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Genomic imbalances in precancerous tissues signal oral cancer risk Garnis, Cathie; Chari, Raj; Buys, Timon P; Zhang, Lewei; Ng, Raymond T; Rosin, Miriam P; Lam, Wan L Jul 23, 2009

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ralssBioMed CentMolecular CancerOpen AcceResearchGenomic imbalances in precancerous tissues signal oral cancer riskCathie Garnis*1, Raj Chari1,2, Timon PH Buys1,2, Lewei Zhang3,4, Raymond T Ng5, Miriam P Rosin2,4 and Wan L Lam1,2Address: 1Department of Cancer Genetics and Developmental Biology; British Columbia Cancer Research Centre, Vancouver, BC, V5Z 1L3, Canada, 2Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, V6T 2B5, Canada, 3Division of Oral Biological and Medical Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada, 4British Columbia Oral Cancer Prevention Program, British Columbia Cancer Agency, Vancouver, BC V5Z 4E6, Canada and 5Department of Computer Science, University of British Columbia, Vancouver, B.C., V6T 1Z4, CanadaEmail: Cathie Garnis* - cgarnis@bccrc.ca; Raj Chari - rchari@bccrc.ca; Timon PH Buys - tbuys@bccrc.ca; Lewei Zhang - lewei@shaw.ca; Raymond T Ng - rng@cs.ubc.ca; Miriam P Rosin - miriam_rosin@shaw.ca; Wan L Lam - wanlam@bccrc.ca* Corresponding author    AbstractOral cancer develops through a series of histopathological stages: through mild (low grade),moderate, and severe (high grade) dysplasia to carcinoma in situ and then invasive disease. Earlydetection of those oral premalignant lesions (OPLs) that will develop into invasive tumors isnecessary to improve the poor prognosis of oral cancer. Because no tools exist for delineatingprogression risk in low grade oral lesions, we cannot determine which of these cases requireaggressive intervention. We undertook whole genome analysis by tiling-path array comparativegenomic hybridization for a rare panel of early and late stage OPLs (n = 62), all of which hadextensive longitudinal follow up (>10 years). Genome profiles for oral squamous cell carcinomas(n = 24) were generated for comparison. Parallel analysis of genome alterations and clinicalparameters was performed to identify features associated with disease progression. Genomealterations in low grade dysplasias progressing to invasive disease more closely resembled thoseobserved for later stage disease than they did those observed for non-progressing low gradedysplasias. This was despite the histopathological similarity between progressing and non-progressing cases. Strikingly, unbiased computational analysis of genomic alteration data correctlyclassified nearly all progressing low grade dysplasia cases. Our data demonstrate that highresolution genomic analysis can be used to evaluate progression risk in low grade OPLs, a markedimprovement over present histopathological approaches which cannot delineate progression risk.Taken together, our data suggest that whole genome technologies could be used in managementstrategies for patients presenting with precancerous oral lesions.BackgroundAt present, risk of progression in oral premalignantlesions (OPLs) is typically determined based on his-considered high risk for progression to invasive disease. Incontrast, only a small proportion of low grade dysplasias(LGDs) – which represent the majority of diagnosed OPLsPublished: 23 July 2009Molecular Cancer 2009, 8:50 doi:10.1186/1476-4598-8-50Received: 31 October 2008Accepted: 23 July 2009This article is available from: http://www.molecular-cancer.com/content/8/1/50© 2009 Garnis et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Page 1 of 7(page number not for citation purposes)topathological evaluation of biopsied material. Highgrade dysplasia (HGD) and carcinoma in situ (CIS) are– progress to invasive disease [1,2]. Histological featurescannot currently be used to delineate "progressing" andMolecular Cancer 2009, 8:50 http://www.molecular-cancer.com/content/8/1/50"non-progressing" LGDs [3]. Consequently, LGDs that areprime candidates for early intervention are not easilyidentified. Novel approaches for defining progressionlikelihood for histopathologically similar LGDs arerequired.Chromosome instability, particularly loss of chromosomearms 3p and 9p, has previously been associated with anincreased probability of progression in oral cancer, dem-onstrating the potential utility of molecular markers inpredicting progression risk [4-7]. Additionally, p53 statushas been used to predict progression in Barretts esophagusand other groups have reported genomic instability intumor-associated dysplastic oral tissue [8-11]. To date,efforts to undertake whole genome analysis of premalig-nant lesions have been precluded by 1) the rarity of LGDspecimens with longitudinal follow-up and clinical out-come details and 2) the lack of robust high resolutiongenome profiling methodologies that can utilize the lim-ited DNA yield from microdissected formalin-fixed paraf-fin-embedded lesions. In this study, we compared thegenomes of precancerous oral tissues from different dis-ease stages to identify stage-specific DNA alterations.Analysis of this rare sample set not only revealed qualita-tive and quantitative differences in DNA alterationsdepending on histopathological stage, but also showedthat these features are associated with known clinical out-comes.Results and discussionGenome profiles were generated by tiling-path array CGHfor a panel of 86 oral lesions with longitudinal follow-upthat included 24 invasive oral squamous cell carcinomas(OSCCs) and 62 OPLs. This sample panel was comprisedof 32 HGD and CIS lesions, 21 non-progressing LGDs,and nine progressing LGDs where the average time to pro-gression to a higher grade was 27.2 months. (Demo-graphic patient information are supplemental – seeAdditional File 1: Table S1.) Two classes of segmentalchanges were defined: whole chromosome arm changesand segmental DNA copy number changes. Segmentalgenomic gains and losses were defined using the aCGH-Smooth algorithm (Figure 1) [12]. Similar to earlier find-ings using locus specific probes, both Figure 1 and Figure2 show how increases in lesion severity paralleledincreases in the degree of genomic instability (i.e. thenumber of genomic alterations) [13,14].HGDs, despite being classified as pre-invasive, showed adegree of genomic instability comparable to what wasobserved in invasive tumors; they had an average of 16.6segmental DNA changes and 2.4 whole chromosome armchanges per sample, while tumors averaged 23.2 segmen-alteration were different for HGD/CIS lesions as com-pared to invasive tumors. In terms of whole chromosomearm changes, the most commonly observed alteration inHGD/CIS lesions was gain of chromosome 20p (10/32cases). On the other hand, deletion of chromosome 3p(11/27) and gain of chromosome 8q (9/27) were themost commonly observed whole arm alterations seen ininvasive tumors. With respect to intra-chromosomal seg-mental DNA copy number changes, the most commonlyaltered regions in HGD/CIS lesions occurred within chro-mosome arms 1p, 2q, 3q, 5q, 7q, and 8p, while the mostcommon changes seen for invasive tumors occurredwithin chromosome arms 5p, 9q, 11q, and 19p (Figure1). This may indicate that the genetic alterations that drivedisease initiation and progression are different from thosethat drive tumor invasion, the earlier alterations maskedby subsequent genomic instability.Amongst low grade dysplasias, only some cases appearedto harbor genome alterations. Review of the clinical datarevealed a striking association between the presence ofgenomic imbalances and subsequent progression to inva-sive disease. Figure 3 shows a typical karyogram of a pro-gressing LGD, where multiple alterations are apparent.Across the progressing LGD cases, an average of 9.2genomic changes was observed (either intra-chromo-somal or whole arm alterations). Interestingly, no altera-tions were shared by all progressing LGD cases.Chromosome arm 9p was the most frequently alteredchromosome (altered in 78% of cases), followed by 8q,20p, and 20q (each observed in 56% of cases). Of the 21non-progressing LGDs, alterations were only detected infour cases – and in these instances, only one or twochanges were typically observed.The total genomic alterations for progressing LGDs moreclosely resembled the HGD cases, which are known tohave a higher likelihood of progression (Figure 2) [15,16].These data suggest that the degree of genomic instabilityin a given OPL may have utility for predicting progressionlikelihood. To investigate this further, we used patterns ofgenomic alteration (Figure 1) to classify individual lesionsrelative to the rest of the sample panel. We first evaluatedwhether DNA alteration features could be used to differ-entiate lesions with a high risk of progression and tumors(HGD, CIS lesions, OSCCs) from lesions that did notprogress (non-progressing LGD lesions). Specifically, weused a k-nearest neighbor statistical analysis (where k = 3;see Methods) to test if these very different groups could bedistinguished based on the number of DNA alterationsthey harbored (with whole chromosome arm and seg-mental changes weighted equally) [17]. Each sample wascalled as either "HGD/CIS/OSCC" or "non-progressingPage 2 of 7(page number not for citation purposes)tal DNA changes and 3.5 whole arm changes. Interest-ingly, the most frequently observed regions of genomicLGD" based on a consensus comparison against the threeclosest samples, as defined by a Euclidean distance calcu-Molecular Cancer 2009, 8:50 http://www.molecular-cancer.com/content/8/1/50Page 3 of 7(page number not for citation purposes)Summary of chromosomal alterations for all 86 casesFigure 1Summary of chromosomal alterations for all 86 cases. Samples are grouped into non-progressing low grade dysplasias, progressing low grade dysplasias, high grade lesions (severe dysplasia and CIS lesions), and oral squamous cell carcinomas. A blue box indicates the presence of at least one segmental change on the chromosome arm and a red box represents a whole arm alteration. Copy number changes due to polymorphic regions were not included in the analysis. Case numbers are listed to the left, while chromosome arms are listed at the top.Molecular Cancer 2009, 8:50 http://www.molecular-cancer.com/content/8/1/50lated using the number of DNA alterations (the histologi-cal subclass was known for all samples except the giventest case). If multiple samples were of equal distance fromthe unclassified sample, then all of the samples at that dis-tance were used. For example, if five samples shared thethird closest distance, a total of seven samples would beused in deriving the consensus classification (the first twonearest neighbors, plus the five neighbors with equal dis-tance). This blind approach, based solely on analysis ofgenome alterations, correctly classified most of the sam-ples we analyzed, including 81% of the LGDs and 87.5%of the HGD/CIS/OSCC lesions. Moreover, the differencein the number of segmental alterations between non-pro-gressing LGDs and HGD/CIS/OSCC was statistically sig-nificant (Mann Whitney U test, p < 10-12).Given our earlier observation that the genome features ofprogressing LGDs more closely resembled higher gradelesions than non-progressing LGDs, we next checked tosee if patterns of DNA alteration could be used to distin-guish between progressing and non-progressing LGDs. Todo this, we applied the same k-nearest neighbor approachdescribed above. Briefly, we analyzed each progressingLGD genome profile against all of the genome profilesgenerated for the non-progressing LGDs and the HGD/CIS/OSCC lesions. (DNA alterations were defined andsified as a progressing LGD. If it more closely resembledthe non-progressing LGDs, it was grouped with thosecases. This approach correctly classified 88.9% of the pro-gressing LGD lesions and the difference in the number ofsegmental alterations between non-progressing LGDs andprogressing LGDs was also statistically significant (p < 10-4). This rate of successful classification stands as a markedimprovement over current histopathological approaches,which are not at all able to predict progression likelihoodfor LGDs.ConclusionThis study provides the first detailed analysis of thegenomes of oral premalignant lesions and supports theuse of genome profiling as a clinical tool for predictingprogression risk. The recent association of chromosomalinstability with post-resection oral tumor recurrence alsosupports application of genomic tools for guiding man-agement strategies [18]. Comparative analysis of thegenome profiles of these early stage specimens revealed aconspicuous difference in the abundance of genetic alter-ations between low grade dysplasias that progressed toinvasive disease and those that did not. The genome pro-files of low grade OPLs known to progress to cancer moreclosely resembled profiles of high grade OPLs than theydid those of non-progressing low grade OPLs. This wasdespite the histopathological similarity between progress-ing and non-progressing cases. As with the higher gradelesions, progressing low grade OPLs showed complex pat-terns of genome alteration. These alterations includedboth gross chromosomal aberrations, which includewhole arm and whole chromosome amplifications anddeletions, as well as localized intra-chromosomal seg-mental gains and losses (alterations in some instancesthat would have been too small to detect by conventionalmolecular cytogenetic techniques). These findings, com-bined with previous reports linking loss of heterozygositystatus to disease progression, demonstrate that there aremultiple genetic mechanisms involved in progression toinvasive oral cancer. More importantly, they show thatcharacterization of genomic alterations in low grade dys-plasias can be used as an effective predictor for diseaseprogression likelihood.MethodsTissue samplesFormalin-fixed paraffin-embedded tissue blocks wereobtained from the British Columbia Oral Biopsy Serviceand diagnoses were confirmed by an oral pathologist.Cells of the OPLs and tumor were microdissected fromH&E-stained sections. Only samples with greater than80% tumor cell content were used in this study. Microdis-sected tissue was placed in a sodium dodecyl sulfate solu-Box plot showing percentage of genome alteredFigure 2Box plot showing percentage of genome altered. As in Figure 1, samples are grouped into non-progressing LGDs, progressing LGDs, HGD/CIS lesions, and OSCCs. Genome altered was calculated by dividing the number of clones deemed changed (gain or loss), by aCGH-Smooth, by the total number of clones assayed for each sample. Chromosomes X and Y were excluded from this analysis.Page 4 of 7(page number not for citation purposes)weighted as above.) If the progressing lesion more closelyresembled the high grade lesions and tumors, it was clas-tion with proteinase K at 48°C and spiked with additionalenzyme twice a day for 72 hours. Genomic DNA wasMolecular Cancer 2009, 8:50 http://www.molecular-cancer.com/content/8/1/50Page 5 of 7(page number not for citation purposes)Whole genome tiling path array CGH karyogram of an oral low grade dysplasia which subsequently progressed to cancerFigur  3Whole genome tiling path array CGH karyogram of an oral low grade dysplasia which subsequently pro-gressed to cancer. Whole genome tiling path array CGH karyogram of an oral low grade dysplasia which subsequently pro-gressed to cancer (Oral51). Each dark blue dot on the karyogram represents the average signal ratio for an individual BAC clone from the array. Clones were plotted vertically against known chromosomal position. Log2 signal intensity ratios for each clone were plotted horizontally, with colored vertical lines denoting log2 signal ratios from -1 to 1. Where the signal intensity ratio equals zero (purple line), equivalent DNA copy number between the sample and the reference DNA was inferred. Alter-natively, DNA copy number increases were inferred where log2 > 0 (red line) and losses were inferred where log2 < 0 (green line). Numerous whole chromosome, whole arm, and segmental changes are apparent. Examples of these alterations were magnified and are represented in orange boxes. High level segmental amplicons for chromosome 2 and 4 are depicted in this manner. Lower copy number segmental (chromosome 8) and whole arm (chromosome 12) gains are similarly shown. The magnified image for Chromosome 9 shows a complex genomic rearrangement that includes multiple segmental losses and a high level segmental amplification event.           QPQ QPPP         PPPPP PPPPPPPPPPPPPPPPQPPMolecular Cancer 2009, 8:50 http://www.molecular-cancer.com/content/8/1/50extracted by a standard phenol:chloroform/ethanol pre-cipitation protocol. Samples were selected for furtherstudy based on the quantity and quality of DNA. Demo-graphic information for these samples can be viewed inAdditional File 1: Table S1. All lesions were obtained fromdifferent patients and were taken before treatment wasgiven.Whole genome tiling-path array comparative genomic hybridization (CGH)The array platform, comprised of 26,363 overlapping ele-ments, was manufactured on site, as previously described[19,20]. Briefly, 200 ng of test and reference DNA wereseparately labeled with Cyanine-3 and Cyanine-5 dCTPsUsing the BioPrime DNA labeling system (Invitrogen,Burlington, Ontario, Canada). DNA probes were thenpooled and unincorporated nucleotides were removedwith a YM-30 Microcon centrifugation tube (Millipore).Next, 100 μg of Cot-1 DNA (Invitrogen) was added andthe entire mixture was precipitated. This material was thenre-suspended in a 45 μl cocktail consisting of DIG Easyhybridization solution (Roche), sheared herring spermDNA (Sigma-Aldrich), and yeast tRNA (Calbiochem).Probe denaturing and blocking steps followed at 85°Cand 45°C for 10 minutes and for one hour respectively.Subsequently, the probe mixture was applied to the sur-face of the array, coverslips were applied, and arrays wereincubated at 45°C for 36 hours. Slides next underwentfive agitating washes in 0.1× saline sodium citrate, 0.1%SDS at 45°C (each wash ~5 min). Rinses with 0.1× SSCfollowed, then drying by centrifugation. Genome profilesare available online through the NCBI Gene ExpressionOmnibus (http://www.ncbi.nlm.nih.gov/geo/,GSE11275).Imaging and analysisA CCD-based imaging system (Arrayworx eAuto, API,Issaquah, WA) was used to determine signal intensities ineach dye channel. Images were analyzed with Softworxarray analysis software. Experimental bias due to the arrayplatform was removed using a stepwise normalizationframework [21]. All spots with standard deviations > 0.1were excluded from the analysis. Custom viewing soft-ware, SeeGH, was used to visualize all data as log2 ratioplots [22]. Array probes were aligned based on the May2004 mapping of the human genome. To delineateregions of copy number gain and loss, segmentation anal-ysis was performed on array data using the aCGH-Smoothalgorithm (default parameters were used on all settingsexcept for the following changes: lambda value = 6.75,maximum number of breakpoints in initial pool = 100,minimum difference between levels = 0.2) [12]. The copynumber status for clones filtered by the above criteria wassegmental change was defined as being a continuous alter-ation between 10 clones and half a chromosome arm insize. Segmental alterations reported to be polymorphismswere excluded from analysis [23]. Tumor genome profiledata are available online through the NCBI Gene Expres-sion Omnibus (http://www.ncbi.nlm.nih.gov/geo/, acces-sion number GSE11275).Statistical analysisK-nearest neighbor analysis was used to classify the sam-ples based on the number of segmental and whole chro-mosome arm changes that were present. Since an evennumber of groups existed, we used the nearest threeneighbors. A standard Euclidean distance metric was usedto determine the distance to each neighbor, with equalweighting given to both segmental and whole armchanges. If more than three neighbors were at equal dis-tance, all neighbors at that distance were used.AbbreviationsOPL: oral premalignant lesion; HGD: high grade dyspla-sia; LGD: low grade dysplasia; CIS: carcinoma in situ;OSCC: oral squamous cell carcinoma; CGH: comparativegenomic hybridization.Competing interestsThe authors declare that they have no competing interests.Authors' contributionsCG, RC, TPHB, and RTN undertook experiments and dataanalysis. LZ provided expert pathological review. MPRand WLL were principal investigators on this project. Allauthors read, provided critical feedback, and approved thefinal manuscript.Additional materialAcknowledgementsThe authors thank Jennifer Kennett and Heather Saprunoff for expert tech-nical assistance. This work was supported by funds from NIDCR grants R01 DE13124 and R01 DE015965; Canadian Institute for Health Research (CIHR); Genome Canada/British Columbia. RC and TPHB were supported by fellowships from CIHR and the Michael Smith Foundation for Health Research.ReferencesAdditional file 1Supplemental table. Demographic patient information.Click here for file[http://www.biomedcentral.com/content/supplementary/1476-4598-8-50-S1.xls]Page 6 of 7(page number not for citation purposes)inferred by the status of neighboring clones. A chromo-some arm was considered changed if ≥ 90% of clonesspanning the arm exhibited the same alteration status. A1. WHO Collaborating Reference Centre for Oral PrecancerousLesions: Definition of leukoplakia and related lesions: an aid tostudies on oral precancer.  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Wong KK, deLeeuw RJ, Dosanjh NS, Kimm LR, Cheng Z, HorsmanDE, MacAulay C, Ng RT, Brown CJ, Eichler EE, Lam WL: A compre-hensive analysis of common copy-number variations in the yours — you keep the copyrightSubmit your manuscript here:http://www.biomedcentral.com/info/publishing_adv.aspBioMedcentralPage 7 of 7(page number not for citation purposes)human genome.  Am J Hum Genet 2007, 80:91-104.

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