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Diagnostic Detection of Allelic Losses and Imbalances by Next-Generation Sequencing
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Diagnostic Detection of Allelic Losses and Imbalances by Next-Generation Sequencing 1P/19Q Co-deletion Analysis of Gliomas Q33
Hendrikus J. Dubbink,* Peggy N. Atmodimedjo,* Ronald van Marion,* Peter H.J. Riegman,* Johan M. Kros,* Martin J. van den Bent,y and Winand N.M. Dinjens* From the Departments of Pathology* and Neuro-Oncology,y Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands Accepted for publication June 1, 2016.
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Address correspondence to Hendrikus J. Dubbink, Department of Pathology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, PO Box 2040, 3000 CA Rotterdam, The Netherlands. E-mail: h.dubbink@ erasmusmc.nl.
Cancer cells are genomic unstable and accumulate tumor typeespecific molecular aberrations, which may represent hallmarks for predicting prognosis and targets for therapy. Co-deletion of chromosomes 1p and 19q marks gliomas with an oligodendroglioma component and predicts a better prognosis and response to chemotherapy. In the current study, we present a novel method to detect chromosome 1p/19q co-deletion or loss of heterozygosity (LOH) in a diagnostic setting, based on single-nucleotide polymorphism (SNP) analysis and next-generation sequencing (NGS) on an Ion Torrent platform. We selected highly polymorphic SNPs distributed evenly over both chromosome arms. To experimentally determine the sensitivity and specificity of targeted SNP analysis, we used DNAs extracted from 49 routine formalin-fixed, paraffin-embedded glioma tissues and compared the outcome with diagnostic microsatellite-based LOH analysis and calculated estimates. We show that targeted SNP analysis by NGS allows reliable detection of 1p and/or 19q deletion in a background of 70% of normal cells according to calculated outcomes, is more sensitive than microsatellite-based LOH analysis, and requires much less DNA. This specific and sensitive SNP assay is broadly applicable for simultaneous allelic imbalance analysis of multiple genomic regions and can be incorporated easily into NGS mutation analyses. The combined mutation and chromosomal imbalance analysis in a single NGS assay is suited perfectly for routine glioma diagnostics and other diagnostic molecular pathology applications. (J Mol Diagn 2016, -: 1e12; http://dx.doi.org/10.1016/j.jmoldx.2016.06.002)
Cancer cells are genomic unstable and accumulate mutations (ie, point and small mutations) and large aberrations including amplification or deletion of whole chromosomes, chromosome arms, or intrachromosomal deletions or amplifications. Detection of these tumor-specific molecular aberrations is of increasing importance in routine pathology diagnostics.1 In this respect, well-known examples are EGFR mutations in nonesmall-cell lung cancer,2 ERBB2 (HER2) amplifications in breast cancer,3 and 1p/19q codeletions in gliomas.4 Molecular classification of malignancies from the central nervous system is important to establish the diagnosis and prognosis and to predict treatment outcome of histologically similar tumors. Oligodendrogliomas are a glioma subtype
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characterized by concurrent loss of the entire chromosomal arms 1p and 19q, resulting from an unbalanced t(1;19) (q10;p10).4,5 Complete 1p/19q loss also has been observed in Q7 oligoastrocytomas, but at a lower frequency. In contrast to tumors with an oligodendroglial component, astrocytomas rarely present with complete 1p/19q loss, but often have smaller losses of genetic material from 1p and 19q.6 Codeletion of the entire chromosome 1p and 19q predicts a better prognosis for patients with oligodendrogliomas independent of treatment, and an improved outcome to treatment Supported by the Department of Pathology, Erasmus MC Cancer Q1 Institute, Rotterdam, the Netherlands. Q2 Disclosures: None declared.
Copyright ª 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jmoldx.2016.06.002
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Dubbink et al with adjuvant chemotherapy resulting in an increased progression-free survival and overall survival as compared with patients with tumors without typical 1p/19q co-deletion or with smaller losses of 1p and/or 19q.6e8 Currently, most routine diagnostics for detection of 1p/19q co-deletion or loss of heterozygosity (LOH) is performed by fluorescent in situ hybridization,9 microsatellite analysis,10 or multiplex ligation-dependent probe amplification.11 Newer comprehensive molecular approaches for the evaluation of chromosomal gains and losses include whole-exome next-generation sequencing (NGS), comparative genomic hybridization arrays, and high-density singlenucleotide polymorphism (SNP) arrays.12 However, these techniques require specific equipment, experience with data analyses, and large amounts of DNA, which often is not present in biopsy specimens or in cases in which only (immune) stained sections or cytology preparations are available, and cannot always be combined with mutation analysis. In addition, the quality and quantity of DNA from formalin-fixed, paraffin-embedded (FFPE) tissues is suboptimal for reliable quantitative analysis of the data from these assays.13 Recent developments in NGS technology allow costeffective clinical implementation of targeted sequencing of only small amounts (10 ng) of DNA from archival FFPE material.1 However, because of the repetitive nature of microsatellites, these markers cannot (yet) be analyzed reliably by most NGS platforms. Several laboratories have shown the usefulness of amplicon-based NGS strategies to generate information on copy number alterations (CNAs).14e18 In the current study, we developed an application of NGS-based, low-density analysis of highly polymorphic SNPs for the routine detection of LOH, in particular 1p/19q co-deletion, with high sensitivity and specificity and a fast turnaround time. This novel assay paves the way toward simultaneous detection of both allelic imbalances and mutations in small amounts of DNA retrieved from FFPE tissues for glioma subtype diagnostics in particular, but also for routine implementation in molecular diagnostics of other tumor types in a pathology laboratory.
Selected tissue areas enriched for a high percentage of neoplastic cells were microdissected manually from hematoxylin-stained 4-mm sections of FFPE glioma tissues. The percentage of neoplastic cells was estimated by our local neuropathologist (J.M.K.). DNA was extracted by proteinase K digestion for 16 hours at 56 C in the presence of 5% Chelex 100 resin and used without further purification after Q9 inactivation of proteinase K and removal of cell debris and the Chelex resin, as previously described.21,22 DNA concentration was measured with the Qubit 2.0 fluorometer (Thermo Fisher Scientific), as described by the manufacturer. Q10 In most cases no (adjacent) normal tissue was available.
Microsatellite-Based LOH Analysis of Chromosomes 1p and 19q LOH analysis was performed within 10 polymorphic microsatellite markers scattered across the entire chromosomes 1p and 19q (Figure 1A). Microsatellite markers and their ½F1 chromosomal localization (human reference genome 19) are shown in Table 1. Microsatellite amplification was per- ½T1 formed after initial denaturation at 95 C for 3 minutes for 28 cycles of 15 seconds at 95 C, 15 seconds at 60 C, and 15 seconds at 72 C, followed by 7 minutes at 72 C. PCR products were analyzed on an ABI 3730 genetic analyzer (Applied Biosystems). Allelic losses were assessed based on Q11 the analysis of multiple informative markers, as described elsewhere.10 Typical oligodendroglial co-deletion of 1p/19q was defined as LOH of all informative markers on both chromosomal arms. If not all informative markers were lost, a chromosome was considered partially lost.
SNP-Based LOH Analysis of Chromosomes 1p and 19q
Forty-nine glioma tissues were collected between 1997 and 2003 during the European Organization of Research and Treatment of Cancer study 26951 on adjuvant procarbazine, lomustine, and vincristine chemotherapy of anaplastic oligodendrogliomas and anaplastic oligoastrocytomas.19 Normal autopsy brain FFPE tissue was obtained from the tissue bank of the Department of Pathology. All tissue samples were assessed anonymously according to the Proper Secondary Use of Human Tissue code established by the Dutch Federation of Medical Scientific Societies.20
A custom primer panel was designed that includes SNPs on chromosomes 1p and 19q using the Ion AmpliSeq Designer Q12 2.0.23 Highly polymorphic SNPs on both chromosomes were selected via the NCBI SNP database with a global Q13 minor allele frequency of at least 45% to obtain a high number of informative SNPs in each assay. The mean SNP density for chromosomes 1p and 19q was set arbitrarily to approximately 1 SNP per 3.5 Mb and 1 SNP per 2 Mb, respectively, yielding a total of 29 SNPs on chromosome 1p and 16 SNPs on chromosome 19q that covered the entire chromosomal arms (Figure 1A). Selected SNPs and their chromosomal localization (SNP database 138) are shown in Table 2. ½T2 Next-generation targeted sequencing was performed by semiconductor sequencing with the Ion Torrent Personal Genome Machine with the suppliers’ materials and protocols (Life Technologies, Carlsbad, CA) as previously described.24 Briefly, DNA input varied between 1 and 10 ng, dependent on the amount of tissue or DNA available. Library and template preparations were performed
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Materials and Methods Glioma Tissues
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DNA Extraction
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Figure 1 Overview on marker location and single-nucleotide polymorphism (SNP)-based loss of heterozygosity (LOH) analysis by targeted nextgeneration sequencing. A: Location of SNP and microsatellite markers on chromosomes 1p and 19q (not at scale, size bars shown in Mbp). The relative positions and distribution of the microsatellite markers (green dots above) and SNPs (blue dots below) on chromosomes 1p and 19q used in this study are indicated. The SNP and microsatellite markers and their exact locations are shown in Tables 1 and 2. B: Explanatory figure showing the possible outcomes of SNP-based LOH analysis of chromosome 1p. The x axis shows the chromosomal position in million base pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency).
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Detection of Chromosomal Loss by NGS
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consecutively with the AmpliSeq Library Kit 2.0-384 LV and the Ion Personal Genome Machine Template OT2 200 kit. Templates were sequenced using the Ion Personal Genome Machine Sequencing 200 Kit v2 on an Ion 318v2 chip. Sequence information was analyzed with Variant Table 1
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Caller v3.6 (Life Technologies), and variants were annotated in a local Galaxy pipeline using ANNOVAR.25e27 Because of the semiquantitative nature of NGS analysis, even more with inferior DNA quality, a SNP was considered to be imbalanced or relatively lost when the variant B-allele
Chromosomal Localization of the Microsatellite Markers Used in This Study
Microsatellite marker (GRCh37/human reference genome 19) Marker
Position
chromosome 1p D1S199 19956993-19957152 D1S513 31331730-31331987 D1S197 50750477-50750694 D1S2806 67868153-67868355 D1S495 102561337-102561767 chromosome 19q D19S875 29797108-29797470 D19S198 42153083-42153201 D19S412 47010944-47011334 D19S606 47973563-47973917 D19S572 54105351-54105693
Locus
Primer forward*
Primer reverse
1p36.13 1p35.2 1p32.3 1p31.3 1p21.1
50 -GATCATGACACTACACTTCAG-30 50 -ATCGCAAGACACAGGCACTG-30 50 -TCATGTCCCTCCTCCCAAAG-30 50 -CATTACATCACAGCCTGATTAGA-30 50 -ACCAAACCTTTGCAGAGGA-30
50 -ACCATGTGCTCCGTAAATAAG-30 50 -ACTAACACACACCATTGCAAG-30 50 -GAGCAAGCATCCAAAAACGA-30 50 -CCACCATGCCTGACCT-30 50 -AACCCTGGTATGCCATCA-30
19q12 19q13.2 19q13.32 19q13.32 19q13.42
50 -TGGTTCTGTGATGACTACTACATGC-30 50 -GAAAGTGTCCACAACGGTAGC-30 50 -CAGCCTGAGCGACAGAATG-30 50 -AGGGCTGGGACCTCAC-30 50 -TTTGGGTGTGCTGACACGTG-30
50 -AACTTGGTTTATGATGTCTCTTGC-30 50 -AAAGGGGTTAGAGGAGAAGGC-30 50 -TGTCTCCTCCTTGGTGCATG-30 50 -TACGAGGCTGTGCCTGTAG-30 50 -TGAAGATCTCGGGCCACATC-30 Q30
*FAM label.
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Chromosomal Localization of the SNPs Used in This Study Q31
SNP (database 138) SNP
Position
chromosome 1p rs7663 16112795 rs169957 19683301 rs169885 21628545 rs742358 22459170 rs309481 23210600 rs189882 24868045 rs9259 25168124 rs7491 25895238 rs159525 26213991 rs7504 27238150 rs6564 28212975 rs157208 29245406 rs6425953 36168038 rs7686 38268918 rs7315 40306898 rs7903 45976472 rs504816 53307957 rs7374 55316322 rs87061 60594980 rs11811946 65952428 rs5680 71477315 rs191142 76990862 rs12754569 85462971 rs54396 88776278 rs106075 91604522 rs1132 95394352 rs8888 101338324 rs6604120 109289487 rs8128 115110683 chromosome 19q rs7283 30106659 rs2542297 31883906 rs33841 34011248 rs12852 35615179 rs1291 38229378 rs17628 39926509 rs166539 40931717 rs3817 44090195 rs10113 47112648 rs8355 48833800 rs6521 49519873 rs11573 51359497 rs193040 53073605 rs3814 53611187 rs10217 56030428 rs10448 59093239
Primer forward
Primer reverse
50 -CATTTTGTACGGCACGGACAA-30 50 -GGTGCCAGAGCCAGATTTGT-30 50 -CTCACTAGGCTCCCCTGATG-30 50 -GGAGCCACCTGCATCCC-30 50 -ATCTCTGCCTGTTGGAATCTTCAG-30 50 -GACCTGAGTTCAACCCCTGT-30 50 -TGCCTAAAAGCATTTATCCTTCATACCA-30 50 -CTGACACAGGCCAGCCTT-30 50 -GGGAATGGAGTACAAGGGCTAT-30 50 -GCAGCCTAAGCTTTCATTCTCATC-30 50 -ATGTGGTTAACATGGATTAATGTGGGA-30 50 -AGCATTTAGTTAGAGGAGAGGAGAGG-30 50 -TGGGCTGTTTCCTCCCTTCTA-30 50 -GACTGAACCCCTGCCAACTAA-30 50 -GCAGCTCGCAAATTTCAAAGTCT-30 50 -TTCCCATGCAGCCCTTTGAATA-30 50 -GCAGGTTATAAGGGTCTTCTCGAGT-30 50 -CTGAGAGGATTCTGGCACCTG-30 50 -TCAAGTTAGAATGACCACTTTCCGTATG-30 50 -GGGAGATGAGCTGAAAGTTCCA-30 50 -CAATTTGGGTAGTCACAAACTCCAT-30 50 -AAATGACTTTCTGGAAAATGAGGTCTATTCA-30 50 -GGGACTTATTCCACGCTTCAG-30 50 -TCTTGCCTTCATCACAGGTTGG-30 50 -TTCACCTGTCTCTTACCCCCATA-30 50 -ACTTGCTAATTTTGTCCAAAGGGAGTA-30 50 -GGTAAACAGAGGCCTAGTTAAGAATTCC-30 50 -GTCGTGTGGCAGAGTGAGT-30 50 -CAAATAGAATTACCACAGCAGCCTACA-30
50 -CTCTAGGCTCAGGGCAAGAC-30 50 -AGGAAGGGAGATGTTAGGATGACC-30 50 -CTAAGGTTGGTTTCTGACTAAGACCTAA-30 50 -GGTTGCTCAGCTCCTTCCT-30 50 -ACTCATGTCTCTCATTCATTCACACAA-30 50 -GCCACTTTCTTGTAAAGGTGTGTT-30 50 -AGGTGCCCATCAGTTTCTCTTC-30 50 -TTTCACAAATAAAGCACAGCAAGACTT-30 50 -CCCCATTTTCTTCCTTTTCTTCCATAC-30 50 -TGTATAGACAGCACTTGGCTCCT-30 50 -CTCAGGTCTCCATAAGGGTCTTCT-30 50 -CCAGTGTGCACTCCAGAGTA-30 50 -GCTTTCCTTCTTTCTGGAATTTCTGTT-30 50 -TGGATAAAGATTGAAGAGCCACAGG-30 50 -TGAGCCACATATTGGGAGTTCTAGAT-30 50 -CCAAGGTGTTACATTTTGTTTCACTACA-30 50 -GCCCCTGAAAATCTGGCAACA-30 50 -TCATTTGTGTGGAAAGTCAGAGGAA-30 50 -CTGAGGATAAAGAGGTCTCTTCAACTG-30 50 -CATATGGCCCACCTCATGTTCT-30 50 -ACAGCAAATTAGCTCCTAACCTAACAAA-30 50 -TGCAGGCCTATGGGAAATGTTC-30 50 -CTGCTTACTTCCTCGGCTCTT-30 50 -TGGTGTGAAAGTAGGATGAAAACCTT-30 50 -TCCTCTGTGTGGTTTGGTAAATTACAT-30 50 -CTCCTAGGTCCCAAAGAAATGTGG-30 50 -TGCATCAATTCATTCTTAAGGTTGCCTA-30 50 -GGAAAGCAGGAAGAAGTCCTCA-30 50 -CGGCAAGACTTCTGAAAAGACAATTTA-30
50 -TGCTCTATGATAAATCAGTTGCATCTGT-30 50 -GAGAGCCATTGTCCCAAATATGGA-30 50 -CACCAGCCTGCTCAGTCTAC-30 50 -CCCAATACCTAATAAGGCATGCGAAA-30 50 -CTCTCTCAATTGCTAAAGCCATACCTA-30 50 -GCTCCCATGTTACCCCCTAGAT-30 50 -CAGCACGTAGAGGTCCGT-30 50 -TTTATTCATTCCTCCAAAGAGCACCA-30 50 -CCAAGCTGCATGATTGCTCTTT-30 50 -CTACGGAAGCGGGAGTGA-30 50 -CCCTGAGGTGGCAGCAT-30 50 -CGTGTCTTTTCAAACCCACATCCTAA-30 50 -GGCCTGGCTTTAGTCCTGT-30 50 -TGAGACAACCAGTGACTTCAAACA-30 50 -GTGTGACCCTCTCCAGGATTT-30 50 -GGTCGAGGGTGATTCGCT-30
50 -GCCATCCAATGGACCTTTGGG-30 50 -TCAACTGGTCCTCTCCTACCC-30 50 -TGCTAGTCCTTCAGCAATGAGAC-30 50 -TGTTTGAGGGATAAAACGGCATGA-30 50 -TGGGAAAACCTTCAGATATGGTTCAG-30 50 -CGCGGTGAGGTTGTCTAGTC-30 50 -GGCTACCTCTTCGTTCTGATTGG-30 50 -GGCATGGAAAACTTGGGTGAGT-30 50 -CCATCCGGGCTGGAGGA-30 50 -GTTCAGGAGAGGTCAAGCGT-30 50 -ATCCAGGGAGCCGCTTC-30 50 -CCAGGGTTGGGAATGCTTCTC-30 50 -ACGTCCCAGGTACGGAAGT-30 50 -GTGAGGAATAATTCAGTCTAGTTGTGCT-30 50 -CAGTCTTGTGATTCTGTCTTTCTAGGATT-30 50 -AACACCAGCCAGAGCTTATTCAT-30
SNP, single-nucleotide polymorphism.
frequency of a heterozygous SNP was either higher than 55% or lower than 45%. All variant frequencies between 45% and 55% were considered not to be aberrant. Similarly, cut-off lines were indicated at 5% and 95%, if not otherwise stated. These values are not absolute but were helpful in interpretation of the outcome. Typical oligodendroglial co-deletion of
1p and 19q was defined as imbalance to a similar degree of all informative SNP on both chromosomes. Partial allelic Q15 imbalance or loss was considered only if at least two consecutive informative SNPs showed imbalance to minimize the chance that apparent losses or imbalances are the result of preferential amplification of one of the alleles.
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Results Interpretation of Low-Density, SNP-Based LOH Analysis Targeted, amplicon-based NGS analysis of SNPs yields different outcomes per SNP (Figure 1B). SNPs may be noninformative homozygous for either a reference or variant SNP (B-allele), or heterozygous and informative. In case of tumor tissues, either the reference or variant heterozygous SNP may be entirely lost, duplicated, or amplified in the neoplastic cells. These genetic aberrations result in an increased or decreased frequency of the variant SNP relative to the reference SNP. Because a tumor is an admixture of neoplastic and normal cells, the degree of the increase or decrease depends on the percentage of neoplastic cells. The higher the percentage of neoplastic cells the larger the shift away from the normal heterozygous situation, and if the percentage is more than 95% all targeted SNPs on a chromosome may seem to be homozygous and noninformative.
Normal Variation of B-Allele Frequencies Using Normal Autopsy Brain FFPE Tissues Because of the frequent occurrence and diagnostic and clinical relevance of 1p and 19q deletions in brain tumors, we used glioma tissues to study the performance of SNPbased LOH analysis by NGS. For NGS detection of allelic imbalances, we selected 29 and 16 highly polymorphic SNPs on chromosomes 1p and 19q, respectively, scattered over both chromosomal arms, and compared the results with classic microsatellite-based LOH analysis using five markers on each chromosomal arm. To define suitable cut-off values for interpretation of the data, we analyzed 10 normal autopsy brain FFPE tissues. As expected, homozygous SNPs showed hardly any variation and
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559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 SNP versus Microsatellite-Based LOH Analysis of 580 581 Chromosomes 1p and 19q 582 Figure 3 shows representative results obtained by SNP-based ½F3 583 584 LOH analysis of DNA isolated from a high percentage of 585 neoplastic cells of FFPE astrocytoma and oligodendroglioma 586 tissue. The astrocytoma showed an equal distribution of 587 informative and noninformative SNPs over both chromosomal 588 arms without obvious LOH related to the percentage of 589 neoplastic cells (Figure 3C). Because of the relative low 590 quality of the DNA from FFPE tissue, informative SNPs 591 without relative loss often are not on a straight line at a B-allele 592 frequency of 50%, but mostly are scattered between B-allele 593 594 frequencies of 45% to 55%. Genomic imbalances therefore are called only if the B-allele frequencies of at least two SNPs Q17 595 596 clearly deviate from the 45% and 55% lines. The oligoden597 droglioma clearly showed 1p/19q co-deletion, leading to an 598 599 600 601 602 Figure 2 Distribution of B-allele frequencies of Q23 603 604 single-nucleotide polymorphisms (SNPs) in next605 generation sequencing (NGS) analysis of normal brain tissues. NGS analyses of 10 normal autopsy 606 brain formalin-fixed, paraffin-embedded tissues 607 were performed. The mean B-allele frequencies of 608 chromosome 1p SNPs, which are either homozygous 609 referent, homozygous variant, or heterozygous, are 610 shown. Corresponding standard deviations were 611 determined based on the number of times the SNPs 612 were homozygous referent, homozygous variant, or 613 heterozygous, which may vary per SNP. The x axis 614 shows the chromosomal position in million base 615 pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency). 616 617 618 619 620
are located close to allele frequencies of 0% or 100%, Q16 respectively. In contrast, heterozygous SNPs are more scattered around the expected B-allele frequency of 50%, probably because of the inferior quality of FFPE DNA (Figure 2). ½F2 Therefore, we set cut-off values at 45% and 55% for heterozygous SNPs to discriminate normal from aberrant allele frequencies. One SNP (in red) is located systematically outside these cut-off values, likely owing to preferential amplification of the B-allele and therefore should be interpreted carefully or removed from the panel or bed file. In addition, cut-off values, for homozygous SNPs only, were set at 5% and 95% to help in data analysis. For the same reason and if not otherwise indicated, SNPs with B-allele frequencies between 5% and 45% and 55% and 95%, respectively, are indicated in red dots. SNPs showing other B-allele frequencies are shown in blue, even though at a very high percentage of neoplastic cells aberrant heterozygous SNPs might be located between frequencies of 0% and 5% or 95% and 100%.
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Figure 3
Representative examples of single-nucleotide polymorphism (SNP)-based loss of heterozygosity (LOH) analysis of glioma tissues. Hematoxylin and eosin stain of the corresponding astrocytoma with an estimated neoplastic cell content of 60% (A), and an oligodendroglioma with 90% neoplastic cell histology (B). C: Astrocytoma without obvious genomic alteration of chromosomes 1p (above) and 19q (below). The x axis shows the chromosomal position in million base pairs (Mbp), and the Y axis shows the percentage variant (B-allele frequency). D: Oligodenglioma with typical 1p/19q codeletion. Note the similar degree of LOH (ie, shifts relative to the location of nonaffected informative SNPs) of both chromosome 1p (above) and 19q (below). The x axis shows the chromosomal position in million base pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency). Original magnification: 20 (B and C).
equal decrease or increase of the B-allele frequency of all informative SNPs on both chromosomes (Figure 3D). Microsatellite-based LOH analysis confirmed these observations (data not shown). Of note, the latter method required 10 times more DNA because for analysis of each of the 10 microsatellite markers the same amount of DNA as for NGSbased SNP analysis of both chromosomal arms is needed.
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Next, we addressed the sensitivity of SNP-based versus microsatellite-based LOH analysis. DNA from glioma tissue
with known 1p/19q co-deletion and an estimated percentage of neoplastic cells of >90% was diluted with DNA isolated from adjacent near-100% normal tissue and the sensitivity of both LOH detection methods was compared using the same tumor/normal DNA dilutions (Figure 4A). Dilution experi- ½F4 ments were performed in duplicate and also with glioma tissue from another patient (data not shown). The results of one representative experiment of the microsatellite analysis are shown, the second experiment showed similar results. SNP-based LOH analysis was at least as accurate as and even more sensitive than the microsatellite-based method (Figure 4, B and C). Moreover, the data were much easier to interpret in the absence of normal tissue and, importantly, in
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Highly Sensitive and Easily Interpretable SNP-Based LOH Analysis
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Figure 4
Sensitivity of single-nucleotide polymorphism (SNP)-based compared with microsatellitebased loss of heterozygosity (LOH) analysis. A: Schematic view of serial dilution preparation from oligodendroglioma tissue (>90% neoplastic cells) with known 1p/19q deletion and adjacent normal tissue. SNP- and microsatellitebased LOH analyses were performed in parallel with the same amount of DNA from the same DNA preparations. B: Serial dilution analysis to test the sensitivity of SNP-based LOH detection. Only results of the chromosome 1p analysis are shown. Experiments were performed in duplicate. The results are indicated per experiment by blue dots and red crosses, respectively. The estimated percentages of neoplastic cells are indicated in the graphs. Calculated outcomes of SNP-based LOH analysis of indicated different admixtures of normal and neoplastic cells are indicated by the lines. The x axis shows the chromosomal position in million base pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency). C: Serial dilution analysis to test the sensitivity of microsatellite-based LOH detection. Results with one (D1S513) of five other chromosome 1p markers are shown. Experiments were performed in duplicate, and one representative experiment is shown. Similar results were obtained with other markers (data not shown). Estimated percentages of neoplastic cells are indicated between the graphs. The x axis shows the DNA fragment size in base pairs (bp), and the y axis shows the relative fluorescence unit (RFU).
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Dubbink et al 869 contrast to microsatellite-based LOH analysis, there was no 870 need for comparison with normal DNA. For example, at 20% 871 neoplastic cells there was unambiguous LOH of chromosome 872 1p in the SNP assay, whereas LOH of the microsatellite 873 markers was disputable and certainly impossible to determine 874 in the absence of reference normal tissue. Furthermore, at 875 near-100% neoplastic cells the microsatellite marker appar876 ently was noninformative and interpretation required results 877 of matched normal DNA, whereas in the SNP assay the 878 879 absence of all highly polymorphic informative markers was a 880 strong argument for LOH, certainly in cases with an esti881 mated high percentage of neoplastic cells. The experimental 882 data are in accordance with the calculated B-allele fre883 quencies in relation to the neoplastic cell percentage 884 (Figure 4B). Apparently, the NGS method is very repro885 ducible, as can be deduced from the small differences be886 tween the B-allele frequencies of the two experiments shown 887 in Figure 4B. In addition, independent dilution experiments 888 with glioma tissue from another patient showed a high 889 concordance between the separate experiments and a similar 890 891 limit of detection (data not shown). 892 893 Performance and Validation of SNP-Based 1p/19q LOH 894 Analysis of FFPE Glioma Tissues 895 896 The performance of NGS-based LOH analysis was exam897 ined further by analysis of a series of 49 glioma samples 898 collected within a prospective trial between 1997 and 899 2003.19 The estimated percentage of neoplastic cells varied 900 901 ½T3 between 50% and >90% (Table 3). No normal reference adjacent tissue was available. 902 903 In all 49 cases, both microsatellite- and SNP-based LOH 904 analysis made a decision possible on the 1p and 19q status 905 (Table 3). In 39 cases, concordant results were obtained with 906 both methods for both chromosomal arms, and in 10 cases the 907 results were distinct for either 1p or 19q. In nine cases, SNP 908 analysis showed partial or complete 1p or 19q LOH, which 909 was not shown by or was not completely overlapping with 910 microsatellite analysis (Table 3). In one case, glioma 1, 911 unambiguous LOH of two of four informative microsatellite 912 markers on 19q was observed, whereas no partial intra913 chromosomal LOH was shown in the SNP analysis. 914 915 Most of these discordant results (seven cases) could be 916 explained by the observed superior lower limit of detection 917 ½F5 of the SNP analyses (Figure 5). Aberrations as shown in 918 Figure 5 may reflect subclonal allelic losses or aberrant copy 919 numbers of the specific chromosomal regions. Partial LOH 920 in glioma 20 might have been missed because probably only 921 one apparently noninformative microsatellite marker 922 (D19S572) was present in the LOH region. The other two 923 discrepancies (gliomas 1 and 26) involving partial losses are 924 more difficult to explain without extensive research, but 925 might reflect the distinct, nonoverlapping, genomic loca926 927 tions and differences in density of the SNP and microsat928 ellite markers and underlying complex chromosomal 929 rearrangements. 930
8
Discussion We describe here, to our knowledge, a thus far unrecognized diagnostic NGS application based on targeted low-density SNP profiling that allows sensitive detection of CNAs, including allelic imbalances and chromosomal losses or LOH. Our method was developed for the detection of molecular aberrations in neoplastic cells surrounded by distinct numbers of normal cells. A simple algorithm was used to calculate allele frequencies from the relative presence of SNPs in genomic regions of interest in tumor tissues. A ratio less than 45% or more than 55% of consecutive informative SNPs was supposed to be indicative for loss of genetic material or for the presence of aberrant numbers of the Q18 respective alleles (allelic imbalance), respectively. Our main purpose was to develop a diagnostic test for implementation in running NGS tests in molecular pathology laboratories. In that respect, NGS-based LOH analysis has several important advantages over alternative approaches, including microsatellite-based LOH detection and multiplex ligation-dependent probe amplification. Probably because of the quantitative nature of NGS, the method has a higher sensitivity than microsatellite-based LOH analysis and even may detect LOH in neoplastic cells in a background of up to 80% normal cells. The sensitivity of multiplex ligation-dependent probe amplification also is lower because it requires at least 50% neoplastic cells for reliable detection of genomic losses.11 The NGS approach is capable to detect LOH in very small amounts of DNA, ranging from as low as 1 to 10 ng, whereas microsatellite marker analysis requires at least 10 times more DNA input and multiplex ligation-dependent probe amplification greater than 250 ng.11 This makes this SNP-based method very suitable in a routine molecular pathology setting because often only limited amounts of tissue, small biopsy specimens, routine immune- or hematoxylin and eosinestained archival sections, or cytology preparations are available. Because of the small-amplicon design, the NGS method appeared very powerful for investigating relatively low-quality DNA from FFPE tissues. For validation we used multicenter archival FFPE glioma tissues obtained between 1997 and 2003, illustrating the robustness of NGS-based LOH detection.19 The limited amount and low quality of DNA of this material is most likely the reason why frequently no results were obtained with individual markers in the microsatellite analysis (Supplemental Table S1). In addition, detection of LOH by NGS is less dependent on normal reference tissue. This is important because in many diagnostic cases, including brain malignancies, tumor biopsy specimens, and cytology specimens, no adjacent normal tissue is available. For microsatellite analyses, simultaneous analysis of adjacent normal tissue is preferable, especially in cases with borderline percentages of neoplastic cells or if the percentage of neoplastic cells is too high (Figure 4C). Because of a high percentage of
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Detection of Chromosomal Loss by NGS Table 3
Parallel Examination of 49 Gliomas by NGS-Based SNP Profiling and Microsatellite Analysis SNP-based LOH
Glioma
Percentage of neoplastic cells
Microsatellite-based LOH
1p
19q
1p
19q
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
80 90 80 80 70 80 85 80 70 70 50 90 60 90 90 70 75 100 90 90 60 90 80 75 90 85 80 80 80 60 90 70 80 70 70 90 80 85 75 90 50 90 75 75 90 50 60 90 80
No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH No LOH LOH LOH LOH No LOH No LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH LOH LOH LOH LOH No LOH No LOH Partial LOH LOH Partial LOH No LOH LOH No LOH Partial LOH No LOH No LOH Partial LOH LOH No LOH Partial LOH
No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH LOH LOH LOH LOH Partial LOH Partial LOH LOH LOH LOH LOH Partial LOH LOH LOH LOH LOH LOH LOH LOH LOH LOH Partial LOH Partial LOH No LOH LOH LOH LOH LOH LOH LOH Partial LOH LOH LOH LOH LOH
No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH No LOH LOH LOH LOH No LOH No LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH LOH LOH LOH LOH No LOH No LOH Partial LOH LOH Partial LOH No LOH Partial LOH No LOH Partial LOH No LOH No LOH No LOH LOH No LOH Partial LOH
Partial LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH LOH LOH LOH LOH No LOH Partial LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH LOH LOH LOH LOH No LOH No LOH No LOH No LOH Partial LOH LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH
LOH, loss of heterozygosity; SNP, single-nucleotide polymorphism.
neoplastic cells in many 1p/19q co-deleted cases, almost all microsatellite markers apparently were noninformative, with only one or two markers left per chromosome arm that seemed informative as a result of the presence of a very
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weak signal of a putative second alternative allele. Decisions on the presence of LOH therefore often are made based on the assumption that it is unlikely that all microsatellite markers are noninformative when using
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1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116
Figure 5 Examples of partial imbalance as observed in single-nucleotide polymorphism (SNP)-based loss of heterozygosity (LOH) analysis of glioma tissues. Unambiguous (partial) allelic imbalance was observed in case of SNP-based LOH analysis, but not with in-parallel microsatellite-based analysis (data not shown). A: Glioma 46 shows a large telomeric imbalance of chromosome 1p; with classic fluorescent in situ hybridization probes this tumor might have been considered 1p/19q co-deleted. Glioma 36 (B) and glioma 37 (C) show both telomeric imbalances of chromosome 19q. See additional information on these gliomas, including percentages of neoplastic cells, in Table 3 and Supplemental Table S1. The x axis shows the chromosomal position in million base pairs, and the y axis shows the percentage variant (B-allele frequency).
polymorphic microsatellite markers.10 However, for a solid conclusion, adjacent normal reference material, tumor tissue with a lower percentage of neoplastic cells, or blood should be tested in parallel if any of these sources is available. In fact, this also may be true for SNP analyses in exceptional cases with extremely high percentages (>90%) of neoplastic cells. However, the chance that all SNPs are noninformative is much lower because there are more putative informative markers that also are distributed better over the chromosomal arms in the SNP test. Another important feature of targeted NGS-based LOH analysis is that it produces quantitative information that, in contrast to microsatellite analysis, can be used to estimate whether LOH likely has resulted from loss of genetic material or from other CNA phenomena. For this purpose, it is essential to relate the degree of LOH (ie, shifts with respect to nonaffected informative SNPs; Figure 1B) to the estimated percentage of neoplastic cells and, if applicable, the observed frequencies of other oncogenic mutations if the assay is combined with simultaneous mutation detection (see later). This is particularly important for molecular classification of gliomas because it allows discrimination between typical oligodendroglial cases of combined 1p/19q deletion (Figure 3D) and an atypical combined 1p/19q LOH pattern caused by complex genetic changes not specific for oligodendroglioma (data not shown). We have shown that a mean number of 1 SNP per 2 to 4 Mb is sufficient to detect LOH of chromosome 1p and 19q. The test can be adapted easily for analyses of other chromosomal regions or increase the density of SNPs to be able to detect smaller losses in, for example, selected genes. Moreover, the method can be extended for simultaneous detection of mutations in any gene of interest without the need for more DNA input. As an example, we recently showed that molecular classification of gliomas better defines clinically relevant subgroups than histologic grading by combining CNA detection, including chromosomal losses and imbalances, of chromosomes 1p, 7, 10q, and 19q with mutation analysis of, among others, IDH1, IDH2, TP53, PTEN, ATRX, CIC, and FUBP1.22 This analysis currently is part of our routine molecular diagnostics of gliomas. In contrast to microsatellite markers, SNPs are compatible with LOH detection in microsatellite-unstable malignancies. Therefore, another obvious diagnostic application is combined mutation and LOH analysis of microsatellite-unstable tumors, for example, to molecularly classify microsatelliteunstable gliomas or to establish the sporadic nature of microsatellite unstable Lynch Syndromeelike tumors, for which no causal germline aberration has been found.24,28,29 Finally, SNP-based LOH analyses extend coverage analyses as described by other groups14e18 and further enhances the information that can be extracted from NGS data. In addition, it allows LOH detection by means of small NGS panels. Classification of cancers for optimal treatment is driven increasingly by the presence of specific molecular
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aberrations, including actionable mutations for precision medicine. Assessment of personalized treatment options would benefit enormously from a comprehensive test that encompasses all essential molecular alterations whether or not for specific tumor types or for the purpose of testing distinct tumor types. NGS rapidly becomes part of standard care delivered by molecular pathology laboratories and allows implementation of single tests to study distinct molecular aberrations that previously could be analyzed only by the use of several methods. Our study adds another option to implement in novel NGS panels and underscores the usefulness of low-density SNP profiling that might be used in parallel with mutation detection and coverage analysis to better address all different types of CNA, including genomic losses, allelic imbalances, and gene amplifications.17 Currently, we are developing a web-based, open-source, diagnostic SNP analysis tool (manuscript in preparation). In summary, we have shown that NGS analysis, apart from detection of mutations and amplifications, is also very suitable and can be diagnostically implemented easily for simultaneous and adequate detection of LOH in archival FFPE tissue. Combined NGS-based LOH and mutation analysis therefore is suited perfectly to become standard practice for routine glioma diagnostics and other diagnostic molecular pathology applications.
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Acknowledgments We thank Lotte Douglas-Berger, Gerard Gathier, and Cathleen van der Lee-Haarloo for technical assistance, Monique Oomen and Shazia Arshad for collecting the tissue bank samples, and Frank van der Panne for preparation of the figures.
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Supplemental Data Supplemental material for this article can be found at http://dx.doi.org/10.1016/j.jmoldx.2016.06.002.
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Diagnostic Detection of Allelic Losses and Imbalances by Next-Generation Sequencing 1P/19Q Co-deletion Analysis of Gliomas Q33
Hendrikus J. Dubbink,* Peggy N. Atmodimedjo,* Ronald van Marion,* Peter H.J. Riegman,* Johan M. Kros,* Martin J. van den Bent,y and Winand N.M. Dinjens* From the Departments of Pathology* and Neuro-Oncology,y Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands Accepted for publication June 1, 2016.
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Address correspondence to Hendrikus J. Dubbink, Department of Pathology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, PO Box 2040, 3000 CA Rotterdam, The Netherlands. E-mail: h.dubbink@ erasmusmc.nl.
Cancer cells are genomic unstable and accumulate tumor typeespecific molecular aberrations, which may represent hallmarks for predicting prognosis and targets for therapy. Co-deletion of chromosomes 1p and 19q marks gliomas with an oligodendroglioma component and predicts a better prognosis and response to chemotherapy. In the current study, we present a novel method to detect chromosome 1p/19q co-deletion or loss of heterozygosity (LOH) in a diagnostic setting, based on single-nucleotide polymorphism (SNP) analysis and next-generation sequencing (NGS) on an Ion Torrent platform. We selected highly polymorphic SNPs distributed evenly over both chromosome arms. To experimentally determine the sensitivity and specificity of targeted SNP analysis, we used DNAs extracted from 49 routine formalin-fixed, paraffin-embedded glioma tissues and compared the outcome with diagnostic microsatellite-based LOH analysis and calculated estimates. We show that targeted SNP analysis by NGS allows reliable detection of 1p and/or 19q deletion in a background of 70% of normal cells according to calculated outcomes, is more sensitive than microsatellite-based LOH analysis, and requires much less DNA. This specific and sensitive SNP assay is broadly applicable for simultaneous allelic imbalance analysis of multiple genomic regions and can be incorporated easily into NGS mutation analyses. The combined mutation and chromosomal imbalance analysis in a single NGS assay is suited perfectly for routine glioma diagnostics and other diagnostic molecular pathology applications. (J Mol Diagn 2016, -: 1e12; http://dx.doi.org/10.1016/j.jmoldx.2016.06.002)
Cancer cells are genomic unstable and accumulate mutations (ie, point and small mutations) and large aberrations including amplification or deletion of whole chromosomes, chromosome arms, or intrachromosomal deletions or amplifications. Detection of these tumor-specific molecular aberrations is of increasing importance in routine pathology diagnostics.1 In this respect, well-known examples are EGFR mutations in nonesmall-cell lung cancer,2 ERBB2 (HER2) amplifications in breast cancer,3 and 1p/19q codeletions in gliomas.4 Molecular classification of malignancies from the central nervous system is important to establish the diagnosis and prognosis and to predict treatment outcome of histologically similar tumors. Oligodendrogliomas are a glioma subtype
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characterized by concurrent loss of the entire chromosomal arms 1p and 19q, resulting from an unbalanced t(1;19) (q10;p10).4,5 Complete 1p/19q loss also has been observed in Q7 oligoastrocytomas, but at a lower frequency. In contrast to tumors with an oligodendroglial component, astrocytomas rarely present with complete 1p/19q loss, but often have smaller losses of genetic material from 1p and 19q.6 Codeletion of the entire chromosome 1p and 19q predicts a better prognosis for patients with oligodendrogliomas independent of treatment, and an improved outcome to treatment Supported by the Department of Pathology, Erasmus MC Cancer Q1 Institute, Rotterdam, the Netherlands. Q2 Disclosures: None declared.
Copyright ª 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jmoldx.2016.06.002
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Dubbink et al with adjuvant chemotherapy resulting in an increased progression-free survival and overall survival as compared with patients with tumors without typical 1p/19q co-deletion or with smaller losses of 1p and/or 19q.6e8 Currently, most routine diagnostics for detection of 1p/19q co-deletion or loss of heterozygosity (LOH) is performed by fluorescent in situ hybridization,9 microsatellite analysis,10 or multiplex ligation-dependent probe amplification.11 Newer comprehensive molecular approaches for the evaluation of chromosomal gains and losses include whole-exome next-generation sequencing (NGS), comparative genomic hybridization arrays, and high-density singlenucleotide polymorphism (SNP) arrays.12 However, these techniques require specific equipment, experience with data analyses, and large amounts of DNA, which often is not present in biopsy specimens or in cases in which only (immune) stained sections or cytology preparations are available, and cannot always be combined with mutation analysis. In addition, the quality and quantity of DNA from formalin-fixed, paraffin-embedded (FFPE) tissues is suboptimal for reliable quantitative analysis of the data from these assays.13 Recent developments in NGS technology allow costeffective clinical implementation of targeted sequencing of only small amounts (10 ng) of DNA from archival FFPE material.1 However, because of the repetitive nature of microsatellites, these markers cannot (yet) be analyzed reliably by most NGS platforms. Several laboratories have shown the usefulness of amplicon-based NGS strategies to generate information on copy number alterations (CNAs).14e18 In the current study, we developed an application of NGS-based, low-density analysis of highly polymorphic SNPs for the routine detection of LOH, in particular 1p/19q co-deletion, with high sensitivity and specificity and a fast turnaround time. This novel assay paves the way toward simultaneous detection of both allelic imbalances and mutations in small amounts of DNA retrieved from FFPE tissues for glioma subtype diagnostics in particular, but also for routine implementation in molecular diagnostics of other tumor types in a pathology laboratory.
Selected tissue areas enriched for a high percentage of neoplastic cells were microdissected manually from hematoxylin-stained 4-mm sections of FFPE glioma tissues. The percentage of neoplastic cells was estimated by our local neuropathologist (J.M.K.). DNA was extracted by proteinase K digestion for 16 hours at 56 C in the presence of 5% Chelex 100 resin and used without further purification after Q9 inactivation of proteinase K and removal of cell debris and the Chelex resin, as previously described.21,22 DNA concentration was measured with the Qubit 2.0 fluorometer (Thermo Fisher Scientific), as described by the manufacturer. Q10 In most cases no (adjacent) normal tissue was available.
Microsatellite-Based LOH Analysis of Chromosomes 1p and 19q LOH analysis was performed within 10 polymorphic microsatellite markers scattered across the entire chromosomes 1p and 19q (Figure 1A). Microsatellite markers and their ½F1 chromosomal localization (human reference genome 19) are shown in Table 1. Microsatellite amplification was per- ½T1 formed after initial denaturation at 95 C for 3 minutes for 28 cycles of 15 seconds at 95 C, 15 seconds at 60 C, and 15 seconds at 72 C, followed by 7 minutes at 72 C. PCR products were analyzed on an ABI 3730 genetic analyzer (Applied Biosystems). Allelic losses were assessed based on Q11 the analysis of multiple informative markers, as described elsewhere.10 Typical oligodendroglial co-deletion of 1p/19q was defined as LOH of all informative markers on both chromosomal arms. If not all informative markers were lost, a chromosome was considered partially lost.
SNP-Based LOH Analysis of Chromosomes 1p and 19q
Forty-nine glioma tissues were collected between 1997 and 2003 during the European Organization of Research and Treatment of Cancer study 26951 on adjuvant procarbazine, lomustine, and vincristine chemotherapy of anaplastic oligodendrogliomas and anaplastic oligoastrocytomas.19 Normal autopsy brain FFPE tissue was obtained from the tissue bank of the Department of Pathology. All tissue samples were assessed anonymously according to the Proper Secondary Use of Human Tissue code established by the Dutch Federation of Medical Scientific Societies.20
A custom primer panel was designed that includes SNPs on chromosomes 1p and 19q using the Ion AmpliSeq Designer Q12 2.0.23 Highly polymorphic SNPs on both chromosomes were selected via the NCBI SNP database with a global Q13 minor allele frequency of at least 45% to obtain a high number of informative SNPs in each assay. The mean SNP density for chromosomes 1p and 19q was set arbitrarily to approximately 1 SNP per 3.5 Mb and 1 SNP per 2 Mb, respectively, yielding a total of 29 SNPs on chromosome 1p and 16 SNPs on chromosome 19q that covered the entire chromosomal arms (Figure 1A). Selected SNPs and their chromosomal localization (SNP database 138) are shown in Table 2. ½T2 Next-generation targeted sequencing was performed by semiconductor sequencing with the Ion Torrent Personal Genome Machine with the suppliers’ materials and protocols (Life Technologies, Carlsbad, CA) as previously described.24 Briefly, DNA input varied between 1 and 10 ng, dependent on the amount of tissue or DNA available. Library and template preparations were performed
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Materials and Methods Glioma Tissues
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DNA Extraction
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Figure 1 Overview on marker location and single-nucleotide polymorphism (SNP)-based loss of heterozygosity (LOH) analysis by targeted nextgeneration sequencing. A: Location of SNP and microsatellite markers on chromosomes 1p and 19q (not at scale, size bars shown in Mbp). The relative positions and distribution of the microsatellite markers (green dots above) and SNPs (blue dots below) on chromosomes 1p and 19q used in this study are indicated. The SNP and microsatellite markers and their exact locations are shown in Tables 1 and 2. B: Explanatory figure showing the possible outcomes of SNP-based LOH analysis of chromosome 1p. The x axis shows the chromosomal position in million base pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency).
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Detection of Chromosomal Loss by NGS
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consecutively with the AmpliSeq Library Kit 2.0-384 LV and the Ion Personal Genome Machine Template OT2 200 kit. Templates were sequenced using the Ion Personal Genome Machine Sequencing 200 Kit v2 on an Ion 318v2 chip. Sequence information was analyzed with Variant Table 1
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Caller v3.6 (Life Technologies), and variants were annotated in a local Galaxy pipeline using ANNOVAR.25e27 Because of the semiquantitative nature of NGS analysis, even more with inferior DNA quality, a SNP was considered to be imbalanced or relatively lost when the variant B-allele
Chromosomal Localization of the Microsatellite Markers Used in This Study
Microsatellite marker (GRCh37/human reference genome 19) Marker
Position
chromosome 1p D1S199 19956993-19957152 D1S513 31331730-31331987 D1S197 50750477-50750694 D1S2806 67868153-67868355 D1S495 102561337-102561767 chromosome 19q D19S875 29797108-29797470 D19S198 42153083-42153201 D19S412 47010944-47011334 D19S606 47973563-47973917 D19S572 54105351-54105693
Locus
Primer forward*
Primer reverse
1p36.13 1p35.2 1p32.3 1p31.3 1p21.1
50 -GATCATGACACTACACTTCAG-30 50 -ATCGCAAGACACAGGCACTG-30 50 -TCATGTCCCTCCTCCCAAAG-30 50 -CATTACATCACAGCCTGATTAGA-30 50 -ACCAAACCTTTGCAGAGGA-30
50 -ACCATGTGCTCCGTAAATAAG-30 50 -ACTAACACACACCATTGCAAG-30 50 -GAGCAAGCATCCAAAAACGA-30 50 -CCACCATGCCTGACCT-30 50 -AACCCTGGTATGCCATCA-30
19q12 19q13.2 19q13.32 19q13.32 19q13.42
50 -TGGTTCTGTGATGACTACTACATGC-30 50 -GAAAGTGTCCACAACGGTAGC-30 50 -CAGCCTGAGCGACAGAATG-30 50 -AGGGCTGGGACCTCAC-30 50 -TTTGGGTGTGCTGACACGTG-30
50 -AACTTGGTTTATGATGTCTCTTGC-30 50 -AAAGGGGTTAGAGGAGAAGGC-30 50 -TGTCTCCTCCTTGGTGCATG-30 50 -TACGAGGCTGTGCCTGTAG-30 50 -TGAAGATCTCGGGCCACATC-30 Q30
*FAM label.
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Chromosomal Localization of the SNPs Used in This Study Q31
SNP (database 138) SNP
Position
chromosome 1p rs7663 16112795 rs169957 19683301 rs169885 21628545 rs742358 22459170 rs309481 23210600 rs189882 24868045 rs9259 25168124 rs7491 25895238 rs159525 26213991 rs7504 27238150 rs6564 28212975 rs157208 29245406 rs6425953 36168038 rs7686 38268918 rs7315 40306898 rs7903 45976472 rs504816 53307957 rs7374 55316322 rs87061 60594980 rs11811946 65952428 rs5680 71477315 rs191142 76990862 rs12754569 85462971 rs54396 88776278 rs106075 91604522 rs1132 95394352 rs8888 101338324 rs6604120 109289487 rs8128 115110683 chromosome 19q rs7283 30106659 rs2542297 31883906 rs33841 34011248 rs12852 35615179 rs1291 38229378 rs17628 39926509 rs166539 40931717 rs3817 44090195 rs10113 47112648 rs8355 48833800 rs6521 49519873 rs11573 51359497 rs193040 53073605 rs3814 53611187 rs10217 56030428 rs10448 59093239
Primer forward
Primer reverse
50 -CATTTTGTACGGCACGGACAA-30 50 -GGTGCCAGAGCCAGATTTGT-30 50 -CTCACTAGGCTCCCCTGATG-30 50 -GGAGCCACCTGCATCCC-30 50 -ATCTCTGCCTGTTGGAATCTTCAG-30 50 -GACCTGAGTTCAACCCCTGT-30 50 -TGCCTAAAAGCATTTATCCTTCATACCA-30 50 -CTGACACAGGCCAGCCTT-30 50 -GGGAATGGAGTACAAGGGCTAT-30 50 -GCAGCCTAAGCTTTCATTCTCATC-30 50 -ATGTGGTTAACATGGATTAATGTGGGA-30 50 -AGCATTTAGTTAGAGGAGAGGAGAGG-30 50 -TGGGCTGTTTCCTCCCTTCTA-30 50 -GACTGAACCCCTGCCAACTAA-30 50 -GCAGCTCGCAAATTTCAAAGTCT-30 50 -TTCCCATGCAGCCCTTTGAATA-30 50 -GCAGGTTATAAGGGTCTTCTCGAGT-30 50 -CTGAGAGGATTCTGGCACCTG-30 50 -TCAAGTTAGAATGACCACTTTCCGTATG-30 50 -GGGAGATGAGCTGAAAGTTCCA-30 50 -CAATTTGGGTAGTCACAAACTCCAT-30 50 -AAATGACTTTCTGGAAAATGAGGTCTATTCA-30 50 -GGGACTTATTCCACGCTTCAG-30 50 -TCTTGCCTTCATCACAGGTTGG-30 50 -TTCACCTGTCTCTTACCCCCATA-30 50 -ACTTGCTAATTTTGTCCAAAGGGAGTA-30 50 -GGTAAACAGAGGCCTAGTTAAGAATTCC-30 50 -GTCGTGTGGCAGAGTGAGT-30 50 -CAAATAGAATTACCACAGCAGCCTACA-30
50 -CTCTAGGCTCAGGGCAAGAC-30 50 -AGGAAGGGAGATGTTAGGATGACC-30 50 -CTAAGGTTGGTTTCTGACTAAGACCTAA-30 50 -GGTTGCTCAGCTCCTTCCT-30 50 -ACTCATGTCTCTCATTCATTCACACAA-30 50 -GCCACTTTCTTGTAAAGGTGTGTT-30 50 -AGGTGCCCATCAGTTTCTCTTC-30 50 -TTTCACAAATAAAGCACAGCAAGACTT-30 50 -CCCCATTTTCTTCCTTTTCTTCCATAC-30 50 -TGTATAGACAGCACTTGGCTCCT-30 50 -CTCAGGTCTCCATAAGGGTCTTCT-30 50 -CCAGTGTGCACTCCAGAGTA-30 50 -GCTTTCCTTCTTTCTGGAATTTCTGTT-30 50 -TGGATAAAGATTGAAGAGCCACAGG-30 50 -TGAGCCACATATTGGGAGTTCTAGAT-30 50 -CCAAGGTGTTACATTTTGTTTCACTACA-30 50 -GCCCCTGAAAATCTGGCAACA-30 50 -TCATTTGTGTGGAAAGTCAGAGGAA-30 50 -CTGAGGATAAAGAGGTCTCTTCAACTG-30 50 -CATATGGCCCACCTCATGTTCT-30 50 -ACAGCAAATTAGCTCCTAACCTAACAAA-30 50 -TGCAGGCCTATGGGAAATGTTC-30 50 -CTGCTTACTTCCTCGGCTCTT-30 50 -TGGTGTGAAAGTAGGATGAAAACCTT-30 50 -TCCTCTGTGTGGTTTGGTAAATTACAT-30 50 -CTCCTAGGTCCCAAAGAAATGTGG-30 50 -TGCATCAATTCATTCTTAAGGTTGCCTA-30 50 -GGAAAGCAGGAAGAAGTCCTCA-30 50 -CGGCAAGACTTCTGAAAAGACAATTTA-30
50 -TGCTCTATGATAAATCAGTTGCATCTGT-30 50 -GAGAGCCATTGTCCCAAATATGGA-30 50 -CACCAGCCTGCTCAGTCTAC-30 50 -CCCAATACCTAATAAGGCATGCGAAA-30 50 -CTCTCTCAATTGCTAAAGCCATACCTA-30 50 -GCTCCCATGTTACCCCCTAGAT-30 50 -CAGCACGTAGAGGTCCGT-30 50 -TTTATTCATTCCTCCAAAGAGCACCA-30 50 -CCAAGCTGCATGATTGCTCTTT-30 50 -CTACGGAAGCGGGAGTGA-30 50 -CCCTGAGGTGGCAGCAT-30 50 -CGTGTCTTTTCAAACCCACATCCTAA-30 50 -GGCCTGGCTTTAGTCCTGT-30 50 -TGAGACAACCAGTGACTTCAAACA-30 50 -GTGTGACCCTCTCCAGGATTT-30 50 -GGTCGAGGGTGATTCGCT-30
50 -GCCATCCAATGGACCTTTGGG-30 50 -TCAACTGGTCCTCTCCTACCC-30 50 -TGCTAGTCCTTCAGCAATGAGAC-30 50 -TGTTTGAGGGATAAAACGGCATGA-30 50 -TGGGAAAACCTTCAGATATGGTTCAG-30 50 -CGCGGTGAGGTTGTCTAGTC-30 50 -GGCTACCTCTTCGTTCTGATTGG-30 50 -GGCATGGAAAACTTGGGTGAGT-30 50 -CCATCCGGGCTGGAGGA-30 50 -GTTCAGGAGAGGTCAAGCGT-30 50 -ATCCAGGGAGCCGCTTC-30 50 -CCAGGGTTGGGAATGCTTCTC-30 50 -ACGTCCCAGGTACGGAAGT-30 50 -GTGAGGAATAATTCAGTCTAGTTGTGCT-30 50 -CAGTCTTGTGATTCTGTCTTTCTAGGATT-30 50 -AACACCAGCCAGAGCTTATTCAT-30
SNP, single-nucleotide polymorphism.
frequency of a heterozygous SNP was either higher than 55% or lower than 45%. All variant frequencies between 45% and 55% were considered not to be aberrant. Similarly, cut-off lines were indicated at 5% and 95%, if not otherwise stated. These values are not absolute but were helpful in interpretation of the outcome. Typical oligodendroglial co-deletion of
1p and 19q was defined as imbalance to a similar degree of all informative SNP on both chromosomes. Partial allelic Q15 imbalance or loss was considered only if at least two consecutive informative SNPs showed imbalance to minimize the chance that apparent losses or imbalances are the result of preferential amplification of one of the alleles.
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Results Interpretation of Low-Density, SNP-Based LOH Analysis Targeted, amplicon-based NGS analysis of SNPs yields different outcomes per SNP (Figure 1B). SNPs may be noninformative homozygous for either a reference or variant SNP (B-allele), or heterozygous and informative. In case of tumor tissues, either the reference or variant heterozygous SNP may be entirely lost, duplicated, or amplified in the neoplastic cells. These genetic aberrations result in an increased or decreased frequency of the variant SNP relative to the reference SNP. Because a tumor is an admixture of neoplastic and normal cells, the degree of the increase or decrease depends on the percentage of neoplastic cells. The higher the percentage of neoplastic cells the larger the shift away from the normal heterozygous situation, and if the percentage is more than 95% all targeted SNPs on a chromosome may seem to be homozygous and noninformative.
Normal Variation of B-Allele Frequencies Using Normal Autopsy Brain FFPE Tissues Because of the frequent occurrence and diagnostic and clinical relevance of 1p and 19q deletions in brain tumors, we used glioma tissues to study the performance of SNPbased LOH analysis by NGS. For NGS detection of allelic imbalances, we selected 29 and 16 highly polymorphic SNPs on chromosomes 1p and 19q, respectively, scattered over both chromosomal arms, and compared the results with classic microsatellite-based LOH analysis using five markers on each chromosomal arm. To define suitable cut-off values for interpretation of the data, we analyzed 10 normal autopsy brain FFPE tissues. As expected, homozygous SNPs showed hardly any variation and
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559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 SNP versus Microsatellite-Based LOH Analysis of 580 581 Chromosomes 1p and 19q 582 Figure 3 shows representative results obtained by SNP-based ½F3 583 584 LOH analysis of DNA isolated from a high percentage of 585 neoplastic cells of FFPE astrocytoma and oligodendroglioma 586 tissue. The astrocytoma showed an equal distribution of 587 informative and noninformative SNPs over both chromosomal 588 arms without obvious LOH related to the percentage of 589 neoplastic cells (Figure 3C). Because of the relative low 590 quality of the DNA from FFPE tissue, informative SNPs 591 without relative loss often are not on a straight line at a B-allele 592 frequency of 50%, but mostly are scattered between B-allele 593 594 frequencies of 45% to 55%. Genomic imbalances therefore are called only if the B-allele frequencies of at least two SNPs Q17 595 596 clearly deviate from the 45% and 55% lines. The oligoden597 droglioma clearly showed 1p/19q co-deletion, leading to an 598 599 600 601 602 Figure 2 Distribution of B-allele frequencies of Q23 603 604 single-nucleotide polymorphisms (SNPs) in next605 generation sequencing (NGS) analysis of normal brain tissues. NGS analyses of 10 normal autopsy 606 brain formalin-fixed, paraffin-embedded tissues 607 were performed. The mean B-allele frequencies of 608 chromosome 1p SNPs, which are either homozygous 609 referent, homozygous variant, or heterozygous, are 610 shown. Corresponding standard deviations were 611 determined based on the number of times the SNPs 612 were homozygous referent, homozygous variant, or 613 heterozygous, which may vary per SNP. The x axis 614 shows the chromosomal position in million base 615 pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency). 616 617 618 619 620
are located close to allele frequencies of 0% or 100%, Q16 respectively. In contrast, heterozygous SNPs are more scattered around the expected B-allele frequency of 50%, probably because of the inferior quality of FFPE DNA (Figure 2). ½F2 Therefore, we set cut-off values at 45% and 55% for heterozygous SNPs to discriminate normal from aberrant allele frequencies. One SNP (in red) is located systematically outside these cut-off values, likely owing to preferential amplification of the B-allele and therefore should be interpreted carefully or removed from the panel or bed file. In addition, cut-off values, for homozygous SNPs only, were set at 5% and 95% to help in data analysis. For the same reason and if not otherwise indicated, SNPs with B-allele frequencies between 5% and 45% and 55% and 95%, respectively, are indicated in red dots. SNPs showing other B-allele frequencies are shown in blue, even though at a very high percentage of neoplastic cells aberrant heterozygous SNPs might be located between frequencies of 0% and 5% or 95% and 100%.
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Figure 3
Representative examples of single-nucleotide polymorphism (SNP)-based loss of heterozygosity (LOH) analysis of glioma tissues. Hematoxylin and eosin stain of the corresponding astrocytoma with an estimated neoplastic cell content of 60% (A), and an oligodendroglioma with 90% neoplastic cell histology (B). C: Astrocytoma without obvious genomic alteration of chromosomes 1p (above) and 19q (below). The x axis shows the chromosomal position in million base pairs (Mbp), and the Y axis shows the percentage variant (B-allele frequency). D: Oligodenglioma with typical 1p/19q codeletion. Note the similar degree of LOH (ie, shifts relative to the location of nonaffected informative SNPs) of both chromosome 1p (above) and 19q (below). The x axis shows the chromosomal position in million base pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency). Original magnification: 20 (B and C).
equal decrease or increase of the B-allele frequency of all informative SNPs on both chromosomes (Figure 3D). Microsatellite-based LOH analysis confirmed these observations (data not shown). Of note, the latter method required 10 times more DNA because for analysis of each of the 10 microsatellite markers the same amount of DNA as for NGSbased SNP analysis of both chromosomal arms is needed.
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Next, we addressed the sensitivity of SNP-based versus microsatellite-based LOH analysis. DNA from glioma tissue
with known 1p/19q co-deletion and an estimated percentage of neoplastic cells of >90% was diluted with DNA isolated from adjacent near-100% normal tissue and the sensitivity of both LOH detection methods was compared using the same tumor/normal DNA dilutions (Figure 4A). Dilution experi- ½F4 ments were performed in duplicate and also with glioma tissue from another patient (data not shown). The results of one representative experiment of the microsatellite analysis are shown, the second experiment showed similar results. SNP-based LOH analysis was at least as accurate as and even more sensitive than the microsatellite-based method (Figure 4, B and C). Moreover, the data were much easier to interpret in the absence of normal tissue and, importantly, in
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Highly Sensitive and Easily Interpretable SNP-Based LOH Analysis
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Figure 4
Sensitivity of single-nucleotide polymorphism (SNP)-based compared with microsatellitebased loss of heterozygosity (LOH) analysis. A: Schematic view of serial dilution preparation from oligodendroglioma tissue (>90% neoplastic cells) with known 1p/19q deletion and adjacent normal tissue. SNP- and microsatellitebased LOH analyses were performed in parallel with the same amount of DNA from the same DNA preparations. B: Serial dilution analysis to test the sensitivity of SNP-based LOH detection. Only results of the chromosome 1p analysis are shown. Experiments were performed in duplicate. The results are indicated per experiment by blue dots and red crosses, respectively. The estimated percentages of neoplastic cells are indicated in the graphs. Calculated outcomes of SNP-based LOH analysis of indicated different admixtures of normal and neoplastic cells are indicated by the lines. The x axis shows the chromosomal position in million base pairs (Mbp), and the y axis shows the percentage variant (B-allele frequency). C: Serial dilution analysis to test the sensitivity of microsatellite-based LOH detection. Results with one (D1S513) of five other chromosome 1p markers are shown. Experiments were performed in duplicate, and one representative experiment is shown. Similar results were obtained with other markers (data not shown). Estimated percentages of neoplastic cells are indicated between the graphs. The x axis shows the DNA fragment size in base pairs (bp), and the y axis shows the relative fluorescence unit (RFU).
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Dubbink et al 869 contrast to microsatellite-based LOH analysis, there was no 870 need for comparison with normal DNA. For example, at 20% 871 neoplastic cells there was unambiguous LOH of chromosome 872 1p in the SNP assay, whereas LOH of the microsatellite 873 markers was disputable and certainly impossible to determine 874 in the absence of reference normal tissue. Furthermore, at 875 near-100% neoplastic cells the microsatellite marker appar876 ently was noninformative and interpretation required results 877 of matched normal DNA, whereas in the SNP assay the 878 879 absence of all highly polymorphic informative markers was a 880 strong argument for LOH, certainly in cases with an esti881 mated high percentage of neoplastic cells. The experimental 882 data are in accordance with the calculated B-allele fre883 quencies in relation to the neoplastic cell percentage 884 (Figure 4B). Apparently, the NGS method is very repro885 ducible, as can be deduced from the small differences be886 tween the B-allele frequencies of the two experiments shown 887 in Figure 4B. In addition, independent dilution experiments 888 with glioma tissue from another patient showed a high 889 concordance between the separate experiments and a similar 890 891 limit of detection (data not shown). 892 893 Performance and Validation of SNP-Based 1p/19q LOH 894 Analysis of FFPE Glioma Tissues 895 896 The performance of NGS-based LOH analysis was exam897 ined further by analysis of a series of 49 glioma samples 898 collected within a prospective trial between 1997 and 899 2003.19 The estimated percentage of neoplastic cells varied 900 901 ½T3 between 50% and >90% (Table 3). No normal reference adjacent tissue was available. 902 903 In all 49 cases, both microsatellite- and SNP-based LOH 904 analysis made a decision possible on the 1p and 19q status 905 (Table 3). In 39 cases, concordant results were obtained with 906 both methods for both chromosomal arms, and in 10 cases the 907 results were distinct for either 1p or 19q. In nine cases, SNP 908 analysis showed partial or complete 1p or 19q LOH, which 909 was not shown by or was not completely overlapping with 910 microsatellite analysis (Table 3). In one case, glioma 1, 911 unambiguous LOH of two of four informative microsatellite 912 markers on 19q was observed, whereas no partial intra913 chromosomal LOH was shown in the SNP analysis. 914 915 Most of these discordant results (seven cases) could be 916 explained by the observed superior lower limit of detection 917 ½F5 of the SNP analyses (Figure 5). Aberrations as shown in 918 Figure 5 may reflect subclonal allelic losses or aberrant copy 919 numbers of the specific chromosomal regions. Partial LOH 920 in glioma 20 might have been missed because probably only 921 one apparently noninformative microsatellite marker 922 (D19S572) was present in the LOH region. The other two 923 discrepancies (gliomas 1 and 26) involving partial losses are 924 more difficult to explain without extensive research, but 925 might reflect the distinct, nonoverlapping, genomic loca926 927 tions and differences in density of the SNP and microsat928 ellite markers and underlying complex chromosomal 929 rearrangements. 930
8
Discussion We describe here, to our knowledge, a thus far unrecognized diagnostic NGS application based on targeted low-density SNP profiling that allows sensitive detection of CNAs, including allelic imbalances and chromosomal losses or LOH. Our method was developed for the detection of molecular aberrations in neoplastic cells surrounded by distinct numbers of normal cells. A simple algorithm was used to calculate allele frequencies from the relative presence of SNPs in genomic regions of interest in tumor tissues. A ratio less than 45% or more than 55% of consecutive informative SNPs was supposed to be indicative for loss of genetic material or for the presence of aberrant numbers of the Q18 respective alleles (allelic imbalance), respectively. Our main purpose was to develop a diagnostic test for implementation in running NGS tests in molecular pathology laboratories. In that respect, NGS-based LOH analysis has several important advantages over alternative approaches, including microsatellite-based LOH detection and multiplex ligation-dependent probe amplification. Probably because of the quantitative nature of NGS, the method has a higher sensitivity than microsatellite-based LOH analysis and even may detect LOH in neoplastic cells in a background of up to 80% normal cells. The sensitivity of multiplex ligation-dependent probe amplification also is lower because it requires at least 50% neoplastic cells for reliable detection of genomic losses.11 The NGS approach is capable to detect LOH in very small amounts of DNA, ranging from as low as 1 to 10 ng, whereas microsatellite marker analysis requires at least 10 times more DNA input and multiplex ligation-dependent probe amplification greater than 250 ng.11 This makes this SNP-based method very suitable in a routine molecular pathology setting because often only limited amounts of tissue, small biopsy specimens, routine immune- or hematoxylin and eosinestained archival sections, or cytology preparations are available. Because of the small-amplicon design, the NGS method appeared very powerful for investigating relatively low-quality DNA from FFPE tissues. For validation we used multicenter archival FFPE glioma tissues obtained between 1997 and 2003, illustrating the robustness of NGS-based LOH detection.19 The limited amount and low quality of DNA of this material is most likely the reason why frequently no results were obtained with individual markers in the microsatellite analysis (Supplemental Table S1). In addition, detection of LOH by NGS is less dependent on normal reference tissue. This is important because in many diagnostic cases, including brain malignancies, tumor biopsy specimens, and cytology specimens, no adjacent normal tissue is available. For microsatellite analyses, simultaneous analysis of adjacent normal tissue is preferable, especially in cases with borderline percentages of neoplastic cells or if the percentage of neoplastic cells is too high (Figure 4C). Because of a high percentage of
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993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054
Detection of Chromosomal Loss by NGS Table 3
Parallel Examination of 49 Gliomas by NGS-Based SNP Profiling and Microsatellite Analysis SNP-based LOH
Glioma
Percentage of neoplastic cells
Microsatellite-based LOH
1p
19q
1p
19q
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
80 90 80 80 70 80 85 80 70 70 50 90 60 90 90 70 75 100 90 90 60 90 80 75 90 85 80 80 80 60 90 70 80 70 70 90 80 85 75 90 50 90 75 75 90 50 60 90 80
No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH No LOH LOH LOH LOH No LOH No LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH LOH LOH LOH LOH No LOH No LOH Partial LOH LOH Partial LOH No LOH LOH No LOH Partial LOH No LOH No LOH Partial LOH LOH No LOH Partial LOH
No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH LOH LOH LOH LOH Partial LOH Partial LOH LOH LOH LOH LOH Partial LOH LOH LOH LOH LOH LOH LOH LOH LOH LOH Partial LOH Partial LOH No LOH LOH LOH LOH LOH LOH LOH Partial LOH LOH LOH LOH LOH
No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH No LOH LOH LOH LOH No LOH No LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH LOH LOH LOH LOH No LOH No LOH Partial LOH LOH Partial LOH No LOH Partial LOH No LOH Partial LOH No LOH No LOH No LOH LOH No LOH Partial LOH
Partial LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH No LOH LOH LOH LOH LOH LOH LOH No LOH Partial LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH LOH LOH LOH LOH No LOH No LOH No LOH No LOH Partial LOH LOH LOH LOH LOH LOH No LOH LOH LOH LOH LOH
LOH, loss of heterozygosity; SNP, single-nucleotide polymorphism.
neoplastic cells in many 1p/19q co-deleted cases, almost all microsatellite markers apparently were noninformative, with only one or two markers left per chromosome arm that seemed informative as a result of the presence of a very
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weak signal of a putative second alternative allele. Decisions on the presence of LOH therefore often are made based on the assumption that it is unlikely that all microsatellite markers are noninformative when using
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1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116
Figure 5 Examples of partial imbalance as observed in single-nucleotide polymorphism (SNP)-based loss of heterozygosity (LOH) analysis of glioma tissues. Unambiguous (partial) allelic imbalance was observed in case of SNP-based LOH analysis, but not with in-parallel microsatellite-based analysis (data not shown). A: Glioma 46 shows a large telomeric imbalance of chromosome 1p; with classic fluorescent in situ hybridization probes this tumor might have been considered 1p/19q co-deleted. Glioma 36 (B) and glioma 37 (C) show both telomeric imbalances of chromosome 19q. See additional information on these gliomas, including percentages of neoplastic cells, in Table 3 and Supplemental Table S1. The x axis shows the chromosomal position in million base pairs, and the y axis shows the percentage variant (B-allele frequency).
polymorphic microsatellite markers.10 However, for a solid conclusion, adjacent normal reference material, tumor tissue with a lower percentage of neoplastic cells, or blood should be tested in parallel if any of these sources is available. In fact, this also may be true for SNP analyses in exceptional cases with extremely high percentages (>90%) of neoplastic cells. However, the chance that all SNPs are noninformative is much lower because there are more putative informative markers that also are distributed better over the chromosomal arms in the SNP test. Another important feature of targeted NGS-based LOH analysis is that it produces quantitative information that, in contrast to microsatellite analysis, can be used to estimate whether LOH likely has resulted from loss of genetic material or from other CNA phenomena. For this purpose, it is essential to relate the degree of LOH (ie, shifts with respect to nonaffected informative SNPs; Figure 1B) to the estimated percentage of neoplastic cells and, if applicable, the observed frequencies of other oncogenic mutations if the assay is combined with simultaneous mutation detection (see later). This is particularly important for molecular classification of gliomas because it allows discrimination between typical oligodendroglial cases of combined 1p/19q deletion (Figure 3D) and an atypical combined 1p/19q LOH pattern caused by complex genetic changes not specific for oligodendroglioma (data not shown). We have shown that a mean number of 1 SNP per 2 to 4 Mb is sufficient to detect LOH of chromosome 1p and 19q. The test can be adapted easily for analyses of other chromosomal regions or increase the density of SNPs to be able to detect smaller losses in, for example, selected genes. Moreover, the method can be extended for simultaneous detection of mutations in any gene of interest without the need for more DNA input. As an example, we recently showed that molecular classification of gliomas better defines clinically relevant subgroups than histologic grading by combining CNA detection, including chromosomal losses and imbalances, of chromosomes 1p, 7, 10q, and 19q with mutation analysis of, among others, IDH1, IDH2, TP53, PTEN, ATRX, CIC, and FUBP1.22 This analysis currently is part of our routine molecular diagnostics of gliomas. In contrast to microsatellite markers, SNPs are compatible with LOH detection in microsatellite-unstable malignancies. Therefore, another obvious diagnostic application is combined mutation and LOH analysis of microsatellite-unstable tumors, for example, to molecularly classify microsatelliteunstable gliomas or to establish the sporadic nature of microsatellite unstable Lynch Syndromeelike tumors, for which no causal germline aberration has been found.24,28,29 Finally, SNP-based LOH analyses extend coverage analyses as described by other groups14e18 and further enhances the information that can be extracted from NGS data. In addition, it allows LOH detection by means of small NGS panels. Classification of cancers for optimal treatment is driven increasingly by the presence of specific molecular
10
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aberrations, including actionable mutations for precision medicine. Assessment of personalized treatment options would benefit enormously from a comprehensive test that encompasses all essential molecular alterations whether or not for specific tumor types or for the purpose of testing distinct tumor types. NGS rapidly becomes part of standard care delivered by molecular pathology laboratories and allows implementation of single tests to study distinct molecular aberrations that previously could be analyzed only by the use of several methods. Our study adds another option to implement in novel NGS panels and underscores the usefulness of low-density SNP profiling that might be used in parallel with mutation detection and coverage analysis to better address all different types of CNA, including genomic losses, allelic imbalances, and gene amplifications.17 Currently, we are developing a web-based, open-source, diagnostic SNP analysis tool (manuscript in preparation). In summary, we have shown that NGS analysis, apart from detection of mutations and amplifications, is also very suitable and can be diagnostically implemented easily for simultaneous and adequate detection of LOH in archival FFPE tissue. Combined NGS-based LOH and mutation analysis therefore is suited perfectly to become standard practice for routine glioma diagnostics and other diagnostic molecular pathology applications.
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Acknowledgments We thank Lotte Douglas-Berger, Gerard Gathier, and Cathleen van der Lee-Haarloo for technical assistance, Monique Oomen and Shazia Arshad for collecting the tissue bank samples, and Frank van der Panne for preparation of the figures.
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Supplemental Data Supplemental material for this article can be found at http://dx.doi.org/10.1016/j.jmoldx.2016.06.002.
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