The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations of neoplastic cells harboring distinct mutations. A fine resolution view of this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all of which may have clinical implications. Single tumor analysis already contributes to understanding these phenomena. However, cryptic subclones are frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating that accurately characterizing a tumor requires analyzing multiple samples from the same patient. To address this need, we present SciClone, a computational method that identifies the number and genetic composition of subclones by analyzing the variant allele frequencies of somatic mutations. We use it to detect subclones in acute myeloid leukemia and breast cancer samples that, though present at disease onset, are not evident from a single primary tumor sample. By doing so, we can track tumor evolution and identify the spatial origins of cells resisting therapy.
Sequencing the genomic DNA of cancers has revealed that tumors are not homogeneous. As a tumor grows, new mutations accumulate in individual cells, and as these cells replicate, the mutations are passed on to their offspring, which comprise only a portion of the tumor when it is sampled. We present a method for identifying the fraction of cells containing specific mutations, clustering them into subclonal populations, and tracking the changes in these subclones. This allows us to follow the clonal evolution of cancers as they respond to chemotherapy or develop therapy resistance, processes which may radically alter the subclonal composition of a tumor. It also gives us insight into the spatial organization of tumors, and we show that multiple biopsies from a single breast cancer may harbor different subclones that respond differently to treatment. Finally, we show that sequencing multiple samples from a patient's tumor is often critical, as it reveals cryptic subclones that cannot be discerned from only one sample. This is the first tool that can efficiently leverage multiple samples to identify these as distinct subpopulations of cells, thus contributing to understanding the biology of the tumor and influencing clinical decisions about therapy.
We report the first large-scale exome-wide analysis of the combined germline-somatic landscape in ovarian cancer. Here we analyze germline and somatic alterations in 429 ovarian carcinoma cases and 557 controls. We identify 3,635 high confidence, rare truncation and 22,953 missense variants with predicted functional impact. We find germline truncation variants and large deletions across Fanconi pathway genes in 20% of cases. Enrichment of rare truncations is shown in BRCA1, BRCA2, and PALB2. Additionally, we observe germline truncation variants in genes not previously associated with ovarian cancer susceptibility (NF1, MAP3K4, CDKN2B, and MLL3). Evidence for loss of heterozygosity was found in 100% and 76% of cases with germline BRCA1 and BRCA2 truncations respectively. Germline-somatic interaction analysis combined with extensive bioinformatics annotation identifies 237 candidate functional germline truncation and missense variants, including 2 pathogenic BRCA1 and 1 TP53 deleterious variants. Finally, integrated analyses of germline and somatic variants identify significantly altered pathways, including the Fanconi, MAPK, and MLL pathways.
Next-generation sequencing has been used to infer the clonality of heterogeneous tumor samples. These analyses yield specific predictions—the population frequency of individual clones, their genetic composition, and their evolutionary relationships—which we set out to test by sequencing individual cells from three subjects diagnosed with secondary acute myeloid leukemia, each of whom had been previously characterized by whole genome sequencing of unfractionated tumor samples. Single-cell mutation profiling strongly supported the clonal architecture implied by the analysis of bulk material. In addition, it resolved the clonal assignment of single nucleotide variants that had been initially ambiguous and identified areas of previously unappreciated complexity. Accordingly, we find that many of the key assumptions underlying the analysis of tumor clonality by deep sequencing of unfractionated material are valid. Furthermore, we illustrate a single-cell sequencing strategy for interrogating the clonal relationships among known variants that is cost-effective, scalable, and adaptable to the analysis of both hematopoietic and solid tumors, or any heterogeneous population of cells.
Human cancers are genetically diverse populations of cells that evolve over the course of their natural history or in response to the selective pressure of therapy. In theory, it is possible to infer how this variation is structured into related populations of cells based on the frequency of individual mutations in bulk samples, but the accuracy of these models has not been evaluated across a large number of variants in individual cells. Here, we report a strategy for analyzing hundreds of variants within a single cell, and we apply this method to assess models of tumor clonality derived from bulk samples in three cases of leukemia. The data largely support the predicted population structure, though they suggest specific refinements. This type of approach not only illustrates the biological complexity of human cancer, but it also has the potential to inform patient management. That is, precise knowledge of which variants are present in which populations of cells may allow physicians to more effectively target combinations of mutations and predict how patients will respond to therapy.
Most mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability, driving clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of AML samples with a known initiating event (PML-RARA) vs. normal karyotype AML samples, and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is “captured” as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse.
The acute myeloid leukemia (AML) genome has been the subject of intensive research over the past four decades. New technologies, enabling characterization of the AML genome at increased resolution, have revealed deeper layers of complexity that have provided insights into the biological basis of this disease, nominated targets for therapy, and identified biomarkers predictive of response to therapy or long-term prognosis. Still, our understanding of AML genomics is incomplete. Recent publications have demonstrated that whole genome sequencing (WGS) of primary AML samples is feasible and can detect novel, clinically relevant mutations. New insights are emerging from this work, including the clonal heterogeneity of this disease and clonal evolution that occurs over time. Some of the novel mutations are highly recurrent (>20% of patients), but there appears to be a continuum of mutation frequency down to rare (<5%) or even singleton mutations that may be relevant for the biology of this disease. Large cohorts of well-annotated samples are needed to establish mutation frequencies, implicate biological pathways, and demonstrate genotype:phenotype correlations. Although many technical and logistical challenges must be overcome, the capacity of WGS to detect all classes of inherited and acquired genetic abnormalities makes it an attractive candidate for development as a clinical diagnostic test.
acute myeloid leukemia; genomics; next generation sequencing
The myelodysplastic syndromes are a group of hematologic disorders that often evolve into secondary acute myeloid leukemia (AML). The genetic changes that underlie progression from the myelodysplastic syndromes to secondary AML are not well understood.
We performed whole-genome sequencing of seven paired samples of skin and bone marrow in seven subjects with secondary AML to identify somatic mutations specific to secondary AML. We then genotyped a bone marrow sample obtained during the antecedent myelodysplastic-syndrome stage from each subject to determine the presence or absence of the specific somatic mutations. We identified recurrent mutations in coding genes and defined the clonal architecture of each pair of samples from the myelodysplastic-syndrome stage and the secondary-AML stage, using the allele burden of hundreds of mutations.
Approximately 85% of bone marrow cells were clonal in the myelodysplastic-syndrome and secondary-AML samples, regardless of the myeloblast count. The secondary-AML samples contained mutations in 11 recurrently mutated genes, including 4 genes that have not been previously implicated in the myelodysplastic syndromes or AML. In every case, progression to acute leukemia was defined by the persistence of an antecedent founding clone containing 182 to 660 somatic mutations and the outgrowth or emergence of at least one subclone, harboring dozens to hundreds of new mutations. All founding clones and subclones contained at least one mutation in a coding gene.
Nearly all the bone marrow cells in patients with myelodysplastic syndromes and secondary AML are clonally derived. Genetic evolution of secondary AML is a dynamic process shaped by multiple cycles of mutation acquisition and clonal selection. Recurrent gene mutations are found in both founding clones and daughter subclones. (Funded by the National Institutes of Health and others.)
Most patients with acute myeloid leukemia (AML) die from progressive disease after relapse, which is associated with clonal evolution at the cytogenetic level1,2. To determine the mutational spectrum associated with relapse, we sequenced the primary tumor and relapse genomes from 8 AML patients, and validated hundreds of somatic mutations using deep sequencing; this allowed us to precisely define clonality and clonal evolution patterns at relapse. Besides discovering novel, recurrently mutated genes (e.g. WAC, SMC3, DIS3, DDX41, and DAXX) in AML, we found two major clonal evolution patterns during AML relapse: 1) the founding clone in the primary tumor gained mutations and evolved into the relapse clone, or 2) a subclone of the founding clone survived initial therapy, gained additional mutations, and expanded at relapse. In all cases, chemotherapy failed to eradicate the founding clone. The comparison of relapse-specific vs. primary tumor mutations in all 8 cases revealed an increase in transversions, probably due to DNA damage caused by cytotoxic chemotherapy. These data demonstrate that AML relapse is associated with the addition of new mutations and clonal evolution, which is shaped in part by the chemotherapy that the patients receive to establish and maintain remissions.
The aim of this study was to determine the association between age and stage at diagnosis of breast cancer with the subsequent development of acute myeloid leukemia (AML). The National Cancer Institute’s Surveillance, Epidemiology, and End Results program were analyzed for incidence of second malignancies by age and stage at diagnosis of breast cancer. 420,076 female patients were identified. There was an age dependent risk of a subsequent diagnosis of AML in women younger than 50 years old (RR 4.14; P <0.001) and women 50–64 years old (RR 2.19; P <0.001), but not those 65 and older (RR 1.19; P = 0.123) when compared with the expected incidence of AML. A similar age dependent pattern was observed for second breast and ovarian cancers. There was also a stage dependent increase in risk of subsequent AML in younger women with stage III disease when compared with stage I disease (RR 2.92; P = 0.004), and to a lesser extent in middle age women (RR 2.24; P = 0.029), but not in older women (RR 0.79; P = 0.80).Younger age and stage III disease at the time of breast cancer diagnosis are associated with increased risk of a subsequent diagnosis of AML. This association maybe explained by either greater chemotherapy exposure or an interaction between therapy and genetic predisposition.
Therapy-related acute myeloid leukemia; Breast cancer; Chemotherapy; SEER; Epidemiology; Radiation therapy
Myelodysplastic syndromes (MDS) are hematopoietic stem cell disorders that often progress to chemotherapy-resistant secondary acute myeloid leukemia (sAML). We used whole genome sequencing to perform an unbiased comprehensive screen to discover all the somatic mutations in a sAML sample and genotyped these loci in the matched MDS sample. Here we show that a missense mutation affecting the serine at codon 34 (S34) in U2AF1 was recurrently mutated in 13/150 (8.7%) de novo MDS patients, with suggestive evidence of an associated increased risk of progression to sAML. U2AF1 is a U2 auxiliary factor protein that recognizes the AG splice acceptor dinucleotide at the 3′ end of introns and mutations are located in highly conserved zinc fingers in U2AF11,2. Mutant U2AF1 promotes enhanced splicing and exon skipping in reporter assays in vitro. This novel, recurrent mutation in U2AF1 implicates altered pre-mRNA splicing as a potential mechanism for MDS pathogenesis.
Alterations in DNA methylation have been implicated in the pathogenesis of myelodysplastic syndromes (MDS), although the underlying mechanism remains largely unknown. Methylation of CpG dinucleotides is mediated by DNA methyltransferases, including DNMT1, DNMT3A, and DNMT3B. DNMT3A mutations have recently been reported in patients with de novo acute myeloid leukemia (AML), providing a rationale for examining the status of DNMT3A in MDS samples. Here, we report the frequency of DNMT3A mutations in patients with de novo MDS, and their association with secondary AML. We sequenced all coding exons of DNMT3A using DNA from bone marrow and paired normal cells from 150 patients with MDS and identified 13 heterozygous mutations with predicted translational consequences in 12/150 patients (8.0%). Amino acid R882, located in the methyltransferase domain of DNMT3A, was the most common mutation site, accounting for 4/13 mutations. DNMT3A mutations were expressed in the majority of cells in all tested mutant samples regardless of blast counts, suggesting that DNMT3A mutations occur early in the course of MDS. Patients with DNMT3A mutations had worse overall survival compared to patients without DNMT3A mutations (p=0.005) and more rapid progression to AML (p=0.007), suggesting that DNMT3A mutation status may have prognostic value in de novo MDS.
myelodysplastic syndrome; DNMT3A; mutation
The full complement of DNA mutations that are responsible for the pathogenesis of acute myeloid leukemia (AML) is not yet known.
We used massively parallel DNA sequencing to obtain a very high level of coverage (approximately 98%) of a primary, cytogenetically normal, de novo genome for AML with minimal maturation (AML-M1) and a matched normal skin genome.
We identified 12 acquired (somatic) mutations within the coding sequences of genes and 52 somatic point mutations in conserved or regulatory portions of the genome. All mutations appeared to be heterozygous and present in nearly all cells in the tumor sample. Four of the 64 mutations occurred in at least 1 additional AML sample in 188 samples that were tested. Mutations in NRAS and NPM1 had been identified previously in patients with AML, but two other mutations had not been identified. One of these mutations, in the IDH1 gene, was present in 15 of 187 additional AML genomes tested and was strongly associated with normal cytogenetic status; it was present in 13 of 80 cytogenetically normal samples (16%). The other was a nongenic mutation in a genomic region with regulatory potential and conservation in higher mammals; we detected it in one additional AML tumor. The AML genome that we sequenced contains approximately 750 point mutations, of which only a small fraction are likely to be relevant to pathogenesis.
By comparing the sequences of tumor and skin genomes of a patient with AML-M1, we have identified recurring mutations that may be relevant for pathogenesis.
The genetic alterations responsible for an adverse outcome in most patients with acute myeloid leukemia (AML) are unknown.
Using massively parallel DNA sequencing, we identified a somatic mutation in DNMT3A, encoding a DNA methyltransferase, in the genome of cells from a patient with AML with a normal karyotype. We sequenced the exons of DNMT3A in 280 additional patients with de novo AML to define recurring mutations.
A total of 62 of 281 patients (22.1%) had mutations in DNMT3A that were predicted to affect translation. We identified 18 different missense mutations, the most common of which was predicted to affect amino acid R882 (in 37 patients). We also identified six frameshift, six nonsense, and three splice-site mutations and a 1.5-Mbp deletion encompassing DNMT3A. These mutations were highly enriched in the group of patients with an intermediate-risk cytogenetic profile (56 of 166 patients, or 33.7%) but were absent in all 79 patients with a favorable-risk cytogenetic profile (P<0.001 for both comparisons). The median overall survival among patients with DNMT3A mutations was significantly shorter than that among patients without such mutations (12.3 months vs. 41.1 months, P<0.001). DNMT3A mutations were associated with adverse outcomes among patients with an intermediate-risk cytogenetic profile or FLT3 mutations, regardless of age, and were independently associated with a poor outcome in Cox proportional-hazards analysis.
DNMT3A mutations are highly recurrent in patients with de novo AML with an intermediate-risk cytogenetic profile and are independently associated with a poor outcome. (Funded by the National Institutes of Health and others.)
The identification of patients with inherited cancer susceptibility syndromes facilitates early diagnosis, prevention, and treatment. However, in many cases of suspected cancer susceptibility, the family history is unclear and genetic testing of common cancer susceptibility genes is unrevealing.
To apply whole-genome sequencing to a patient with suspected cancer susceptibility (and lacking a clear family history of cancer and no BRCA1 and BRCA2 mutations) to identify rare or novel germline variants in cancer susceptibility genes.
Design, Setting, and Participant
Skin (normal) and bone marrow (leukemia) DNA were obtained from a patient with early-onset breast and ovarian cancer and therapy-related acute myeloid leukemia (t-AML), and analyzed with: 1) whole genome sequencing using paired end reads; 2) SNP genotyping; 3) RNA expression profiling; and 4) spectral karyotyping.
Main Outcome Measures
Structural variants, copy number alterations, single nucleotide variants and small insertions and deletions (indels) were detected and validated using the above platforms.
Whole genome sequencing revealed a novel, heterozygous 3 Kb deletion removing exons 7-9 of TP53 in the patient’s normal skin DNA, which was homozygous in the leukemia DNA as a result of uniparental disomy. In addition, a total of 28 validated somatic single nucleotide variations or indels in coding genes, 8 somatic structural variants, and 12 somatic copy number alterations were detected in the patient’s leukemia genome.
Whole genome sequencing can identify novel, cryptic variants in cancer susceptibility genes in addition to providing unbiased information on the spectrum of mutations in a cancer genome.
Whole genome sequencing (WGS) is becoming increasingly available for research purposes, but it has not yet been routinely used for clinical diagnosis.
To determine whether whole genome sequencing can identify cryptic, actionable mutations in a clinically relevant time frame.
Design, Setting, and Patient
We were referred a difficult diagnostic case of acute promyelocytic leukemia with no pathogenic X-RARA fusion identified by routine metaphase cytogenetics or interphase FISH. The patient was enrolled in an IRB approved protocol, with consent specifically tailored to the implications of whole genome sequencing. The protocol employs a ‘movable firewall,’ which maintains patient anonymity within the entire research team, but allows the research team to communicate medically relevant information to the treating physician.
Main Outcome Measure
Clinical relevance of whole genome sequencing and time to communicate validated results to the treating physician.
Massively parallel paired-end sequencing allowed us to identify a cytogenetically cryptic event: 77 kilobases from chromosome 15 was inserted en bloc into the second intron of the RARA gene on chromosome 17, resulting in a classic bcr3 PML-RARA fusion gene. RT-PCR subsequently validated the expression of the fusion transcript. Novel FISH probes identified two additional cases of t(15;17)-negative acute promyelocytic leukemia that had cytogenetically invisible insertions. Whole genome sequencing and validation were completed in seven weeks, and changed the treatment plan for the patient.
Whole genome sequencing can identify cytogenetically invisible oncogenes in a clinically relevant timeframe.
The natural killer gene complex (NKC) on chromosome 6 contains clusters of genes that encode both activation and inhibitory receptors expressed on mouse natural killer (NK) cells. NKC genes, particularly belonging to the Nkrp1 and Ly49 gene families, display haplotype differences between different mouse strains and allelic polymorphisms of individual genes, as previously revealed by conventional analysis in a small number of inbred mouse strains. Herein we used array-based comparative genomic hybridization (aCGH) to efficiently compare the NKC in 21 mouse strains to the reference C57BL/6 strain. By using unsupervised clustering methods, we could sort these variations into the same groups as determined by previous RFLP analyses of Nkrp1 and Ly49 genes. Prospective analyses of aCGH and RFLP data validated these relationships. Moreover, aCGH data predicted monoclonal antibody reactivity with an allospecific determinant on molecules expressed by NK cells. Taken together, these data demonstrate the structural variation in the NKC between mouse strains as well as the usefulness of aCGH in analysis of complex, polymorphic gene clusters.
Natural killer (NK) cells; natural killer gene complex (NKC); array-based comparative genomic hybridization (aCGH); RFLPs
Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML). It is characterized by the t(15;17)(q22;q11.2) chromosomal translocation that creates the promyelocytic leukemia–retinoic acid receptor α (PML-RARA) fusion oncogene. Although this fusion oncogene is known to initiate APL in mice, other cooperating mutations, as yet ill defined, are important for disease pathogenesis. To identify these, we used a mouse model of APL, whereby PML-RARA expressed in myeloid cells leads to a myeloproliferative disease that ultimately evolves into APL. Sequencing of a mouse APL genome revealed 3 somatic, nonsynonymous mutations relevant to APL pathogenesis, of which 1 (Jak1 V657F) was found to be recurrent in other affected mice. This mutation was identical to the JAK1 V658F mutation previously found in human APL and acute lymphoblastic leukemia samples. Further analysis showed that JAK1 V658F cooperated in vivo with PML-RARA, causing a rapidly fatal leukemia in mice. We also discovered a somatic 150-kb deletion involving the lysine (K)-specific demethylase 6A (Kdm6a, also known as Utx) gene, in the mouse APL genome. Similar deletions were observed in 3 out of 14 additional mouse APL samples and 1 out of 150 human AML samples. In conclusion, whole genome sequencing of mouse cancer genomes can provide an unbiased and comprehensive approach for discovering functionally relevant mutations that are also present in human leukemias.
Therapy-related acute myeloid leukemia (t-AML) is a secondary, generally incurable, malignancy attributable to chemotherapy exposure. Although there is a genetic component to t-AML susceptibility in mice, the relevant loci and the mechanism(s) by which they contribute to t-AML are largely unknown. An improved understanding of susceptibility factors and the biological processes in which they act may lead to the development of t-AML prevention strategies.
In this work we applied an integrated genomics strategy in inbred strains of mice to find novel factors that might contribute to susceptibility. We found that the pre-exposure transcriptional state of hematopoietic stem/progenitor cells predicts susceptibility status. More than 900 genes were differentially expressed between susceptible and resistant strains and were highly enriched in the apoptotic program, but it remained unclear which genes, if any, contribute directly to t-AML susceptibility. To address this issue, we integrated gene expression data with genetic information, including single nucleotide polymorphisms (SNPs) and DNA copy number variants (CNVs), to identify genetic networks underlying t-AML susceptibility. The 30 t-AML susceptibility networks we found are robust: they were validated in independent, previously published expression data, and different analytical methods converge on them. Further, the networks are enriched in genes involved in cell cycle and DNA repair (pathways not discovered in traditional differential expression analysis), suggesting that these processes contribute to t-AML susceptibility. Within these networks, the putative regulators (e.g., Parp2, Casp9, Polr1b) are the most likely to have a non-redundant role in the pathogenesis of t-AML. While identifying these networks, we found that current CNVR and SNP-based haplotype maps in mice represented distinct sources of genetic variation contributing to expression variation, implying that mapping studies utilizing either source alone will have reduced sensitivity.
The identification and prioritization of genes and networks not previously implicated in t-AML generates novel hypotheses on the biology and treatment of this disease that will be the focus of future research.
The t(8;21)(q22;q22) translocation, present in ~5% of adult acute myeloid leukemia (AML) cases, produces the AML1/ETO fusion protein. Dysregulation of the POU domain-containing transcription factor POU4F1 is a recurring abnormality in t(8;21) AML. Here, we show that POU4F1 over-expression is highly correlated with, but not caused by AML1/ETO. AML1/ETO markedly increases the self-renewal capacity of myeloid progenitors from murine bone marrow or fetal liver and drives expansion of these cells in liquid culture. POU4F1 is neither necessary nor sufficient for these AML1/ETO-dependent properties, suggesting that it contributes to leukemia through novel mechanisms. To identify targets of POU4F1, we performed gene expression profiling in primary mouse cells with genetically defined levels of POU4F1 and identified 140 differentially expressed genes. This expression signature was significantly enriched in human t(8;21) AML samples and was sufficient to cluster t(8;21) AML samples in an unsupervised hierarchical analysis. Among the most highly differentially expressed genes, half are known AML1/ETO targets, implying that the unique transcriptional signature of t(8;21) AML is, in part, attributable to POU4F1 and not AML1/ETO itself. These genes provide novel candidates for understanding the biology and developing therapeutic approaches for t(8;21) AML.
POU4F1; AML1/ETO; acute myeloid leukemia; gene expression profiling
The systematic karyotyping of bone marrow cells was the first genomic approach used to personalize therapy for patients with leukemia. The paradigm established by cytogenetic studies in leukemia (from gene discovery to therapeutic intervention) now has the potential to be rapidly extended with the use of whole-genome sequencing approaches for cancer, which are now possible. We are now entering a period of exponential growth in cancer gene discovery that will provide many novel therapeutic targets for a large number of cancer types. Establishing the pathogenetic relevance of individual mutations is a major challenge that must be solved. However, after thousands of cancer genomes have been sequenced, the genetic rules of cancer will become known and new approaches for diagnosis, risk stratification and individualized treatment of cancer patients will surely follow.
array CGH; cancer; comparative genomic hybridization; genomics; next-generation sequencing; SNP array
The extent to which differences in germ line DNA copy number contribute to natural phenotypic variation is unknown. We analyzed the copy number content of the mouse genome to a sub-10 kb resolution. We identified over 1,300 copy number variant regions (CNVRs), most of which are < 10 kb in length, are found in more than one strain, and, in total, span 3.2% (85 Mb) of the genome. To assess the potential functional impact of copy number variation, we mapped expression profiles of purified hematopoietic stem/progenitor cells, adipose tissue and hypothalamus to CNVRs in cis. Of the more than 600 significant associations between CNVRs and expression profiles, most map to CNVRs outside of the transcribed regions of genes. In hematopoietic stem/progenitor cells, up to 28% of strain-dependent expression variation is associated with copy number variation, supporting the role of germ line CNVs as major contributors to natural phenotypic variation in the laboratory mouse.
Acute myeloid leukemia is a highly malignant hematopoietic tumor that affects about 13,000 adults yearly in the United States. The treatment of this disease has changed little in the past two decades, since most of the genetic events that initiate the disease remain undiscovered. Whole genome sequencing is now possible at a reasonable cost and timeframe to utilize this approach for unbiased discovery of tumor-specific somatic mutations that alter the protein-coding genes. Here we show the results obtained by sequencing a typical acute myeloid leukemia genome and its matched normal counterpart, obtained from the patient’s skin. We discovered 10 genes with acquired mutations; two were previously described mutations thought to contribute to tumor progression, and 8 were novel mutations present in virtually all tumor cells at presentation and relapse, whose function is not yet known. Our study establishes whole genome sequencing as an unbiased method for discovering initiating mutations in cancer genomes, and for identifying novel genes that may respond to targeted therapies.
We used massively parallel sequencing technology to sequence the genomic DNA of tumor and normal skin cells obtained from a patient with a typical presentation of FAB M1 Acute Myeloid Leukemia (AML) with normal cytogenetics. 32.7-fold ‘haploid’ coverage (98 billion bases) was obtained for the tumor genome, and 13.9-fold coverage (41.8 billion bases) was obtained for the normal sample. Of 2,647,695 well-supported Single Nucleotide Variants (SNVs) found in the tumor genome, 2,588,486 (97.7%) also were detected in the patient’s skin genome, limiting the number of variants that required further study. For the purposes of this initial study, we restricted our downstream analysis to the coding sequences of annotated genes: we found only eight heterozygous, non-synonymous somatic SNVs in the entire genome. All were novel, including mutations in protocadherin/cadherin family members (CDH24 and PCLKC), G-protein coupled receptors (GPR123 and EBI2), a protein phosphatase (PTPRT), a potential guanine nucleotide exchange factor (KNDC1), a peptide/drug transporter (SLC15A1), and a glutamate receptor gene (GRINL1B). We also detected previously described, recurrent somatic insertions in the FLT3 and NPM1 genes. Based on deep readcount data, we determined that all of these mutations (except FLT3) were present in nearly all tumor cells at presentation, and again at relapse 11 months later, suggesting that the patient had a single dominant clone containing all of the mutations. These results demonstrate the power of whole genome sequencing to discover novel cancer-associated mutations.
Deletions spanning chromosome 5q31.2 are among the most common recurring cytogenetic abnormalities detectable in myelodysplastic syndromes (MDS). Prior genomic studies have suggested that haploinsufficiency of multiple 5q31.2 genes may contribute to MDS pathogenesis. However, this hypothesis has never been formally tested. Therefore, we designed this study to systematically and comprehensively evaluate all 28 chromosome 5q31.2 genes and directly test whether haploinsufficiency of a single 5q31.2 gene may result from a heterozygous nucleotide mutation or microdeletion. We selected paired tumor (bone marrow) and germline (skin) DNA samples from 46 de novo MDS patients (37 without a cytogenetic 5q31.2 deletion) and performed total exonic gene resequencing (479 amplicons) and array comparative genomic hybridization (CGH). We found no somatic nucleotide changes in the 46 MDS samples, and no cytogenetically silent 5q31.2 deletions in 20/20 samples analyzed by array CGH. Twelve novel single nucleotide polymorphisms were discovered. The mRNA levels of 7 genes in the commonly deleted interval were reduced by 50% in CD34+ cells from del(5q) MDS samples, and no gene showed complete loss of expression. Taken together, these data show that small deletions and/or point mutations in individual 5q31.2 genes are not common events in MDS, and implicate haploinsufficiency of multiple genes as the relevant genetic consequence of this common deletion.
Copy number variants (CNVs) are currently defined as genomic sequences that are polymorphic in copy number and range in length from 1000 to several million base pairs. Among current array-based CNV detection platforms, long-oligonucleotide arrays promise the highest resolution. However, the performance of currently available analytical tools suffers when applied to these data because of the lower signal:noise ratio inherent in oligonucleotide-based hybridization assays. We have developed wuHMM, an algorithm for mapping CNVs from array comparative genomic hybridization (aCGH) platforms comprised of 385 000 to more than 3 million probes. wuHMM is unique in that it can utilize sequence divergence information to reduce the false positive rate (FPR). We apply wuHMM to 385K-aCGH, 2.1M-aCGH and 3.1M-aCGH experiments comparing the 129X1/SvJ and C57BL/6J inbred mouse genomes. We assess wuHMM's performance on the 385K platform by comparison to the higher resolution platforms and we independently validate 10 CNVs. The method requires no training data and is robust with respect to changes in algorithm parameters. At a FPR of <10%, the algorithm can detect CNVs with five probes on the 385K platform and three on the 2.1M and 3.1M platforms, resulting in effective resolutions of 24 kb, 2–5 kb and 1 kb, respectively.
Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.
A major goal of genetics and genomics is to understand how genetic differences between individuals (genotypes) translate into variation in disease susceptibility, behavior, and many other organism-level characteristics (phenotypes). While the sizes of genetic variants range from a single base to whole chromosomes, historically, only the extreme ends of this spectrum have been explored. DNA copy number variants (CNVs) lie between these two extremes, ranging in size from hundreds to millions of bases. The recent application of microarray technology to detect genetic variation in humans has led to the realization that CNVs are common. In fact, rough estimates indicate that CNVs and small-scale variants may constitute similar proportions of total genomic DNA. In this report, the authors characterize 80 CNVs across the genomes of 21 inbred strains of mice. The identification and characterization of mouse CNVs are important because inbred strains of mice are the most widely used model system to explore biomedical genetics. These CNVs are located near another class of genomic features, segmental duplications, more often than would be expected by chance, which supports the hypothesis that CNVs and segmental duplications are causally linked. Importantly, many of the CNVs contain known genes and thus may underlie both gene expression and phenotypic variation between strains.