Clonal and microclonal mutational heterogeneity in high hyperdiploid acute lymphoblastic leukemia.

High hyperdiploidy (HD), the most common cytogenetic subtype of B-cell acute lymphoblastic leukemia (B-ALL), is largely curable but significant treatment-related morbidity warrants investigating the biology and identifying novel drug targets. Targeted deep-sequencing of 538 cancer-relevant genes was performed in 57 HD-ALL patients lacking overt KRAS and NRAS hotspot mutations and lacking common B-ALL deletions to enrich for discovery of novel driver genes. One-third of patients harbored damaging mutations in epigenetic regulatory genes, including the putative novel driver DOT1L (n=4). Receptor tyrosine kinase (RTK)/Ras/MAPK signaling pathway mutations were found in two-thirds of patients, including novel mutations in ROS1, which mediates phosphorylation of the PTPN11-encoded protein SHP2. Mutations in FLT3 significantly co-occurred with DOT1L (p=0.04), suggesting functional cooperation in leukemogenesis. We detected an extraordinary level of tumor heterogeneity, with microclonal (mutant allele fraction <0.10) KRAS, NRAS, FLT3, and/or PTPN11 hotspot mutations evident in 31/57 (54.4%) patients. Multiple KRAS and NRAS codon 12 and 13 microclonal mutations significantly co-occurred within tumor samples (p=4.8x10-4), suggesting ongoing formation of and selection for Ras-activating mutations. Future work is required to investigate whether tumor microheterogeneity impacts clinical outcome and to elucidate the functional consequences of epigenetic dysregulation in HD-ALL, potentially leading to novel therapeutic approaches

Telomere length connects melanoma and glioma predispositions

Glioma and melanoma are rapidly-progressing malignancies that arise from neuroectodermal origin.SEER registry data indicate that melanoma patients areat significantly increased risk of developing glioma(OR=1.42, 95%CI=1.22-1.62)[1]. Although a sharedgenetic etiology is suggested by melanoma-astrocytomasyndrome, an inherited cancer predisposition due togermline CDKN2A mutation, this Mendelian disordercannot account for the increased co-occurrence ofmelanoma and glioma observed at the populationlevel[1]. Recent epidemiologic research has identifiedadditional germline variants that confer risk of bothglioma and melanoma and which implicate telomeremaintenance in the development of these cancers.Telomeres are repetitive DNA sequences that cap andprotect chromosomes and are depleted with eachsomatic cellular division. Because telomere attritioncauses replicative senescence, increased telomere lengthmay allow for prolonged cell survival, increased accrualof mutations, and greater propensity for malignanttransformation. A very large genome-wide associationstudy (GWAS) conducted by the ENGAGE Consortiumhas identified seven genes that are reproduciblyassociated with inter-individual variation in leukocytetelomere length (LTL), including single nucleotidepolymorphisms (SNPs) in: ACYP2, TERC, NAF1,TERT, OBFC1, ZNF208, and RTEL1[2]. In addition tothe effects of these genes on LTL, recent GWAS alsoidentified glioma susceptibility loci near TERT, TERC,and RTEL1[3] and melanoma susceptibility loci nearTERC, TERT, OBFC1, and RTEL1[4]. Taken together,these GWAS suggest that telomere length may be acommon link between the genetic architecture ofmelanoma and glioma predispositio

Telomere length connects melanoma and glioma predispositions.

Glioma and melanoma are rapidly-progressing malignancies that arise from neuroectodermal origin.SEER registry data indicate that melanoma patients areat significantly increased risk of developing glioma(OR=1.42, 95%CI=1.22-1.62)[1]. Although a sharedgenetic etiology is suggested by melanoma-astrocytomasyndrome, an inherited cancer predisposition due togermline CDKN2A mutation, this Mendelian disordercannot account for the increased co-occurrence ofmelanoma and glioma observed at the populationlevel[1]. Recent epidemiologic research has identifiedadditional germline variants that confer risk of bothglioma and melanoma and which implicate telomeremaintenance in the development of these cancers.Telomeres are repetitive DNA sequences that cap andprotect chromosomes and are depleted with eachsomatic cellular division. Because telomere attritioncauses replicative senescence, increased telomere lengthmay allow for prolonged cell survival, increased accrualof mutations, and greater propensity for malignanttransformation. A very large genome-wide associationstudy (GWAS) conducted by the ENGAGE Consortiumhas identified seven genes that are reproduciblyassociated with inter-individual variation in leukocytetelomere length (LTL), including single nucleotidepolymorphisms (SNPs) in: ACYP2, TERC, NAF1,TERT, OBFC1, ZNF208, and RTEL1[2]. In addition tothe effects of these genes on LTL, recent GWAS alsoidentified glioma susceptibility loci near TERT, TERC,and RTEL1[3] and melanoma susceptibility loci nearTERC, TERT, OBFC1, and RTEL1[4]. Taken together,these GWAS suggest that telomere length may be acommon link between the genetic architecture ofmelanoma and glioma predispositio

Telomere length connects melanoma and glioma predispositions.

Glioma and melanoma are rapidly-progressing malignancies that arise from neuroectodermal origin.SEER registry data indicate that melanoma patients areat significantly increased risk of developing glioma(OR=1.42, 95%CI=1.22-1.62)[1]. Although a sharedgenetic etiology is suggested by melanoma-astrocytomasyndrome, an inherited cancer predisposition due togermline CDKN2A mutation, this Mendelian disordercannot account for the increased co-occurrence ofmelanoma and glioma observed at the populationlevel[1]. Recent epidemiologic research has identifiedadditional germline variants that confer risk of bothglioma and melanoma and which implicate telomeremaintenance in the development of these cancers.Telomeres are repetitive DNA sequences that cap andprotect chromosomes and are depleted with eachsomatic cellular division. Because telomere attritioncauses replicative senescence, increased telomere lengthmay allow for prolonged cell survival, increased accrualof mutations, and greater propensity for malignanttransformation. A very large genome-wide associationstudy (GWAS) conducted by the ENGAGE Consortiumhas identified seven genes that are reproduciblyassociated with inter-individual variation in leukocytetelomere length (LTL), including single nucleotidepolymorphisms (SNPs) in: ACYP2, TERC, NAF1,TERT, OBFC1, ZNF208, and RTEL1[2]. In addition tothe effects of these genes on LTL, recent GWAS alsoidentified glioma susceptibility loci near TERT, TERC,and RTEL1[3] and melanoma susceptibility loci nearTERC, TERT, OBFC1, and RTEL1[4]. Taken together,these GWAS suggest that telomere length may be acommon link between the genetic architecture ofmelanoma and glioma predispositio

Somatic Mutation Allelic Ratio Test Using ddPCR (SMART-ddPCR): An Accurate Method for Assessment of Preferential Allelic Imbalance in Tumor DNA.

The extent to which heritable genetic variants can affect tumor development has yet to be fully elucidated. Tumor selection of single nucleotide polymorphism (SNP) risk alleles, a phenomenon called preferential allelic imbalance (PAI), has been demonstrated in some cancer types. We developed a novel application of digital PCR termed Somatic Mutation Allelic Ratio Test using Droplet Digital PCR (SMART-ddPCR) for accurate assessment of tumor PAI, and have applied this method to test the hypothesis that heritable SNPs associated with childhood acute lymphoblastic leukemia (ALL) may demonstrate tumor PAI. These SNPs are located at CDKN2A (rs3731217) and IKZF1 (rs4132601), genes frequently lost in ALL, and at CEBPE (rs2239633), ARID5B (rs7089424), PIP4K2A (rs10764338), and GATA3 (rs3824662), genes located on chromosomes gained in high-hyperdiploid ALL. We established thresholds of AI using constitutional DNA from SNP heterozygotes, and subsequently measured allelic copy number in tumor DNA from 19-142 heterozygote samples per SNP locus. We did not find significant tumor PAI at these loci, though CDKN2A and IKZF1 SNPs showed a trend towards preferential selection of the risk allele (p = 0.17 and p = 0.23, respectively). Using a genomic copy number control ddPCR assay, we investigated somatic copy number alterations (SCNA) underlying AI at CDKN2A and IKZF1, revealing a complex range of alterations including homozygous and hemizygous deletions and copy-neutral loss of heterozygosity, with varying degrees of clonality. Copy number estimates from ddPCR showed high agreement with those from multiplex ligation-dependent probe amplification (MLPA) assays. We demonstrate that SMART-ddPCR is a highly accurate method for investigation of tumor PAI and for assessment of the somatic alterations underlying AI. Furthermore, analysis of publicly available data from The Cancer Genome Atlas identified 16 recurrent SCNA loci that contain heritable cancer risk SNPs associated with a matching tumor type, and which represent candidate PAI regions warranting further investigation

Somatic Mutation Allelic Ratio Test Using ddPCR (SMART-ddPCR): An Accurate Method for Assessment of Preferential Allelic Imbalance in Tumor DNA.

The extent to which heritable genetic variants can affect tumor development has yet to be fully elucidated. Tumor selection of single nucleotide polymorphism (SNP) risk alleles, a phenomenon called preferential allelic imbalance (PAI), has been demonstrated in some cancer types. We developed a novel application of digital PCR termed Somatic Mutation Allelic Ratio Test using Droplet Digital PCR (SMART-ddPCR) for accurate assessment of tumor PAI, and have applied this method to test the hypothesis that heritable SNPs associated with childhood acute lymphoblastic leukemia (ALL) may demonstrate tumor PAI. These SNPs are located at CDKN2A (rs3731217) and IKZF1 (rs4132601), genes frequently lost in ALL, and at CEBPE (rs2239633), ARID5B (rs7089424), PIP4K2A (rs10764338), and GATA3 (rs3824662), genes located on chromosomes gained in high-hyperdiploid ALL. We established thresholds of AI using constitutional DNA from SNP heterozygotes, and subsequently measured allelic copy number in tumor DNA from 19-142 heterozygote samples per SNP locus. We did not find significant tumor PAI at these loci, though CDKN2A and IKZF1 SNPs showed a trend towards preferential selection of the risk allele (p = 0.17 and p = 0.23, respectively). Using a genomic copy number control ddPCR assay, we investigated somatic copy number alterations (SCNA) underlying AI at CDKN2A and IKZF1, revealing a complex range of alterations including homozygous and hemizygous deletions and copy-neutral loss of heterozygosity, with varying degrees of clonality. Copy number estimates from ddPCR showed high agreement with those from multiplex ligation-dependent probe amplification (MLPA) assays. We demonstrate that SMART-ddPCR is a highly accurate method for investigation of tumor PAI and for assessment of the somatic alterations underlying AI. Furthermore, analysis of publicly available data from The Cancer Genome Atlas identified 16 recurrent SCNA loci that contain heritable cancer risk SNPs associated with a matching tumor type, and which represent candidate PAI regions warranting further investigation

Clonal and microclonal mutational heterogeneity in high hyperdiploid acute lymphoblastic leukemia.

High hyperdiploidy (HD), the most common cytogenetic subtype of B-cell acute lymphoblastic leukemia (B-ALL), is largely curable but significant treatment-related morbidity warrants investigating the biology and identifying novel drug targets. Targeted deep-sequencing of 538 cancer-relevant genes was performed in 57 HD-ALL patients lacking overt KRAS and NRAS hotspot mutations and lacking common B-ALL deletions to enrich for discovery of novel driver genes. One-third of patients harbored damaging mutations in epigenetic regulatory genes, including the putative novel driver DOT1L (n=4). Receptor tyrosine kinase (RTK)/Ras/MAPK signaling pathway mutations were found in two-thirds of patients, including novel mutations in ROS1, which mediates phosphorylation of the PTPN11-encoded protein SHP2. Mutations in FLT3 significantly co-occurred with DOT1L (p=0.04), suggesting functional cooperation in leukemogenesis. We detected an extraordinary level of tumor heterogeneity, with microclonal (mutant allele fraction <0.10) KRAS, NRAS, FLT3, and/or PTPN11 hotspot mutations evident in 31/57 (54.4%) patients. Multiple KRAS and NRAS codon 12 and 13 microclonal mutations significantly co-occurred within tumor samples (p=4.8x10-4), suggesting ongoing formation of and selection for Ras-activating mutations. Future work is required to investigate whether tumor microheterogeneity impacts clinical outcome and to elucidate the functional consequences of epigenetic dysregulation in HD-ALL, potentially leading to novel therapeutic approaches

Candidates for tumor PAI: recurrent SCNA loci from TCGA that overlap cancer-associated SNPs (NHGRI GWAS Catalog) identified in matching tumor types.

<p>SNP associations and tumor types highlighted in bold indicate those whereby cancer type of SNP associations matches tumor type in which recurrent SCNAs were identified.</p><p>* Chromosomal locations based on human genome build hg19.</p><p>** Cancer type of SNP association loci that overlap SCNA regions (SNPs retrieved from January 2015 version of NHGRI GWAS catalog).</p><p>‡ Tumor type in which recurrent SCNAs were detected in TCGA.</p><p>ALL = acute lymphoblastic leukemia; BLCA = bladder; BRCA = breast; CLL = chronic lymphoblastic leukemia; CRC = colorectal; GBM = glioblastoma multiforme; HNSC = head and neck squamous cell carcinoma; KIRC = kidney renal cell carcinoma; LAML = acute myeloid leukemia; LUAD = lung adenocarcinoma; LUSC = lung squamous cell carcinoma; OV = serous ovarian carcinoma; UCEC = endometrial (uterine).</p><p>Candidates for tumor PAI: recurrent SCNA loci from TCGA that overlap cancer-associated SNPs (NHGRI GWAS Catalog) identified in matching tumor types.</p

<i>CDKN2A</i> and <i>IKZF1</i> SNP allele proportions in tumor DNA relative to genomic control copy number.

<p>Stacked histograms showing tumor DNA copy number of (A) <i>CDKN2A</i> and (B) <i>IKZF1</i> SNPs relative to a genomic control locus (<i>SLC24A3</i>). Black and grey bars represent the proportions of normalized SNP copy number accounted for by the risk and protective alleles respectively. White bars represent the difference between <i>CDKN2A</i>/<i>IKZF1</i> SNP copy number and the genomic control gene copy number. SMART-ddPCR was used to measure copy number of SNP risk/protective alleles, as well as the genomic control locus, in 35 leukemia bone marrow (tumor) DNA samples for <i>CDKN2A</i> (SNP rs3731249) and 75 tumor DNA samples for <i>IKZF1</i> (SNP rs4132601). Samples are grouped into those with allelic imbalance (AI) and those without AI, and arranged in order of normalized gene copy number relative to the genomic control.</p

Risk allele proportions at genomic loci with somatic gain (<i>i</i>.<i>e</i>. hyperdiploid chromosomes).

<p>Allelic copy number was measured in constitutional DNA and leukemia bone marrow (tumor) DNA from HeH ALL patients heterozygous for ALL-associated SNPs on chromosomes frequently gained in HeH ALL: <i>CEBPE</i> SNP rs2239633 (A), <i>ARID5B</i> SNP rs7089424 (B), <i>PIP4K2A</i> SNP rs10764338 (C), and <i>GATA3</i> SNP rs3824662 (D). Risk allele proportions are displayed as a fraction of the total allelic copy number measured in each patient using ddPCR. Each subject was assayed in duplicate, and error bars represent the standard error of the mean (some error bars not visible due to their range falling within boundaries of the data point). Upper/lower thresholds of allelic imbalance (AI) were +/- 3 SDs from the mean allelic proportion from repeat measurements in constitutional DNA samples (white squares). For rs2239633, 19 tumor samples showed AI favoring the risk allele versus 13 patients with AI favoring the protective allele (P = 0.19). For rs7089424, 20 tumor samples showed AI favoring the risk allele versus 15 patients with AI favoring the protective allele (P = 0.25). For rs10764338, 4 tumor samples showed AI favoring the risk allele versus 5 patients with AI favoring the protective allele (P = 0.50). For rs3824662, 10 tumor samples showed AI favoring the risk allele versus 9 patients with AI favoring the protective allele (P = 0.50). Data points clustering at ~0.66 and ~0.33 represent a 3:2 or 2:3 risk:protective allele proportion due to chromosomal copy number shifting from diploid (n = 2) to triploid (n = 3). Data points at ~0.75 represents a 3:1 risk:protective allele proportion due to a diploid to tetraploid (n = 4) shift in chromosome ploidy. Data points at 1 and 0 likely represent HeH ALL that has arisen via near-haploidy, leading to chromosomal LOH (Paulsson <i>et al</i>. 2005) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143343#pone.0143343.ref031" target="_blank">31</a>].</p