Information

Which sample type is more proper for whole genome sequencing in AML patients? Peripheral blood or bone marrow?


I intend to perform whole genome sequencing in AML patients in order to find genomic abnormalities, particularly translocation and gene fusions. However, I am not sure whether it is better to obtain peripheral blood or bone marrow or if there is no significant preference between them.

Please, provide me with scientific resources to refer to.

Thank you in advance.


Molecular pathogenesis of relapse after allogeneic hematopoietic cell transplantation is poorly understood. Data regarding relapse mechanisms after transplantation is scarcely available. We investigated genomic aberrations (GAs) in 21 patients undergoing related and unrelated HLA-matched transplantation in leukemic blasts before transplant and at relapse after transplantation. We found a higher number of GAs after transplantation, suggesting increased genomic instability during relapse. Two of 21 patients showed a large homozygous region spanning the whole HLA-locus on chromosome 6p in the relapse sample. In both patients sequence-based HLA typing of the blasts revealed a loss of the patient-specific allele at the mismatched locus leading to homozygosity for the HLA haplotype shared by the patient and the donor. In addition, GAs were found in critical regions such as 12p13, 13q12.2, and 17p13. Our results suggest that escape from immunologic surveillance may be a relevant mechanism of relapse after transplantation in patients with GAs on chromosome 6p. A combination of continuous immunologic pressure mediated by donor T cells and clonal evolution of myeloid leukemia may result in acquired GAs after transplantation.

Financial disclosure: See acknowledgments on page 1458.


Introduction

Splenic Marginal Zone Lymphoma (SMZL) is a low grade chronic B cell lymphoproliferative disorder that predominantly affects elderly patients and involves the spleen, bone marrow, and peripheral blood [1]. Although the median survival is around 10 years, approximately 70% of SMZL patients require treatment, of whom 25% experience progressive disease, leading to early death [1].

Our understanding of the molecular pathogenesis of SMZL remains limited. Early cytogenetic studies identified recurrent deletions of 7q31-q32 and duplications of 3q in approx. 30% and 20% of cases, respectively [2], but subsequent molecular investigations have failed to identify causative genes within these regions [3]. Candidate gene studies are limited to mutations in TP53, which is disrupted in 10-15% of cases [2], and to genes within the NF-ƘB pathway, which are mutated in a third of all cases [4,5]. The presence of a highly restricted immunoglobulin gene repertoire, in particular the selective usage of the immunoglobulin heavy chain variable (IGHV) 1-2*04 allele in 20-30% of patients, suggests that antigenic stimulation may be important in the pathogenesis of this disease [6].

The recent application of whole exome sequencing to frozen splenic tissue from 14 patients with SMZL followed by targeted resequencing of recurrent variants in larger cohorts has identified further biologically relevant genes [7,8]. Mutations in NOTCH2, which eliminate the C-terminal PEST domain and result in compromised protein degradation, were identified in 20 - 25% of cases although there was no consensus as to the clinical significance of these mutations between studies [7,8]. Gene mutations in modulators or other members of the Notch signalling pathway and in other pathways, such as chromatin remodelling and transcriptional regulation were also implicated [8].

In view of the relatively small number of patients investigated so far and the biological heterogeneity of SMZL, it is vital to perform additional gene discovery experiments to fully catalogue the molecular lesions that contribute to disease pathogenesis. To this aim, we performed whole exome sequencing and copy number analysis of tumour and germ-line DNA extracted from a clinically homogeneous cohort of SMZL patients. In doing so, we expand the reported directory of recurrently mutated cancer genes in this disease, thereby expanding our understanding of SMZL pathogenesis that will ultimately facilitate improvements in disease management and the promise of novel therapies.


Next Generation Sequencing Technologies

In the past decade, conventional Sanger sequencing method has been overtaken by several new technological advances collectively known as next generation sequencing (NGS). These technologies apply different target enrichment strategies and clonal amplification of the DNA resulting in the possibility of sequencing millions of DNA strands in parallel. This massively parallel sequencing facilitates high-throughput sequencing with a significant reduction in costs. The advent of NGS has significantly accelerated the effort to understand the molecular basis of cancers [6]. Recent development of “bench-top NGS Instruments” such as Ion Torrent PGM from Life Technologies and Mi-Seq from Illumina has been of tremendous utility in clinical settings and individual laboratories. Ion torrent PGM is based on semiconductor sequencing in which detection is done on a semiconductor chip. This technology detects the pH change due to release of hydrogen ions when a new nucleotide is inserted during synthesis [7]. Mi-Seq technology adopted the ‘sequencing by synthesis’ approach in which the template amplification and data analysis is combined in a single instrument. These instruments are smaller in size, having high throughput, high accuracy and less running time. In addition, these machines provide shorter read lengths which makes them more suitable for clinical and diagnostic applications [8]. Comprehensive reviews are available that discuss various technological aspects of NGS and its recent advancements [8–10].


Discussion

Here we present the development of a targeted RNA-sequencing method for the detection and measurement of MRD in AML. This assay, which can cover over two-thirds of patients in a single standardized assay (Figure 1), is highly specific, sensitive, and resilient to variations in sequencing depth and platform used during data collection. MRD status is now integrated into response criteria for AML,4 with ELN consensus guidelines for measurement now available.6 The assay presented here detects all of the molecular targets included in these guidelines.

To date, molecular MRD detection in AML has primarily focused on single target qPCR assays.18 The use of next-generation sequencing for AML MRD detection has begun to emerge but has primarily focused on DNA as the starting material.2721 Several features of the AML MRD RNA-sequencing assay presented here in theory make it ideal for MRD detection, including: (i) the use of next-generation sequencing allows for both target multiplexing and flexibility in identifying mutations that could vary between patients (variations in fusion breakpoints insertion sequences, etc.) (ii) use of primers targeting recurrent AML abnormalities greatly increases the sensitivity of the assay over bulk RNA- or DNA-sequencing (iii) RNA as the starting material allows for the simultaneous examination of mutations/fusions and changes transcript expression (iv) RNA increases the limit detection over that provided by DNA if the transcript expressed at a level greater than the genomic equivalent per cell (v) UMIs allow for the absolute quantification target levels and (vi) targeted primers during reverse transcription increase the limit of detection and allow for efficient use of the starting material. However, it is conceivable that this RNA-sequencing assay could be complemented in the future by the use of a DNA-based AML MRD next-generation sequencing approach (tracking, for example, somatic mutations in TP53, IDH1, IDH2, FLT3, etc.) which together would allow coverage of almost cases of AML.

Utilizing cell lines and patient samples expressing the targets included in our assay, we demonstrated that the AML MRD RNA-sequencing assay has a sensitivity for residual disease detection down to as low as 1 in 100,000 cells (Figure 2). Importantly, this detection limit is well below the threshold of 1 in 1,000 cells currently suggested by the ELN MRD consortium6 and is comparable to that of the gold standard single-target molecular techniques (Figure 3). Furthermore, due to the MRD-focused design of our assay, it can achieve up to a 1,000-fold greater sensitivity than that of the most similar targeted RNA-sequencing assay for myeloid malignancies available on the commercial market (Figure 4). However, since RNA expression levels can vary from one patient to another, it is important to note that sensitivity levels can vary and a detection limit of 1 in 100,000 cells may not always be attainable. This is a general difficulty affecting all RNA-based methods of MRD detection, including qPCR, and is reflected in the recommendation that molecular relapse be determined by the progression of trends across multiple time-points in an individual patient rather than by a single landmark assessment.6

Several important considerations for the clinical utility of an MRD assay include sample input requirements, cost, time, and ease of assay adaptation. Each of these factors were considered in the assay design. The use of targeted primers and the addition of UMIs during the reverse transcription step allow for maximal usage of the starting material while simplifying the workflow (Figure 1B), which can be completed in a single day and is easy to adopt and/or automate. Additionally, with a minimal sequencing requirement of only 1-3 million reads (Online Supplementary Figure S4), a single patient sample can be assessed for immediate results or multiplexed on larger scale runs to minimize costs (Online Supplementary Table S4). Importantly, this multiplex assay and analytic workflow is both flexible and expandable. The design allows for all targets to be screened at diagnosis, with the ability to tailor analysis to a subset of patient-specific targets at later time-points to further minimize sequencing costs. Additional targets can easily be added to the assay design, potentially allowing for the detection of other AML MRD markers, chimerism,2928 and HLA loss30 for those poor-risk AML patients who are not optimally covered by this assay but who will often undergo allogeneic stem cell transplantation.

While we confirmed the feasibility of use of this test in patient blood and bone marrow (Table 1, Figure 5), future work is needed to test the utility of this technique in large cohorts of patients and to determine the specific impact of MRD detection on AML patient outcomes in this setting. Overall, we believe that this UMI-based RNA-sequencing assay provides a high-throughput, reproducible, and broadly applicable tool for standardized detection of residual disease in patients with AML.


Results

Design of an integrated next-generation sequencing platform for comprehensive genetic analyses in acute myeloid leukemia

Our NGS platform for comprehensive genetic characterization of AML samples was designed to enable fast and reliable detection of genetic aberrations that are of critical importance for diagnosis, prognosis and therapy in adult AML.931 The complete workflow including three NGS-library preparations and data analysis by five different algorithms can be completed within 5 days (Figure 1A).

Figure 1. Comprehensive genetic diagnosis of acute myeloid leukemia by next-generation sequencing. (A) Outline of the workflow: each sample is subjected to preparation of three sequencing libraries. Libraries are indexed separately for sequencing on the same flowcell. Data are analyzed using five distinct algorithms for the detection of CNV, fusions, and DNA variants. The whole workflow can be completed within 5 days if performed by one person times to perform individual steps of the composite assay are indicated on the right. (B) Outline of the CAI[N] algorithm for CNV analysis. Reads are mapped to 1 Mb fixed genomic windows and read distributions are compared to the average of more than 2,500 normal karyotypes (Nfemale=2,819, Nmale=2,605) generated by random sampling of 150-250 bp reads from the reference genome. A region is called amplified or deleted if the observed read number in a window differs significantly (P<0.003) from the average of in silico-generated karyotypes. (C) Flow cell occupancy by three sequencing libraries. Two samples can be analyzed in parallel in one sequencing run on a standard MiSeq v2 flowcell when libraries are sequenced with the read numbers indicated in (A).

In order to limit the required sequencing resources to the capacities of a benchtop sequencing device, we addressed AML-relevant translocations on the level of RNA using anchored multiplex PCR10 for targeted enrichment of chimeric transcripts. RNA-based detection of common gene fusions in AML and DNA-based mutational screening are already available through predesigned commercial kits (Online Supplementary Tables S1-S4) with associated analysis software. Thus, we included numerical karyotyping into our platform by a strategy that does not require specific target enrichment. In particular, we performed low coverage whole genome sequencing (lc-WGS), which has been shown previously to enable robust detection of CNV.1211 For data analysis, we developed novel algorithms for the detection of CNV (Figure 1B) and KMT2A-PTD (CAI[N] and PTDi, respectively). Moreover, we added ITD-seek7 for the identification of FLT3-ITD to the available bioinformatics pipelines for fusion- or mutation calling. Depending on the size of the mutation panel, one or two samples can be analyzed at a time on a standard (maximum 15 ×10 reads) flowcell (Figure 1C). Operational costs per sample are comparable to the total expenses for conventional cytogenetics, fluorescence in situ hybridization (FISH) and mutation analysis. Taken together, our integrated NGS approach rapidly and economically delivers clinically meaningful insights into AML genomes, opening up the possibility to inform treatment decisions early based on molecular features and calculated cytogenetic information.

Principles of the CAI[N] algorithm and stability of in silico-generated reference karyotypes

In order to facilitate clinical interpretation, we modified the concept of &ldquovirtual&rdquo or &ldquodigital&rdquo karyotypes1413 and constructed &ldquocalculated karyotypes&rdquo from NGS data which resemble cytogenetic karyotypes. CNV in the range from cytogenetic bands to whole chromosomes are conveniently identified using a read depth approach15 and require only 5-10% genome coverage for detection with >90% sensitivity and specificity,1716 corresponding to 1-2×10 reads. CAI[N] compares read frequencies in 1 Mb fixed genomic windows to in silico-generated normal reference karyotypes and maps amplified/deleted regions to cytogenetic bands so that chromosomal gains or losses can be reported using cytogenetic notation (Figures 1B and 2A). Centromeres are not covered by our NGS karyotyping method as they include repetitive sequences that prevent unique alignment of sequencing reads.

To examine the stability of in silico reference karyotypes, we analyzed read distributions on whole chromosomes and in 1 Mb windows for random normal female and male karyotypes. Read frequencies showed very narrow variances and more reads mapped to autosomes in male karyotypes than in female ones, consistent with fewer reads mapping to the Y chromosome compared to a second X (Figure 2B). Of note, the Y chromosome appears smaller than its actual size, also due to repetitive sequences. To further investigate whether lc-WGS data resemble the results of in silico random experiments, we sequenced two libraries from healthy female donors at 1-4 ×10 reads. Read distribution patterns matched the in silico reference at all read depths examined (Figure 2C). These results confirm that lc-WGS can be accurately simulated computationally, allowing us to use random normal karyotypes as a stable reference for CNV analyses.

Figure 2. Calculated chromosome banding and in silico-generated reference karyotypes. (A) Calculated chromosome banding by CAI[N] analysis of lc-WGS data. Read distributions in genomic windows along chromosome 9 of an AML patient (AML-2, Table 1) are indicated (left: cytogenetic bands, right: 1 Mb windows. (B) Frequencies of uniquely mapped reads on whole chromosomes for in silico-generated normal karyotypes. RF: random female (N=2,819), RM: random male (N=2,605). Error bars represent the standard deviation (below visibility <0.01%). Note that in (A) the centromere of a chromosome is not covered and in (B) the Y chromosome appears smaller than its actual size because of repetitive DNA sequences, which prevent unique alignment of sequencing reads. (C) Scalability of the CAI[N] algorithm: Four whole genome libraries from two healthy female donors were sequenced with different read numbers in multiplexed sequencing runs (right panel). Healthy F1.1-4: four runs of the same library.

Table 1. Patients&rsquo samples and karyotypes.

Detection of chromosomal gains and losses by copy number variation karyotyping

After evaluation of CAI[N] for consistency with normal karyotypes, we determined its capacity to detect numerical aberrations. First, we examined an individual with Down syndrome (T21) and the benign meningioma cell line BEN-MEN-118 by lc-WGS and CAI[N] analysis. Both trisomy 21 in the T21 proband and loss of chromosome 22 in BEN-MEN-1 cells were identified correctly (Figure 3).

Figure 3. Detection of whole chromosome gains and losses by copy number variation karyotyping. Whole genome libraries from (A) an individual with Down syndrome (T21) and (B) the BEN-MEN-1 cell line were sequenced with low coverage and analyzed by CAI[N]. RF: random female (N=2,819), RM: random male (N=2,605). Error bars represent the standard deviation (below visibility).

Next, we investigated deletions or additions of chromosome parts in three AML patients&rsquo samples exhibiting loss of the long arm of chromosome 5 (Table 1, Online Supplementary Figures S1-S3). CAI[N] recovered 5q deletions with different breakpoints that closely matched reference laboratory results (Figure 4A, Table 1). Moreover, a gain of chromosome 1p was detected in patient AML-1, consistent with a previously reported partial trisomy 1p (Figure 4B, Online Supplementary Figure S1, Table 1).

Figure 4. Detection of partial chromosome losses and gains by copy number variation karyotyping. Whole genome libraries from three AML patients&rsquo samples were sequenced with low coverage and analyzed by CAI[N]. (A) Region plots for chromosome 5. (B) Region plot of chromosome 1 for patient AML-1. Read numbers in 1 Mb windows were normalized to 1 ×10 6 total reads. RF: random female (n=2,819), RM: random male (n=2,605). See also Online Supplementary Figures S1-S3.

Finally, to test the capability of our approach to identify chromosomal gains or losses that are not readily detected by cytogenetic banding, we performed CNV karyotyping on two AML cell lines, HL-60 and NB-4. We observed complex patterns of copy number alterations in both cell lines, including massive overrepresentation of 8q24.21 (containing the MYC locus) with loss of the remaining parts of chromosome 8 (Online Supplementary Figures S4A,B, S5 and S6, Online Supplementary Tables S5 and S6), as described previously.2619 Amplification of MYC was validated by quantitative PCR in HL-60 and NB-4 cells and in patient AML-2, in whom a copy number gain of 8q24 had not been observed by cytogenetics. Similarly, quantitative PCR analysis of three loci on chromosome 7q (ARHGEF5, PIK3CG, VKORC1L1) confirmed that this region was amplified in NB-4 cells and not lost in AML-2 (Online Supplementary Figures S2 and S4C, Table 1).

In summary, our results demonstrate that lc-WGS followed by CAI[N] analysis correctly identifies copy number changes with high resolution and allows specific genes to be linked directly to amplified or deleted regions.

Sensitivity of CAI[N] copy number variation karyotyping

To test the sensitivity of our karyotyping approach, we performed lc-WGS and CAI[N] analysis on a dilution series of BEN-MEN-1 DNA in healthy donor DNA. Moreover, we investigated samples with different blast contents which were prepared after enrichment of CD34-positive cells from the peripheral blood of patient AML-4 by magnetic bead separation.27 Loss of chromosome 22 was readily detectable in mixtures containing as little as 10% BEN-MEN-1 DNA (Figure 5). Deletion of chromosome 7q was recovered by CNV karyotyping for blast contents &ge20% with almost identical breakpoints (Online Supplementary Figure S7, Table 1). As loss of chromosome 7q was not present in all cells in the CD34-positve blast population (Table 1), the detection limit for this aberration was slightly higher than for monosomy 22, which is found in all BEN-MEN-1 cells. These findings indicate that the sensitivity of CAI[N]-CNV karyotyping is sufficient to detect highly prevalent chromosomal aberrations in AML samples with a blast count of at least 20% without prior enrichment of the blast population.

Figure 5. Sensitivity of copy number variation karyotyping. Genomic DNA from the BEN-MEN-1 cell line (monosomy 22) was diluted in healthy donor DNA (Healthy F1, Figure 2) in different ratios and subjected to lc-WGS and CAI[N] analysis. (A) Region plots for chromosome 22. The range ±3 standard deviations around the mean is indicated in pale red. (B) CNV decision plots. Read numbers in 1 Mb windows were normalized to 1×10 6 total reads. RF: random female (N=2,819). Color coding in (B) as in (A).

Fusion gene and DNA variant detection

Our composite assay relies on predesigned amplicon panels for the detection of fusion transcripts and DNA variants. Amplification strategies implemented in these kits10 or, respectively, specific panels, have already been extensively evaluated.287 Thus, we focused our studies on the detection of all subclass-defining translocations and all major types of clinically relevant DNA variants in adult AML. To investigate coverage of important fusion genes, we analyzed cell lines and patients&rsquo samples harboring or lacking frequent chimeric transcripts. All expected fusions were identified in KASUMI-1,29 ME-1,30 NB-4,21 AML-5, AML-6 and CML-1, including two variants31 of BCR-ABL1 in the last sample. On the other hand, no fusions were detected in HL-6019 cells and in a patient with hypereosinophilic syndrome (HES-1), as reported by the reference laboratory (Online Supplementary Figure S8A, Online Supplementary Table S7). In a pool of the four cell lines, all fusions were recovered, but in a 1:25 dilution thereof, only the RUNX1-RUNX1T1 fusion transcript was identified. This finding underlines that RNA-based fusion detection is expression-dependent, so that the sensitivity of the assay varies for different samples and fusions.

Moreover, we exemplarily tested the TruSight Myeloid panel (Illumina) and the QIASeq&trade Myeloid Neoplasms panel (Qiagen), which incorporates molecular barcodes for PCR-error correction,32 as screening tools to identify short DNA variants in AML genomes. All single nucleotide variants detected in HL-60, NB-4, ME-1, MV4-11 and SKNO-1 cells by the TruSight Myeloid panel were consistent with COSMIC33 data or confirmed by Sanger sequencing, and the QiaSeq&trade panel uncovered all reported mutations in samples from two patients with AML (Online Supplementary Table S8). Sequencing a dilution series of MV4-11 DNA revealed detection limits for the two p53 mutations of 1% and 10% with the TruSight® and QiaSeq&trade panels, respectively (Online Supplementary Figure S8B). Therefore, amplicon sequencing enables variant detection with analytical sensitivities that, in well-covered regions, are equivalent to those of Sanger sequencing, the reference method for clinical mutation testing.3534

Larger DNA sequence variants such as FLT3-ITD and KMT2A-PTD require special attention in NGS data analysis as they may be missed by common variant calling tools.3736 Thus, previous authors have added ITD-seek to the TruSight Myeloid analysis pipeline.7 Applying this tool to our MV4-11 dilution series, we identified a 34 bp insertion in FLT3 exon 14, which closely matched published results,38 with an analytical sensitivity of 10% (Online Supplementary Figure S9A). The FLT3-ITD was not detected in the 10% MV4-11 sample using the QiaSeq&trade panel with smCounter analysis, presumably because of suboptimal coverage achieved in our sequencing runs. However, given that our work with commercial kits aimed at clarifying their principal applicability for diagnostic purposes, we did not repeat these experiments.

For the identification of KMT2A-PTD in amplicon sequencing data, we developed PTDi by adapting a tool that had been used previously with a capture-based targeted sequencing approach.36 PTDi analysis revealed amplification of exons 3-8 in patient AML-7 with a known e3e9 KMT2A-PTD (Online Supplementary Figure S9B, Online Supplementary Table S9). Thus, not only are short DNA variants detectable by amplicon sequencing, but also difficult ITD and PTD. Taken together, our results clearly confirm that combining RNA- and DNA-based amplicon panels allows all major translocations and all types of clinically relevant mutations in AML to be uncovered by NGS.

Evaluation of the comprehensive next-generation sequencing platform for the diagnosis of acute myeloid leukemia in a clinical setting

After testing the performance of all sequencing modules and bioinformatics procedures, we evaluated the clinical utility of our platform as a diagnostic tool. As our karyotype studies in cell lines clearly showed that NGS detects a higher number of numerical aberrations than chromosome banding (Online Supplementary Tables S5 and S6), we first investigated a potential need for manual review of the raw CAI[N] output in order to avoid overestimation of karyotype complexity and enable appropriate risk stratification (Table 1, Online Supplementary Tables S10 and S11). We performed lc-WGS on additional patients&rsquo samples and reconstructed CNV karyotypes by cross comparison of CAI[N] results and known cytogenetic findings. All non-complex karyotypes, including three samples with presumably normal karyotypes in which cytogenetic analysis had failed, were identified correctly (AML-5, -7-11a/b, -13, -16, -17, -19, HES-1 / AML-14, -15, -20). In two samples that had not been characterized extensively by FISH, CNV karyotyping apparently identified marker chromosomes or detected additional aberrations (AML-2 / AML-1). Moreover, CAI[N] revealed copy number changes for five of six chromosomes involved in translocations in a highly complex karyotype (AML-3), but missed loss of chromosome 10, which had been detected in <10% of cells by interphase FISH. In four patients, for whom cytogenetics had not been performed when samples were taken, NGS recovered at least a subset of aberrant clones or a normal karyotype as reported at initial diagnosis (AML-4, -6, -12 / AML-18, respectively). Taken together, overall karyotype complexity was determined correctly in all cases and 13/13 samples without risk-defining translocations were accurately assigned to prognostic groups based on CNV karyotyping alone (Online Supplementary Table S10). Thus, we did not specifically validate discordant results between conventional and NGS karyotyping.

Next, to study patients&rsquo samples in an unbiased manner, a group of four of the authors performed blinded analysis of CNV, fusion genes and mutations on eight additional AML samples and one acute lymphocytic leukemia sample (AML-21&ndash28, ALL-139 Table 1, Online Supplementary Tables S7-S9). Two samples were excluded before unblinding because of insufficient read coverage resulting from poor DNA quality (AML-26, -27). In the remaining samples, CNV karyotyping uncovered all expected numerical changes and one additional aberration, gain of chromosome 19 in patient AML-28. Fusion analysis identified all translocations previously described in these patients. Variant analysis revealed no single nucleotide variants, insertions, deletions or ITD in this series of samples, in agreement with reference results. These findings further underscore the potential diagnostic value of our assay for the clinical management of AML.


4 OTHER AETIOLOGIES OF HYPOPLASTIC BONE MARROW FAILURE

As briefly mentioned in the earlier sections on AA and h-MDS, the diagnostic process of diseases viewed as hypoplastic bone marrow failure is frequently complicated by a wide range of differential diagnoses. Bone marrow biopsies are routinely implemented in the diagnostic algorithm at some point after an appropriate clinical evaluation is made, with the aim of ruling out bone marrow failure manifestation due to other aetiologies than haematological diseases. Pancytopenia, which in itself is not a disease, but merely a symptom of an underlying disorder affecting the bone marrow and peripheral cell lines, may as well be attributable to a non-malignant or an inherited condition as to a frank malignancy. 73 Non-malignant causes of pancytopenia include toxicity as a consequence of drug effect or irradiation, infections, nutritional deficiencies, autoimmune diseases, splenic sequestration, PNH and haemophagocytic lymphohistiocytosis. 73 Furthermore, there is a significant group of patients exhibiting unexplained cytopenias without completely fulfilling diagnostic criteria for haematological diseases, termed idiopathic cytopenia of undetermined significance (ICUS). 24 Clonal cytopenia of undetermined significance (CCUS) is a subgroup of ICUS, in which a mutation in at least one disease-causing gene is identified. 74 In spite of this, a newly published study 75 speculated, in reflection of their discovery of the presence of mutations among ICUS patients, that mutations in ASXL1 might be the first hit in the progression to MDS. Other studies 76, 77 have demonstrated that NGS technologies can be useful in the detection of MDS-associated mutations in cohorts of patients presenting with unexplained cytopenias. Their findings suggest that mutational discoveries by NGS can aid the identification of patients at risk of malignancy progression. The two studies, however, report contradicting results regarding disease progression to MDS/AML. Fernandez-Pol et al 76 advocate, in the light of their progression-free cohort, that NGS results should be interpreted with caution in the context of unexplained cytopenias. On the other hand, Hansen et al 77 argue for careful medical follow-up in the setting of unexplained cytopenias, while presenting a progression rate of 7 out of 60 patients. A large prospective cohort 23 demonstrated that mutational profiling of peripheral blood cells using NGS has high predictive value for the identification of patients who already have, or are prone to develop a myeloid malignancy. The study revealed that patients with CCUS had a 14-fold higher risk of progression to myeloid neoplasms (MDS/AML) compared to patients without clonal changes (ICUS). 23 The progression rate of CCUS depends not only on the existence of mutations, but also on the number of mutated genes, their clone size and the specific VAFs of the individual mutations. 23 In a newly published article, Malcovati et al 78 demonstrated that the discovery of SF3B1 mutations among CCUS patients, almost invariably, is associated with later development of manifest MDS with ring sideroblasts. They further suggest that mutations in SF3B1 are indicative of MDS in the setting of persistent, unexplained cytopenia, which in turn, may have implications on treatment strategies and risk stratification. 78 Two other studies 79, 80 have demonstrated that NGS has led to the validation of a firm haematological diagnosis in patients presenting with unexplained cytopenias.


Materials and methods

Patients and samples

We recruited 335 adult patients newly diagnosed with de novo non-M3 AML at the National Taiwan University Hospital with adequate cryopreserved bone marrow (BM) specimens. AML was diagnosed according to the 2016 World Health Organization (WHO) criteria. 17 Patients with antecedent cytopenia, hematologic disease, or therapy-related AML were excluded. This retrospective study was approved by the National Taiwan University Hospital Research Ethics Committee, and written informed consents were obtained from all participants in accordance with the Declaration of Helsinki. All patients achieved a morphologic CR, defined by the 2017 ELN recommendation, 18 after standard induction chemotherapy and received 2 to 4 courses of postremission chemotherapy with high-dose cytarabine with or without anthracycline. 19 The patients who achieved CR with incomplete hematologic recovery were not included. The choice of allogeneic HSCT was based on chromosomal findings, age, availability of donors, and response to induction treatment, evaluated by morphologic observation and MFC examination, which is a routine test in our institute. The pre-HSCT status was defined by cytomorphologic evaluation. NGS MRD analysis results were made unavailable to physicians to avoid bias in the choice of consolidation options. The median follow-up time of this cohort was 8.8 years (range, 0.3-23.3 years).

Gene mutation, cytogenetics, and flow cytometry analyses

We analyzed 1,005 BM samples serially collected at diagnosis, first CR after induction chemotherapy (first time point for MRD analysis), and after the first consolidation chemotherapy (second time point). We used the TruSight myeloid sequencing panel and HiSeq platform (Illumina, San Diego, CA) to survey mutations in 54 genes related to myeloid malignancies (supplemental Table 1). Library preparation and sequencing were performed according to the manufacturer’s instructions. The median reading depth was 10 550×. We used COSMIC database version 86, dbSNP version 151, ClinVar, PolyPhen-2, and SIFT to evaluate the consequence of every variant. The detailed variant analysis algorithm for diagnostic samples was described previously, 20 and the minimum variant allele frequency (VAF) for diagnostic samples was 5%. As shown in previous studies, 11,13 all variants detected at diagnosis were compiled to determine their background VAF error levels. The variant-specific error level was determined in all samples obtained from patients not carrying the specific variant at diagnosis. Variants with VAF more than mean background error plus 2 standard deviations of background error were selected for MRD analysis (supplemental Table 2). Because of the sequencing sensitivity issue, we excluded CEBPA mutations and FLT3-ITD in subsequent MRD analyses. The mutational status of these 2 genes at diagnosis was analyzed using previously described methods. 21

Cytogenetic analysis was performed and classified according to refined Medical Research Council criteria. 22 MRD monitoring was routinely done using MFC, as described previously. 23,24

Statistical analysis

To evaluate the clinical robustness of prognostic models contributed by either the first or second MRD, we randomly divided the cohort into the training (80%) and validation (20%) sets. To minimize the bias introduced during this procedure, the division process was performed repeatedly 1000 times 1000 AUC values of the MRD 1st model, derived from the time-dependent receiver operating characteristic curve, 25 were compared with the other 1000 AUC values of the MRD 2nd model, using the paired Student t test in the validation cohort. The model construction process and other statistical methods are thoroughly described in supplemental Materials.


Patients and methods

Cohort

Included in the study were primary sequential specimens from 48 adult and 25 pediatric patients with AML from the Nordic countries, all of whom had relapsed or PR disease. All patients were diagnosed according to World Health Organization criteria. 19 Only cases with relapse or PR specimens of sufficient quality and yield available via the Uppsala Biobank or Karolinska Institute Biobank, collected from 1995 through 2016, were included. Cases of the clinically distinct acute promyelocytic leukemia (APL) subtype were excluded. Sixty-six patients had de novo AML, whereas the remaining 7 had a prior diagnosis of a myelodysplastic syndrome (MDS) or other malignancy. Associated clinical characteristics are summarized in Table 1, Figure 1, supplemental Tables 1-3, and supplemental Figures 1 and 2. Informed consent was obtained according to the Declaration of Helsinki, and study approval was acquired from the Uppsala Ethical Review Board (Sweden) and the Regional Ethics Committee South-East (Norway).

. Data .
Patients73 (100)
Adult cases 48 (65.8)
Elderly (≥60 y) 25 (34.2)
Adult (40-59 y) 17 (23.3)
Young adult (19-39 y) 6 (8.2)
Pediatric cases 25 (34.2)
Adolescent (15-18 y) 3 (4.1)
Child (3-14 y) 15 (20.5)
Infant (<3 y) 7 (9.6)
Sex, female 38 (52.1)
Background
De novo AML 66 (90.4)
Potential t-AML 3 (4.0)
MDS-AML 2 (2.7)
t-MDS-AML 2 (2.7)
Tumor samples138 (100)
Diagnosis samples 52 (37.7)
Relapse samples 80 (58.0)
R1 and R1-P 60 (43.5)
R2 and R2-P 16 (11.6)
R3 4 (2.9)
Primary resistant samples 6 (4.3)
Matched normal controls61 (100)
BMS cells 43 (70.5)
Complete remission samples 17 (27.9)
BMS/complete remission cell combination 1 (1.6)
Average age at onset, y
Adult cases 59.3 (range, 20.5-83.1 median, 61.7)
Pediatric cases 8.2 (range, 0.4-18.2 median, 7.7)
Average length of EFS, d (D>R1)
Adult relapse cases 624 (range, 34-5958 median, 306)
Pediatric relapse cases 365 (range, 69-1110 median, 312.5)
Average WBC
Adult cases* 100 (range, 1-395 median, 80)
Pediatric cases 104 (range, 11-232 median, 50)
NK-AML
Adult cases† 21 (46.7)
Pediatric cases 7 (28.0)
Sample purity 86% (>80% tumor cells range, 41-100)
Cell viability‡ 61% (≥75% viable cells range, 6-94)
Sampling duration 1995 through 2016
. Data .
Patients73 (100)
Adult cases 48 (65.8)
Elderly (≥60 y) 25 (34.2)
Adult (40-59 y) 17 (23.3)
Young adult (19-39 y) 6 (8.2)
Pediatric cases 25 (34.2)
Adolescent (15-18 y) 3 (4.1)
Child (3-14 y) 15 (20.5)
Infant (<3 y) 7 (9.6)
Sex, female 38 (52.1)
Background
De novo AML 66 (90.4)
Potential t-AML 3 (4.0)
MDS-AML 2 (2.7)
t-MDS-AML 2 (2.7)
Tumor samples138 (100)
Diagnosis samples 52 (37.7)
Relapse samples 80 (58.0)
R1 and R1-P 60 (43.5)
R2 and R2-P 16 (11.6)
R3 4 (2.9)
Primary resistant samples 6 (4.3)
Matched normal controls61 (100)
BMS cells 43 (70.5)
Complete remission samples 17 (27.9)
BMS/complete remission cell combination 1 (1.6)
Average age at onset, y
Adult cases 59.3 (range, 20.5-83.1 median, 61.7)
Pediatric cases 8.2 (range, 0.4-18.2 median, 7.7)
Average length of EFS, d (D>R1)
Adult relapse cases 624 (range, 34-5958 median, 306)
Pediatric relapse cases 365 (range, 69-1110 median, 312.5)
Average WBC
Adult cases* 100 (range, 1-395 median, 80)
Pediatric cases 104 (range, 11-232 median, 50)
NK-AML
Adult cases† 21 (46.7)
Pediatric cases 7 (28.0)
Sample purity 86% (>80% tumor cells range, 41-100)
Cell viability‡ 61% (≥75% viable cells range, 6-94)
Sampling duration 1995 through 2016

Data are number of patients (% of total group), unless otherwise stated. Detailed biological and clinical data for each patient/sample are presented in supplemental Tables 2 and 3.

BMS, bone marrow–derived stromal cells D, diagnosis NK-AML, normal karyotype AML at diagnosis R1/2/3, sequential relapses R1/2-P, persistent relapse specimen t-AML, treatment related AML WBC, white blood cell count (at diagnosis).

Information lacking for 6 adults.

Information lacking for 3 adults.

Accounts only for cryopreserved cells.

Event timeline of the study cohort. The time from diagnosis to longitudinal events for each patient is shown. Cases are depicted from top to bottom, grouped based on age at onset. Stars indicate occurrence of an allogeneic HSCT. Samples included in the current study as well as the next-generation sequencing method applied are indicated by filled circles (WGS, 90×), open circles (WGS, 30×), and diamonds (WES). Patients in remission at the latest follow-up are indicated with an ellipsis at the end of the respective bar. R1/2/3/4, sequential relapses HSCT, hematopoietic stem cell transplantation.

Event timeline of the study cohort. The time from diagnosis to longitudinal events for each patient is shown. Cases are depicted from top to bottom, grouped based on age at onset. Stars indicate occurrence of an allogeneic HSCT. Samples included in the current study as well as the next-generation sequencing method applied are indicated by filled circles (WGS, 90×), open circles (WGS, 30×), and diamonds (WES). Patients in remission at the latest follow-up are indicated with an ellipsis at the end of the respective bar. R1/2/3/4, sequential relapses HSCT, hematopoietic stem cell transplantation.

Sample preparation

Mononuclear cells were enriched through Ficoll gradient centrifugation and cryopreserved or stored as frozen pellets until they were used. Cryopreserved AML specimens with leukemia cell content <80% were, if applicable, purified by immune-based depletion of nontumor cells (supplemental Table 4). Normal BM-derived stromal cells were cultivated from leukemic BM according to a published method 20 as a source of germline DNA. Genomic DNA was obtained with Qiagen extraction kits.

Library preparation and next-generation sequencing (NGS WGS: HiSeq X, Illumina [San Diego, CA] WES: Ion Proton, Thermo Fisher Scientific [Waltham, MA]) were performed at the Science for Life Laboratory (SciLifeLab), National Genomics Infrastructure (Uppsala, Sweden). Detailed information, including variant calling, filtering, and validation, is provided in supplemental Methods.

Statistics

Kaplan-Mayer curves and associated statistical tests were generated in GraphPad Prism 7.02. Other statistical tests were performed in R, 21 as detailed in supplemental Methods.


Endometrial and acute myeloid leukemia cancer genomes characterized

Two studies from The Cancer Genome Atlas (TCGA) program reveal details about the genomic landscapes of acute myeloid leukemia (AML) and endometrial cancer. Both provide new insights into the molecular underpinnings of these cancers with the potential to improve treatment. These studies represent the sixth and seventh in a series of genomes of at least 20 major cancers.

The first study is on endometrial cancer:

Study establishes basis for genomic classification of endometrial cancers proper categorization is important for choosing the best treatment

A comprehensive genomic analysis of nearly 400 endometrial tumors suggests that certain molecular characteristics - such as the frequency of mutations - could complement current pathology methods and help distinguish between principal types of endometrial tumors, as well as provide insights into potential treatment strategies. In addition, the study, led by investigators in The Cancer Genome Atlas (TCGA) Research Network, revealed four novel tumor subtypes, while also identifying genomic similarities between endometrial and other types of cancers, including breast, ovarian, and colorectal cancers.

These findings represent the most comprehensive characterization of the molecular alterations in endometrial cancers available to date. They were published May 2, 2013, in the journal Nature. TCGA is funded and managed by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), both part of the National Institutes of Health.

"With this latest study in a series of 20 planned TCGA tumor type characterizations, more genomic similarities are emerging between disparate tumor types," said NIH Director Francis S. Collins, M.D., Ph.D. "Teasing out heretofore unknown genomic markers or mutations in various cancers is again proving the value of TCGA."

Clinically, endometrial cancers fall into two categories: endometrioid (type I) and serous (type II) tumors. Type I is correlated with excess estrogen, obesity, and a favorable prognosis, while type II is more common in older women and generally has a less favorable outcome. Type I tumors are often treated with radiation therapy, which helps stop or slow cancer growth, given in addition to or after the primary treatment. Type II tumors are generally treated with chemotherapy, in which drugs are used to kill the cancer cells or stop them from growing.

Distinguishing between different types of endometrial cancers is currently based on histology, an examination of a thin slice of tissue under a microscope. But categorizing endometrial cancer tissues is often difficult, and specialists frequently disagree on the classification of individual cases.

In this study, investigators showed that approximately 25 percent of tumors that pathologists classified as high-grade endometrioid showed frequent mutations in TP53, a tumor suppressor gene, as well as extensive copy number alterations, a term for when a cell has too many or too few copies of a genomic segment. Both are key molecular characteristics associated with serous tumors, along with a small number of DNA methylation changes, which are additions of a basic chemical unit to pieces of DNA. Most endometrioid tumors, by contrast, have few copy number alterations or mutations in TP53, though there are frequent mutations in other well known cancer-associated genes, including PTEN, another tumor suppressor gene, and KRAS, a gene involved in regulating cell division.

These data suggest that some high grade endometrioid tumors have developed a strikingly similar pattern of alterations to serous tumors, and may benefit from a similar course of treatment.

"This study highlights the fact that some tumors with the same characterization by pathologists may have very different molecular features. That's where these findings will be directly implemented in additional research, and also in the context of clinical trials," said Douglas A. Levine, M.D., head of the Gynecology Research Laboratory at Memorial Sloan-Kettering Cancer Center, New York, and a co-leader in the study.

According to the authors, the new findings provide a roadmap for future clinical trials for endometrial cancer. "Each tumor subtype might warrant dedicated clinical trials because of the marked genomic differences between them that are indicative of different drivers of cancer," said study co-leader Elaine Mardis, Ph.D., co-director of the Genome Institute at Washington University School of Medicine, St. Louis. "Developing therapies for each subtype independent of the other may improve outcomes, as has been shown in breast cancer."

Investigators also found genomic similarities between endometrial cancers and other tumor types. Previous TCGA research showed that a form of ovarian cancer (high-grade serous ovarian carcinoma) and a subtype of breast cancer (basal-like breast cancer) share many genomic features. In this study, the scientists found that endometrial serous carcinoma also has some of these same genomic characteristics. The cancers share a high frequency of mutations in TP53 (between 84 and 96 percent) and a low frequency in PTEN, with only 1 to 2 percent mutated. Surprisingly, the researchers also found many shared characteristics between endometrioid tumors and colorectal tumors. Both cancer types demonstrate a high frequency of microsatellite instability, where the repair mechanism for DNA is broken, and mutations in POLE, a gene responsible for producing a protein involved in DNA replication and repair. These genomic changes led to high mutation rates in both tumor types.

"TCGA's multidimensional approach to collecting genomic data, including clinical and pathology information, have made these findings possible," said Harold Varmus, M.D., NCI director. "Without the integrated characterization of so many tumor samples, correlations between histology and genomic data may not have been observed or potential clinical outcomes identified."

With a complete analysis of the study's findings, investigators have identified four novel genomic-based subtypes of endometrial cancer, which may set the stage for new diagnostic and treatment approaches. Each of the four genomic subtypes clustered together and was named for one of its notable characteristics:

The POLE ultramutated group was named for its unusually high mutation rates and hotspot mutations (sequences highly susceptible to mutation) in the POLE gene. The hypermutated microsatellite instability group exhibited a high mutation rate, as well as few copy number alterations, but did not carry mutations in the POLE gene. The copy number low group showed the greatest microsatellite stability but a high frequency of mutations in CTNNB1, a gene critical for maintaining the linings of organs, such as the endometrium. The copy number high subtype was composed of mostly serous tumors, but included some endometrioid samples. This subtype displayed copy number alterations and a mutation landscape that was characteristic of serous tumors.

Endometrial cancer is the fourth most commonly diagnosed cancer among women in the United States. NCI estimates that close to 50,000 women will be diagnosed with endometrial cancer in 2013, with more than an estimated 8,000 deaths from the disease. For a majority of patients diagnosed with aggressive, high grade tumors with metastases, the five-year survival rate is about 16 percent, though chemotherapy has been associated with an improvement in survival, and new targeted agents are being tested.

"Finding genomic similarities among types of breast, ovarian, endometrial and colorectal tumors once again reveals that cancer, although very complex, may have themes extending beyond tissue type that can be exploited for therapeutic benefit," said Eric D. Green, M.D., Ph.D., NHGRI director. "These similar genomic features demonstrate hitherto unknown commonalities among these cancers.

To date, the TCGA Research Network has generated data and published analyses on glioblastoma multiforme, ovarian serous adenocarcinoma, colorectal adenocarcinoma, lung squamous cell carcinoma and invasive breast cancer. Data generated by TCGA are freely available at the TCGA Data Portal and CGHub.

This work was supported by the following grants from the NIH: 5U24CA143799-04, 5U24CA143835-04, 5U24CA143840-04, 5U24CA143843-04, 5U24CA143845-04, 5U24CA143848-04, 5U24CA143858-04, 5U24CA143866-04, 5U24CA143867-04, 5U24CA143882-04, 5U24CA143883-04, 5U24CA144025-04, U54HG003067-11, U54HG003079-10 and U54HG003273-10 and supplemented by the Recovery Act.

More details about The Cancer Genome Atlas, including Quick Facts, Q&A, graphics, glossary, a brief guide to genomics and a media library of available images can be found at http://cancergenome. nih. gov.

Reference: The Cancer Genome Atlas Research Network. Integrated Genomic Characterization of Endometrial Carcinoma. Nature. May 2, 2013. DOI:10.1038/nature12113.

The second study is on acute myeloid leukemia:

TCGA researchers identify potential drug targets, markers for leukemia risk New study reveals relatively few mutations in AML genomes

Investigators for The Cancer Genome Atlas (TCGA) Research Network have detailed and broadly classified the genomic alterations that frequently underlie the development of acute myeloid leukemia (AML), a deadly cancer of the blood and bone marrow. Their work paints a picture of a cancer marked by relatively few mutations compared to other types of cancer occurring in adults. They also found that AML is powerfully influenced by mutations in genes that cause epigenetic changes (chemical changes to the genome that do not change the DNA nucleotide sequence) that can affect the expression of genes. TCGA is jointly supported and managed by the National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI), both part of the National Institutes of Health.

The findings, which appeared online May 1, 2013, in the New England Journal of Medicine set the stage for identifying potential new drug targets and treatment strategies for AML. They may also offer better guidance for predicting the severity of disease for individual patients.

"These results provide important new insights into the genomics of a deadly and difficult-to-treat cancer, and underscore the power and scope of The Cancer Genome Atlas project," said NIH Director Francis S. Collins, M.D., Ph.D.

"Rather than just random snapshots about individual patients, this study provides a more detailed look at the aberrant genomes of AML than we have ever had before," said NHGRI Director Eric D. Green, M.D., Ph.D. "It has the potential to open up new directions in AML research, and perhaps, in the design of new therapeutics, its impact could be felt in the near future."

AML, the most common acute form of adult leukemia, develops when immature white blood cells fail to mature and instead accumulate in the bone marrow. The leukemia cells reduce the production of healthy blood cells, leading to anemia, abnormal bleeding and infections, and, if untreated, death.

Researchers examined the genomes of tumor specimens from 200 adult cases of spontaneously occurring, newly diagnosed AML. These cases represented all of the known subtypes of AML in approximately the same proportion as the general population. In this way, the study provided a realistic view of the disease, particularly in the number and frequency of genomic alterations. Each AML genome was compared to the normal genome derived from a skin sample of the same patient. Out of the 200 samples, 50 were analyzed by using whole genome sequencing, which is an examination of the complete DNA blueprint of the cells. Researchers analyzed the genome's protein-coding regions in the remaining samples, and used powerful new sequencing methods to look at changes in RNA in each case.

By studying a large number of AML cases, investigators were able to predict that they have identified virtually all of the mutations that occur in at least 5 percent of AML patients. Surprisingly, they found that overall, AML genomes have relatively few mutations, and such tumors are among the least mutated adult cancers. The average number of mutations in genes for each AML genome was 13, in contrast to solid tumors such as breast, lung or pancreatic cancer, which often have hundreds of mutated genes.

Because investigators found more than 1,600 genes that were mutated at least once in the 200 samples, they organized the recurrently mutated genes into nine categories based on their function or the known pathways involved. Some of these categories include tumor suppressor genes, signaling genes and epigenetic modifiers, with the latter being the most frequently mutated class of genes in the study. Epigenetic changes are alterations to DNA that often involve the addition or removal of chemical tags (such as methyl groups), which can affect when genes are turned on and off.

"This data set helps to integrate what was previously fragmented information," said study co-leader Timothy J. Ley, M.D., associate director for cancer genomics at The Genome Institute at Washington University School of Medicine in St. Louis. "We didn't realize how few recurrent mutations there were, and no one was thinking even five years ago that AML was associated with a high frequency of mutations in genes that encode epigenetic modifiers."

By finding comparatively few recurrently mutated genes, yet frequent alterations in genes that help control gene expression, the investigators may have narrowed the search for likely drug targets and disease markers.

Other results were also somewhat surprising. Researchers knew that mutations in signaling genes, which help control cell growth and development, were very common in AML, and thought that all AML samples may have at least one signaling gene mutation. But the TCGA findings showed that these genes are mutated in only 60 percent of cases. These include mutations in the gene FLT3, which occur in about a third of cases, making it one of the most commonly mutated genes in AML. FLT3 is important for normal blood cell development. The researchers also found that many AML patients have concurrent mutations in three commonly mutated genes: FLT3, NPM1 and DNMT3A. Patients with this combination of gene mutations appear to have a unique subtype of AML.

Investigators unexpectedly found recurring mutations in cohesin genes, which are important in cell division.

The study is the first to report a recurrently mutated microRNA gene in AML. MicroRNAs can play an important role in regulating gene expression, particularly in turning off gene activity.

Abnormal chromosome rearrangements and gene fusions (where two genes join to form a new, altered gene) are frequently useful in diagnosing and providing prognostic information for AML patients. The study uncovered many such fusions that had not been described before, and nearly half of the AML samples were found to have gene fusions.

Currently, only a few good markers exist to help guide treatment decisions for the majority of patients with intermediate risk. Some of the recurrently mutated genes identified in this study may allow for better prognostic information that will be relevant for AML patients.

"We've never had such a complete picture of AML, and this data set will be mined by researchers for years," said co-study leader Richard Wilson, Ph.D., director of Washington University's Genome Institute. "These findings have probably identified every pathway in which a modification - and perhaps new drugs - might be beneficial. They also further refine our understanding of the importance of individual mutations for disease classification and prognostication, and will help us build better disease models."

"These results will enable investigators to examine patient samples for mutation patterns and affected pathways, and to begin new studies to try to understand the relationships between these genetic mutations and treatment results," added Ley.

"This study of AML reinforces the value of the approach we are using to study the genomic diversity among tumors of many different cancer types and even within a single kind of cancer such as AML," noted NCI Director Harold Varmus, M.D. "Only such a systematic analysis of cancer types could have uncovered such clear patterns, such as the apparent importance in AML of genetic mutations that lead to changes in gene expression and cell traits."

This work was supported by the following grants: U24CA143845, U24CA143858, U24CA144025, U24CA143882, U24CA143866, U24CA143867, U24CA143848, U24CA143840, U24CA143835, U24CA143799, U24CA143883, U24CA143843, U54HG003067, U54HG003079, U54HG003273, and P01CA101937.

Reference: The Cancer Genome Atlas Network. Genomic and epigenomic landscape of adult de novo acute myeloid leukemia. New England Journal of Medicine. Online May 1, 2013. In print May 30, 2013. DOI: 10.1056/NEJMoa1301689.

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