Comparing malignant monocytosis across the updated WHO and ICC classifications of 2022

ABSTRACT

The World Health Organization (WHO) classification of hematolymphoid tumors and the International Consensus Classification (ICC) of 2022 introduced major changes to the definition of chronic myelomonocytic leukemia (CMML). To assess its qualitative and quantitative implications for patient care, we started with 3311 established CMML cases (according to WHO 2017 criteria) and included 2130 oligomonocytosis cases fulfilling the new CMML diagnostic criteria. Applying both 2022 classification systems, 356 and 241 of oligomonocytosis cases were newly classified as myelodysplastic (MD)-CMML (WHO and ICC 2022, respectively), most of which were diagnosed as myelodysplastic syndrome (MDS) according to the WHO 2017 classification. Importantly, 1.5 times more oligomonocytosis cases were classified as CMML according to WHO 2022 than based on ICC, because of different diagnostic criteria. Genetic analyses of the newly classified CMML cases showed a distinct mutational profile with strong enrichment of MDS-typical alterations, resulting in a transcriptional subgroup separated from established MD and myeloproliferative CMML. Despite a different cytogenetic, molecular, immunophenotypic, and transcriptional landscape, no differences in overall survival were found between newly classified and established MD-CMML cases. To the best of our knowledge, this study represents the most comprehensive analysis of routine CMML cases to date, both in terms of clinical characterization and transcriptomic analysis, placing newly classified CMML cases on a disease continuum between MDS and previously established CMML.

The clinical and genomic landscape of patients with DDX41 variants identified during diagnostic sequencing

Deleterious germ line variants in DDX41 are a common cause of genetic predisposition to hematologic malignancies, particularly myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML). Targeted next-generation sequencing was performed in a large cohort of sequentially recruited patients with myeloid malignancy, covering DDX41 as well as 30 other genes frequently mutated in myeloid malignancy. Whole genome transcriptome sequencing data was analyzed on a separate cohort of patients with a range of hematologic malignancies to investigate the spectrum of cancer predisposition. Altogether, 5737 patients with myeloid malignancies were studied, with 152 different DDX41 variants detected. Multiple novel variants were detected, including synonymous variants affecting splicing as demonstrated by RNA-sequencing. The presence of a somatic DDX41 variant was highly associated with DDX41 germ line variants in patients with MDS and AML, and we developed a statistical approach to incorporate the co-occurrence of a somatic DDX41 variant into germ line variant classification at a very strong level (as per the American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines). Using this approach, the MDS cohort contained 108 of 2865 (3.8%) patients with germ line likely pathogenic/pathogenic (LP/P) variants, and the AML cohort 106 of 2157 (4.9%). DDX41 LP/P variants were markedly enriched in patients with AML and MDS compared with those in patients with myeloproliferative neoplasms, B-cell neoplasm, and T- or B-cell acute lymphoblastic leukemia. In summary, we have developed a framework to enhance DDX41 variant curation as well as highlighted the importance of assessment of all types of genomic variants (including synonymous and multiexon deletions) to fully detect the landscape of possible clinically relevant DDX41 variants.

Interplay of TP53 allelic state, blast count, and complex karyotype on survival of patients with AML and MDS

Several clinical and genetic factors impact overall survival (OS) in myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML), including complex karyotype (CK), TP53 allelic state, and blast count. We analyzed the interplay of these factors by performing Cox regression analysis and by determining the frequency of TP53 single-hit (sh) and double-hit (dh) events and OS in MDS (n = 747) with <5% blasts, with ≥5% but <10% blasts, and ≥10% but <20% blasts and AML (n = 772). MDS with <5% blasts showed the best outcome, followed by with ≥5% but <10% blasts, and ≥10% but <20% blasts, and AML (median OS: 75, 54, 27, and 18 months, respectively). The same hierarchy was observed when each subgroup was divided into TP53sh, TP53dh, and without TP53 alterations (alt), revealing a dismal outcome of TP53dh in all subgroups (17, 10, 8, and 1 month[s], respectively). MDS with <5% blasts differed from the other subgroups by showing predominantly TP53sh (76% of TP53alt cases), and by an independent adverse impact of CK on OS (hazard ratio, 5.2; P < .001). The remaining subgroups displayed many similarities, with TP53dh found at high frequencies (67%, 91%, and 71%, respectively) and only TP53alt but not CK independently influencing OS, and TP53dh showing the strongest influence. When the total cohort was split based on TP53 state, only the blast count and not CK had an independent adverse impact on OS in all subgroups. Thus, TP53dh is the strongest prognostic factor, further supporting its integration into risk stratification guidelines and classification as a separate entity. However, the blast count also influences OS independent of TP53 state, whereas CK plays a minor prognostic role.

Prevalence and Therapeutic Implications of Clonal Hematopoiesis of Indeterminate Potential in Young Patients With Stroke

BACKGROUND

Undetermined stroke etiology hampers optimal secondary prevention in a large proportion of young patients. We explored whether genetic screening for clonal hematopoiesis of indetermined potential (CHIP), a novel risk factor for stroke, could identify patients with myeloid precursor lesions or covert myeloid neoplasm requiring specific treatment.

METHODS

We performed targeted sequencing on 56 genes recurrently mutated in hematologic neoplasms in a prospective cohort of patients with acute brain ischemia between 18 and 60 years. CHIP prevalence was compared with age-matched healthy controls from the Nijmegen Biomedical Study (n=1604) and the UK Biobank (n=101 678). Patients with suspicion of high-risk CHIP or myeloid neoplasm were invited for further hematologic evaluation.

RESULTS

We included 248 consecutive patients (39% women) of whom 176 (71%) had cryptogenic stroke etiology. Fifty-one (21%) patients had CHIP, 3-fold more than in the general population (7.7% versus 2.6% for the Nijmegen Biomedical Study and 11.9% versus 4.1% for UK Biobank; P<0.001 for both). Patients with CHIP were older (median [interquartile range], 53 [50-59] versus 51 [41-56] years; P<0.001), had higher carotid intima-media thickness (0.68 [0.58-0.80] versus 0.59 [0.51-0.73] mm; P=0.009), and had higher burden of atherosclerosis (29.4% versus 16.7%; P=0.04). We invited 11 patients (4.4%) for further hematologic assessment, which in 7 led to the diagnosis of high-risk CHIP and in 2 to the new diagnosis of a myeloproliferative neoplasm with indication for cytoreductive therapy.

CONCLUSIONS

Using genetic screening for myeloid disorders in patients with stroke of predominantly undetermined etiology, we found a 3-fold higher CHIP prevalence than in the general population. We identified high-risk CHIP and previously covert myeloproliferative neoplasms as potential stroke etiologies in 4.4% and 1% of patients, respectively. Our findings demonstrate the diagnostic and therapeutic yield of genetic screening in young patients with stroke. Future studies should investigate the role of CHIP for stroke recurrence and optimal secondary prevention.

Artificial intelligence in hematological diagnostics: Game changer or gadget?

The future of clinical diagnosis and treatment of hematologic diseases will inevitably involve the integration of artificial intelligence (AI)-based systems into routine practice to support the hematologists' decision making. Several studies have shown that AI-based models can already be used to automatically differentiate cells, reliably detect malignant cell populations, support chromosome banding analysis, and interpret clinical variants, contributing to early disease detection and prognosis. However, even the best tool can become useless if it is misapplied or the results are misinterpreted. Therefore, in order to comprehensively judge and correctly apply newly developed AI-based systems, the hematologist must have a basic understanding of the general concepts of machine learning. In this review, we provide the hematologist with a comprehensive overview of various machine learning techniques, their current implementations and approaches in different diagnostic subfields (e.g., cytogenetics, molecular genetics), and the limitations and unresolved challenges of the systems.

How artificial intelligence might disrupt diagnostics in hematology in the near future

Artificial intelligence (AI) is about to make itself indispensable in the health care sector. Examples of successful applications or promising approaches range from the application of pattern recognition software to pre-process and analyze digital medical images, to deep learning algorithms for subtype or disease classification, and digital twin technology and in silico clinical trials. Moreover, machine-learning techniques are used to identify patterns and anomalies in electronic health records and to perform ad-hoc evaluations of gathered data from wearable health tracking devices for deep longitudinal phenotyping. In the last years, substantial progress has been made in automated image classification, reaching even superhuman level in some instances. Despite the increasing awareness of the importance of the genetic context, the diagnosis in hematology is still mainly based on the evaluation of the phenotype. Either by the analysis of microscopic images of cells in cytomorphology or by the analysis of cell populations in bidimensional plots obtained by flow cytometry. Here, AI algorithms not only spot details that might escape the human eye, but might also identify entirely new ways of interpreting these images. With the introduction of high-throughput next-generation sequencing in molecular genetics, the amount of available information is increasing exponentially, priming the field for the application of machine learning approaches. The goal of all the approaches is to allow personalized and informed interventions, to enhance treatment success, to improve the timeliness and accuracy of diagnoses, and to minimize technically induced misclassifications. The potential of AI-based applications is virtually endless but where do we stand in hematology and how far can we go?

Complex landscape of alternative splicing in myeloid neoplasms

Myeloid neoplasms are characterized by frequent mutations in at least seven components of the spliceosome that have distinct roles in the process of pre-mRNA splicing. Hotspot mutations in SF3B1, SRSF2, U2AF1 and loss of function mutations in ZRSR2 have revealed widely different aberrant splicing signatures with little overlap. However, previous studies lacked the power necessary to identify commonly mis-spliced transcripts in heterogeneous patient cohorts. By performing RNA-Seq on bone marrow samples from 1,258 myeloid neoplasm patients and 63 healthy bone marrow donors, we identified transcripts frequently mis-spliced by mutated splicing factors (SF), rare SF mutations with common alternative splicing (AS) signatures, and SF-dependent neojunctions. We characterized 17,300 dysregulated AS events using a pipeline designed to predict the impact of mis-splicing on protein function. Meta-splicing analysis revealed a pattern of reduced levels of retained introns among disease samples that was exacerbated in patients with splicing factor mutations. These introns share characteristics with “detained introns,” a class of introns that have been shown to promote differentiation by detaining pro-proliferative transcripts in the nucleus. In this study, we have functionally characterized 17,300 targets of mis-splicing by the SF mutations, identifying a common pathway by which AS may promote maintenance of a proliferative state.

Molecular characterization of a second myeloid neoplasm developing after treatment for acute myeloid leukemia

Therapy-related myeloid neoplasms (tMN) following successful treatment of acute myeloid leukemia (AML) are rare and poorly characterized. To evaluate the presence of a common ancestral clone, we performed whole-exome sequencing of 25 patients at AML diagnosis, tMN diagnosis (tMDS: 13; tAML: 12), and matched remission samples, identifying 607 mutations affecting 504 different genes (46 recurrently mutated). Number of mutations was higher in tAML vs. tMDS cases (median 19 vs 13 mutations, p = 0.05). Focusing on 24 genes commonly mutated in hematological malignancies, 19/25 (76%) patients were found to share mutations between AML and tMN, mostly affecting epigenetic modifiers (21/32; 66%), splicing factors (6/32; 19%), and chromatin modifiers (3/32; 9%). Analysis of remission samples identified 13 persisting mutations in 10/22 patients, affecting DNMT3A (n = 6), TET2 (n = 5), IDH1 and SRSF2 (n = 1, each). Comparison of cytogenetics revealed that 9/12 patients with a normal karyotype (NK) in AML harbored aberrations in tMN, four aberrant AML cases presented with NK in tMN, four other patients showed unrelated cytogenetic aberrations. Our study provides novel insights into the pathogenesis of tMN, hypothesizing the presence of a common ancestral clone in AML and tMN. Mutations mostly affected epigenetic modifiers, which have previously been linked to clonal hematopoiesis.

Abstract 4259: Defining subtle cancer subtypes using the darkest DNA

The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can classify the fine subtypes of disease that are otherwise gnomically indistinguishable. We introduce a novel stochastic regularization, ReVeal, that empowers ML to classify subtle cancer subtypes even from the same ‘cell of origin’. Analogous to heritability, implicitly defined on whole genome, we use predictability (F1 score) definable on portions of the genome. In an effort to classify cancer subtypes using dark-matter DNA, we applied ReVeal to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, dark. ReVeal allowed the classification of all segments of the genome better than standard ML algorithms. The non-genic, non-coding and the dark-matter had the highest F1 scores with dark-matter having the highest level of predictability (F1 = 0.78). Based on ReVeal’s predictability of different sectors of the genome, dark matter contains signal significant enough to classify fine subtypes of disease. The agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention.

Citation Format: Laxmi Parida, Claudia Haferlach, Kahn Rhrissorrakrai, Filippo Utro, Chaya Levovitz, Kern Wolfgang, Niroshan Nadarajah, Stephan Hutter, Manja Meggendorfer, Wencke Walter, Constance Baer, Torsten Haferlach. Defining subtle cancer subtypes using the darkest DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4259.

Identification of prognostic parameters in CLL with no abnormalities detected by chromosome banding and FISH analyses

Chronic Lymphocytic Leukaemia (CLL) is a heterogeneous disease with a clinical course dependent on cytogenetic features. However, in 15-20% of cases both chromosome banding and fluorescence in situ hybridisation analyses do not show any kind of abnormality. With the aim to identify dependable molecular prognostic factors in this subgroup, we performed a comprehensive analysis on 171 patients including genomic arrays (comparative genomic hybridisation and single nucleotide polymorphism), immunoglobulin heavy chain variable region genes (IGHV) status, flow cytometry and targeted sequencing. Genomic arrays detected 73 aberrations in 39 patients (23%). Most frequently, patients had 1 aberration (25/171; 15%), while 14 patients (8%) had at least 2 aberrations. IGHV status was unmutated in 53/171 (31%) patients. SF3B1 was the most frequently mutated gene (26/171 patients; 15%), followed by NOTCH1 (15/171; 9%). At univariate analysis, an adverse impact on time to treatment (TTT) was evident for SF3B1 mutations, higher white blood cell count, higher CLL cells percentage by flow cytometry, CD38 positivity, IGHV unmutated status and at least 2 genomic array abnormalities. Of these, SF3B1 mutations, CLL cells percentage, IGHV unmutated status and number of genomic array aberrations maintained their impact in multivariate analysis. In conclusion, by integrating genomic and molecular data, we identified patients at higher risk for treatment need.

Abstract 3275: Comparison of somatic variant interpretation results between human experts and automated classification using AMP/ASCO/CAP guidelines

Introduction: Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories have to consider. Deciding how to weigh each type of evidence is difficult, and standards are needed. In 2017, AMP/ASCO/CAP released a joint consensus recommendation proposing a four-tiered system to categorize somatic sequence variations based on their clinical significance in cancer diagnosis, prognosis, and/or therapeutic.

Aim: Evaluate how the AMP/ASCO/CAP guidelines compare to an accredited laboratory approach to variant classification and explore the variance in the use and interpretation of the pathogenicity criteria. Identifying disease-contributory variants for various human genetic diseases will greatly improve diagnosis and facilitate development of therapies.

Patients and Methods: 50 cases with myeloid malignancies were selected, analyzed either with a 26 genes myeloid panel (ThunderStorm Target Enrichment library; Raindance, Billerica, MA) or a 63 genes panel (TruSeq Custom Amplicon; Illumina, San Diego, CA). Alignment and Variant calling was performed with JSI SeqPilot (JSI Medisys, Ettenheim, Germany). Molecular geneticists in the lab annotated each variant manually in a 3-tier system (pathogenic, uncertain significance, benign) given the lab's SOP for variant classification. Each variant was checked against the following databases: COSMIC (v76), ClinVar, dbSNP (v147) and IARC TP53 (r17). Population frequency information was extracted from ExAC. Mutation impact prediction was performed using PolyPhen-2, SIFT and VEP.

Results: Among the 50 cases 681 variants were classified during routine workup according to SOPs accredited by EN ISO15189, subsequent to the elimination of sequencing artefacts. 405 were classified as benign, 52 with variant of uncertain significance (VUS) and 224 as pathogenic. Using the computed classification yielded 377 Tier IV (Benign), 184 Tier III (Unknown clinical significance), 93 Tier II (Potential clinical significance) and 27 Tier I (Strong clinical significance). To be able to compare, Tier I and II were binned. In 80% (542/681) of instances both approaches are concordant. 4 variants classified diagnostically discrepant (3 VUS to Tier I/II, 1 benign variant to Tier II) (Table 1). Manual interrogation revealed these were difficult variants with scarce public data and poor concordance of prediction tools.

Conclusion: Systematic evaluation of an automated classification based on AMP/ASCO/CAP with manual curated data found a concordance rate of 80%. The automated approach seems to be more cautious, thus the bias towards more VUS calls, which is preferable to miscalls. The guidelines seem to yield results sufficiently good for clinical use, especially for labs with little experience in variant classification and a big step forward regarding standardization.

Citation Format: Niroshan Nadarajah, Manja Meggendorfer, Claudia Haferlach, Wolfgang Kern, Torsten Haferlach. Comparison of somatic variant interpretation results between human experts and automated classification using AMP/ASCO/CAP guidelines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3275.

Selective inhibition of BCL-2 is a promising target in patients with high-risk myelodysplastic syndromes and adverse mutational profile

Somatic mutations in genes such as ASXL1, RUNX1, TP53 or EZH2 adversely affect the outcome of patients with myelodysplastic syndromes (MDS). Since selective BCL-2 inhibition is a promising treatment strategy in hematologic malignancies, we tested the therapeutic impact of ABT-199 on MDS patient samples bearing an adverse mutational profile. By gene expression, we found that the level of pro-apoptotic BIM significantly decreased during MDS disease progression in line with an acquired resistance to cell death. Supporting the potential for ABT-199 treatment in MDS, high-risk MDS patient samples specifically underwent cell death in response to ABT-199 even when harbouring mutations in ASXL1, RUNX1, TP53 or EZH2. ABT-199 effectively targeted the stem- and progenitor compartment in advanced MDS harbouring mutations in ASXL1, RUNX1, TP53 or EZH2 and even proved effective in patients harbouring more than one of the defined high-risk mutations. Moreover, we utilized the protein abundance of BCL-2 family members in primary patient samples using flow cytometry as a biomarker to predict ABT-199 treatment response. Our data demonstrate that ABT-199 effectively induces apoptosis in progenitors of high-risk MDS/sAML despite the presence of adverse genetic mutations supporting the notion that pro-apoptotic intervention will hold broad therapeutic potential in high-risk MDS patients with poor prognosis.

Using reciprocity to derive the far field displacements due to buried sources and scatterers

It is shown that elastodynamic reciprocity provides a simpler approach for deriving the far-field displacements due to buried (sub-surface) sources in a half-space, compared with integral transform techniques. The auxiliary fields employed in this approach are the fields associated with the reflection of plane waves of the three possible polarisations, and the required far field can be expressed in terms of these well-known auxiliary fields. The crucial step in this approach is to evaluate a surface integral involving cross-work terms between an outgoing spherical wavefront and the auxiliary fields consisting of incident and reflected plane waves. This integral can be evaluated by the stationary phase approximation for the two-dimensional case, or by a generalisation of this approximation for the three-dimensional case. Although this evaluation involves several distinct contributions, the final result is shown to be very simple, and it can be interpreted as a generalisation of a known result for the one-dimensional case, whereby the net contribution arises only from counter-propagating waves of the same mode. The results derived for a buried force are extended to the case of buried cracks by exploiting the body force equivalents for displacement discontinuities across a surface.

Abstract 2707: Targeted RNA sequencing reveals thus far unknown diagnostically relevant fusion partners confirming its diagnostic potential

Introduction: The genomic landscape of hematological malignancies has been resolved mainly based on whole exome and whole genome sequencing, primarily targeting gene mutations. In addition to mutations, gene fusions have also been identified as therapeutic targets, impressively shown e.g. for BCR-ABL1 and ETV6-PDGFRB. Even though fluorescence in situ hybridization (FISH) is the current gold standard in fusion detection, it is by concept limited to the selected genes it is applied to. In contrast, targeted RNA sequencing is a valuable hypothesis-free approach to discover all possible fusion junctions in a single reaction.

Aim: Explore the value of targeted RNA sequencing in a routine diagnostic work up.

Patients and Methods: We sequenced 134 cases in parallel to our routine diagnostics workflow using chromosome banding analysis (CBA), FISH and real-time quantitative (RQ-PCR). Targeted RNA sequencing was performed on the NextSeq 500 using the TruSight RNA Fusion panel (Illumina, San Diego, CA) consisting of 7690 probes covering 507 genes known to be involved in gene fusions. Analysis was performed with the RNA-Seq Alignment App v1.2.0 (BaseSpace Sequence Hub) using Star for Alignment and Manta for gene fusion calling with default parameters (Illumina, San Diego, CA).

Results: In 127 of 134 (95%) cases the results of FISH, subsequently confirmed with RT-PCR were also picked up by RNA Seq. This included diagnostically highly relevant fusions like BCR-ABL1 (n=8), KMT2A rearrangements (n=7), PML-RARA (n=4), and ETV6 and NPM1 rearrangements. In addition to the confirmation of orthogonal results, we were able to identify novel rare gene fusions, which we subsequently confirmed by RQ-PCR. This included immediately targetable fusions like TNIP1-PDGFRB and ETV6-EFL1, ETV6-FOXO1, IRF2PB1-RARA, RARA-SAE1).

Conclusion: 1) In the vast majority of instances targeted RNA sequencing confirmed results obtained by FISH/RT-PCR and in addition discovered new rare gene fusions 2) Targetable genetic aberrations were identified, which were not identifiable by chromosome banding analysis but would now lead to more individualized treatment. 3) Thus, targeted RNA sequencing may be a valuable tool in routine diagnostics and for patients with rearrangements unresolved by standard techniques, also paving the way to precision medicine in a considerable number of patients.

Citation Format: Niroshan Nadarajah, Manja Meggendorfer, Torsten Haferlach, Wolfgang Kern, Claudia Haferlach. Targeted RNA sequencing reveals thus far unknown diagnostically relevant fusion partners confirming its diagnostic potential [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2707. doi:10.1158/1538-7445.AM2017-2707

Epigenetically induced ectopic expression of UNCX impairs the proliferation and differentiation of myeloid cells

We here describe a leukemogenic role of the homeobox gene UNCX, activated by epigenetic modifications in acute myeloid leukemia (AML). We found the ectopic activation of UNCX in a leukemia patient harboring a t(7;10)(p22;p14) translocation, in 22 of 61 of additional cases [a total of 23 positive patients out of 62 (37.1%)], and in 6 of 75 (8%) of AML cell lines. UNCX is embedded within a low-methylation region (canyon) and encodes for a transcription factor involved in somitogenesis and neurogenesis, with specific expression in the eye, brain, and kidney. UNCX expression turned out to be associated, and significantly correlated, with DNA methylation increase at its canyon borders based on data in our patients and in archived data of patients from The Cancer Genome Atlas. UNCX-positive and -negative patients displayed significant differences in their gene expression profiles. An enrichment of genes involved in cell proliferation and differentiation, such as MAP2K1 and CCNA1, was revealed. Similar results were obtained in UNCX-transduced CD34⁺ cells, associated with low proliferation and differentiation arrest. Accordingly, we showed that UNCX expression characterizes leukemia cells at their early stage of differentiation, mainly M2 and M3 subtypes carrying wild-type NPM1. We also observed that UNCX expression significantly associates with an increased frequency of acute promyelocytic leukemia with PML-RARA and AML with t(8;21)(q22;q22.1); RUNX1-RUNX1T1 classes, according to the World Health Organization disease classification. In summary, our findings suggest a novel leukemogenic role of UNCX, associated with epigenetic modifications and with impaired cell proliferation and differentiation in AML.

Application of an NGS-based 28-gene panel in myeloproliferative neoplasms reveals distinct mutation patterns in essential thrombocythaemia, primary myelofibrosis and polycythaemia vera

Molecular routine diagnostics for BCR-ABL1-negative myeloproliferative neoplasms (MPN) currently focusses on mutations in JAK2, CALR and MPL. In recent years, recurrent mutations in MPNs have been identified in several other genes. We here present the validation of a next generation sequencing (NGS)-based 28-gene panel and its use in MPN. We analysed the mutation status of 28 genes in 100 MPN patients [40 essential thrombocythaemia (ET), 30 primary myelofibrosis (PMF), 30 polycythaemia vera (PV)] and found two or more mutated genes in 53 patients. Moreover, significantly more mutated splicing genes (SF3B1, SRSF2 and U2AF1) were present in PMF (0·60 mutated genes/patient) compared to ET (0·15) while no mutations in splicing genes were found in PV. Additionally, chromatin modification genes (ASXL1 and EZH2) were frequently mutated in PMF patients (0·50) and, to a significantly lesser extent, in ET (0·13) and PV (0·07). Contrarily, DNA methylation genes (DNMT3A, IDH1, IDH2 and TET2) were mutated most often in PV (0·5) and less frequently in ET (0·23) and PMF (0·20), but without reaching statistical significance. Our results demonstrate the feasibility and utility of NGS-based panel diagnostics for MPN. With 53% of the patients bearing two or more mutated genes, their prognostic relevance needs further studies.

Abstract LB-329: Enhancing the resolution and accelerating the pace of translational fusion characterization in oncology by RNA sequencing

Chromosomal rearrangements are common markers of cancer progression across a wide range of cancer types, and therefore, identification of fusion transcripts in cancer biopsies may have potential to provide tumor-specific insight toward diagnosis, prognosis and precision treatment. Currently, routine methods for fusion detection using fluorescent in-situ hybridization (FISH) provide a low-resolution view of the aberrant fusion transcript. We describe an RNA-Seq approach designed to survey cancer fusions in a single assay by selectively enriching the cancer transcriptome using probes that target the coding regions of over 1385 cancer-associated genes.

We tested the performance of the 1385 gene, RNA-Seq Pan-Cancer panel on RNA extracted from 47 patient-derived samples from brain, sarcoma and leukemia, including blood, bone marrow, and formalin-fixed paraffin-embedded (FFPE) samples. Each sample harbored at least one orthogonally verified gene fusion transcript, previously confirmed by FISH or Reverse Transcriptase PCR (RT-PCR). RNA-Seq libraries were prepared from 10-100 ng of total RNA from blood or bone marrow and 20-200 ng total RNA from FFPE tissue and subsequently enriched by hybridization to the Pan-Cancer panel. All samples yielded sufficient library and were sequenced with 76 base-pair paired-end reads on an Illumina MiSeq at 8 samples per flow cell (∼3 million reads per sample). Sequencing data was analyzed using RNA-Seq with STAR aligner and Manta fusion caller. Using this capture-based single-assay approach, we successfully detected fusions commonly associated with leukemia (BCR-ABL1, MLL-MLLT3, MLL-AFF1, RUNX1-ETV6, EBF1-PDGFRB, TCF3-PBX1, IKZF1-PAX5), sarcoma (EWSR1-ATF1, EWSR1-FLI1, JAZF1-SUZ12, SS18-SSX, FUS-DDIT3, FUS-KLF17, YWHAE-FAM22B) and brain cancer (KIAA1459-BRAF) consistent with previously confirmed RT-PCR or FISH results. Several examples of previously unknown fusion partners or additional structural information that were not identified from the FISH or RT-PCR testing were also uncovered in this study. These cases are described in detail.

In summary, we show that selective enrichment of RNA-Seq libraries with cancer-specific probes enables detection of known and novel fusions across a broad range of cancer pathologies in a single reaction, creating new opportunities for discovery and translational cancer studies.

Citation Format: Lisa C. Watson, Stephen M. Gross, Felix Schlesinger, Anthony Mai, Mariko Kellogg, Steve Lee, Claire Attwooll, Monica Brenca, David Swanson, Andrew Wong, Angelo P. Dei Tos, Claudia Haferlach, Torsten Haferlach, Wolfgang Kern, Roberta Maestro, Manja Meggendorfer, Niroshan Nadarajah, Maurizio Polano, Sabrina Rossi, Marta Sbaraglia, George S. Charames, Gary P. Schroth, Grace DeSantis. Enhancing the resolution and accelerating the pace of translational fusion characterization in oncology by RNA sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-329.

Abstract 1514: Significance assessment of mutations in 944 MDS patients using publicly available variant databases and mutation impact prediction software

Introduction: In 2015 the FDA issued a call to the public to receive feedback on FDA's regulatory approaches to diagnostic tests using next generation sequencing technology. For the clinical performance of such tests one of the proposals was to use community-derived databases to classify variants, especially ClinVar, conceived as a clinically grade database. To test this we here applied ultra-deep sequencing and subsequent mutation profiling in patients with myelodysplastic syndomes (MDS).

Aim: Investigate the performance of public databases and mutation impact prediction software for the interpretation and distinct classification of variants of a well-characterized MDS mutation dataset (Haferlach et al, Leukemia 2014).

Patients and Methods: A total of 944 patients with various MDS subtypes were screened for gene mutations in 104 known/putative genes relevant to MDS using targeted deep-sequencing (Illumina, San Diego, CA). For this assessment the following databases were used: ClinVar (release 2015-11), COSMIC (v73) and dbSNP (v142). Additionally, mutations were computationally tested for their severity of impact on protein level using PolyPhen-2 and SIFT.

Results: In total, 845/944 patients (89.5%) harbored at least one mutation (median, 3 per patient; range, 0-12). A total of 2764 variants were called, among them 1,608 being distinct in 96 genes. Assessment was conducted by submitting positional information of each mutation to the database/prediction software. ClinVar yielded information for 141 (9%) of the mutations, with TP53 being the best-characterized gene out of 34, comprising of 33 entries (23%). Querying COSMIC yielded information for 671 (42%) mutations in 61 genes, with a subset of them being particularly well characterized (TET2, TP53, DNMT3A, and ASXL1). 255/1608 variants were listed in dbSNP. In the majority of instances, no global minor allele frequency (MAF, frequency of occurrence in the population of a variant base) is given and the validation status lists only a single submitter, indicating poorer reliability.

Additionally, we analyzed the mutations with two tools (PolyPhen-2, SIFT) to predict the possible impact of an amino acid substitution on the structure and function of human proteins. Results were available for 1137/1608 mutations. In 72% (820/1137) results were concordant, but surprisingly in 28% (317/1137) instances, results were contradicting, leaving them non-interpretable based on the combined use of both tools.

Conclusion: 1) Assessment demonstrates that current methods for variant interpretation using publicly available databases have to be improved for the characterization of mutations in patients with myeloid neoplasms. 2) So far COSMIC seems to outperform ClinVar. 3) Tools for novel mutations (no record in any databases) seem to perform well in quite a few instances, but a consensus of multiple tools is needed due to contradicting results.

Citation Format: Niroshan Nadarajah, Manja Meggendorfer, Wolfgang Kern, Claudia Haferlach, Torsten Haferlach. Significance assessment of mutations in 944 MDS patients using publicly available variant databases and mutation impact prediction software. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1514.

Ultra-deep sequencing leads to earlier and more sensitive detection of the tyrosine kinase inhibitor resistance mutation T315I in chronic myeloid leukemia

Chronic myeloid leukemia cells acquire resistance to tyrosine kinase inhibitors through mutations in the ABL1 kinase domain. The T315I mutation mediates resistance to imatinib, dasatinib, nilotinib and bosutinib, whereas sensitivity to ponatinib remains. Mutation detection by conventional Sanger sequencing requires 10%-20% expansion of the mutated subclone. We studied the T315I mutation development by ultra-deep sequencing on the 454 XL+ platform (Roche) in comparison to Sanger sequencing. By ultra-deep sequencing, mutations were detected at loads of 1%-2%. We selected 40 patients who had failed first-line to third-line treatment (imatinib, dasatinib, nilotinib) and had high loads of the T315I mutation detected by Sanger sequencing. We confirmed T315I mutations by ultra-deep sequencing and investigated the mutation dynamics by backtracking earlier samples. In 20 of 40 patients, we identified the T315I three months (median) before Sanger sequencing detection limits were reached. To exclude sporadic low percentage mutation development without subsequent mutation outgrowth, we selected 42 patients without resistance mutations detected by Sanger sequencing but loss of major molecular response. Here, no mutation was detected by ultradeep sequencing. Additional non-T315I resistance mutations were found in 20 of 40 patients. Only 15% had two mutations per cell; the other cases showed multiple independently mutated clones and the T315I clone demonstrated a rapid outgrowth. In conclusion, T315I mutations could be detected earlier by ultra-deep sequencing compared to Sanger sequencing in a selected group of cases. Earlier mutation detection by ultra-deep sequencing might allow treatment to be changed before clonal increase of cells with the T315I mutation.

Gain of chromosome 21 or amplification of chromosome arm 21q is one mechanism for increased ERG expression in acute myeloid leukemia

In acute myeloid leukemia (AML), acquired genomic gains and losses are common and lead to altered expression of genes located within or nearby the affected regions. Increased expression of the ETS-related transcription factor gene ERG has been described in myeloid malignancies with chromosomal rearrangements involving chromosome band 21q22, but also in cytogenetically normal AML, where it is associated with adverse prognosis. In this study, fluorescence in situ hybridization on interphase nuclei disclosed an amplification of the ERG gene (more than six copies) in 33 AML patients with structural rearrangements of 21q22. Array comparative genomic hybridization of these cases disclosed a minimal amplified region at the position 39.6-40.0 Mbp from pter that harbors ERG as the only gene. Analysis by quantitative real-time reverse transcription polymerase chain reaction revealed significantly higher ERG mRNA expression in these patients and in a group of 95 AML patients with complete or partial gain of chromosome 21 (three to six copies) compared with 351 AML patients without gain of chromosome 21. Quantification of ERG DNA copy numbers revealed a strong correlation with ERG mRNA expression. Furthermore, in patients with gain of chromosome 21, higher ERG expression was found to be associated with RUNX1 mutations. Our results suggest that acquired gain of chromosome 21 or amplification of chromosome arm 21q is one mechanism contributing to increased ERG expression in AML.

BRCC3 mutations in myeloid neoplasms

Next generation sequencing technologies have provided insights into the molecular heterogeneity of various myeloid neoplasms, revealing previously unknown somatic genetic events. In our cohort of 1444 cases analyzed by next generation sequencing, somatic mutations in the gene BRCA1-BRCA2-containing complex 3 (BRCC3) were identified in 28 cases (1.9%). BRCC3 is a member of the JAMM/MPN+ family of zinc metalloproteases capable of cleaving Lys-63 linked polyubiquitin chains, and is implicated in DNA repair. The mutations were located throughout its coding region. The average variant allelic frequency of BRCC3 mutations was 30.1%, and by a serial sample analysis at two different time points a BRCC3 mutation was already identified in the initial stage of a myelodysplastic syndrome. BRCC3 mutations commonly occurred in nonsense (n=12), frameshift (n=4), and splice site (n=5) configurations. Due to the marginal male dominance (odds ratio; 2.00, 0.84-4.73) of BRCC3 mutations, the majority of mutations (n=23; 82%) were hemizygous. Phenotypically, BRCC3 mutations were frequently observed in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms and associated with -Y abnormality (odds ratio; 3.70, 1.25-11.0). Clinically, BRCC3 mutations were also related to higher age (P=0.01), although prognosis was not affected. Knockdown of Brcc3 gene expression in murine bone marrow lineage negative, Sca1 positive, c-kit positive cells resulted in 2-fold more colony formation and modest differentiation defect. Thus, BRCC3 likely plays a role as tumor-associated gene in myelodysplastic syndromes and myelodysplastic/myeloproliferative neoplasms.

AML with gain of chromosome 8 as the sole chromosomal abnormality (+8sole) is associated with a specific molecular mutation pattern including ASXL1 mutations in 46.8% of the patients

Trisomy 8 is the most frequent cytogenetically gained aberration in AML. We compared 79 adult de novo AML with trisomy 8 as the sole cytogenetic abnormality (+8sole) to 511 normal karyotype AML patients (NK). +8sole patients were older (p=0.013), presented lower WBC counts (p=0.010), harbored more often ASXL1 mutations (p<0.001) and RUNX1 mutations (p=0.009), but less frequent FLT3-ITD (p=0.038), NPM1 mutations (p<0.001) and double-mutated CEBPA (p=0.038) than NK patients. No prognostic difference was found between +8sole and NK. With respect to genetic stability we found +8sole was instable, and molecular markers were either stable or gained in number and diversity.

BAALC expression: a suitable marker for prognostic risk stratification and detection of residual disease in cytogenetically normal acute myeloid leukemia

High brain and acute leukemia, cytoplasmic (BAALC) expression defines an important risk factor in cytogenetically normal acute myeloid leukemia (CN-AML). The prognostic value of BAALC expression in relation to other molecular prognosticators was analyzed in 326 CN-AML patients (<65 years). At diagnosis, high BAALC expression was associated with prognostically adverse mutations: FLT3 internal tandem duplication (FLT3-ITD) with an FLT3-ITD/FLT3 wild-type (wt) ratio of ⩾0.5 (P=0.001), partial tandem duplications within the MLL gene (MLL-PTD) (P=0.002), RUNX1 mutations (mut) (P<0.001) and WT1mut (P=0.001), while it was negatively associated with NPM1mut (P<0.001). However, high BAALC expression was also associated with prognostically favorable biallelic CEBPA (P=0.001). Survival analysis revealed an independent adverse prognostic impact of high BAALC expression on overall survival (OS) and event-free survival (EFS), and also on OS when eliminating the effect of allogeneic stem cell transplantation (SCT) (OS^TXcens). Furthermore, we analyzed BAALC expression in 416 diagnostic and follow-up samples of 66 patients. During follow-up, BAALC expression correlated with mutational load or expression levels, respectively, of other minimal residual disease markers: FLT3-ITD (r=0.650, P<0.001), MLL-PTD (r=0.728, P<0.001), NPM1mut (r=0.599, P<0.001) and RUNX1mut (r=0.889, P<0.001). Moreover, a reduction in BAALC expression after the second cycle of induction chemotherapy was associated with improved EFS. Thus, our data underline the utility of BAALC expression as a marker for prognostic risk stratification and detection of residual disease in CN-AML.

High number of additional genetic lesions in acute myeloid leukemia with t(8;21)/RUNX1-RUNX1T1: frequency and impact on clinical outcome

t(8;21)/RUNX1-RUNX1T1-positive acute myeloid leukemia (AML) is prognostically favorable; however, outcome is heterogeneous. We analyzed 139 patients with t(8;21)/RUNX1-RUNX1T1-positive AML (de novo: n=117; therapy-related: n=22) to determine frequency and prognostic impact of additional genetic abnormalities. All patients were investigated for mutations (mut) in ASXL1, FLT3, KIT, NPM1, MLL, IDH1, IDH2, KRAS, NRAS, CBL and JAK2. Sixty-nine of 139 cases (49.6%) had 1 mutation in addition to RUNX1-RUNX1T1, and 23/139 (16.5%) had ⩾2 additional mutations. Most common were KITmut (23/139; 16.5%), NRASmut (18/139; 12.9%) and ASXL1mut (16/139; 11.5%). FLT3-ITD, FLT3-TKDmut, CBLmut, KRASmut, IDH2mut and JAK2mut were found in 2.9-5.0%. Additional chromosomal abnormalities (ACAs) were found in 97/139 (69.8%). Two-year overall survival (OS) was 73.4% in 111 intensively treated patients. KITD816mut negatively impacted on OS in de novo AML (2-year OS: 59.1% vs 82.0%, P=0.03), ASXL1mut on EFS (de novo AML: 20% vs 59.1%, P=0.011; total cohort: 28.6% vs 56.7%, P=0.021). Sex chromosome loss was favorable (2-year EFS: 66.9% vs 43.0%, P=0.031), whereas +8 was adverse on EFS (2-year EFS: 26.7% vs 55.9%, P=0.02). In conclusion, t(8;21)/RUNX1-RUNX1T1-positive AML shows a high frequency of additional genetic alterations. Investigation for KITD816 and ASXL1mut combined with investigation of ACAs is recommended in t(8;21)/RUNX1-RUNX1T1-positive AML because of the prognostic significance of these parameters.

Landscape of genetic lesions in 944 patients with myelodysplastic syndromes

High-throughput DNA sequencing significantly contributed to diagnosis and prognostication in patients with myelodysplastic syndromes (MDS). We determined the biological and prognostic significance of genetic aberrations in MDS. In total, 944 patients with various MDS subtypes were screened for known/putative mutations/deletions in 104 genes using targeted deep sequencing and array-based genomic hybridization. In total, 845/944 patients (89.5%) harbored at least one mutation (median, 3 per patient; range, 0-12). Forty-seven genes were significantly mutated with TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1 mutated in >10% of cases. Many mutations were associated with higher risk groups and/or blast elevation. Survival was investigated in 875 patients. By univariate analysis, 25/48 genes (resulting from 47 genes tested significantly plus PRPF8) affected survival (P<0.05). The status of 14 genes combined with conventional factors revealed a novel prognostic model ('Model-1') separating patients into four risk groups ('low', 'intermediate', 'high', 'very high risk') with 3-year survival of 95.2, 69.3, 32.8, and 5.3% (P<0.001). Subsequently, a 'gene-only model' ('Model-2') was constructed based on 14 genes also yielding four significant risk groups (P<0.001). Both models were reproducible in the validation cohort (n=175 patients; P<0.001 each). Thus, large-scale genetic and molecular profiling of multiple target genes is invaluable for subclassification and prognostication in MDS patients.

CEBPA double-mutated acute myeloid leukaemia harbours concomitant molecular mutations in 76·8% of cases with TET2 and GATA2 alterations impacting prognosis

Acute myeloid leukaemia (AML) with CEBPA mutations is listed as a provisional entity in the current World Health Organization classification. A difference in clinical outcome between single- (sm) and double-mutated (dm) cases has been reported, whereupon CEBPAdm cases were shown to be associated with better overall survival (OS). The occurrence and prognostic impact of concomitant molecular mutations in addition to CEBPAdm has not been assessed until now with exception of GATA2 mutations. Here, we investigated a cohort of 95 AML CEBPAdm cases for concomitant mutations. TET2 was found to be most frequently mutated (34·0%) gene, followed by GATA2 (21·0%), WT1 (13·7%), DNMT3A (9·6%), ASXL1 (9·5%), NRAS (8·4%), KRAS (3·2%), IDH1/2 (6·3%), FLT3-internal tandem duplication (6·3%), FLT3-tyrosine kinase domain (2·1%), NPM1 (2·1%), and RUNX1 (1/94). Patients harbouring additional mutations in the TET2 gene showed significantly worse OS than TET2 wild-type cases (P = 0·035), whereas GATA2-mutated patients showed improved OS (P = 0·032). Serial analyses were performed for 39 CEBPAdm cases with concomitant mutations. Here, we observed that CEBPA mutations present the primary pathogenetic event in the majority of cases (76·9%). Further, a distinct gene expression profile (GEP) was confirmed for CEBPAdm versus CEBPAsm or CEBPA wild-type cases while no significant changes in GEP were observed related to additional mutations within the CEBPAdm AML.

Next-generation sequencing - feasibility and practicality in haematology

Next-generation sequencing platforms have evolved to provide an accurate and comprehensive means for the detection of molecular mutations in heterogeneous tumour specimens. Here, we review the feasibility and practicality of this novel laboratory technology. In particular, we focus on the utility of next-generation sequencing technology in characterizing haematological neoplasms and the landmark findings in key haematological malignancies. We also discuss deep-sequencing strategies to analyse the constantly increasing number of molecular markers applied for disease classification, patient stratification and individualized monitoring of minimal residual disease. Although many facets of this assay need to be taken into account, amplicon deep-sequencing has already demonstrated a promising technical performance and is being continuously developed towards routine application in diagnostic laboratories so that an impact on clinical practice can be achieved.

Enhanced transformation of polycyclic aromatic hydrocarbons using a combined Fenton's reagent, microbial treatment and surfactants

The potential for using Fenton's reagent (H(2)O(2)+ Fe(2+)) as an advanced oxidation pretreatment process to enhance microbial transformation of two model polycyclic aromatic hydrocarbons, anthracene and benzo[a]pyrene, in an aqueous system was evaluated. Fenton's reagent at a concentration of 0.5% H(2)O(2) and 10 mM Fe(2+) (molar ratio, 15:1) was most effective in transforming anthracene at pH 4. Application of non-ionic surfactants during Fenton's pre-treatment was found to be more effective in the transformation of both anthracene and benzo[a]pyrene. The extent of removal of substrates by a combined Fenton's-biotreatment was 2-4 times higher than with Fenton's treatment or biotreatment alone. In a chemical-biological treatment train, 48 h of Fenton's pre-treatment in the presence of a non-ionic surfactant, followed by 7 days of biological treatment resulted in 80-85% removal of PAHs (100 ppm).

Degradation of carbon tetrachloride in the presence of iron and sulphur containing compounds

The effect of several sulphur compounds: sodium sulphate, sodium sulphide, ferrous sulphide,pyrite and an organosulphonic acid on the kinetics of the iron (Fe °) induced degradation of carbon tetrachloride was examined under aerobic conditions. It was observed that all of the sulphur compounds investigated significantly accelerated the reaction. The mechanisms of the processes studied as well as their possible influence on the efficiency of the iron-induced dehalogenation of pollutants, both in situ and in above-ground treatment are discussed.

Leptospirosis risk in public cleansing and sewer workers

The degree of leptospirosis risk was investigated in 80 sewer and 120 public cleansing workers. They were interviewed and their serum samples tested for the presence of leptospiral antibodies by the sensitised erythrocyte lysis (SEL) test. Another 100 control subjects matched by sex, age and ethnic group were similarly studied. The study subjects had higher seroprevalence than the controls--over six times higher for SEL titres of greater than 1:100 and over 1.5 times for titres of greater than 1:25. The highest seroprevalence was found in workers cleaning wet markets and food centres. There was no significant correlation between the prevalence of positive titres and symptom prevalence or hospitalisation. Five of the study subjects (all sewer workers) gave a history of jaundice.