Signiﬁcance of TP53 Mutation in Wilms Tumors with Diffuse ... · Reinier de Graaf Hospital,...

Biology of Human Tumors

Significance of TP53 Mutation in Wilms Tumorswith Diffuse Anaplasia: A Report from theChildren's Oncology GroupAriadne H.A.G. Ooms1,2,3, Samantha Gadd1, Daniela S. Gerhard4, Malcolm A. Smith5,Jaime M. Guidry Auvil4, Daoud Meerzaman6, Qing-Rong Chen6, Chih Hao Hsu6, ChunhuaYan6, Cu Nguyen6, Ying Hu6, Yussanne Ma7, Zusheng Zong7, Andrew J. Mungall7,Richard A. Moore7, Marco A. Marra7,8, Vicki Huff9, Jeffrey S. Dome10, Yueh-Yun Chi11,Jing Tian11, James I. Geller12, Charles G. Mullighan13, Jing Ma13, David A.Wheeler14,Oliver A. Hampton14, Amy L.Walz15,16, Marry M. van den Heuvel-Eibrink2,Ronald R. de Krijger2,17, Nicole Ross18, JulieM.Gastier-Foster18,19, and Elizabeth J. Perlman1

Abstract

Purpose: To investigate the role and significance of TP53mutation in diffusely anaplastic Wilms tumors (DAWTs).

Experimental Design: All DAWTs registered on NationalWilms Tumor Study-5 (n ¼ 118) with available samples wereanalyzed for TP53 mutations and copy loss. Integrative genomicanalysis was performed on 39 selected DAWTs.

Results: Following analysis of a single random sample, 57DAWTs (48%) demonstrated TP53 mutations, 13 (11%) copyloss without mutation, and 48 (41%) lacked both [defined asTP53-wild-type (wt)]. Patients with stage III/IV TP53-wt DAWTs(but not those with stage I/II disease) had significantly lowerrelapse and death rates than those with TP53 abnormalities. In-depth analysis of a subset of 39 DAWTs showed seven (18%) tobe TP53-wt: These demonstrated gene expression evidence of anactive p53 pathway. Retrospective pathology review of TP53-wt

DAWT revealed no or very low volume of anaplasia in six of seventumors. When samples from TP53-wt tumors known to containanaplasia histologically were available, abnormal p53 proteinaccumulation was observed by immunohistochemistry.

Conclusions: These data support the key role of TP53 loss inthe development of anaplasia in WT, and support its signif-icant clinical impact in patients with residual anaplastic tumorfollowing surgery. These data also suggest that most DAWTswill show evidence of TP53 mutation when samples selectedfor the presence of anaplasia are analyzed. This suggests thatmodifications of the current criteria to also consider volumeof anaplasia and documentation of TP53 aberrations maybetter reflect the risk of relapse and death and enable opti-mization of therapeutic stratification. Clin Cancer Res; 22(22);5582–91. �2016 AACR.

IntroductionThe most common pediatric renal malignancy is Wilms tumor

(WT; ref. 1). Histopathologic categories of WT differing in theirprognosis were first reported by Beckwith and Palmer, whoidentified the presence of anaplasia (defined as nuclear hyper-

chromasia and enlargement and atypical polyploid mitoses) in5% of WTs (2). Subsequent studies subclassified anaplastic WTinto those with focal or diffuse anaplasia (DAWT), based on thecircumscription and distribution of anaplasia (3). WTs lackinganaplasia are classified as favorable histology (FHWT). The

1Department of Pathology and Laboratory Medicine, Ann and RobertH. Lurie Children's Hospital of Chicago, Robert H. Lurie Cancer Center,NorthwesternUniversity,Chicago, Illinois. 2PrincessMaximaCentre forPediatric Oncology, Utrecht, the Netherlands. 3Department of Pathol-ogy, Pathan BV, Sint FranciscusGasthuis, Rotterdam, theNetherlands.4Office of Cancer Genomics, National Cancer Institute, Bethesda,Maryland. 5Cancer Therapy Evaluation Program, National CancerInstitute, Bethesda, Maryland. 6Center for Biomedical Informatics andInformation Technology, National Cancer Institute, Bethesda, Mary-land. 7Canada's Michael Smith Genome Sciences Centre, BritishColumbia Cancer Agency (BCCA), Vancouver, British Columbia,Canada. 8Department of Medical Genetics, University of BritishColumbia, Vancouver, British Columbia, Canada. 9Department ofGenetics, The University of Texas MDAnderson Cancer Center, Hous-ton, Texas. 10Division of Pediatric Hematology/Oncology, Children'sNational Medical Center, Washington, DC. 11Department of Biostatis-tics, University of Florida, Gainesville, Florida. 12Division of PediatricOncology, Cincinnati Children's Hospital Medical Center, University ofCincinnati, Cincinnati, Ohio. 13Department of Pathology, St. Jude Chil-dren's Research Hospital, Memphis, Tennessee. 14Department ofMolecular and Human Genetics, Baylor College of Medicine, Houston,

Texas. 15Division of Hematology-Oncology and Transplantation, Annand Robert H. Lurie Children's Hospital of Chicago, NorthwesternUniversity's Feinberg School of Medicine, Chicago, Illinois. 16North-western Medicine Developmental Therapeutics Institute, Northwest-ern Memorial Hospital, Chicago, Illinois. 17Department of Pathology,Reinier de Graaf Hospital, Delft, the Netherlands. 18Department ofPathology and Laboratory Medicine, Nationwide Children's Hospital,Ohio State University College of Medicine, Columbus, Ohio. 19Depart-ments of Pathology and Pediatrics, Ohio State University College ofMedicine, Columbus, Ohio.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

Corresponding Author: Elizabeth J. Perlman, Ann & Robert H. Lurie Children'sHospital, 225 East ChicagoAvenue, Chicago, IL 60611. Phone: 312-227-3967; Fax:312-227-9615; E-mail: [email protected]

doi: 10.1158/1078-0432.CCR-16-0985

�2016 American Association for Cancer Research.

ClinicalCancerResearch

Clin Cancer Res; 22(22) November 15, 20165582

on January 20, 2020. © 2016 American Association for Cancer Research. clincancerres.aacrjournals.org Downloaded from

Published OnlineFirst October 4, 2016; DOI: 10.1158/1078-0432.CCR-16-0985

http://clincancerres.aacrjournals.org/

presence of anaplasia has been consistently associated with apoorer prognosis compared with FHWT, and the current thera-peutic protocols continue to rely on these histologic classifica-tions for treatment stratification (4–6). Anaplasia has long beenconsidered to represent a clonal event within a WT that wasoriginally of favorable histology. This concept has largely beenbased on the examination of anaplastic and nonanaplasticregions of the same tumor, inwhich TP53mutationwas identifiedonly in the anaplastic region (7–9). Studies of small conveniencecohorts have identified TP53mutations in 50% to 86% of DAWTwith the mutation frequency varying with the methods used andsamples analyzed (8–10). The presence of TP53 mutationsdetected by immunopositivity (due to abnormal accumulationof mutant p53 protein) has also been associated with bothanaplasia and with poorer prognosis in WTs (11, 12). Recently,25 of 40 (62.5%) selected patients with DAWT were reported toshow either TP53mutation or copy loss; the 15 patients (37.4%)lacking both had a significantly better outcome (20% relapsed)than those with detectable TP53 abnormalities (56% relapsed,P ¼ 0.008), with similar differences in overall survival (13).However, correlations between stage, 17p13 abnormality, andoutcome could not be analyzed. The current study addresses theprevalence of TP53mutation and 17p13 copy loss in 118 DAWTregistered in the National Wilms Tumor Study (NWTS)-5 coop-erative group protocol and discusses the benefits and problemsassociated with the use of TP53 status to therapeutically stratifypatients with DAWT. We accomplish this through participationwith the NCI's "Therapeutically Applicable Research to GenerateEffective Treatments" (TARGET) initiative, which investigateshigh-risk pediatric tumors through comprehensive integrativegenomics (http://ocg.cancer.gov/program/target). We then select39 of these 118 patients for in-depth investigation by compre-hensive integrative genomic analysis focusing on TP53 and rel-evant pathways.

Experimental ProceduresThis study was conducted as a part of the TARGET initiative.

The raw sequencing data (BAM files) are deposited in theSequence Read Archive (SRA) at the National Center for Bio-

technology Information, and are accessible through the data-base of genotypes and phenotypes (dbGAP, http://www.ncbi.nlm.nih.gov/gap) under the accession number phs000471. Thegene expression, chromosome copy number, as well as theresults of sequence analysis (i.e., MAF and summary files) andclinical information on the cases studied are available throughthe TARGET Data Matrix (http://target.nci.nih.gov/dataMatrix/TARGET_DataMatrix.html), annotated within MIAME compli-ant MAGE-TAB files fully describing the methods, the specimenprocessing details, and the quality control parameters. A sum-mary of the methods used in this study is provided below.

SpecimensAll tumors registered on the NWTS-5 protocol that were

classified as DAWT based on central pathology review and forwhich pre-therapy tumor was banked by the Children's Oncol-ogy Group (COG) Biopathology Center (BPC; 118 DAWTs),were evaluated by target capture sequencing and MLPA. For in-depth analysis, 39 of the 118 patients who also had sufficientnormal DNA from peripheral blood or kidney and for which atleast 50% of the tumor slides demonstrated anaplasia wereevaluated comprehensively. Frozen sections were evaluated,and tumors with <70% viable tumor cellularity were excluded.RNA and DNA were coextracted from tissue using a modifi-cation of the DNA/RNA AllPrep Kit (Qiagen). DNA wasextracted from blood using the QiaAmp blood midi Kit (Qia-gen). Studies were performed with the approval of the LurieChildren's Hospital Institutional Review Board.

SequencingFor target capture sequencing,TP53probeswere designed using

Agilent's SureDesign online web-based tool (https://earray.chem.agilent.com/suredesign/) using RefSeq IDs limited to codingexons (chromosomal location 7571645-7590899). Each regionwas padded with an additional 10 bases on both the 50 and 30

ends. Probe density was specified at 2x, and 98.7% of the targetregion was covered by a probe. Genomic DNA libraries wereconstructed according to BCCA-GSC plate-based and paired-endlibrary protocols on a Biomek FX liquid handling robot (Beck-man-Coulter). The pooled libraries were hybridized to the RNAprobes. Post-capture material was purified and enriched with 10cycles of PCR. Paired-end 100 base reads were sequenced per poolin a single lane of an Illumina HiSeq2500 instrument. Thepredicted impact of the variants was annotatedwith the followingalgorithms: SIFT using Ensembl Variant Effect Predictor Version75 (14), PolyPhen Version 2 (15), MutationTaster (16), or Pro-vean Version 1.1.3 (17, 18).

Of the 39 cases analyzed in depth, 21 underwent whole-genome sequencing (WGS) and 18 whole-exome sequencing(WES). WGS libraries were constructed and sequenced usingComplete Genomics Inc. (CGI) technology (http://www.comple-tegenomics.com/customer-support/documentation/162097975.html; ref. 19). Variants were identified through a pipeline that isdescribed on the TARGET DataMatrix. The variants were filteredretaining all somatic, nonsynonymous variants in exons with asomatic score >�10, somatic rank � 0.1, and Fisher's exact testP < 0.05. WES was performed on the Illumina HiSeq platform.Variant calling from the aligned BAM files was performed usingboth the ATLAS and SAMtools, and annotation and filteringwere performed using the SACBE annotation pipeline (20, 21).In addition, the WES BAM files were also analyzed using

Translational Relevance

Anaplasia in Wilms tumor (WT) has long been associatedwith TP53mutation, although determining its significance hasbeen limited by both methodology and the patient popula-tions analyzed. We show 41% of 118 prospectively identifiedDAWTs to lack TP53 abnormalities by sequencing or copy-number analysis performed on a random sample. This lackwas associated with (1) no or a very low volume of anaplasticcells in the entire tumor, (2) evidence of abnormal TP53protein accumulation (consistent with mutation) in othersamples of the same tumor selected for the presence ofanaplasia, and (3) a significantly lower relapse rate comparedwith thosewithTP53 abnormalities in patientswith stage III orIV disease. Future studies that evaluate volume and location ofanaplasia and confirm TP53 abnormalities may enable opti-mized therapeutic stratification and thereby avoid toxic ther-apy in some children.

Significance of TP53 Mutation in Anaplastic Wilms Tumor

www.aacrjournals.org Clin Cancer Res; 22(22) November 15, 2016 5583




Bambino (22) and then combined. High-quality somatic, non-synonymous exonic variants from both platforms were identi-fied and annotated using the Oncotator algorithm (http://www.broadinstitute.org/oncotator/).

For mRNA sequencing, following first- and second-strandcDNA synthesis, quantification, and quality verification, plate-based libraries were prepared following the BCCA-GSC paired-end protocol. The libraries were sequenced on the IlluminaHiSeq2000/2500 platform using v3 chemistry and HiSeq ControlSoftware version 2.0.10, aligned to GRCh37-lite genome-plus-junctions (23) using BWA Version 0.5.7 (24). Variants were thendetected on positive- and negative-split BAMs separately andannotated with SnpEff (ref. 25; Ensembl 66) and SnpSift (ref. 26;dbSNP137 and COSMIC64).

Copy-number analysisWithin the 39 samples analyzed in depth, nucleic acid labeling,

hybridization, and array scanning were performed on tumor andcorresponding normal samples according to the manufacturer'sprotocol for the Affymetrix 6.0 SNP array. The resulting .cel fileswere processed using Affymetrix Genotyping Console (GTC) 4.0software. Reference normalization utilized a diploid chromo-some for each sample, as previously described (27). Circularbinary segmentation (CBS) was performed in R using the DNA-copy BioConductor package. When Affy SNP 6.0 data were notavailable, copy-number data were calculated based on the CGI-relative coverage smoothed in 100-kb windows, corrected forthe GC content, and normalized using composite baselinecoverage from multiple healthy samples. The determinationof areas of gain and loss was accomplished by importingsegmented (Level 3) data into IGV (http://www.broadinsti-tute.org/igv/). Segmented regions containing at least eightmarkers in which the log2 value was �þ0.5 or ��0.5 wereconsidered regions of gain or loss, respectively.

Within the 118 initial cases, analysis for 17p13 copy-numberchanges was performed with Multiplex Ligation Probe Amplifi-cation (MLPA) using the SALSA MLPA Kit (MRC Holland), usingmethods previously described (28). The probes used are providedin Supplementary Table S4. The raw data peaks were visualized byusing Genemarker to ensure the presence of distinct peaks; sam-ples that passed these criteria were then normalized by usingpopulation normalization. Samples with TP53 peak values < 0.75for two out of three TP53 probes were classified as having copy-number loss.

Gene expression analysisTotal RNA was analyzed using the Affymetrix U133þ2 chip,

according to themanufacturer's protocol. The arrayswere scannedand analyzed using the Gene-Chip Operating Software (GCOS).Robust Multichip Average (RMA) normalization was performedusing the ExpressionFileCreator module of the Broad Institute'sGenePattern server (http://www.broadinstitute.org/cancer/soft-ware/genepattern/); the data were collapsed by using the Collap-seDataset module.

Statistical evaluationUnsupervised analysis was performed using Non-negative

Matrix Factorization Consensus Version 5 (NMF; ref. 29). Com-parisons of gene expression between two groups of samples wereperformed using Significance Analysis of Microarray 4.0 (30)following removal of probe-sets classified as absent in >95% of

the samples analyzed; genes with SAM q-values of < 0.1 andStudent t test BH-corrected P values <0.05 were considered sig-nificant. Supervised hierarchical clustering was performed usingthe Hierarchical Clustering module of the Broad Institute's GenePattern server (http://www.broadinstitute.org/cancer/software/genepattern/). Gene Set Enrichment Analyses (GSEA), version2.0.14 (http://www.broadinstitute.org/gsea; ref. 31), were used toperform a comparison between tumors with or without TP53abnormalities by using the c2 Biocarta module (v5). Analyseswere run using 1000 permutations, phenotype permutation, anddefault basic and advanced fields. We used the default GSEAsettings (excluding genes sets with <15 genes or >500 genes).Significant enrichment was defined as those lists with FDR <20%,and a P value <5%. Time to relapse or progression was charac-terized by the Kaplan–Meier curve of disease-free survival (DFS).The log-rank test was used to compare the difference in DFSbetween DAWTs with TP53 mutation and/or copy loss andDAWTs without either. Statistical significance was assessed at the0.05 level.

ResultsTP53 mutations and copy-number changes in 118 DAWTs

To determine the overall frequency of TP53 mutation in unse-lected DAWTs, we identified all patients with DAWT registeredon the NWTS-5 protocol for which tumor samples were available(n ¼ 118), and analyzed these for TP53 copy-number alterationsusingMLPA and for variants in TP53 using target capture sequenc-ing that covered the coding region (chromosomal location7571645-7590899). Variants were retained that had a total tumorread count >10, alternative base count in the tumor comparedwith reference genome >3 with an allelic fraction � 0.05, and aminor allele frequency �0.005 in the relevant population indbSNP142. TP53 variants were identified in 57 of 118 DAWTs(48%), with four tumors showing two different TP53 variants.The details of each variant are provided in Supplementary TableS1. All single-nucleotide variants (SNV) were present in COSMICversion 76 and were evaluated as damaging by at least onealgorithm (see methods). Of note, 21 of 61 (34%) of the TP53mutations involved the exon 10 tetramerization motif, with13 involving p.R342 (five c.1024C>T nonsense mutations andeight c.1025G>C missense mutations); one nonsense mutationremoved the tetramerization domain entirely (p.R306�). FourTP53 variants were splice site mutations, and the remainingmutations were distributed over or just outside the DNA-bindingdomain (Fig. 1). Given the prior association between WTand constitutional TP53 splice site mutations in patients withLi–Fraumeni syndrome (LFS; refs. 32–34), we sequenced avail-ableDNA samples frombloodor normal kidney of twoof the fourpatients with somatic splice site mutations and did not find thevariants in the germline. All TP53 variants were verified bycomprehensive sequencing of tumor DNA or mRNA (see below).

Loss of TP53 (17p13) was analyzed by MLPA in 116 of 118tumors with available tumor DNA.Of the 53 tumors with a singleTP53mutation, 42 (79%) also showed loss of one copy of 17p13,9 (17%) lacked 17p13 loss, and two lacked available DNA. Sevenof the nine tumors with TP53 mutations lacking 17p13 lossdemonstrated a mutant TP53 allelic fraction of >75%, providingevidence for loss of the chromosome segment harboring the wild-type (wt) TP53 and duplication of the chromosome segmentcontaining the mutant allele. Thus, of the 55 fully evaluable

Ooms et al.

Clin Cancer Res; 22(22) November 15, 2016 Clinical Cancer Research5584




tumors carrying TP53mutations [including four tumors with twodifferent TP53 mutations (compound heterozygotes)], only twoare predicted to have retained one wt allele. Thirteen of the 61TP53mutation-negative DAWTs had loss of 17p13. Overall, 48 of118 DAWTs (41%) lacked TP53 mutation and/or copy loss(defined asTP53-wt). Themean age at diagnosis of all 118DAWTswas 58months (range, 8.4–184.8months). This is higher than thereported mean age at diagnosis for FHWTs (42 months; ref. 35).There was no significant difference in gender, predominant his-tologic pattern (blastemal, epithelial, stromal, or mixed), ornephrogenic rest status between FHWTs and DAWTs. Clinicaland pathologic features and the presence or absence of copy-number changes and TP53 mutations are provided in Supple-mentary Table S2.

Relapse occurred in 34 of 118 patients (29%; median time torelapse 313 days). All patients who relapsed died, 33 fromdisease and one from toxicity of therapy. Eight additionalpatients showed disease progression despite therapy, and alldied from disease. The remaining patients (n ¼ 76) did notrelapse and are alive at a mean of 2,378-day follow-up (range,301–4,520 days; Supplementary Table S2). When analyzed bystage, there was no overt difference in prevalence of TP53abnormalities by stage (Table 1). Those patients with stage I–IIdisease showed no difference in outcome based on TP53 status;however, those patients with stage III or IV disease and TP53abnormalities in their tumors showed a significantly worse DFSand overall survival compared with those that were TP53-wt (P¼0.0006 and P ¼ 0.0007, respectively; Table 1, Fig. 2).

Integrative in-depth analysis of 39 DAWTComprehensive genomic analysis of 39of the above118DAWT

was performed (see Supplementary Tables S1 and S2 for specificsamples examined). Included were DAWTs with sufficient case-matched peripheral blood or normal kidney samples and whosetumor demonstrated anaplasia in at least 50% of reviewed slides(regardless of the volume of anaplasia in each slide), as recordedat the time of central pathology review. Characterization includedeither WGS (n ¼ 21) or WES (n ¼ 18) as well as global chromo-some segment copy-number analysis (Affymetrix 6.0), gene

expression analysis (Affymetrix U133þ2), andmRNA sequencing(mRNA seq).

Recurrent mutations previously reported in FHWT were alsoidentified in a minority of DAWT including those involvingWT1 (1), WTX (1), CTNNB1 (1), DROSHA (1), DGCR8 (1),and SIX1 (1; Supplementary Table S3). TP53 was the only genewith somatic mutations more highly represented in DAWTsthan in FHWTs (sequencing and verification of all TARGEThigh-risk WTs will be reported in full when the analysis iscompleted). Twenty-seven high-quality, somatic, nonsynon-ymous variants in TP53 (transcript NM_001126112) wereidentified in 25 (64%) of these 39 DAWT by either WGS orWES (Supplementary Table S1). Variants in other genes withinthe p53 pathway were not identified. Of the 39 cases, 37 hadsufficient RNA to perform mRNAseq. Two additional cases withTP53 mutations were identified by mRNAseq, but not by WGS(PAJMRL) or WES (PAKXXF). Unfiltered variants detected byWGS and WES were also evaluated for TP53 mutations thatfailed filtering; one additional TP53 mutation was identified(PALLCK), for a total of 30 TP53 mutations in 28 of the 39DAWT. These three additional TP53 variants were verified bytarget capture (above).

DNA chromosomal segment analysisSegmental loss of 17p13 including the TP53 locus was iden-

tified in 25 of 28 DAWTs containing mutant TP53. In 21 of 25 ofthese DAWTs, the complete chromosome 17 short arm was lost.The remaining three tumors with TP53 mutations, but lackingcopy loss, either had two different TP53 mutations (PAKFYV) ordemonstrated a mutant allelic fraction >95% and segmentaluniparental disomy of 17p (PAJLKC, PADXAY), consistent withloss of the normal allele and duplication of the mutant allele. Ofthe 11 DAWTs lacking TP53 sequence variants, loss of one allelewas identified in four tumors (three showing loss restricted to theshort arm and one showing loss of the entire chromosome 17).One of these tumors (PAKUIT) demonstrated an additional smallsegment of loss (definedby 23SNPs) involving the 30 endofTP53,resulting in homozygous loss of this region. Normal 17p13 copynumber was present in seven cases, and they lacked evidence of

Figure 1.

TP53mutations inDAWTs. Illustrated is the location of the TP53mutations (n¼61)within the knownp53protein domains. The number of variants detected for each isprovided in the parenthesis. TAD, Transcription-Activation Domain; DNABD, DNA-binding domain; TM, Tetramerization Domain.






uniparental disomy of 17p13. Therefore, seven of 39DAWTswereidentified as TP53-wt. Of note, neither 17p loss nor TP53 muta-tion was identified in any of the 77 TARGET FHWT comprehen-sively analyzed (36).

Segmental loss at 11p13 (the location ofWT1)was identifiedin six DAWTs, and segmental loss at Xq11.2 (the location ofWTX) was identified in eight cases (Supplementary Table S3);these proportions are similar to what was seen in FHWTs (37).The seven TP53-wt DAWT showed fewer total copy-numberalterations in their genomes (defined as segments with � 8markers and log2 ratio�þ0.5 or ��0.5) when compared withthe DAWTs carrying TP53 mutations and/or copy loss. In fact,TP53-wt DAWT showed a distribution of segmental gains andlosses similar to the 77 TARGET FHWTs previously reported(36). DAWTs with TP53 abnormalities had 169� 226 segmentsof gain or loss, compared with TP53-wt DAWTs, which had 55� 51 segments of gain or loss (P ¼ 0.016), and with FHWTs,which had 47 � 52 (P ¼ 0.006) segments of gain or loss. Inaddition to loss of 17p, the most common copy-numberchanges in DAWTs with TP53 abnormalities included loss of4q [identified in 69% (22/32) DAWT with TP53 abnormalities,14% (1/7) TP53-wt DAWT, and 8% (2/77) FHWT], loss of 14q[66% (21/32) DAWT with TP53 abnormalities, 14% (1/7)TP53-wt DAWTs, and 11.7% (9/77) FHWT], loss of 16q[62.5% (20/32) DAWT with TP53 abnormalities, 28.6% (2/7) TP53-wt DAWTs, and 26% (20/77) FHWT], and loss ofchromosome 22 [56% (18/32) DAWT with TP53 abnormali-ties, 14% (1/7) TP53-wt DAWTs, and 12% (9/77) FHWT; Fig.3A; Supplementary Table S3]. These findings are similar toprevious reports of DAWT (37, 38). Of note, gain of 1q wasidentified in 50% (16/32) of DAWT with TP53 abnormalities,comparable with 51% (39/77) identified in relapsed FHWT(18), similar to previous reports (31). There was a lower rate of1q gain in TP53-wt DAWT (2/7, 28.6%), likewise consistentwith the previously reported data from FHWT (31) consideringthat this group was not selected for relapse status. Of note, noneof the DAWTs demonstrated amplification of 12q15, a regionencompassing the MDM2 gene which encodes an E3 ubiquitinligase that targets p53 for degradation (39).

Gene expression analysisUnsupervised analysis of the 38 tumors for which gene

expression data were available did not show clustering of theTP53-wt DAWT. Supervised analysis comparing the sevenTP53-wt DAWTs with the remaining 31 tumors showing TP3mutation and/or copy loss using Statistical Analysis for Micro-

array (SAM) identified 35 differentially expressed genes (SAMq < 0.10 and Student t test BH corrected P value < 0.05).Hierarchical analysis of these 35 genes (Fig. 3B) shows all to beupregulated in tumors lacking TP53 abnormalities. Nineteenare located on 17p11–13. In addition, genes within apoptoticpathways known to be positively regulated by p53 (such asBAX and CDKN1A) were upregulated. Notably, TP53 itself wasnot significantly transcriptionally upregulated in TP53-wttumors compared with the remaining 31 tumors, becausesome TP53-mutant tumors express relatively high levels of themutant mRNA. To identify canonical pathways and biologicalfunctions associated with TP53-wt tumors, we performedGSEA Version 2.0.14 (31) using the same comparison groups.Two gene sets were significantly enriched (FDR < 20%),including genes involved in the Biocarta p53 (P ¼ 0.012, FDR¼ 0.190) and FAS apoptosis (P ¼ 0.004, FD ¼ 0.19) pathways.In summary, analysis of gene expression patterns supports anactive p53 pathway within the TP53-wt tumors.

Figure 2.

Association between stage, TP53 status, andDFS. Kaplan–Meier curve of DFS (inyears), comparing DAWTs with TP53 mutation and/or copy loss and DAWTswithout either. Numbers at risk are listed at the bottomof the graphs. All patientswho relapsed or progressed also died.

Table 1. Clinical outcome by stage and TP53 status

Disease stageN (% of stage

group)Relapse orprogression

Death fromdisease

Stage I (n ¼ 14)TP53 abnormality 8 (57%) 3 2No TP53 abnormality 6 (43%) 2 1

Stage II (n ¼ 37)TP53 abnormality 18 (48.6%) 4 4No TP53 abnormality 19 (51.4%) 3 3

Stage III (n ¼ 57)TP53 abnormality 39 (68.4%) 24 24No TP53 abnormality 18 (31.6%) 3 3

Stage IV (n ¼ 10)TP53 abnormality 5 (50%) 3 3No TP53 abnormality 5 (50%) 0 0

Ooms et al.





Histology and p53 immunohistochemistryIt has long been recognized that tumors with TP53 mutations

often (but not always) show nuclear accumulation of the abnor-mal protein (40, 41). Immunohistochemistry is widely usedclinically to document the presence of TP53 mutation in many

tumor types due to its speed, low cost, and ability to assesslocalized areas showing features suspicious for anaplasia. Wetherefore examined the available TP53-wt tumors for abnormalprotein accumulation by p53 immunohistochemistry using theprediluted DO7 antibody (Ventana catalogue # 790-2912). It isimportant to note that for the COG biology studies, frozen andformalin-fixed tissue samples are randomly taken by the localpathologist prior to histologic evaluation. The sample that isfrozen is commonly taken from a different area than the sampleplaced in formalin. For six of the seven TP53-wt tumors thatunderwent in-depth molecular analyses, a randomly submittedformalin-fixed sample was submitted to the COG BPC. Unequiv-ocal anaplasia was present histologically in three of six samples,and each of these three tumors demonstrated unequivocal evi-dence of abnormal nuclear p53 protein accumulation in theregions of anaplasia (Fig. 4). The individual blocks available fromthe BPC for the remaining three cases did not show histologicevidence of anaplasia and did not show abnormal protein accu-mulation. This suggests that for the three evaluable TP53-wtDAWTs, the failure to detect TP53 abnormalities in the frozensamples results from failure to sample tissue containing theanaplastic clone. Lastly, retrospective analysis of the full set ofslides from the sevenTP53-wt tumors demonstratedfive to showavery low volume of anaplastic cells (<1%). This varied highly inpattern,with some showing small foci of anaplastic cells in a smallnumber of slides and others showing individual quite rare indi-vidual anaplastic cells in most slides. One of these six cases wasevaluated by three pathologists, who were not able to confidentlymake the diagnosis of anaplasia. TheonlyTP53-wtDAWT to showappreciable volumes of anaplasia (PAJMLZ) had stage II disease,relapsed, and died.

DiscussionTP53, the most commonly mutated gene in human cancer,

encodes a transcription factor that regulates the expression ofgenes involved in cell cycle, senescence, and apoptosis. Untilrecently, sequencing of the TP53 gene has largely relied onassessment of the highly conserved DNA-binding domain (exons5–8), explaining why most mutations (>80%) in Cosmic havebeen reported in these domains. Such studies underestimate TP53mutations identified in WTs, a third of which we demonstrate tooccur in exon 10, the tetramerization domain. Many mutant p53proteins evade degradation and accumulate to high levels that aretherefore able to be detected by immunohistochemistry. As aresult, p53 immunohistochemistry is often used as an alternativesimple and low-cost surrogate for detecting TP53 mutations intumors. However, not all TP53 mutations result in abnormalprotein accumulation (such as many nonsense mutations). It istherefore not surprising that there is a considerable lack ofcorrelation between p53 immunopositivity and TP53 mutationdetected historically by sequencing (41, 42). This lack of consis-tency has also been demonstrated in anaplastic WTs (8, 11).

We report TP53 mutations detected by sequencing alone tooccur with an overall frequency of 48% in 118 unselected patientswithDAWT registered on a single cooperative groupprotocol, andTP53 segmental copy loss without mutation was identified inanother 11%. While the majority of mutations involved the TP53DNA binding domain, a high proportion (34%) occurred in thetetramerization motif, also known as the oligomerizationdomain. Mutations in this domain have previously been shown

Figure 3.

Comparison of copy-number variations and gene expression in DAWTswith andwithout TP53 abnormalities. A, copy-number variations (CNVs; defined assegmentswith�8markers and log2 ratio�þ0.5 or��0.5) identified inDAWTswith TP53 abnormalities (top) orwithoutTP53 abnormalities (bottom). Each rowrepresents one DAWT. Segments in red represent CN loss and those in blue CNgain. The seven TP53-wt samples showed fewer copy-number alterations intheir genome when compared with the DAWTs carrying TP53mutations and/orcopy loss, and are similar to those previously reported in FHWTs. The tumorswith TP53 abnormalities had recurrent loss of chromosomes 4q, 14q, 16q, 17p,and 22. B, hierarchical analysis of genes differentially expressed in TP53mutantDAWT: SAM comparing the seven TP53-wt tumors with the remaining31 tumors identified 35 genes differentially expressed (SAMq <0.10 and Studentt test BH correctedP value <0.05). Hierarchical analysis of these 35 genes showsall to be upregulated in the tumors lacking TP53mutation or 17p13 copy-numberloss (red is upregulation, and blue indicates downregulation). These includeseveral genes located on 17p, and other genes associated within apoptoticpathways known to be regulated by p53 (such as BAX and CDKN1A).






to result in defective transcription, ubiquitylation, and protea-some-mediated degradation (43–45). WTs are infrequently asso-ciated with LFS, and five of six reported patients with both LFSand WT had TP53 splice site mutations (46). While we identifiedfour DAWTs with splice site mutations, no evidence of constitu-tional TP53 mutations was identified in the two with availablenormal samples.

To better understand the nature of TP53-wt DAWTs, we per-formed an in-depth genomic analysis of 39DAWTs.We identifiedmutations inWT1,WTX, CTNNB1, DROSHA, DGCR8, and SIX1/2 in patients with DAWTs, supporting the concept that TP53mutation occurs as a second event within WTs of multipleunderlying genetic causes. While the majority (82%) of these39 tumors demonstrated TP53 abnormalities (mutation and/orloss), seven DAWTs were TP53-wt. We did not identify anymutations in other genes within the p53 pathway in TP53-wtDAWT, or in any other geneswith knownbiologic relevance.Geneexpression analysis documented an intact p53 pathway and didnot provide evidence of disruption of another pathway inTP53-wtDAWTs. By gene expression and segmental copy-number analysis,TP53-wt DAWTs were not distinguishable from a previouslyreported larger group of FHWTs that were analyzed in the samemanner (36). Immunohistochemical analysis of all three evalu-able DAWTs that were TP53-wt by sequencing (performed on arandomly selected frozen sample) displayed unequivocallyabnormal p53 protein accumulation in an archival sample froma different area of the tumor (again randomly selected) thatcontained histologic evidence of anaplasia. Lastly, retrospectivehistologic analysis of the original set of hematoxylin and eosinslides from all seven TP53-wt DAWTs (by sequencing and copynumber alone) demonstrated all but one to have no or a lowvolume of anaplasia. Of note, in one of 39 tumors, the diag-nosis of anaplasia was not definitive upon retrospective reviewby three pathologists. Establishing a confident diagnosis ofanaplasia (based on nuclear enlargement, nuclear hyperchro-masia, and atypical mitoses) by histology alone is difficult, dueto the fact that neither nuclear enlargement nor atypical mitosesare able to be evaluated in a dichotomous fashion with fullconfidence. Tumors borderline for these criteria have beenclassified as "nuclear unrest" and have been shown to be mostappropriately grouped with FHWT based on clinical and path-ologic features (47).

The data acquired during this in-depth, integrative analysissupport the hypothesis that for TP53-wt DAWTs, the frozen tissuethat underwent comprehensive genomic analysis contained no orlow volume of anaplastic cells. By gene expression and copy-number analysis, this sample was comparable with FHWTs. Thediagnosis of DAWT is established by a pathologist after analyzingmultiple representative slides taken from all regions of the tumor.In contrast, tissue samples for banking or biologic studies aretakenwithout knowledge of the histology and are often limited toa small number of samples. This results in a variety of possibleoutcomes, as illustrated in Fig. 5. Conceptually, clonal develop-ment within a FHWT resulting from TP53 mutation may occurwithin an undifferentiated cell that may then proliferate in adiscohesive manner throughout much of the WT, resulting inscattered individual anaplastic cells that may be quite difficult todetect both histologically andmolecularly (Fig. 5A). Anaplasia insuch tumors is by current definition classified as diffuse, despitethe very small percentage of anaplastic cells. In some tumors, thesecells may differentiate and grow cohesively resulting in scattered

Figure 4.

Abnormal protein accumulation by p53 immunohistochemistry. Archivaltissue blocks containing histologic evidence of anaplasia were available forthree of the seven DAWTs determined to be TP53-wt by the absence of TP53mutation and copy-number loss in a single randomly selected frozen tumorsample (the remaining four cases did not have archival tissue within the BPCcontaining clear histologic evidence of anaplasia). (Original magnification,40X for all.). A, PAJMLZ: The block containing anaplasia shows diffuseabnormal p53 protein accumulation. B, PALEZT: The block containsanaplastic cells that were stromal that surrounded nonanaplastic blastemalcells. Immunohistochemistry shows nodules of blastemal cells that werelargely negative for p53 protein, with anaplastic stromal cells containingmarked accumulation of p53 protein. C, PAJNRH: The block had amicroscopic focus of anaplasia, which shows intense abnormal nuclearp53 staining.

Ooms et al.





nodules of anaplastic cells (Fig. 5B). Well-defined nodules ofanaplastic cells are easier to identify, depending on their size.

The most intriguing finding of this study is that stage III and IVDAWTs containing TP53 abnormalities within a randomly select-ed sample had a relapse and a death rate of 61%, compared with a13% relapse and death rate in DAWT that were determined to beTP53-wt in a randomly selected sample. Stage I and II DAWTs didnot show a significant impact of TP53 abnormality on outcome.These data together with the finding that six of seven TP53-wttumors had a very low volume of anaplasia suggests that theabsence or presence of TP53 abnormalities is a surrogate for theoverall extent of TP53 abnormalities within the tumor, in turnreflecting the burden of anaplasia. The burden of anaplasia mayhave less impact on outcome for stage I and II tumors, which arecompletely resected, than for stage III and IV tumors, which bydefinition have a high risk of residual tumor following nephrec-tomy. Our observations therefore raise the important question ofwhether or not the diagnostic criteria of anaplasia need to be re-evaluated, or alternatively if stratification based on p53 status isappropriate. Unfortunately, analysis of the copy-number andsequencing data within the 70 patients containing TP53 abnor-malities indicates that neither method alone is sufficiently sen-sitive to be clinically useful. Sequencing alone missed 13 of 70(19%, thoseDAWTs inwhich only 17p13 copy losswas detected),and copy-number analysis alone missed 13 of 70 (19%, thoseDAWTswithTP53mutations involvingboth alleles). This demon-strates that both modalities (i.e., sequencing and copy-numberanalysis of TP53) would need to be performed in order to rely onTP53 status to guide therapy. Platforms utilizing next-generationsequencing that enable the analysis of both are rapidly becomingavailable. Due to the retrospective nature of this study, and to ourreliance on material available from the BPC, we were unable toperform immunohistochemistry on anaplasia-containing tumorfor all cases and therefore were unable to document its sensitivity.

In conclusion, there is an opportunity for refining our diag-nostic and/or therapeutic strategy for DAWTs based on TP53status. However, two issues need to be addressed. First, theanalysis of TP53 abnormalities performed on random sections

of DAWT is insufficient. A better alternative would be for theinstitutional pathologist to identify a block (or a microdissectedregion) that optimally demonstrates anaplasia, and to submit thisblock or unstained slides for evaluation by p53 immunohis-tochemistry, 17p13 copy loss, and/or TP53 sequencing. Second,a new classification system for anaplasia needs to be developedthat better takes into account the location and burden of anapla-sia; this must show acceptable intra- and inter-reviewer reliabilitytesting and must correlate with outcome better than the currentclassification. Given these two changes, an algorithm could thenbe evaluated that allows for the identification of the most cost-effective method of stratification that is also able to be performedwithin an optimal time frame.

Lastly, the available wealth of information regarding TP53mutation in WTs may provide important lessons regarding theimplementation of precision medicine overall. First, despite thesophisticated tools now available, there are limitations to ourability to detect mutations that likely exist outside of the proteincoding region (for example, it is possible if not likely that at leastsome of the DAWTs with 17p13 copy-number loss alone haveundetected variants affecting TP53 directly or indirectly). Moreimportantly, our ability to recognize the mutant anaplastic cloneby histology enabled the full evaluation of the data. This ability isnot known to exist for the vast majority of other mutations thatmay be associated with differences in prognosis. Therefore, in theabsence of histologic clues, when attempting to implement pre-cision medicine by analyzing pretherapy diagnostic tumor sam-ples, we are in many ways limited to pathogenetic clonal eventsthat exist in the vast majority of cells analyzed, rather thanprogression-related events such as TP53 mutation, which mayalso be important determinants of prognosis. Relapse samples, onthe other hand, have undergone selection, and similar analysesusing these samples warrant prioritization as they will provideimportant information regarding both pathogenetic geneticevents as well as subsequent progression-related events.

Disclosure of Potential Conflicts of InterestC.G. Mullighan reports receiving commercial research grants from Loxo

Oncology; speakers bureauhonoraria fromAmgen; and is a consultant/advisoryboard member for Cancer Science Institute of Singapore and Incyte.No potential conflicts of interest were disclosed by the other authors.

DisclaimerThe content of this publication is solely the responsibility of the authors

and does not necessarily reflect the views or policies of the NIH or theDepartment of Health and Human Services, nor does the mention of tradenames, commercial products, or organizations imply endorsement by theU.S. Government.

Authors' ContributionsConceptionanddesign:D.S.Gerhard,M.A. Smith, V.Huff, J.S.Dome,M.M. vanden Heuvel-Eibrink, E.J. PerlmanDevelopment of methodology: A.J. Mungall, R.A. Moore, M.A. Marra,J.S. Dome, J.M. Gastier-Foster, E.J. PerlmanAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): A.J. Mungall, R.A. Moore, M.A. Marra, J.S. Dome,J.I. Geller, C.G. Mullighan, D.A. Wheeler, O.A. Hampton, J.M. Gastier-Foster,E.J. PerlmanAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): A.H.A.G. Ooms, S. Gadd, D.S. Gerhard, J.M. GuidryAuvil, D. Meerzaman, Q.-R. Chen, C.H. Hsu, C. Yan, C. Nguyen, Y. Hu,Y. Ma, Z. Zong, J.S. Dome, Y.-Y. Chi, J. Tian, J.I. Geller, C.G. Mullighan, J. Ma,D.A. Wheeler, O.A. Hampton, A.L. Walz, M.M. van den Heuvel-Eibrink,E.J. Perlman

Figure 5.

Tumor heterogeneity and sample selection in detecting TP53 abnormalities. Thepredominant underlying cause of failure to detect TP53 abnormalities isheterogeneity in tumorswith a low volume of anaplasia. The diagnosis of DAWTis established by a pathologist after analyzing multiple representative slidestaken from all regions of the tumor. In contrast, single randomly selected tissuesamples are taken for banking or biologic studies without knowledge of thehistology. In some cases, anaplasia may be diffuse, but may still be due to a verysmall percentage of cells,making it difficult to detect TP53 abnormalities. If thereare scattered nodules of anaplasia, area(s) of anaplasia may not be selected; orthere might be only a very small focus of anaplasia within the sample selected,insufficient for the detection of TP53 abnormalities.






Writing, review, and/or revision of the manuscript: A.H.A.G. Ooms,S. Gadd, D.S. Gerhard, M.A. Smith, J.M. Guidry Auvil, Q.-R. Chen, Y. Ma,A.J. Mungall, V. Huff, J.S. Dome, Y.-Y. Chi, J.I. Geller, A.L. Walz, M.M. vanden Heuvel-Eibrink, R.R. de Krijger, J.M. Gastier-Foster, E.J. PerlmanAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): A.H.A.G. Ooms, D.S. Gerhard, N. Ross,J.M. Gastier-Foster, E.J. PerlmanStudy supervision: D.S. Gerhard, J.M. Guidry Auvil, J.S. Dome, E.J. Perlman

AcknowledgmentsThe authors thank Patee Gesuwan and Leandro Hermida and the Data

Coordinating Center for their support. We also thank the Clinical Applica-tions of Core Technology Laboratory of the Hartwell Center for Bioinfor-matics and Biotechnology of St. Jude Children's Research Hospital forperforming the copy-number analysis, and the Northwestern UniversityGenomic Core facility for performing the methylation analysis. The authorsare grateful for the expertise of Karen Novik and Laura Monovich, PatriciaBeezhold, Donna Kersey, Debbie-Payne Turner, Mary McNulty, and YvonneMoyer. This work would not be possible without the dedication of all theexperts within the many clinical disciplines at the local institutions and

centrally within the Children's Oncology Group and National Wilms TumorStudy Group.

Grant SupportThe TARGET initiative is supported by NCI Grant U10 CA98543. Work

performedunder contracts from theNCI (T32CA079447, to A.L.Walz),USNIH[The Children's Oncology Group award numbers NIH U10CA180886,NIHU10CA180899; NIH U10CA098413; NIHU10CA42326 (E.J. Perlman);U10CA98543 (to J.S. Dome and E.J. Perlman); U24 CA114766; UO1CA88131(E.J. Perlman)] within HHSN261200800001E includes specimen processing(the COG BPC), WGS (CGI, Inc.), WES (Baylor College of Medicine),miRNAseq, RNAseq, and target capture sequencing (BCCA Genome SciencesCenter). This study was also supported by Dutch Cancer Society (to A.H.A.G.Ooms) and American and Lebanese Syrian Associated Charities of St. Jude (toC.G. Mullighan and Jing Ma).

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received April 18, 2016; revised July 17, 2016; accepted August 14, 2016.published OnlineFirst October 4, 2016.

References1. Howlader N NA, KrapchoM, Garshell J, Miller D, Altekruse SF, Cronin KA,

et al. (eds). SEER Cancer Statistics Review, 1975–2012. National CancerInstitute; 2014.

2. Beckwith JB, Palmer NF. Histopathology and prognosis of Wilms tumors:Results from the First National Wilms' Tumor Study. Cancer 1978;41:1937–48.

3. Faria P, Beckwith JB,Mishra K, ZuppanC,Weeks DA, BreslowN, et al. Focalversus diffuse anaplasia in Wilms tumor–new definitions with prognosticsignificance: A report from the National Wilms Tumor Study Group. Am JSurg Pathol 1996;20:909–20.

4. Dome JS, Cotton CA, Perlman EJ, BreslowNE, Kalapurakal JA, Ritchey ML,et al. Treatment of anaplastic histologyWilms' tumor: Results from the fifthNational Wilms' Tumor Study. J Clin Oncol 2006;24:2352–8.

5. Pritchard-Jones K,Moroz V, VujanicG, PowisM,Walker J,Messahel B, et al.Treatment and outcome ofWilms' tumour patients: An analysis of all casesregistered in the UKW3 trial. Ann Oncol 2012;23:2457–63.

6. Dome JS, Perlman EJ, Graf N. Risk stratification for Wilms Tumor:Current approach and future directions. Am Soc Clin Oncol Educ Book2014:215–23.

7. Huang J, Soffer SZ, Kim ES, Yokoi A, Moore JT, McCrudden KW, et al. p53accumulation in favorable-histology Wilms tumor is associated withangiogenesis and clinically aggressive disease. J Pediatr Surg 2002;37:523–7.

8. Bardeesy N, Beckwith JB, Pelletier J. Clonal expansion and attenuatedapoptosis in Wilms' tumors are associated with p53 gene mutations.Cancer Res 1995;55:215–9.

9. Bardeesy N, Falkoff D, Petruzzi MJ, Nowak N, Zabel B, Adam M, et al.Anaplastic Wilms' tumour, a subtype displaying poor prognosis, harboursp53 gene mutations. Nat Genet 1994;7:91–7.

10. Malkin D, Sexsmith E, Yeger H, Williams BR, Coppes MJ. Mutations of thep53 tumor suppressor gene occur infrequently inWilms' tumor. Cancer Res1994;54:2077–9.

11. Lahoti C, Thorner P, Malkin D, Yeger H. Immunohistochemical detectionof p53 inWilms' tumors correlates with unfavorable outcome. Am J Pathol1996;148:1577–89.

12. Franken J, Lerut E, Van Poppel H, Bogaert G. p53 immunohistochemistryexpression in Wilms tumor: A prognostic tool in the detection of tumoraggressiveness. J Urol 2013;189:664–70.

13. Maschietto M, Williams RD, Chagtai T, Popov SD, Sebire NJ, VujanicG, et al. TP53 mutational status is a potential marker for risk strat-ification in Wilms tumour with diffuse anaplasia. PLoS One 2014;9:e109924.

14. McLarenW, Pritchard B, Rios D, Chen Y, Flicek P, Cunningham F. Derivingthe consequences of genomic variantswith the Ensembl API and SNPEffectPredictor. Bioinformatics (Oxford, England) 2010;26:2069–70.

15. Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P,et al. A method and server for predicting damaging missense mutations.Nat Methods 2010;7:248–9.

16. Schwarz JM, Cooper DN, Schuelke M, Seelow D. MutationTaster2:Mutation prediction for the deep-sequencing age. Nat Methods 2014;11:361–2.

17. Choi Y, Sims GE, Murphy S, Miller JR, Chan AP. Predicting the func-tional effect of amino acid substitutions and indels. PLoS One 2012;7:e46688.

18. Choi Y. A fast computation of pairwise sequence alignment scoresbetween a protein and a set of single-locus variants of another protein.In ACM International Conference on Bioinformatics, ComputationalBiology and Biomedicine. Orlando, FL, USA—October 8–10, 2012,ACM New York, NY, USA �2012, p. 414–7.

19. Drmanac R, Sparks AB, Callow MJ, Halpern AL, Burns NL, KermaniBG, et al. Human genome sequencing using unchained base reads onself-assembling DNA nanoarrays. Science (New York, NY) 2010;327:78–81.

20. BainbridgeMN,HuH,MuznyDM,Musante L, Lupski JR,GrahamBH, et al.De novo truncatingmutations in ASXL3 are associatedwith a novel clinicalphenotype with similarities to Bohring-Opitz syndrome. Genome Med2013;5:11.

21. Lupski JR, Gonzaga-Jauregui C, Yang Y, BainbridgeMN, Jhangiani S, BuhayCJ, et al. Exome sequencing resolves apparent incidental findings andreveals further complexity of SH3TC2 variant alleles causing Charcot-Marie-Tooth neuropathy. Genome Med 2013;5:57.

22. Edmonson MN, Zhang J, Yan C, Finney RP, Meerzaman DM, Buetow KH.Bambino: A variant detector and alignment viewer for next-generationsequencing data in the SAM/BAM format. Bioinformatics (Oxford, Eng-land) 2011;27:865–6.

23. Morin R, Bainbridge M, Fejes A, Hirst M, Krzywinski M, Pugh T, et al.Profiling the HeLa S3 transcriptome using randomly primed cDNAand massively parallel short-read sequencing. BioTechniques 2008;45:81–94.

24. Li H, Durbin R. Fast and accurate short read alignment withBurrows-Wheeler transform. Bioinformatics (Oxford, England) 2009;25:1754–60.

25. Cingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, et al. Aprogram for annotating and predicting the effects of single nucleotidepolymorphisms, SnpEff: SNPs in the genome of Drosophila melanogasterstrain w1118; iso-2; iso-3. Fly 2012;6:80–92.

26. Cingolani P, Patel VM, Coon M, Nguyen T, Land SJ, Ruden DM, et al.Using drosophila melanogaster as a model for genotoxic chemicalmutational studies with a new program, SnpSift. Front Genet 2012;3:35.


Ooms et al.




27. Pounds S, Cheng C, Mullighan C, Raimondi SC, Shurtleff S, DowningJR. Reference alignment of SNP microarray signals for copy num-ber analysis of tumors. Bioinformatics (Oxford, England) 2009;25:315–21.

28. Gratias EJ, Jennings LJ, Anderson JR, Dome JS, Grundy P, Perlman EJ. Gainof 1q is associated with inferior event-free and overall survival in patientswith favorable histology Wilms tumor: A report from the Children'sOncology Group. Cancer 2013;119:3887–94.

29. Brunet JP, Tamayo P, Golub TR, Mesirov JP. Metagenes and molecularpattern discovery using matrix factorization. Proc Natl Acad Sci U S A2004;101:4164–9.

30. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarraysapplied to the ionizing radiation response. Proc Natl Acad Sci U S A2001;98:5116–21.

31. SubramanianA, TamayoP,Mootha VK,Mukherjee S, Ebert BL,GilletteMA,et al. Gene set enrichment analysis: A knowledge-based approach forinterpreting genome-wide expression profiles. Proc Natl Acad Sci U S A2005;102:15545–50.

32. Schlegelberger B, Kreipe H, Lehmann U, Steinemann D, Ripperger T,Gohring G, et al. A child with Li-Fraumeni syndrome: Modes to inactivatethe second allele of TP53 in three different malignancies. Pediatr BloodCancer 2015;62:1481–4.

33. Birch JM, Alston RD, McNally RJ, Evans DG, Kelsey AM, Harris M, et al.Relative frequency andmorphology of cancers in carriers of germline TP53mutations. Oncogene 2001;20:4621–8.

34. Varley JM, Chapman P, McGown G, Thorncroft M, White GR, Greaves MJ,et al. Genetic and functional studies of a germline TP53 splicing mutationin a Li-Fraumeni-like family. Oncogene 1998;16:3291–8.

35. Gadd S, Huff V, Huang CC, Ruteshouser EC, Dome JS, Grundy PE,et al. Clinically relevant subsets identified by gene expression pat-terns support a revised ontogenic model of Wilms tumor: A Chil-dren's Oncology Group Study. Neoplasia (New York, NY) 2012;14:742–56.

36. Walz AL, Ooms A, Gadd S, Gerhard DS, Smith MA, Guidry Auvil JM, et al.Recurrent DGCR8, DROSHA, and SIX homeodomain mutations in favor-able histology Wilms tumors. Cancer Cell 2015;27:286–97.

37. Williams RD, Al-Saadi R, Natrajan R, Mackay A, Chagtai T, Little S, et al.Molecular profiling reveals frequent gain of MYCN and anaplasia-specificloss of 4q and 14q in Wilms tumor. Genes Chromosomes Cancer 2011;50:982–95.

38. Wittmann S, Zirn B, Alkassar M, Ambros P, Graf N, Gessler M. Loss of11q and 16q in Wilms tumors is associated with anaplasia, tumorrecurrence, and poor prognosis. Genes Chromosomes Cancer 2007;46:163–70.

39. Xu C, Fan CD, Wang X. Regulation of Mdm2 protein stability and the p53response by NEDD4-1 E3 ligase. Oncogene 2015;34:281–9.

40. Beniers AJ, Efferth T, Fuzesi L, Granzen B, Mertens R, Jakse G. p53expression in Wilms' tumor: A possible role as prognostic factor. Int JOncol 2001;18:133–9.

41. Yemelyanova A, Vang R, Kshirsagar M, Lu D, Marks MA, Shih Ie M, et al.Immunohistochemical staining patterns of p53 can serve as a surrogatemarker for TP53 mutations in ovarian carcinoma: An immunohisto-chemical and nucleotide sequencing analysis. Mod Pathol 2011;24:1248–53.

42. Watanabe G, Ishida T, Furuta A, Takahashi S, Watanabe M, Nakata H, et al.Combined immunohistochemistry of PLK1, p21, and p53 for predictingTP53 status: An independent prognostic factor of breast cancer. Am J SurgPathol 2015;39:1026–34.

43. Chene P. The role of tetramerization in p53 function. Oncogene2001;20:2611–7.

44. Lang V, Pallara C, Zabala A, Lobato-Gil S, Lopitz-Otsoa F, Farras R, et al.Tetramerization-defects of p53 result in aberrant ubiquitylation and tran-scriptional activity. Mol Oncol 2014;8:1026–42.

45. LubinDJ, Butler JS, LohSN. Foldingof tetrameric p53: oligomerization andtumorigenic mutations induce misfolding and loss of function. J Mol Biol2010;395:705–16.

46. Scott RH, Stiller CA, Walker L, Rahman N. Syndromes and constitutionalchromosomal abnormalities associated with Wilms tumour. J Med Genet2006;43:705–15.

47. Hill DA, Shear TD, Liu T, Billups CA, Singh PK, Dome JS. Clinical andbiologic significance of nuclear unrest in Wilms tumor. Cancer 2003;97:2318–26.






2016;22:5582-5591. Published OnlineFirst October 4, 2016.Clin Cancer Res Ariadne H.A.G. Ooms, Samantha Gadd, Daniela S. Gerhard, et al. Anaplasia: A Report from the Children's Oncology Group

Mutation in Wilms Tumors with DiffuseTP53Significance of

Updated version

10.1158/1078-0432.CCR-16-0985doi:

Access the most recent version of this article at:

Material

Supplementary

http://clincancerres.aacrjournals.org/content/suppl/2016/10/25/1078-0432.CCR-16-0985.DC1

Access the most recent supplemental material at:

Cited articles

http://clincancerres.aacrjournals.org/content/22/22/5582.full#ref-list-1

This article cites 44 articles, 7 of which you can access for free at:

E-mail alerts related to this article or journal.Sign up to receive free email-alerts

Subscriptions

Reprints and

[email protected]

To order reprints of this article or to subscribe to the journal, contact the AACR Publications Department at

Permissions

Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)

.http://clincancerres.aacrjournals.org/content/22/22/5582To request permission to re-use all or part of this article, use this link



http://clincancerres.aacrjournals.org/lookup/doi/10.1158/1078-0432.CCR-16-0985

http://clincancerres.aacrjournals.org/content/suppl/2016/10/25/1078-0432.CCR-16-0985.DC1

http://clincancerres.aacrjournals.org/content/22/22/5582.full#ref-list-1

http://clincancerres.aacrjournals.org/cgi/alerts

mailto:[email protected]

http://clincancerres.aacrjournals.org/content/22/22/5582


Signiﬁcance of TP53 Mutation in Wilms Tumors with Diffuse ... · Reinier de Graaf Hospital,...

Documents

Transcript of Signiﬁcance of TP53 Mutation in Wilms Tumors with Diffuse ... · Reinier de Graaf Hospital,...