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. 2015 Nov 17;10(11):e0143343.
doi: 10.1371/journal.pone.0143343. eCollection 2015.

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

Adam J de Smith  1 , Kyle M Walsh  2 , Helen M Hansen  2 , Alyson A Endicott  1 , John K Wiencke  2 , Catherine Metayer  3 , Joseph L Wiemels  1   2
Affiliations

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

Adam J de Smith et al. PLoS One. .

Abstract

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Risk allele proportions at genomic loci with somatic loss.
Allelic copy number was measured in constitutional DNA and leukemia bone marrow (tumor) DNA from ALL patients heterozygous for CDKN2A tagging SNP rs3731217 (A), and IKZF1 SNP rs4132601 (B). 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 rs3731217, 11 tumor samples showed AI favoring the risk allele versus 6 patients with AI favoring the protective allele (P = 0.17). For rs4132601, 17 tumor samples showed AI favoring the risk allele versus 12 patients with AI favoring the protective allele (P = 0.23).
Fig 2
Fig 2. Risk allele proportions at genomic loci with somatic gain (i.e. hyperdiploid chromosomes).
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: CEBPE SNP rs2239633 (A), ARID5B SNP rs7089424 (B), PIP4K2A SNP rs10764338 (C), and GATA3 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 et al. 2005) [31].
Fig 3
Fig 3. CDKN2A and IKZF1 SNP allele proportions in tumor DNA relative to genomic control copy number.
Stacked histograms showing tumor DNA copy number of (A) CDKN2A and (B) IKZF1 SNPs relative to a genomic control locus (SLC24A3). 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 CDKN2A/IKZF1 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 CDKN2A (SNP rs3731249) and 75 tumor DNA samples for IKZF1 (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.
Fig 4
Fig 4. Comparison between deletion gene copy number measurements made by SMART-ddPCR and MLPA.
Copy number measurements were available from ddPCR and MLPA assays for SNPs at the two deletion genes CDKN2A (SNP rs3731249) and IKZF1 (SNP rs4132601) in 27 and 75 tumor DNA samples respectively. (A) High correlation (R2 = 0.91) between the combined deletion gene copy number measurements made by ddPCR and MLPA. (B) Bland-Altman plot displaying the difference between measurements made in the same individual against their mean, as measured by two different methodologies (i.e. ddPCR and MLPA). There is very close agreement between the copy number measurements made by the two assays, as demonstrated by the narrow limits of agreement (-0.170 to 0.138) either side of the observed average agreement (-0.016).
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References

    1. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr., Kinzler KW. Cancer genome landscapes. Science. 2013;339(6127):1546–58. 10.1126/science.1235122 - DOI - PMC - PubMed
    1. Dworkin AM, Ridd K, Bautista D, Allain DC, Iwenofu OH, Roy R, et al. Germline variation controls the architecture of somatic alterations in tumors. PLoS Genet. 2010;6(9):e1001136 10.1371/journal.pgen.1001136 - DOI - PMC - PubMed
    1. Landi MT, Bauer J, Pfeiffer RM, Elder DE, Hulley B, Minghetti P, et al. MC1R germline variants confer risk for BRAF-mutant melanoma. Science. 2006;313(5786):521–2. - PubMed
    1. Ewart-Toland A, Briassouli P, de Koning JP, Mao JH, Yuan J, Chan F, et al. Identification of Stk6/STK15 as a candidate low-penetrance tumor-susceptibility gene in mouse and human. Nat Genet. 2003;34(4):403–12. - PubMed
    1. Ruivenkamp CA, van Wezel T, Zanon C, Stassen AP, Vlcek C, Csikos T, et al. Ptprj is a candidate for the mouse colon-cancer susceptibility locus Scc1 and is frequently deleted in human cancers. Nat Genet. 2002;31(3):295–300. - PubMed

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