and validate specific droplet digital PCR assays, using the Bio-Rad QX100 instrument. RESULTS: A 54-year-old patient with high-risk t-MDS received two subsequent allo-HSCTs from partially-incompatible family donors, and after each transplant experienced disease recurrences. Genomic HLA typing and HLA allele-specific qPCR demonstrated that both relapses were due to mutant variants of the original leukemia that had evaded immune pressure through genomic loss of the HLA haplotype targeted by the respective donor’s T cells. Immunogenetic studies ruled out any linear relationship between the two relapses, suggesting that both might have derived from a common HLA-heterozygous progenitor. Accordingly, whole exome sequencing demonstrated direct clonal evolution from the initial presentation of t-MDS to first relapse, whereas the large majority of mutations present at second relapse were unique to the sample. Only five non-synonymous coding mutations were present in all three t-MDS samples, comprising disrupting mutations in TP53, in NHEJ1 (a key factor in DNA double strand-break repair), and in the T cell costimulatory receptor BTNL8. Of notice secondary mutations, detected only in one or two of the three disease presentations, were predicted to result in partially overlapping functional effects, and could be modeled in a conjoint DNA damage repair network, centered around the putative founder mutation in TP53. By ultra-sensitive droplet digital PCR, the same TP53 mutation was backtracked throughout the whole nine years of patient clinical history, including the phases of apparent complete remission, up to a preleukemic progenitor present in the patient bone marrow at the time of B-ALL initial diagnosis. CONCLUSIONS: Our results demonstrate that therapies, and the immune pressure of allo-HSCT in particular, can have a dramatic effect in shaping leukemia clonal evolution. Importantly, by identifying leukemia founder mutations, we might further our insights into leukemogenesis, and identify novel targets for post-transplantation diagnostics and leukemia-eradicating therapies. Disclosures Bonini: MolMed S.p.A.: Consultancy.

In the last decade the landscape in hematological diseases has been newly defined. New platforms and assays in research have been used, new pathways, variations in genes and targets for precision medicine have been detected. Next generation sequencing (NGS) contributed a lot to these important achievements. In parallel, NGS has emerged from a research tool to a diagnostic tool and is increasingly applied in routine diagnostic laboratories. Today, NGS techniques are capable of facilitating diagnostics to detect mutations, many variants of uncertain significance, translocations but also gains and losses of chromosomal material. We now have to define, which scenario will be useful for daily routine, which application should still be considered research and how we can improve in the next few years. For sure, NGS is able to reproduce findings from Sanger sequencing to detect variants in single genes as well as to apply gene panels. The latter approach is increasingly used. It will substitute Sanger sequencing in many cases. Also the investigation of gene fusions and translocations will soon be available by NGS based assays in a routine setting. So far, whole exome sequencing (WES) studies have been published from several groups on AML, MDS, CML, ALL, lymphoma entities, CLL or myeloma, in a total ~ 1,500 cases. However, the investigation by WES or even whole genome sequencing so far is not a method of choice in routine diagnostics in hematology. The drawbacks are not only the technical applicability or costs but much more important: data handling and interpretation, and data storage. This is especially true as curated data is still limited and easy-to-use software applications are needed for routine application. If big data sets shall contribute in a routine diagnostic approach, significant bioinformatic processing is mandatory. Further, in many circumstances today WES is hampered as germline material is often missing and data have to be calculated from the "tumor only" sample. Therefore, the routine use of WES to define targets for precision medicine in hematology in a timely manner has only been established in very few places worldwide. The technique itself, instruments, assays and bioinformatic tools will however have the chance to be included in routine workflows at a reasonable turn-around-time within the next 5 years. This will shift or abolish several of today´s standard techniques. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Abstract Introduction In acute myeloid leukemia (AML), the karyotype and molecular mutation profile are the strongest determinants for prognosis and biological subclassification. Yet, diagnostic analyses rely on chromosome banding technique and sequencing of a constantly growing number of genes. Aims In an era of novel high-throughput sequencing assays becoming viable options for diagnostic implementation we aimed to evaluate whether the application of targeted exome sequencing can reliably identify copy number states and molecular mutations in a single-step procedure. Patients and Methods The pilot cohort included four AML cases with a complex karyotype with known chromosomal alterations as detected by chromosome banding analysis, 24-color FISH and array CGH (12x270K microarrays, NimbleGen, Madison, WI). The size of the aberrant clone was determined by suitable probes using interphase-FISH on bone marrow smears. For sequencing analysis genomic DNA was extracted from mononuclear cells and 50 ng were processed using the TruSight Rapid Capture kit (Illumina, San Diego, CA). Sequencing was performed on a MiSeq instrument using the 2x150 bp paired-end read chemistry targeting a subset of the human exome (2,761 genes; 37,366 exons). This exome enrichment library contained >50,000 probes (7.75 Mb) focusing on disease-causing variants in specific inherited conditions (Illumina). Data analysis was performed applying default settings of the on-board MiSeq Reporter Software version 2.2.29 using the Burrows-Wheeler Aligner to align the reads against the hg19 reference genome. Further processing to delineate copy number states was performed using the ExomeCNV package. Results Each patient was analyzed in a single MiSeq run and in median 22,022,240 (range 19,233,134 - 23,507,016) reads were generated. The median coverage per target region was in the range of 74-186 reads. Coverage uniformity was assessed according to the manufacturer's recommendations. Over 98% of bases were covered at 0.12X mean coverage for each sample. Next, two data analysis pipelines were triggered, i.e. copy number states and mutation analysis. With respect to copy number alterations (CNA), in total 65 CNA were detected by chromosome banding analysis/array CGH. Of these, 21 were gains, 44 were losses. The size of the deletions ranged between 378,377 and 141,048,720 bp (median 10,731,680 bp), the size of the gains ranged between 281,608 and 46,404,876 bp (median 4,947,125 bp), respectively. In total, 63/65 (96.9%) copy number alterations were correctly identified by targeted exome sequencing. The NGS assay was able to detect copy number alterations that were present in only 23% of cells as determined by interphase-FISH. In detail, one of the deletions was homozygous with a larger deletion on the long arm of chromosome 17 (size: 1,070,162 bp) and a small intragenic deletion within the NF1 gene. This homozygous deletion was detected by array-CGH and by exome sequencing. Interestingly, the higher resolution of the exome sequencing assay in this area enabled the exact localization (exons 37 to 58) and size determination (78,415 bp) of the deletion. Overall, only 2 gains escaped detection. These were two small gained regions on a highly rearranged chr. 19. Secondly, with respect to mutation analysis, the same assay detected 19, 20, 21 and 28 mutations in the four analyzed patients. This pipeline took only putative variants into account that were not present in the control sample, were having a coverage ≥30 reads with a mutation load ≥10%, and had a confirmed COSMIC mutation entry (v66). 12/2,761 (0.4%) genes harbored mutations in at least 2/4 patients. This included genes known to be involved in leukemogenesis. TP53 mutations were detected in all four cases and all were confirmed by Sanger sequencing. Conclusions A targeted exome sequencing assay allowed to robustly assess copy number states in AML at diagnosis at a resolution greater than current conventional array CGH analyses. Moreover, exome sequencing read data also can be used to delineate mutation profiles. Thus, this workflow enabled to call gene mutations and copy number states in a single assay and is a promising option for a routine diagnostics assay in the future. The gene panel has to be further optimized by adding genes known to be mutated in hematological malignancies. More data is necessary to precisely determine the detection limit and to optimize software tools for a routine use. Disclosures: Kohlmann: MLL Munich Leukemia Laboratory: Employment. Roller:MLL Munich Leukemia Laboratory: Employment. Weissmann:MLL Munich Leukemia Laboratory: Employment. Kuznia:MLL Munich Leukemia Laboratory: Employment. Zenger:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Abstract Whole exome and transcriptome sequencing (WES and RNAseq) technologies are able to provide a comprehensive analysis of the genomic aberrations acquired by malignant cells, of their synergistic effects and functional consequences. In particular, RNAseq enables the detection of gene fusions originating from rare chromosomal translocations that have been involved in the pathogenesis of Acute Myeloid Leukemia (AML). We performed WES and RNAseq of AML patients to identify novel genetic abnormalities playing a causative role in leukemia development. We collected bone marrow or peripheral blood samples of 31 patients. Sequencing was performed using the Illumina Hiseq2000 platform. WES raw data were analysed with Whole-Exome sequencing Pipeline web tool for variants detection (WEP). The presence of gene fusions was assessed in RNAseq data with deFuse and Chimerascan. Selected genes fusions and variants were validated by Sanger sequencing. By RNAseq we identified a rare gene fusion transcript involving the BCL11B gene, which been previously suggested to play an oncogenic role in AML. The gene encodes for a zinc-finger protein participating to chromatin remodelling and regulating the differentiation and apoptosis of hematopoietic cells. The fusion was identified in a patient with poorly differentiated leukemia phenotype and unfavourable karyotypic abnormalities: 46,XX, t(2;14)(q21;q32), t(11;12)(p15;q22), who received standard chemotherapy, underwent allogeneic bone marrow transplantation and is currently in complete remission. Differently from previous data, the BCL11B translocation was associated neither with FLT3-ITD nor DNMT3A mutations. WES analysis revealed mutations in the TET2 and WTAP genes, which are known to act as co-players in the leukemic transformation. The exome data of our AML cohort identified neither INDELs nor nonsynonymous mutations in the BCL11Bgene, suggesting that the oncogenic function of BCL11B is activated by chromosomal translocations. Gene expression profiling showed a 4-fold upregulation of BCL11B transcript in the patient’s blasts, compared to 53 AML samples with no chromosomal aberrations in the 14q32 region, according to cytogenetic analysis. The increased expression of BCL11B was associated with an upregulation of potential targets including the antiapoptotic protein SPP1. Our data suggest that chromosomal translocations involving the BCL11B gene are rare events in AML and associate with somatic mutations in the malignant transformation of myeloid lineage cells, potentially by altering the differentiation and apoptotic processes. Future studies will investigate putative fusion partners of BCL11Band elucidate the biological consequences of its upregulation in AML pathogenesis. The results highlight the molecular heterogeneity of AML and the need for high-resolution sequencing analysis of leukemic samples at diagnosis in order to tailor personalized therapies. Supported by: FP7 NGS-PTL project, ELN, AIL, AIRC, PRIN, progetto Regione-Università 2010-12 (L. Bolondi). Disclosures Martinelli: Novartis: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau; Pfizer: Consultancy; ARIAD: Consultancy.

Abstract Acute erythroid leukemia (AEL) is a distinct subtype of acute myeloid leukemia (AML) characterized by predominant erythropoiesis. Currently, only few studies using next-generation sequencing were reported in AEL. To decipher the somatic mutation spectrum and discover disease-driving genes responsible for the pathogenesis of AEL, we performed whole exome-sequencing (WES) in 6 AEL and validating using targeted next generation sequencing (NGS) and Sanger sequencing in 58 AEL. From August 2003 to October 2014, a total of 158 patients fulfilling the WHO criteria for AEL were identified, comprising 91 males and 67 females. Median age was 50 years. These patients were further subclassified into 3 groups: 37 AEL after MDS, 108 de novo AEL, and 13 AML with myelodysplasia-related changes. In total, we identified 52 genes with somatic mutations in at least 2 patients, including CEBPA in 4 patients and GATA2 in 2 patients. We identified high frequencies of mutations in CEBPA (40.0%, 22/55; about 1/4 are biallelic mutations), GATA2 (22.4%, 13/58), NPM1 (15.5%, 9/58), SETBP1 (12.1%, 7/58), and U2AF1 (12.1%, 7/58), followed by TP53 (5.2%, 3/58), RUNX1 (3.5%, 2/58), TET2 (3.5%,2/58), ASXL1 (3.5%, 2/58), DNMT3A (3.5%, 2/58), SRSF2 (1.7%, 1/58) and FLT3 (1.7%, 1/58). We did not detect alterations of some of commonly mutated genes associated with AML, including IDH1, IDH2 and RAS. The results are summarized in Figure 1. To further identify the prevalence of GATA2 mutations in hematologic malignancies, we amplified and sequenced the entire coding region of GATA2 gene in 253 non-AEL AML, 40 chronic myeloid leukemia in blast crisis (CML-BC), 55 B-cell acute lymphoblastic leukemia (B-ALL), and 38 T-cell acute lymphoblastic leukemia (T-ALL). We detected GATA2 mutations in 5.5% of non-AEL AML, 15% of CML-BC, and none of B-ALL or T-ALL. The GATA2 mutations in AEL are mainly localized in ZF1 domain (P304H, D309E, A318V/T, G320S/D, L321P, and R330X) and TAD domain (Q20H). To find out the implications of GATA2 mutations in the leukemogenesis of AEL, we overexpressed the mutants of GATA2 (P304H, L321P, and R330X) in 293T cells and demonstrate that GATA2 mutant led to reduced transcriptional activity. Whereas overexpression of GATA2 mutants in mouse myeloid progenitor cell line, 32D, has no effect on the proliferative or colony formation abilities, it caused increased expression of erythroid-related antigen Ter-119 (Figure 2), b-globin and bh1-globin. Furthermore, 32D cells transfected with GATA2 mutants showed increased positivity than control cells by Benzidine staining. Taken together, our findings demonstrate that the mutatome of AEL is different from other types of AML. AEL is associated with a high frequency of mutations in GATA2 and CEBPA. GATA2 mutations resulted in a decrease of transcriptional activity and erythroid development of mouse myeloid progenitors, suggest an important role of GATA2 mutations in AEL. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures No relevant conflicts of interest to declare.

Abstract Introduction: Adult ALL represents a biologically and clinically heterogeneous group. Incidence and cure rates differ among children and adults. In adults, ALL is less common and generally carries a worse prognosis with shorter long-term survival probability. Although the remarkable progress made in the treatment of ALL in children and, with less efficacy, in adults, several ALL subtypes continue to have a poor prognosis. Aims: focus our attention on adult Ph-negative ALL pts using whole exome experiments to discover novel insights into the mechanisms involved in leukemogenesis and to develop genetic models that accurately define novel ALL subtypes based on the genomic profile of individual patients (pts). Patients and Methods: we performed the WES analysis of 72 samples of B-cell precursor ALL acute lymphoblastic leukemia (B-ALL) cases using the Illumina Hiseq2000 platform. All were adult patients (18-79 years) and were negative for Philadelphia chromosome (BCR-ABL) translocation and negative for the recurrent known molecular rearrangements (E2A-PBX, TEL, AML1-MLL-AF4). Peripheral blood and/or bone marrow samples were collected from adult B-ALL at the time of diagnosis and/or at the time of relapse. Matched samples of primary tumour (peripheral blood or bone marrow) and germline DNA from buccal swab or peripheral blood at the remission time were analyzed. MuTect and GATK tools to call mutations (Single Nucleotide Variants=SNVs and/or INDELs) were used and we selected variants with a minor allele frequency (MAF) lower than 0.05 and filtered using dbSNP142. Results: The WES analysis of the 41 Ph negative cases identified 735 point mutations and 25 mutations that occur in splicing sites in 651 genes. The average number of somatic coding mutations was 17 per case (range 1-47). 38 genes were recurrently mutated with 11 genes mutated in at least 3 cases: PAX5, PRDM12, JAK2, TTN, TP53, PTPN11, PKHD1L1, CUL3, PIEZO2, TACC2, RBBP6. The first two genes present more point mutations, in 5 pts and in 4 pts respectively. Some mutations in genes like PAX5, JAK2, TP53, PTPN11 were deeply described in acute lymphoblastic leukemic; PKHD1L1 was described mutated in one case of T-cell large granular lymphocyte leukemia; PRDM12 disruption was described in an aggressive CML case;TACC2 expression in infant ALL was described as predictor of outcome andtranscription factor and RBBP6 expression was differentially expressed in leukemic cells that overexpressed Gfi-1B gene. The alterations in the remaining genes were not previously described in ALL and/or leukemia. Using KEGG database we mapped the 651 mutated genes to detect the mostly represented pathways. The following resulted significantly enriched (p=0.0004 to p=0.006): Jak-STAT signaling pathway (11 genes), Cell Cycle (13), Dilated Cardiomyophaty (9), Hypertrophic cardiomyophaty (8), Axon Guidance (9), Calcium Signaling pathways (10), Huntington's disease (10), Wnt signaling pathway (9), Metabolic pathways (30), Pacreat Secretion (7). Preliminar analysis lead considering both SNVs and INDELs, detected totally 956 gene variations. Again the pathways mainly significantly (p=8.05e-05 to p=0.0076) affected are the Jak-STAT signaling pathway (14) and the Cell Cycle (13). Also Huntington's disease (14), Dilated Cardiomyophaty (10), Hypertrophic cardiomyophaty (9), Wnt signaling pathway (12), Metabolic pathways (40 genes), Calcium Signaling pathways (12), Metabolic pathways (40), TGF-Beta signaling pathway (8), Pacreat Secretion (8) were alterated. Prediction of protein interactions, using STRING database, generated a network with the genes mutated in more than 5 patients. Then, the nodes were clustered with K-means identifying 4 groups that contain several of our analysis variations (Fig.1). Conclusions: Point mutations are the prevalent mechanism identified in our pts cohort (75.5%). INDELs are less represented (21.5%). Altogether the identified mutations may help cluster Ph- ALL pts. Analysis of SNVs confirmed mutations in important genes known to be involved in leukemogenesis. Relevant alterations affect crucial pathways as cell cycle and Jak-STAT signaling which may be effectively targeted by currently available JAK inhibitors. Supported by: ELN, AIL, AIRC, PRIN, progetto Regione-Università 2010-12 (L. Bolondi), FP7 NGS-PTL project. Disclosures Haferlach: MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Martinelli:AMGEN: Consultancy; Ariad: Consultancy; Pfizer: Consultancy; ROCHE: Consultancy; MSD: Consultancy; BMS: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau.

Abstract Atypical Chronic Myeloid Leukemia (aCML) is a clonal disorder belonging to the myelodisplastic-myeloproliferative neoplasms, according to the WHO-2008 classification. From a clinical point of view it closely resembles the classical Chronic Myeloid Leukemia (CML), however it lacks the presence of the Philadelphia chromosome and of the BCR-ABL1 fusion gene. In recent works, we and others characterized the somatic lesions present in the aCML genome, mainly by using Next Generation Sequencing (NGS) technologies, demonstrating the presence of a large set of recurrent somatic mutations involving, among the others, SETBP1, ETNK1, ASXL1, EZH2, CBL, TET2, NRAS and U2AF1 genes. The identification of somatic variants occurring in a large number of genes clearly indicates that the genetic bases of aCML are very heterogeneous, in striking contrast with classical CML. This heterogeneity poses a great challenge to the dissection of the molecular steps required for aCML leukemogenesis. The hierarchical reconstruction of the different mutations occurring in a clonal disorder can have important biological, prognostic and therapeutic repercussions; therefore we started a project focused on the dissection of the aCML clonal evolution steps through the analysis of individual leukemic clones by methylcellulose assays in samples whose mutational status has been previously characterized by matched whole-exome sequencing. Patient CMLPh-019 was characterized by the presence of a complex mutational status, with somatic variants occurring in SETBP1, ETNK1, ASXL1 and CBL genes (Fig. 1a). Targeted resequencing analysis of individual clones revealed the presence of all the 4 variants in 44/60 (73.3%) clones; in 15/60 (25%) we detected the presence of mutated ETNK1, ASXL1 and CBL and wild-type (WT) SETBP1. Of these 15 clones, 33% carried heterozygous and 67% homozygous CBL mutations. In one clone (1.7%) we detected heterozygous ETNK1, homozygous CBL and WT sequences for ASXL1 and SETBP1, suggesting a strong selective pressure towards the acquisition of homozygous CBL mutations. Identification of homozygous CBL mutations in all the main clonal phases suggests that a significant positive selective pressure is associated with this event. Allelic imbalance analysis of CMLPh-019 exome using CEQer revealed that CBL homozygosity is caused by a somatic uniparental disomy event occurring in the telomeric region of the long arm of chromosome 11. Patient CMLPh-005 (Fig. 1b) was mutated in ASXL1, CBL and SETBP1. Targeted analysis done on 68 clones revealed a complex, branching evolution, with 63 clones carrying all the 3 variants. Of them, 47 (74.6%) had a heterozygous and 16 (25.4%) a homozygous CBL variant. Four clones (4.2%) carried ASXL1 and SETBP1 but not CBL mutations, while 1 clone was mutated in ASXL1 and CBL in absence of SETBP1 mutations, which suggests that CBL mutations occurred independently in two different subclones. Also in this case, allelic imbalance analysis of exome data revealed that CBL homozygosity was caused by a telomeric somatic uniparental disomy event. According to exome sequencing, patient CMLPh-003 carried SETBP1 mutation G870S and NRAS variant G12R. Clonal analysis confirmed the presence of SETBP1 G870S in all the clones analyzed, while heterozygous NRAS G12R mutation was detected in 67% (Fig. 1c). Notably in the remaining 33% another heterozygous NRAS variant, G12D, was detected. Retrospective reanalysis of exome data confirmed the presence of the newly identified variant, which had been previously filtered-out from exome data because of the low frequency. Patient CMLPh-013 was mutated in ASXL1, ETNK1, NRAS and SETBP1. Of the 39 clones analyzed, 34 (82.9%) showed the coexistence of ASXL1, ETNK1, NRAS and SETBP1, 4 were mutated in ASXL1, ETNK1 and NRAS and 1 in ETNK1 and NRAS, suggesting that ETNK1 and NRAS were early events, ASXL1 an intermediate one and SETBP1 a late variant (Fig. 1d). Taken globally, these data indicate that ETNK1 variants occur very early in the clonal evolution history of aCML, while ASXL1 represents an early/intermediate event and SETBP1 is often a late event. They also suggest that, in the context of aCML, there is a strong selective pressure towards the accumulation of homozygous CBL variants, as already shown in other leukemias. Figure 1. Clonal analysis of four aCML cases. The asterisks indicate hypothetical clones. Figure 1. Clonal analysis of four aCML cases. The asterisks indicate hypothetical clones. Disclosures Rea: Novartis: Honoraria; Bristol-Myers Squibb: Honoraria; Pfizer: Honoraria; Ariad: Honoraria.

Identification of recurrent mutations through next-generation sequencing (NGS) has given us a deeper understanding of the molecular mechanisms involved in chronic lymphocytic leukemia (CLL) development and progression and provided novel means for risk assessment in this clinically heterogeneous disease. In paper I, we screened a population-based cohort of CLL patients (n=364) for TP53, NOTCH1, SF3B1, BIRC3 and MYD88 mutations using Sanger sequencing, and confirmed the negative prognostic impact of TP53, SF3B1 or NOTCH1 aberrations, though at lower frequencies compared to previous studies. In paper II, we assessed the feasibility of targeted NGS using a gene panel including 9 CLL-related genes in a large patient cohort (n=188). We could validate 93% (144/155) of mutations with Sanger sequencing; the remaining were at the detection limit of the latter technique, and technical replication showed a high concordance (77/82 mutations, 94%). In paper III, we performed a longitudinal study of CLL patients (n=41) relapsing after fludarabine, cyclophosphamide and rituximab (FCR) therapy using whole-exome sequencing. In addition to known poor-prognostic mutations (NOTCH1, TP53, ATM, SF3B1, BIRC3, and NFKBIE), we detected mutations in a ribosomal gene, RPS15, in almost 20% of cases (8/41). In extended patient series, RPS15-mutant cases had a poor survival similar to patients with NOTCH1, SF3B1, or 11q aberrations. In vitro studies revealed that RPS15mut cases displayed reduced p53 stabilization compared to cases wildtype for RPS15. In paper IV, we performed RNA-sequencing in CLL patients (n=50) assigned to 3 clinically and biologically distinct subsets carrying stereotyped B-cell receptors (i.e. subsets #1, #2 and #4) and revealed unique gene expression profiles for each subset. Analysis of SF3B1-mutated versus wildtype subset #2 patients revealed a large number of splice variants (n=187) in genes involved in chromatin remodeling and ribosome biogenesis. Taken together, this thesis confirms the prognostic impact of recurrent mutations and provides data supporting implementation of targeted NGS in clinical routine practice. Moreover, we provide evidence for the involvement of novel players, such as RPS15, in disease progression and present transcriptome data highlighting the potential of global approaches for the identification of molecular mechanisms contributing to CLL development within prognostically relevant subgroups.

Leukemias are a cancer type which affects the leukocytes progenitor cells. These malignancies are highly heterogeneous in terms of molecular mechanisms involved in their onset and progression. Heterogeneity can be further observed within the same subgroup of disease at the inter-individual level, being reflected by different clinical outcomes and responses to treatment in different patients. Unfortunately, the exact leukemia aetiology is still poorly understood and consequently also related prevention, diagnostic, prognostic and follow up methods remain mainly unidentified. Therefore, early-diagnosis, together with specifically tailored approaches to leukemia treatment, still represents a key point in determining patients’ health, life quality and estimated life. Several efforts have been started to improve diagnosis, treatment and disease monitoring of leukemia. In this regard, the work presented in my PhD thesis is part of an international project, named “NGS-PTL: Next Generation Sequencing platform for targeted Personalized Therapy of Leukemia”, whose objective is the development of technologies for the diagnosis and prognosis of haematological cancers. According to the project’s objective, my thesis work aims to identify sequence variants from Whole Exome Sequencing data for the acute types of leukemia, to be used as potential biomarkers to improve therapeutic interventions and for personalize treatments. The work describes the setup and application of a bioinformatic pipeline able to identify the somatic mutations in the leukemia patients and the driver carrier genes, again with the result obtained by its application on all the samples of the project. The setup of the pipeline has required the identification of a set of tools to apply to Cancer sequencing data. In particular, selection of dedicated software to perform the initial pre-processing of the data guarantees the use of sequencing data of high quality and ensures that the subsequent analysis will be performed on well-generated data. Moreover, the selection of MuTect as variant caller has allowed us to overcome specific problems related to the heterogeneity of Cancer sample. The application of these software has led us to the identification of a large and reliable set of somatic variants to be evaluated for the identifications of new biomarkers and driver genes. Then, the interpretation of the somatic variants has required the use of specific database and resources to correctly interpret them and eventually to correlate the mutations with the driving or the development of the leukemia. Using the available biological knowledge, we were able to select likely highly damaging variants, some of which already connected with leukemia in cancer-related sources (COSMIC, ICGC and CIViC). At the end, the discover of genes that drives the development of the disease was performed using three statistical tools on the set of annotated mutations for each leukemia type, leading to the identification of a total of 32 biomarkers. In conclusion, the discovery of potential novel biomarkers, again with the additional biological information provided by the specific resources applied has demonstrated the importance of the application of NGS in the study of Leukemic patients.