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• W2012753533 abstract "Most mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive 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 M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-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. Most mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive 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 M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-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. Normal HSPCs contain random background mutations that increase with aging AML genomes contain hundreds of mutations, but very few are recurrent Comparison of M1 and M3 AML genomes identifies initiating versus cooperating mutations Most AML mutations are probably background events in HSPCs, “captured” by cloning The molecular pathogenesis of acute myeloid leukemia (AML) has not yet been completely defined. Recurrent chromosomal structural variations (e.g., t(15;17), t(8;21), inv(16), t(9;21), t(9;11), del5, del7, etc.) are established diagnostic and prognostic markers, suggesting that acquired genetic abnormalities play an essential role in leukemogenesis (Betz and Hess, 2010Betz B.L. Hess J.L. Acute myeloid leukemia diagnosis in the 21st century.Arch. Pathol. Lab. Med. 2010; 134: 1427-1433PubMed Google Scholar). However, nearly 50% of AML cases have a normal karyotype (NK), and many of these lack recurrent structural abnormalities, even with high density comparative genomic hybridization (CGH) or SNP arrays (Bullinger et al., 2010Bullinger L. Krönke J. Schön C. Radtke I. Urlbauer K. Botzenhardt U. Gaidzik V. Carió A. Senger C. Schlenk R.F. et al.Identification of acquired copy number alterations and uniparental disomies in cytogenetically normal acute myeloid leukemia using high-resolution single-nucleotide polymorphism analysis.Leukemia. 2010; 24: 438-449Crossref PubMed Scopus (100) Google Scholar; Suela et al., 2007Suela J. Alvarez S. Cigudosa J.C. DNA profiling by arrayCGH in acute myeloid leukemia and myelodysplastic syndromes.Cytogenet. Genome Res. 2007; 118: 304-309Crossref PubMed Scopus (40) Google Scholar; Walter et al., 2009Walter M.J. Payton J.E. Ries R.E. Shannon W.D. Deshmukh H. Zhao Y. Baty J. Heath S. Westervelt P. Watson M.A. et al.Acquired copy number alterations in adult acute myeloid leukemia genomes.Proc. Natl. Acad. Sci. USA. 2009; 106: 12950-12955Crossref PubMed Scopus (207) Google Scholar). Targeted sequencing efforts have identified several mutations that carry diagnostic and prognostic information, including mutations in FLT3, NPM1, KIT, CEBPA, and TET2 (reviewed in (Bacher et al., 2010Bacher U. Schnittger S. Haferlach T. Molecular genetics in acute myeloid leukemia.Curr. Opin. Oncol. 2010; 22: 646-655Crossref PubMed Scopus (55) Google Scholar; Stirewalt and Radich, 2003Stirewalt D.L. Radich J.P. The role of FLT3 in haematopoietic malignancies.Nat. Rev. Cancer. 2003; 3: 650-665Crossref PubMed Scopus (703) Google Scholar)). The advent of massively parallel sequencing enabled the discovery of recurrent mutations in DNMT3A (Ley et al., 2010Ley T.J. Ding L. Walter M.J. McLellan M.D. Lamprecht T. Larson D.E. Kandoth C. Payton J.E. Baty J. Welch J. et al.DNMT3A mutations in acute myeloid leukemia.N. Engl. J. Med. 2010; 363: 2424-2433Crossref PubMed Scopus (1523) Google Scholar; Yamashita et al., 2010Yamashita Y. Yuan J. Suetake I. Suzuki H. Ishikawa Y. Choi Y.L. Ueno T. Soda M. Hamada T. Haruta H. et al.Array-based genomic resequencing of human leukemia.Oncogene. 2010; 29: 3723-3731Crossref PubMed Scopus (210) Google Scholar) and IDH1 (Mardis et al., 2009Mardis E.R. Ding L. Dooling D.J. Larson D.E. McLellan M.D. Chen K. Koboldt D.C. Fulton R.S. Delehaunty K.D. McGrath S.D. et al.Recurring mutations found by sequencing an acute myeloid leukemia genome.N. Engl. J. Med. 2009; 361: 1058-1066Crossref PubMed Scopus (1800) Google Scholar). Despite these efforts, more than 25% of AML patients carry no mutations in the known leukemia-associated genes (Shen et al., 2011Shen Y. Zhu Y.M. Fan X. Shi J.Y. Wang Q.R. Yan X.J. Gu Z.H. Wang Y.Y. Chen B. Jiang C.L. et al.Gene mutation patterns and their prognostic impact in a cohort of 1185 patients with acute myeloid leukemia.Blood. 2011; 118: 5593-5603Crossref PubMed Scopus (277) Google Scholar). Furthermore, defining the molecular consequences of recurring mutations (e.g., whether a mutation is an initiating or a cooperating event) has been challenging. PML-RARA is one of the best-characterized leukemia-initiating mutations. This fusion gene results from t(15;17)(q22;21) and is associated exclusively with acute promyelocytic leukemia (APL, FAB M3 AML) (Allford et al., 1999Allford S. Grimwade D. Langabeer S. Duprez E. Saurin A. Chatters S. Walker H. Roberts P. Rogers J. Bain B. et al.The Medical Research Council (MRC) Adult Leukaemia Working PartyIdentification of the t(15;17) in AML FAB types other than M3: evaluation of the role of molecular screening for the PML/RARalpha rearrangement in newly diagnosed AML.Br. J. Haematol. 1999; 105: 198-207Crossref PubMed Scopus (46) Google Scholar; Rowley et al., 1977Rowley J.D. Golomb H.M. Vardiman J. Fukuhara S. Dougherty C. Potter D. Further evidence for a non-random chromosomal abnormality in acute promyelocytic leukemia.Int. J. Cancer. 1977; 20: 869-872Crossref PubMed Scopus (122) Google Scholar). Its expression is diagnostic of this single type of leukemia with unique clinical features (Sanz et al., 2009Sanz M.A. Grimwade D. Tallman M.S. Lowenberg B. Fenaux P. Estey E.H. Naoe T. Lengfelder E. Büchner T. Döhner H. et al.Management of acute promyelocytic leukemia: recommendations from an expert panel on behalf of the European LeukemiaNet.Blood. 2009; 113: 1875-1891Crossref PubMed Scopus (711) Google Scholar). Its presence predicts a near universal therapeutic response to a targeted agent, all-trans retinoic acid (ATRA), which is abrogated by mutations that inhibit ATRA binding to PML-RARA (Imaizumi et al., 1998Imaizumi M. Suzuki H. Yoshinari M. Sato A. Saito T. Sugawara A. Tsuchiya S. Hatae Y. Fujimoto T. Kakizuka A. et al.Mutations in the E-domain of RAR portion of the PML/RAR chimeric gene may confer clinical resistance to all-trans retinoic acid in acute promyelocytic leukemia.Blood. 1998; 92: 374-382PubMed Google Scholar; Larson and Le Beau, 2011Larson R.A. Le Beau M.M. Prognosis and therapy when acute promyelocytic leukemia and other “good risk” acute myeloid leukemias occur as a therapy-related myeloid neoplasm.Mediterr J Hematol Infect Dis. 2011; 3: e2011032Crossref PubMed Google Scholar; Takayama et al., 2001Takayama N. Kizaki M. Hida T. Kinjo K. Ikeda Y. Novel mutation in the PML/RARalpha chimeric gene exhibits dramatically decreased ligand-binding activity and confers acquired resistance to retinoic acid in acute promyelocytic leukemia.Exp. Hematol. 2001; 29: 864-872Abstract Full Text Full Text PDF PubMed Scopus (34) Google Scholar). Early myeloid expression of PML-RARA results in leukemia with promyelocytic features in multiple mouse models of the disease, although long latency (which can be shortened by radiation, alkylator treatment, or FLT3 ITD coexpression), suggests that PML-RARA requires cooperating events to cause leukemia (Funk et al., 2008Funk R.K. Maxwell T.J. Izumi M. Edwin D. Kreisel F. Ley T.J. Cheverud J.M. Graubert T.A. Quantitative trait loci associated with susceptibility to therapy-related acute murine promyelocytic leukemia in hCG-PML/RARA transgenic mice.Blood. 2008; 112: 1434-1442Crossref PubMed Scopus (13) Google Scholar; Kelly et al., 2002Kelly L.M. Kutok J.L. Williams I.R. Boulton C.L. Amaral S.M. Curley D.P. Ley T.J. Gilliland D.G. PML/RARalpha and FLT3-ITD induce an APL-like disease in a mouse model.Proc. Natl. Acad. Sci. USA. 2002; 99: 8283-8288Crossref PubMed Scopus (265) Google Scholar; Kogan, 2007Kogan S.C. Mouse models of acute promyelocytic leukemia.Curr. Top. Microbiol. Immunol. 2007; 313: 3-29PubMed Google Scholar; Sohal et al., 2003Sohal J. Phan V.T. Chan P.V. Davis E.M. Patel B. Kelly L.M. Abrams T.J. O’Farrell A.M. Gilliland D.G. Le Beau M.M. Kogan S.C. A model of APL with FLT3 mutation is responsive to retinoic acid and a receptor tyrosine kinase inhibitor, SU11657.Blood. 2003; 101: 3188-3197Crossref PubMed Scopus (85) Google Scholar; Walter et al., 2004Walter M.J. Park J.S. Lau S.K. Li X. Lane A.A. Nagarajan R. Shannon W.D. Ley T.J. Expression profiling of murine acute promyelocytic leukemia cells reveals multiple model-dependent progression signatures.Mol. Cell. Biol. 2004; 24: 10882-10893Crossref PubMed Scopus (25) Google Scholar). In this study, we sequenced the genomes of 24 AML cases. We chose to compare 12 genomes from patients with FAB M3 AML (where the initiating event is known) to 12 genomes from patients with AML without maturation (FAB M1) with normal cytogenetics, where the initiating event is less clear for most patients. In this and previous studies, we have demonstrated that AML genomes generally contain hundreds of mutations, that the total number of mutations per AML genome is related to the age of the patient, and that nearly all AML cells in the samples contain all of the mutations (although very few of these mutations are recurrent in AML or other malignancies) (Ding et al., 2012Ding L. Ley T.J. Larson D.E. Miller C.A. Koboldt D.C. Welch J.S. Ritchey J.K. Young M.A. Lamprecht T. McLellan M.D. et al.Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing.Nature. 2012; 481: 506-510Crossref PubMed Scopus (1539) Google Scholar; Ley et al., 2008Ley T.J. Mardis E.R. Ding L. Fulton B. McLellan M.D. Chen K. Dooling D. Dunford-Shore B.H. McGrath S. Hickenbotham M. et al.DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome.Nature. 2008; 456: 66-72Crossref PubMed Scopus (994) Google Scholar; Link et al., 2011Link D.C. Schuettpelz L.G. Shen D. Wang J. Walter M.J. Kulkarni S. Payton J.E. Ivanovich J. Goodfellow P.J. Le Beau M. et al.Identification of a novel TP53 cancer susceptibility mutation through whole-genome sequencing of a patient with therapy-related AML.JAMA. 2011; 305: 1568-1576Crossref PubMed Scopus (133) Google Scholar; Mardis et al., 2009Mardis E.R. Ding L. Dooling D.J. Larson D.E. McLellan M.D. Chen K. Koboldt D.C. Fulton R.S. Delehaunty K.D. McGrath S.D. et al.Recurring mutations found by sequencing an acute myeloid leukemia genome.N. Engl. J. Med. 2009; 361: 1058-1066Crossref PubMed Scopus (1800) Google Scholar; Welch et al., 2011bWelch J.S. Westervelt P. Ding L. Larson D.E. Klco J.M. Kulkarni S. Wallis J. Chen K. Payton J.E. Fulton R.S. et al.Use of whole-genome sequencing to diagnose a cryptic fusion oncogene.JAMA. 2011; 305: 1577-1584Crossref PubMed Scopus (210) Google Scholar). We show here that clonally derived hematopoietic cells from normal individuals also accumulate mutations as a function of age. This suggests that most of the mutations present in AML genomes were already present in the hematopoietic cell that was transformed by the initiating mutation; nearly all of these preexisting mutations are probably benign and irrelevant for pathogenesis. Consistent with this hypothesis, we observed that M1 and M3 genomes have similar numbers of total mutations and that M1 genomes contain unique mutations (e.g., DNMT3A, NPM1, IDH1, or TET2) that almost never occur in M3 cases. In addition, there are many mutations that are shared between the two subtypes (e.g., FLT3 ITD), suggesting that these mutations can cooperate with a variety of initiating mutations. Because the data are comprehensive for all 24 genomes, it also allows us to estimate the minimum number of recurring mutations that may be responsible for the pathogenesis of AML. We subjected 12 cases of NK M1 AML and 12 cases of t(15;17)-positive M3 AML to whole-genome sequencing (WGS) (case descriptions provided in Extended Experimental Procedures, summarized in Table S1 and Figure S1 available online). To identify somatic, AML-associated mutations, we subjected both the bone marrow (leukemic tissue) and skin (normal tissue) to WGS (average haploid coverage 28x, Figure 1A and Table S2); the mutations in the AML1 and AML2 genomes have been previously reported and deposited in dbGaP (Ding et al., 2012Ding L. Ley T.J. Larson D.E. Miller C.A. Koboldt D.C. Welch J.S. Ritchey J.K. Young M.A. Lamprecht T. McLellan M.D. et al.Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing.Nature. 2012; 481: 506-510Crossref PubMed Scopus (1539) Google Scholar; Ley et al., 2008Ley T.J. Mardis E.R. Ding L. Fulton B. McLellan M.D. Chen K. Dooling D. Dunford-Shore B.H. McGrath S. Hickenbotham M. et al.DNA sequencing of a cytogenetically normal acute myeloid leukaemia genome.Nature. 2008; 456: 66-72Crossref PubMed Scopus (994) Google Scholar; Mardis et al., 2009Mardis E.R. Ding L. Dooling D.J. Larson D.E. McLellan M.D. Chen K. Koboldt D.C. Fulton R.S. Delehaunty K.D. McGrath S.D. et al.Recurring mutations found by sequencing an acute myeloid leukemia genome.N. Engl. J. Med. 2009; 361: 1058-1066Crossref PubMed Scopus (1800) Google Scholar). They are included in this study for ease of reference. Because of the prevalence of false-positive calls in WGS (between 20%–50%, depending on the stringency of type I errors tolerated), we validated all single nucleotide variants (SNVs), small insertions and deletions (indels), and structural variants (SVs) identified in tiers 1, 2, or 3 (which contain the nonrepetitive portion of the genome (see Mardis et al., 2009Mardis E.R. Ding L. Dooling D.J. Larson D.E. McLellan M.D. Chen K. Koboldt D.C. Fulton R.S. Delehaunty K.D. McGrath S.D. et al.Recurring mutations found by sequencing an acute myeloid leukemia genome.N. Engl. J. Med. 2009; 361: 1058-1066Crossref PubMed Scopus (1800) Google Scholar for definitions of tiers) by using patient-specific custom NimbleGen capture arrays, followed by Illumina sequencing (Figure 1B). All subsequent analysis relies on these validated data and not on the primary genome discovery sequence. An average coverage of 972 reads per somatic variant was obtained at validation. We observed a higher validation frequency in tier 1 than in tier 2 and 3 (mean frequency 0.5 versus 0.35 and 0.29, p < 0.002 and p < 0.0001, respectively; Table S2), which may reflect the lower guanine and cytosine content and increased uniqueness of tier 1. Numbers of mutations and validation frequencies were similar across all tiers in M1 versus M3 genomes (Figures 1C–1E and Table S2). These data yielded a total of 10,563 validated somatic variants for the 24 genomes (average 440/genome) (Tables S2, S3, and S4). Indels were less frequent than SNVs in M1 and M3 AML (M1: average 19.1 per genome, range 4–45; M3: average 20.3 per genome, range 4–56), and occurred proportionally less often in tier 1 (average 1.4 per genome, range 0–4). Of these total somatic mutations, 319 occurred in the coding regions of 287 unique genes; an average of 10 somatic mutations had translational consequences in each genome (Table S3). A fusion event between PML and RARA was identified in all 12 M3 AML cases (Table S5). Only 43 additional structural variants (translocations, insertions, deletions, and inversions) were identified (median 2 per genome, range 0–8, Table S5). The t(15;17) breakpoints occurred in exon 5 and introns 3 and 5 of PML and within RARA intron 2 in all cases, as expected; two cases were associated with large deletions that are predicted to result in PML-RARA expression without reciprocal RARA-PML expression (Figure S2). None of the other structural variations found by WGS were identified with metaphase cytogenetics; most are predicted to be cryptic when examined by routine cytogenetics. The others may exist in minor leukemic subclones that were not otherwise detected, or in cells that did not expand during preparation for cytogenetic studies.Figure 1Coverage and Number of Validated SNVs by Tier per GenomeShow full caption(A) Gigabase pairs of sequence obtained for each genome assessed by whole-genome sequencing.(B) Mean number of reads obtained for each variant assessed per genome during validation.(C and D) Number of tier 1, 2, 3, and total variants validated in each sample.(E) Total number of validated SNVs by tier in M1 AML (red) versus M3 AML (blue) cases.(F) Total number of validated SNVs per genome in nonredundant regions (tier 1, 2, and 3) versus age of patient; M1 AML (red), M3 AML (blue). The R2 for the combined 24 cases is 0.5, p < 0.0001.See also Figures S1 and S2 and Table S1. Patient Clinical Characteristics, Table S2. Coverage and Variants, Table S3. Tier 1 Validated Somatic Variants in 24 AML Cases, Table S4. Tier 2 and 3 Validated Somatic Variants in 24 AML Cases.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure S2PML-RARA Breakpoints, Related to Figure 1Show full caption(A–C) Breakpoint positions within PML intron 3 (A), PML intron 5 (B), and RARA intron 2 (C). Blue triangles indicate breakpoint positions reported in this paper. Other triangles indicate previously reported breakpoint positions (orange: Hasan et al., 2008Hasan, S.K., Mays, A.N., Ottone, T., Ledda, A., La Nasa, G., Cattaneo, C., Borlenghi, E., Melillo, L., Montefusco, E., Cervera, J., et al. (2008). Molecular analysis of t(15;17) genomic breakpoints in secondary acute promyelocytic leukemia arising after treatment of multiple sclerosis. Blood 112, 3383–3390.Google Scholar; green: Hasan et al., 2010Hasan, S.K., Ottone, T., Schlenk, R.F., Xiao, Y., Wiemels, J.L., Mitra, M.E., Bernasconi, P., Di Raimondo, F., Stanghellini, M.T., Marco, P., et al. (2010). Analysis of t(15;17) chromosomal breakpoint sequences in therapy-related versus de novo acute promyelocytic leukemia: association of DNA breaks with specific DNA motifs at PML and RARA loci. Genes Chromosomes Cancer 49, 726–732.Google Scholar; Mistry et al., 2005Mistry, A.R., Felix, C.A., Whitmarsh, R.J., Mason, A., Reiter, A., Cassinat, B., Parry, A., Walz, C., Wiemels, J.L., Segal, M.R., et al. (2005). DNA topoisomerase II in therapy-related acute promyelocytic leukemia. N. Engl. J. Med. 352, 1529–1538.Google Scholar; purple: Reiter et al., 2003Reiter, A., Saussele, S., Grimwade, D., Wiemels, J.L., Segal, M.R., Lafage-Pochitaloff, M., Walz, C., Weisser, A., Hochhaus, A., Willer, A., et al. (2003). Genomic anatomy of the specific reciprocal translocation t(15;17) in acute promyelocytic leukemia. Genes Chromosomes Cancer 36, 175–188.Google Scholar).(D and E) Genomic PML-RARA rearrangements associated with a large deletion in PML (D). AML10 and (E) AML15.View Large Image Figure ViewerDownload Hi-res image Download (PPT) (A) Gigabase pairs of sequence obtained for each genome assessed by whole-genome sequencing. (B) Mean number of reads obtained for each variant assessed per genome during validation. (C and D) Number of tier 1, 2, 3, and total variants validated in each sample. (E) Total number of validated SNVs by tier in M1 AML (red) versus M3 AML (blue) cases. (F) Total number of validated SNVs per genome in nonredundant regions (tier 1, 2, and 3) versus age of patient; M1 AML (red), M3 AML (blue). The R2 for the combined 24 cases is 0.5, p < 0.0001. See also Figures S1 and S2 and Table S1. Patient Clinical Characteristics, Table S2. Coverage and Variants, Table S3. Tier 1 Validated Somatic Variants in 24 AML Cases, Table S4. Tier 2 and 3 Validated Somatic Variants in 24 AML Cases. (A–C) Breakpoint positions within PML intron 3 (A), PML intron 5 (B), and RARA intron 2 (C). Blue triangles indicate breakpoint positions reported in this paper. Other triangles indicate previously reported breakpoint positions (orange: Hasan et al., 2008Hasan, S.K., Mays, A.N., Ottone, T., Ledda, A., La Nasa, G., Cattaneo, C., Borlenghi, E., Melillo, L., Montefusco, E., Cervera, J., et al. (2008). Molecular analysis of t(15;17) genomic breakpoints in secondary acute promyelocytic leukemia arising after treatment of multiple sclerosis. Blood 112, 3383–3390.Google Scholar; green: Hasan et al., 2010Hasan, S.K., Ottone, T., Schlenk, R.F., Xiao, Y., Wiemels, J.L., Mitra, M.E., Bernasconi, P., Di Raimondo, F., Stanghellini, M.T., Marco, P., et al. (2010). Analysis of t(15;17) chromosomal breakpoint sequences in therapy-related versus de novo acute promyelocytic leukemia: association of DNA breaks with specific DNA motifs at PML and RARA loci. Genes Chromosomes Cancer 49, 726–732.Google Scholar; Mistry et al., 2005Mistry, A.R., Felix, C.A., Whitmarsh, R.J., Mason, A., Reiter, A., Cassinat, B., Parry, A., Walz, C., Wiemels, J.L., Segal, M.R., et al. (2005). DNA topoisomerase II in therapy-related acute promyelocytic leukemia. N. Engl. J. Med. 352, 1529–1538.Google Scholar; purple: Reiter et al., 2003Reiter, A., Saussele, S., Grimwade, D., Wiemels, J.L., Segal, M.R., Lafage-Pochitaloff, M., Walz, C., Weisser, A., Hochhaus, A., Willer, A., et al. (2003). Genomic anatomy of the specific reciprocal translocation t(15;17) in acute promyelocytic leukemia. Genes Chromosomes Cancer 36, 175–188.Google Scholar). (D and E) Genomic PML-RARA rearrangements associated with a large deletion in PML (D). AML10 and (E) AML15. The total number of validated SNVs per genome increased in proportion to patient age, in both M1 and M3 AML genomes (Figure 1F). We also observed that somatic AML mutations were widely distributed throughout the genome; in all 24 cases, the number of SNVs in each tier was directly proportional to the amount of the genome present in that tier (SNVs per Mb: tier 1: 0.264 ± 0.024; tier 2: 0.283 ± 0.026; tier 3: 0.283 ± 0.024, p < 0.91) (Figure 2A) and these mutations were distributed across all chromosomes (Figure 2B). However, with this sample size, modestly increased mutational frequency within small regions of the genome cannot be excluded (Figures 2C and 2D). The mutational spectrum was dominated by C>T/A>G transitions, and was similar for M1 and M3 cases (Figure 2E). Tier 1 mutations favored C>T/A>G transitions, probably due to an increased proportion of methylated cytosine nucleotides in tier 1, which is associated with increased susceptibility to deamination and subsequent transition mutations (Figure 2F) (Pfeifer, 2006Pfeifer G.P. Mutagenesis at methylated CpG sequences.Curr. Top. Microbiol. Immunol. 2006; 301: 259-281Crossref PubMed Scopus (200) Google Scholar). For this study, skin samples were obtained when the patients presented with leukemia. As expected, we observed low-level contamination of leukemic variants in the skin samples, which was proportional to the peripheral white blood cell (WBC) count at the time of skin collection (Figures S3A–S3C). M3 AML cases usually had very low leukemia contamination in the skin (often completely absent), although we observed two outlier cases. There was no correlation between disproportionally high skin contamination and clinical history (e.g., leukemia cutis, gum hypertrophy, pulmonary hemorrhage, or intracranial hemorrhage).Figure S4Accuracy of Variant Allele Frequency by Digital Reads in AML51, Related to Figure 3Show full captionMetaphase cytogenetics and SNP arrays identified del7, +8, and LOH on chromosomes 16 and 20.(A) Variant allele frequency of all validated SNVs in AML51. The x axis represents chromosome position, starting at chromosome 1 and continuing to the X and Y chromosomes.(B) SNP array analysis of AML51 demonstrating copy number abnormalities. The x axis in A and B are proportional.(C) Total read counts for each validated variant in A.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Figure S5Chromosome X Analysis and Calculation of Tumor Burden, Related to Figure 3Show full caption(A) Variant allele frequency for all variants on chromosome X in 24 AML cases.(B) Percentage of total variants, which are located on chromosome X in males versus female subjects.(C) Bone marrow tumor burden assessed by flow cytometry for M1 versus M3 AML cases.(D) Bone marrow tumor burden calculated by validated allele frequency on chromosome X (male patients) and in regions of LOH (males and females, when available).(E) Comparison of bone marrow tumor burden calculated by validated variant allele frequency and by clinical cytomorphologic blast count.(F) Comparison of bone marrow tumor burden calculated by validated variant allele frequency and by clinical flow cytometry.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Metaphase cytogenetics and SNP arrays identified del7, +8, and LOH on chromosomes 16 and 20. (A) Variant allele frequency of all validated SNVs in AML51. The x axis represents chromosome position, starting at chromosome 1 and continuing to the X and Y chromosomes. (B) SNP array analysis of AML51 demonstrating copy number abnormalities. The x axis in A and B are proportional. (C) Total read counts for each validated variant in A. (A) Variant allele frequency for all variants on chromosome X in 24 AML cases. (B) Percentage of total variants, which are located on chromosome X in males versus female subjects. (C) Bone marrow tumor burden assessed by flow cytometry for M1 versus M3 AML cases. (D) Bone marrow tumor burden calculated by validated allele frequency on chromosome X (male patients) and in regions of LOH (males and females, when available). (E) Comparison of bone marrow tumor burden calculated by validated variant allele frequency and by clinical cytomorphologic blast count. (F) Comparison of bone marrow tumor burden calculated by validated variant allele frequency and by clinical flow cytometry. Clusters of mutations with similar variant allele frequencies within individual cases provide evidence of a single founding clone in both M1 and M3 samples (Ding et al., 2012Ding L. Ley T.J. Larson D.E. Miller C.A. Koboldt D.C. Welch J.S. Ritchey J.K. Young M.A. Lamprecht T. McLellan M.D. et al.Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing.Nature. 2012; 481: 506-510Crossref PubMed Scopus (1539) Google Scholar). Using kernel density analysis, we identified one to four clusters of mutations (representing the founding clone in all cases, with or without additional subclones derived from the founding clone) in each genome (Figures 3A–3D); the clusters were independent of the number of read counts for each SNV. In cases with subclones, the number of variants specific to each subclone was relatively small (an average of 40.4 SNVs per subclone [range 6–110]); SNVs in subclones represented only 14% of the total SNVs per genome (range 2%–33%). Because each genome’s founding clone contains heterozygous SNVs that appear to be present in nearly all of the cells in the sample, subclones must also contain all of the SNVs in the founding clone. For example, the average variant frequency of heterozygous SNVs in the founding clone of AML13 (Figure 3D) is 44%, suggesting that 88% of the cells in the sample contain these heterozygous mutations; therefore, the subclones with average variant allele frequencies of 12%, 22%, and 32% must also contain the mutations found in the founding clone. Genomes with two or more mutation clusters displayed a similar standard deviation of variant frequencies within separate clusters (Figure 3E). However, genomes with a single cluster tended to have an increased standard deviation of the variant frequency within that cluster, suggesting that overlapping subclones may exist in these samples that are below this level of resolution. There was a trend toward more subclones in M3 cases (M1 average, 1.5 clones/genome; M3 average, 2.2 clones/genome; p = 0.04) (Figure 3F). Several pieces of data sugges" @default.
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