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INTRODUCTION Wilms tumor (WT) is the most common childhood renal malignancy.1 Most patients are treated effectively, with approximately 90% achieving 5-year survival, but new approaches are needed to improve the outcome of the remainder, especially in cases of recurrence, where only approximately 50% will survive.2,3 More specific biomarkers for treatment stratification could also reduce the therapeutic burden on the successfully treated majority. Treatment planning is currently determined by clinical staging and histopathologic criteria. In countries that follow the protocols of the International Society of Paediatric Oncology (SIOP), patients with WT typically receive neoadjuvant chemotherapy, and the histopathology at nephrectomy is used to classify patients into risk groups. Tumors with diffuse anaplasia or that contain a high proportion of chemoresistant blastema (blastemal type) are regarded as high risk; epithelial, stromal, mixed, and regressive subtypes are classed as intermediate risk, and completely necrotic tumors are classed as low risk.4 Using this classification, the SIOP WT 2001 trial recently reported that doxorubicin can be safely omitted from the treatment of stage II to III intermediate-risk histology tumors, although it still adds benefit when patients have high-risk histology.5,6 However, high-risk tumors are relatively uncommon, and most relapses still occur in patients with localized (stage I to III) low- and intermediate-risk histology tumors. Therefore, there is a clinical need to improve the sensitivity and specificity of risk prediction in WT. The SIOP WT 2001 trial included, as a secondary aim, investigation of the potential value of including molecular biomarkers in addition to the current use of tumor stage and histology in risk stratification.

tumors. Therefore, there is a clinical need to improve the sensitivity and specificity of risk prediction in WT. The SIOP WT 2001 trial included, as a secondary aim, investigation of the potential value of including molecular biomarkers in addition to the current use of tumor stage and histology in risk stratification. Previous analyses have identified multiple recurrent aberrations in WT. Notable genes with documented mutations include WT1,7-9 CTNNB1,10 WTX (AMER1),11 TP53,12 FBXW7,13 MYCN, SIX1/2, DICER1, DROSHA, and DGCR8.14-18 Copy neutral loss of heterozygosity on 11p, common in stromal-type tumors, can lead to both second hit inactivation of mutated WT1 on 11p13 and aberrant expression of the imprinted genes H19 and IGF2 on 11p15; the latter locus is also frequently targeted by epigenetic abnormalities.19 Several WT genes, including WT1, WTX, TP53, FBXW7, and MYCN are also subject to recurrent copy number aberrations, as are a number of larger-scale genomic regions, but few of these are of known prognostic relevance. Simultaneous allele loss of 1p and 16q is associated with adverse outcome in patients with favorable-histology WT treated with immediate nephrectomy, and this biomarker is already used in treatment stratification by the Children's Oncology Group of North America.20 We have recently shown that TP53 mutation and 17p loss, aberrations largely confined to anaplastic histology WT, are potential adverse indicators within this subtype.21 However, the utility of both these biomarkers is limited by their relative rarity. Genomic gain of 1q, one of the most common copy number changes in WT,22-25 seems to be associated with poor outcome, as is gain of MYCN.18 Recent studies in the United States and United Kingdom have focused on the significance of 1q gain and support its prognostic value.26,27

arkers is limited by their relative rarity. Genomic gain of 1q, one of the most common copy number changes in WT,22-25 seems to be associated with poor outcome, as is gain of MYCN.18 Recent studies in the United States and United Kingdom have focused on the significance of 1q gain and support its prognostic value.26,27 The principal aim of this study was to assess the feasibility of using 1q gain as a prognostic biomarker by determining its association with event-free survival (EFS) and overall survival (OS) in a cohort drawn entirely from the SIOP WT 2001 clinical trial (which is, to our knowledge, the largest SIOP cohort so far analyzed for this biomarker). Accordingly, a rapid and relatively low-cost multiplex ligation-dependent probe amplification (MLPA) assay28 was developed and optimized to assess the copy number status of 1q and other key regions or gene-specific loci, including 1p, 16q, WT1, WTX, TP53, MYCN, and FBXW7. MATERIALS AND METHODS Patients Patients registered prospectively in the SIOP WT 2001 clinical trial and treated with preoperative chemotherapy according to standardized risk-stratified regimens on the basis of tumor stage, histology, and metastatic response to preoperative chemotherapy5,29 with stage I to IV WT and available frozen tumor were eligible for this study. Selection criteria and patient characteristics are provided in the Data Supplement (Methods). Informed consent was obtained from all families. Our research was approved by local ethics committees and conducted in accordance with the Helsinki Declaration.

to IV WT and available frozen tumor were eligible for this study. Selection criteria and patient characteristics are provided in the Data Supplement (Methods). Informed consent was obtained from all families. Our research was approved by local ethics committees and conducted in accordance with the Helsinki Declaration. Samples All samples were freshly frozen specimens obtained at nephrectomy. Genomic DNA was prepared by standard methods. Only WT with a tumor content ≥ 50% as determined by a pediatric pathologist were used for this study (N = 586; Data Supplement Table S1). Full details, including sample inclusion criteria and DNA quality control (QC) metrics, are listed in the Data Supplement. MLPA The MLPA assay (P380-X2) was designed and developed in collaboration with MRC-Holland (Amsterdam, the Netherlands). The panel included 33 probes for regions or genes of interest, including seven on 1p, five on 1q, six on 16q, and three each targeting MYCN (2p), TP53 (17p), FBXW7 (4q), WT1 (11p), and WTX (AMER1, Xq), as well as reference and QC probes (Data Supplement Table S2). MLPA reactions were performed according to the manufacturer’s instructions, with appropriate internal quality and external normal controls. Polymerase chain reaction products were analyzed on an ABI 3730 DNA Analyzer, (Thermo Fisher Scientific, Waltham, MA).

s well as reference and QC probes (Data Supplement Table S2). MLPA reactions were performed according to the manufacturer’s instructions, with appropriate internal quality and external normal controls. Polymerase chain reaction products were analyzed on an ABI 3730 DNA Analyzer, (Thermo Fisher Scientific, Waltham, MA). Data Analysis Copy number ratios relative to the normal reference were calculated with Coffalyser.NET software (MRC-Holland) using the default settings. A numerical gain was scored when the ratios exceeded 1.2 and a loss when the ratios were lower than 0.8; all other values were considered to be normal diploid. For individual genes, aberrations were scored by the median ratio of the gene-specific probes. For 1p, 1q, and 16q, a gain or loss of at least two consecutive probed loci was required to score a chromosome arm aberration. Associations between copy number aberrations and histopathologic subtypes (Fig 1) were calculated by logistic regression, and survival analyses (Table 1; Fig 2; Data Supplement) were performed using the Kaplan-Meier estimator, log-rank test, and Cox proportional hazards regression model (Data Supplement Methods). For multivariable analyses, the factors considered are listed in the “Variable” column of Table 2. Fig 1. Aberration frequency histograms for loci of interest in specific histologic subtypes of Wilms tumor (full series, N = 586). AH, anaplastic histology.

Data Analysis Copy number ratios relative to the normal reference were calculated with Coffalyser.NET software (MRC-Holland) using the default settings. A numerical gain was scored when the ratios exceeded 1.2 and a loss when the ratios were lower than 0.8; all other values were considered to be normal diploid. For individual genes, aberrations were scored by the median ratio of the gene-specific probes. For 1p, 1q, and 16q, a gain or loss of at least two consecutive probed loci was required to score a chromosome arm aberration. Associations between copy number aberrations and histopathologic subtypes (Fig 1) were calculated by logistic regression, and survival analyses (Table 1; Fig 2; Data Supplement) were performed using the Kaplan-Meier estimator, log-rank test, and Cox proportional hazards regression model (Data Supplement Methods). For multivariable analyses, the factors considered are listed in the “Variable” column of Table 2. Fig 1. Aberration frequency histograms for loci of interest in specific histologic subtypes of Wilms tumor (full series, N = 586). AH, anaplastic histology. Fig 2. (A, C, E) Event-free (EFS) and (B, D, F) overall survival (OS) curves for (A, B) complete series, (C, D) intermediate-risk localized disease, and (E, F) nonanaplastic localized disease Wilms tumors, stratified by 1q status. AH, anaplastic histology. Table 1. Univariable Survival Analyses Patient Series Aberration No. of Patients No. of Relapses Event P Event HR 5-Year EFS No.

Fig 2. (A, C, E) Event-free (EFS) and (B, D, F) overall survival (OS) curves for (A, B) complete series, (C, D) intermediate-risk localized disease, and (E, F) nonanaplastic localized disease Wilms tumors, stratified by 1q status. AH, anaplastic histology. Table 1. Univariable Survival Analyses Patient Series Aberration No. of Patients No. of Relapses Event P Event HR 5-Year EFS No. of Deaths Death P Death HR 5-Year OS Unselected patients 1q gain 167 43 < .001 2.33 75 19 .01 2.16 88.4 (N = 586) 1q other 419 49 88.2 22 94.4 1p loss 49 11 .17 1.55 77.9 5 .38 1.52 89 1p other 537 81 85 36 93 16q loss 94 20 .12 1.48 78.5 11 .07 1.88 89.1 16q other 492 72 85.5 30 93.3 1p and 16q loss 16 3 .76 1.22 81.2 0 .27 0.01 100 1p and 16q other 570 89 84.5 41 92.4 TP53 (17p) loss 44 19 < .001 4.03 55.2 16 < .001 9.80 63.7 TP53 (17p) other 542 73 86.7 25 94.9 WT1 (11p) loss 50 6 .45 0.73 86.6 1 .15 0.26 97.8 WT1 (11p) other 536 86 84.2 40 92.2 WTX (Xq) loss 93 10 .13 0.61 91.4 2 .04 0.26 97.8 WTX (Xq) other 493 82 83 39 91.6 MYCN (2p) gain 88 26 < .001 2.45 71.2 14 < .001 3.09 83.7 MYCN (2p) other 498 66 86.7 27 94.2 MYCN (only) gain 60 20 < .001 2.72 67.9 12 < .001 3.91 79.4 MYCN (only) other 526 72 86.3 29 94.2 FBXW7 (4q) loss 24 15 < .001 6.58 38 10 < .001 9.62 59.3 FBXW7 (4q) other 562 77 86.4 31 94 IR stage I-III 1q gain 114 22 .004 2.21 82.2 3 .99 1.01 98 (n = 441) 1q other 327 29 91.3 8 97.3 1p loss 34 6 .27 1.61 83.7 1 .88 1.17 97 1p other 407 45 89.4 10 97.5 16q loss 59 9 .4 1.36 84.6 3 .21 2.27 96.4 16q other 382 42 89.5 8 97.6 1p and 16q loss 13 2 .69 1.33 84.6 0 .56 0.01 100 1p and 16q other 428 49 89 11 97.4 TP53 (17p) loss 19 6 .004 3.23 67.4 3 < .001 8.33 88.2 TP53 (17p) other 422 45 89.9 8 97.8 WT1 (11p) loss 42 5 .94 1.03 86.3 0 .29 0.00 100 WT1 (11p) other 399 46 89.2 11 97.2 WTX (Xq) loss 79 8 .58 0.81 92.4 0 .11 0.00 100 WTX (Xq) other 362 43 88.1 11 96.9 MYCN (2p) gain 61 14 .003 2.49 78.2 4 .03 3.50 93.4 MYCN (2p) other 380 37 90.7 7 98.1 MYCN (only) gain 42 11 .001 2.86 75.7 4 .002 5.49 90.3 MYCN (only) other 399 40 90.3 7 98.2 FBXW7 (4q) loss 13 6 < .001 4.85 59.3 1 .23 3.25 100 FBXW7 (4q) other 428 45 89.9 10 97.4 Non-AH stage I-III 1q gain 131 26 .001 2.34 81.4 6 .1 2.48 95.7 (n = 482) 1q other 351 30 91.4 6 98.1 1p loss 42 8 .13 1.78 82 3 .05 3.47 92.3 1p other 440 48 89.3 9 97.9 16q loss 64 9 .59 1.22 85.7 2 .8 1.22 98.4 16q other 418 47 89 10 97.2 1p and 16q loss 14 2 .76 1.25 85.7 0 .55 0.01 100 1p and 16q other 468 54 88.7 12 97.3 TP53 (17p) loss 17 5 .02 2.82 69.3 2 .02 5.24 93.3 TP53 (17p) other 465 51 89.3 10 97.5 WT1 (11p)

oss 42 8 .13 1.78 82 3 .05 3.47 92.3 1p other 440 48 89.3 9 97.9 16q loss 64 9 .59 1.22 85.7 2 .8 1.22 98.4 16q other 418 47 89 10 97.2 1p and 16q loss 14 2 .76 1.25 85.7 0 .55 0.01 100 1p and 16q other 468 54 88.7 12 97.3 TP53 (17p) loss 17 5 .02 2.82 69.3 2 .02 5.24 93.3 TP53 (17p) other 465 51 89.3 10 97.5 WT1 (11p) loss 45 5 .9 0.94 87.4 0 .27 0.00 100 WT1 (11p) other 437 51 88.7 12 97.1 WTX (Xq) loss 81 8 .5 0.77 92.6 0 .1 0.00 100 WTX (Xq) other 401 48 87.7 12 96.8 MYCN (2p) gain 63 14 .01 2.30 78.9 4 .04 3.23 93.4 MYCN (2p) other 419 42 90.1 8 98 MYCN (only) gain 43 11 .002 2.68 76.2 4 .003 5.10 90.3 MYCN (only) other 439 45 89.8 8 98.1 FBXW7 (4q) loss 13 6 < .001 4.83 59.3 1 .23 3.28 100 FBXW7 (4q) other 469 50 89.5 11 97.3 Abbreviations: AH, anaplastic histology; EFS, event-free survival; HR, hazard ratio; IR, intermediate risk; OS, overall survival. Table 2. Multivariable Survival Analyses

loss 45 5 .9 0.94 87.4 0 .27 0.00 100 WT1 (11p) other 437 51 88.7 12 97.1 WTX (Xq) loss 81 8 .5 0.77 92.6 0 .1 0.00 100 WTX (Xq) other 401 48 87.7 12 96.8 MYCN (2p) gain 63 14 .01 2.30 78.9 4 .04 3.23 93.4 MYCN (2p) other 419 42 90.1 8 98 MYCN (only) gain 43 11 .002 2.68 76.2 4 .003 5.10 90.3 MYCN (only) other 439 45 89.8 8 98.1 FBXW7 (4q) loss 13 6 < .001 4.83 59.3 1 .23 3.28 100 FBXW7 (4q) other 469 50 89.5 11 97.3 Abbreviations: AH, anaplastic histology; EFS, event-free survival; HR, hazard ratio; IR, intermediate risk; OS, overall survival. Table 2. Multivariable Survival Analyses Patient Series Variable Comparison Event-Free Survival Overall Survival P HR Lower Upper P HR Lower Upper Unselected patients (n = 585) 1p loss No loss .95 0.98 0.5 1.91 .45 0.67 0.24 1.89 1q gain No gain .002 1.98 1.27 3.07 .16 1.61 0.83 3.15 16q loss No loss .63 1.14 0.68 1.91 .39 1.37 0.67 2.83 Female Male .98 0.99 0.65 1.51 .81 0.93 0.49 1.74 Stage II Stage I .43 1.27 0.71 2.27 .06 3.13 0.96 10.26 Stage III Stage I .17 1.52 0.83 2.79 .01 4.39 1.36 14.12 Stage IV Stage I < .001 4.58 2.58 8.15 < .001 21.65 6.93 67.66 High risk Intermediate risk .001 2.28 1.41 3.68 < .001 8.13 4.05 16.32 Age Per unit .06 1.01 1 1.01 .48 1 0.99 1.01 IR stage I-III (n = 440) 1p loss No loss .97 1.02 0.41 2.5 .84 0.81 0.1 6.74 1q gain No gain .04 1.92 1.05 3.51 .44 0.56 0.13 2.42 16q loss No loss .64 1.2 0.56 2.55 .09 3.51 0.82 15.12 Female Male .27 0.73 0.41 1.28 .04 0.24 0.06 0.92 Stage II Stage I .76 1.11 0.57 2.18 .13 3.25 0.71 14.82 Stage III Stage I .13 1.73 0.85 3.54 .02 7.01 1.45 33.78 Age Per unit .32 1 1 1.01 .71 1 0.99 1.02 Non-AH stage I-III (n = 481) 1p loss No loss .73 1.15 0.52 2.54 .45 1.75 0.4 7.61 1q gain No gain .02 2 1.13 3.57 .62 1.39 0.38 5.11 16q loss No loss .96 0.98 0.46 2.06 .77 1.27 0.26 6.29 Female Male .33 0.77 0.45 1.31 .04 0.24 0.06 0.93 Stage II Stage I .36 1.34 0.72 2.5 .05 5.12 0.99 26.4 Stage III Stage I .26 1.51 0.74 3.08 .06 5.58 0.91 34.08 High risk Intermediate risk .71 0.85 0.38 1.94 .45 1.71 0.42 7 Age Per unit .11 1.01 1 1.01 .53 1.01 0.99 1.02 Abbreviations: AH, anaplastic histology; HR, hazard ratio; IR, intermediate risk.

4 0.24 0.06 0.93 Stage II Stage I .36 1.34 0.72 2.5 .05 5.12 0.99 26.4 Stage III Stage I .26 1.51 0.74 3.08 .06 5.58 0.91 34.08 High risk Intermediate risk .71 0.85 0.38 1.94 .45 1.71 0.42 7 Age Per unit .11 1.01 1 1.01 .53 1.01 0.99 1.02 Abbreviations: AH, anaplastic histology; HR, hazard ratio; IR, intermediate risk. RESULTS Sample Series and Histologic Subtypes A total of 586 patients with stages I to IV WTs, in which tumor content was confirmed by histologic review, high-quality DNA was successfully extracted, and data exceeded QC thresholds (Data Supplement Methods), were included in the analysis. In this series (Data Supplement Table S1), median clinical follow-up was 68 months, 92 patients had an event (relapse), and 41 patients died. In 55% of tumors (321 of 586), at least one of the major copy number aberrations targeted by the assay (1q gain, 1p loss, 16q loss, MYCN gain, TP53 loss, WT1 loss, WTX loss, or FBXW7 loss) was detected (Data Supplement Table S1). Overall, the numbers of alterations identified across all markers were consistent with previous reports. Some aberrations were more common in specific subtypes (Fig 1; Data Supplement Table S3) and some significant associations were noted. Compared with mixed-type histology, diffuse anaplasia was significantly associated with TP53 (17p) loss (P < .001), MYCN (2p) gain (P < .001), 16q loss (P < .001), and FBXW7 (4q) loss (P < .001), the latter presumably reflecting an association between anaplasia and whole-arm 4q loss, which we have described previously.30 The stromal subtype was associated with WT1 (11p) loss (P = .0014), consistent with previous reports, and with a significantly lower frequency of 1q gain than the other subtypes (P = .00912). A gain of 1q was most frequent in blastemal-type tumors (Fig 1), but not to a statistically significant extent. We also noted an association between the regressive type and a lower frequency of WTX (AMER1, Xq) loss. Most aberrations, including 1q gain, were somewhat less common in stage I than in higher stage tumors (Data Supplement Table S4).

quent in blastemal-type tumors (Fig 1), but not to a statistically significant extent. We also noted an association between the regressive type and a lower frequency of WTX (AMER1, Xq) loss. Most aberrations, including 1q gain, were somewhat less common in stage I than in higher stage tumors (Data Supplement Table S4). Univariable Outcome Analysis of 1q Gain In the complete series of 586 patients (Table 1; Figs 2A and 2B), 167 tumors (28.5%) had 1q gain. Five-year EFS in the 1q-gain group was 75.0% (95% CI, 68.5% to 82.0%) and 88.2% in the no-gain group (95% CI, 85.0% to 91.4%). The corresponding OS values were 88.4% (95% CI, 83.5% to 93.6%) and 94.4% (95% CI, 92.1% to 96.7%), respectively. At the alpha significance level of .05, univariable analyses using the Cox proportional hazards regression model showed that 1q gain was associated with poorer EFS (hazard ratio [HR], 2.33; log-rank P < .001) and OS (HR, 2.16; P = .01).

re 88.4% (95% CI, 83.5% to 93.6%) and 94.4% (95% CI, 92.1% to 96.7%), respectively. At the alpha significance level of .05, univariable analyses using the Cox proportional hazards regression model showed that 1q gain was associated with poorer EFS (hazard ratio [HR], 2.33; log-rank P < .001) and OS (HR, 2.16; P = .01). Because 1q gain as a potential biomarker would be of most value in optimizing risk stratification in localized tumors, we also considered two important subsets. The first consisted of 441 patients with localized disease (stage I to III), intermediate-risk histology tumors according to the SIOP classification. In univariable analysis (Table 1; Figs 2C and 2D), 1q gain was significantly associated with inferior EFS (P = .004; HR, 2.21) but not OS (P = .99; HR, 1.01). The second subset was selected to allow direct comparison with the Children’s Oncology Group risk stratification. Among 482 patients with localized, nonanaplastic tumors (ie, excluding both diffuse and focal anaplastic but including blastemal-type WTs), 1q gain was associated with poorer EFS (P = .001; HR, 2.34) but not OS (P = .1; HR, 2.48; Table 1; Figs 2E and 2F).

mparison with the Children’s Oncology Group risk stratification. Among 482 patients with localized, nonanaplastic tumors (ie, excluding both diffuse and focal anaplastic but including blastemal-type WTs), 1q gain was associated with poorer EFS (P = .001; HR, 2.34) but not OS (P = .1; HR, 2.48; Table 1; Figs 2E and 2F). Univariable Outcome Analysis of 1p Loss and 16q Loss Neither 1p loss nor 16q loss, nor combined loss of 1p and 16q, considered as a single biomarker in a univariable Cox model, was significantly associated with EFS or OS in the entire tumor series at the P = .05 level (Data Supplement). This was also true for the subsets, with the single exception of a marginal association between 1p loss and poorer OS in nonanaplastic patients (Table 1; Data Supplement Figs S1, S2, and S3). Multivariable Outcome Analyses In a multivariable outcome analysis including 1q gain, 1p loss, 16q loss, tumor stage and histologic risk group, sex, and age, 1q gain was significantly associated with poorer EFS (HR, 1.98; P = .002), but not OS (HR, 1.61; P = .16; Table 2). The only other independent factors of those assessed for adverse outcome in the full series (N = 586) were high-risk histology and stage IV disease. The significant independent association of 1q gain with adverse EFS but not OS persisted in the subsets of intermediate-risk histology, localized WT (n = 440; EFS HR, 1.92; P = .04) and nonanaplastic, localized WT (n = 481; EFS HR, 2.0; P = .02).

the full series (N = 586) were high-risk histology and stage IV disease. The significant independent association of 1q gain with adverse EFS but not OS persisted in the subsets of intermediate-risk histology, localized WT (n = 440; EFS HR, 1.92; P = .04) and nonanaplastic, localized WT (n = 481; EFS HR, 2.0; P = .02). Univariable Analysis of Gene-Specific Markers The outcome data for the other markers covered by the assay were also analyzed on an exploratory basis (Table 1; Data Supplement Figs S4-S9). MYCN (2p) gain was significantly associated with poorer EFS and OS in the complete data set, in the localized disease intermediate-risk subset, and in the localized disease subset with anaplastic WTs excluded (Data Supplement Fig S4). Using a more specific definition of MYCN gain, MYCN-only gain (excluding from the MYCN-gain group those tumors in which the DYSF control probe on 2p was also gained, because gains at both loci were likely to be whole-arm gains), we saw higher HRs and lower P values (Table 1; Data Supplement Fig S5). Similarly, TP53 (17p) loss was significantly associated with inferior EFS and OS in the complete series and, perhaps surprisingly, in both subsets, neither of which included diffuse anaplastic WTs (Table 1; Data Supplement Fig S6).

hole-arm gains), we saw higher HRs and lower P values (Table 1; Data Supplement Fig S5). Similarly, TP53 (17p) loss was significantly associated with inferior EFS and OS in the complete series and, perhaps surprisingly, in both subsets, neither of which included diffuse anaplastic WTs (Table 1; Data Supplement Fig S6). A third copy number change, loss of the FBXW7 locus on 4q, was significantly associated with poorer EFS and OS in the complete 586 tumor series, but only with poorer EFS in both subsets (Table 1; Data Supplement Fig S7). No significant associations were noted between the copy number status of WT1 and outcome at the P = .05 significance level (Table 1; Data Supplement Fig S8). For WTX, there was no significant association with EFS, but improved OS was marginally associated with copy number loss in the complete series only (P = .04; Data Supplement Fig S9).

iations were noted between the copy number status of WT1 and outcome at the P = .05 significance level (Table 1; Data Supplement Fig S8). For WTX, there was no significant association with EFS, but improved OS was marginally associated with copy number loss in the complete series only (P = .04; Data Supplement Fig S9). DISCUSSION This is, to our knowledge, the first study to carry out a large-scale analysis of 1q copy number aberrations in WT sampled at nephrectomy after neoadjuvant chemotherapy according to the SIOP WT 2001 protocol. The clinical characteristics of the patient cohort were representative of the entire registered population who had received preoperative chemotherapy and presented with unilateral disease; 586 patients with stage I to IV WT, including all intermediate- and high-risk histologic subtypes, were analyzed. We found that 1q gain is significantly associated with poorer EFS and OS in univariable analyses, with HRs in excess of two-fold for relapse and death. These results are broadly consistent with those recently reported in a study of patients treated by immediate nephrectomy under Children's Oncology Group protocols without preoperative chemotherapy26 and, although it is essential to assess 1q gain independently in cohorts treated under both regimens, it is encouraging to note that it seems to be a prognostically valuable marker regardless of treatment protocol. However, in our multivariable analysis of the SIOP data, which also considered 1p loss, 16q loss, sex, stage, age, and histologic risk group, 1q gain remained significantly associated only with EFS (HR, 1.98; P = .002) and not OS (HR, 1.61; P = .16). This lack of association with OS is perhaps not surprising, given the comparatively low number of deaths in the patient series (41, compared with 92 relapses), reflecting the relative success of second-line therapy.

ain remained significantly associated only with EFS (HR, 1.98; P = .002) and not OS (HR, 1.61; P = .16). This lack of association with OS is perhaps not surprising, given the comparatively low number of deaths in the patient series (41, compared with 92 relapses), reflecting the relative success of second-line therapy. Because just over half of all relapses occur in children with localized WT that are not of high-risk histology, we analyzed this subset of patients (n = 441) in which treatment intensification to reduce relapse risk would be clinically appropriate and feasible. Here, we found that 1q gain retained its independent prognostic significance for EFS (HR, 1.92; P = .04) but not OS in multivariable analysis. Similar results (HR, 2.00; P = .02) were obtained for localized nonanaplastic tumors (n = 481), excluding both diffuse and focal anaplastic WTs but retaining blastemal type. This subset is comparable to the current North American definition of favorable histology for localized patients treated by immediate nephrectomy (where blastemal type, which implies chemoresistance, cannot be defined).

stic tumors (n = 481), excluding both diffuse and focal anaplastic WTs but retaining blastemal type. This subset is comparable to the current North American definition of favorable histology for localized patients treated by immediate nephrectomy (where blastemal type, which implies chemoresistance, cannot be defined). In contrast to a previous report on immediate nephrectomy patients,20 we did not find that the combination of 1p loss and 16q loss was prognostically significant in the SIOP series in the univariable or multivariable analyses. This was true for both EFS and OS, in the entire series, and in the nonanaplastic and intermediate-risk subsets. However, the size of our sample series (significantly smaller than the immediate nephrectomy cohort) meant that the current study did not have sufficient power to assess reliably the prognostic significance of relatively rare aberrations such as combined 1p and 16q loss, observed in only 16 patients (three of whom relapsed). We note also that any copy neutral loss of heterozygosity, another possible mechanism of allele loss at these loci, would not be detected by MLPA. A substantially larger series would be required to obtain definitive results for this rare combined marker in SIOP patients.

ed in only 16 patients (three of whom relapsed). We note also that any copy neutral loss of heterozygosity, another possible mechanism of allele loss at these loci, would not be detected by MLPA. A substantially larger series would be required to obtain definitive results for this rare combined marker in SIOP patients. In a previous study,18 we presented an analysis of MYCN copy number status that included 234 of the samples described in this study. Therefore, our observations are not independent, but the current expanded series should give a more reliable indication of the prognostic relevance of MYCN gain. As before, we note that MYCN gain seems to be a promising adverse prognostic indicator for WT, for both EFS and OS (Data Supplement Fig S4). We also analyzed the data using a more specific definition of gain (MYCN-only gain; Data Supplement Fig S5), excluding whole-arm gains. The adverse association with both EFS and OS was retained in all univariable analyses, but with lower P values and higher HRs throughout, perhaps suggesting that the type of genomic disruption that has given rise to MYCN gain, rather than the relative dose of MYCN with regard to the genomic baseline, is more prognostically relevant. A higher resolution (eg, single nucleotide polymorphism array) platform that allows precise delineation of the region of gain and distinguishes between focal events, such as those we described previously,13 and larger segmental changes would allow us to address this question.

baseline, is more prognostically relevant. A higher resolution (eg, single nucleotide polymorphism array) platform that allows precise delineation of the region of gain and distinguishes between focal events, such as those we described previously,13 and larger segmental changes would allow us to address this question. In a previous study we described an association between poor outcome and TP53 aberrations (typically point mutation coincident with whole-arm copy number loss of 17p) in diffuse anaplastic tumors.21 Interestingly, TP53 (17p) loss in the current study was associated with poorer EFS and OS, even in the subsets that excluded anaplastic tumors. It is currently not known whether the nonanaplastic tumors with copy number loss at this locus also had TP53 mutations or whether these tumors had any unusual histologic features, such as nuclear unrest.31 Loss of the FBXW7 locus on 4q was significantly associated with poorer EFS and OS in the complete tumor series and with adverse EFS only in the subsets. In earlier studies, we reported focal homozygous loss and point mutation of FBXW7 in several intermediate-risk histology WTs,13 as well as broader but typically single copy loss of 4q associated with anaplasia30; the current assay does not distinguish between these types of aberrations.

adverse EFS only in the subsets. In earlier studies, we reported focal homozygous loss and point mutation of FBXW7 in several intermediate-risk histology WTs,13 as well as broader but typically single copy loss of 4q associated with anaplasia30; the current assay does not distinguish between these types of aberrations. Optimizing treatment to minimize the risk of long-term adverse effects without compromising EFS or OS is a principal aim of clinical research in WT. The previous SIOP randomized trial5,6 showed that therapeutic intensity could be reduced in patients with localized intermediate-risk tumors without affecting OS, at the cost of a 4.4% reduction in EFS (95% CI, 0.4% to 9.3%). Because it is clearly desirable for patients to avoid even treatable relapses, further refinement of first-line therapy remains a priority, and novel biomarkers may provide the key data required to improve risk stratification and maximize EFS. In this study, we have shown that MLPA provides a rapid and effective means of determining the status of copy number aberrations associated with poorer EFS. The relatively high frequency of 1q gain makes this marker particularly attractive for potential use in risk stratification. However, any change in intensity on the basis of 1q status alone would affect a significant proportion of patients who have experienced a reasonably good EFS when treated with current therapies and where relapse is salvageable. Hence, the SIOP Renal Tumours Study Group considers it may be more appropriate to define risk groups for treatment stratification on the basis of several combined molecular biomarkers, taking account of our findings of the adverse significance of MYCN gain and TP53 loss and incorporating mutations in recently discovered WT genes, some of which are reported to have prognostic significance. This requires a prospective clinical study powered to include tumor stage and histologic risk group, both individually significant in our multivariable analysis, alongside quantitative assessment of the volume of blastema that survives preoperative chemotherapy, a further potential prognostic factor.32 This prospective study will also incorporate multiple sampling of each WT to determine the extent of intratumoral heterogeneity of 1q gain and other biomarkers. It will register all patients with a newly diagnosed renal tumor and continue the risk stratification and treatment arms for localized WT used in the SIOP WT 2001 trial.

ective study will also incorporate multiple sampling of each WT to determine the extent of intratumoral heterogeneity of 1q gain and other biomarkers. It will register all patients with a newly diagnosed renal tumor and continue the risk stratification and treatment arms for localized WT used in the SIOP WT 2001 trial. The study will be known as UMBRELLA, and is expected to open in 2016. Listen to the podcast by Dr Geoerger at www.jco.org/podcasts Written on behalf of the International Society of Paediatric Oncology Renal Tumours Study Group. Supported in the United Kingdom by Cancer Research UK (Grant No. C1188/A4614), Great Ormond Street Hospital (GOSH) Children's Charity, Children with Cancer (Grant No. 11MH16), and the National Institute for Health Research GOSH University College London Biomedical Research Centre; in Germany by the Deutsche Forschungsgemeinschaft (Grant No. Ge539/12-1), the Wilhelm-Sander-Stiftung, and the Competence Network Paediatric Oncology and Haematology; in France by L'Association Léon Bérard pour les Enfants Cancéreux, Enfants et Santé, Société Française du Cancer de l'Enfant, Institut National de la Santé et de la Recherche Médicale and Université Pierre et Marie Curie (Grant No. UMR.S 938); in Austria by a clinical investigator–driven grant of the St Anna Kinderkrebsforschung (P.F.A. and L.K.); and in multiple countries by the European Network for Cancer Research in Children and Adolescents (EU FP7 Grant No. 261474) and the P-medicine Project (EU FP7 Grant No. 270089).

t Marie Curie (Grant No. UMR.S 938); in Austria by a clinical investigator–driven grant of the St Anna Kinderkrebsforschung (P.F.A. and L.K.); and in multiple countries by the European Network for Cancer Research in Children and Adolescents (EU FP7 Grant No. 261474) and the P-medicine Project (EU FP7 Grant No. 270089). Authors’ disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article. Clinical trial information: 2007-004591-39.

t Marie Curie (Grant No. UMR.S 938); in Austria by a clinical investigator–driven grant of the St Anna Kinderkrebsforschung (P.F.A. and L.K.); and in multiple countries by the European Network for Cancer Research in Children and Adolescents (EU FP7 Grant No. 261474) and the P-medicine Project (EU FP7 Grant No. 270089). Authors’ disclosures of potential conflicts of interest are found in the article online at www.jco.org. Author contributions are found at the end of this article. Clinical trial information: 2007-004591-39. Acknowledgment We thank all the families who donated samples and all the staff at the treatment centers in the United Kingdom, Republic of Ireland, Germany, Austria, France, the Netherlands, and Sweden who enrolled patients in the SIOP WT 2001 trial and study and collected frozen tumor for the biologic studies. This study builds on the work of Jan de Kraker, MD, original chief investigator of the SIOP WT 2001 trial, who died on January 19, 2012. We thank Rebecca West and Nelly Bier for technical assistance, and Mariana Maschietto for helpful comments during the development of this study. The United Kingdom clinical database was managed by the Children's Cancer Trials Team, Cancer Research UK Clinical Trials Unit, Birmingham. Samples were made available by individual treatment centers, in the United Kingdom by the Children's Cancer and Leukaemia Group, and in France by the French Pediatric Renal Tumor Pathology Group, Cardiobiotec, Tumorothèque Marseille, Service de Pathologie Robert-Debré Assistance Publique Hôpitaux de Paris–Université Denis-Diderot Paris 7–Sorbonne Paris Cité, Tumorothèque Necker–Enfants malades, Centre de Ressources Biologiques (CRB) Paris Sud, Tumorothèque Champagne-Ardenne, Tumorothèque Caen Basse-Normandie, Tumorothèque Régionale Franche Comté, CRB Grenoble, Tumorothèque Lille–Centre Régional de Référence en Cancérologie, Tumorothèque du Limousin, and CRB Hôpitaux Universitaires de Strasbourg.

ants malades, Centre de Ressources Biologiques (CRB) Paris Sud, Tumorothèque Champagne-Ardenne, Tumorothèque Caen Basse-Normandie, Tumorothèque Régionale Franche Comté, CRB Grenoble, Tumorothèque Lille–Centre Régional de Référence en Cancérologie, Tumorothèque du Limousin, and CRB Hôpitaux Universitaires de Strasbourg. AUTHOR CONTRIBUTIONS Conception and design: Tasnim Chagtai, Suvi Savola, Gordan Vujanić, David Gisselsson, Marry M. van den Heuvel-Eibrink, Norbert Graf, Harm van Tinteren, Aurore Coulomb, Manfred Gessler, Richard Dafydd Williams, Kathy Pritchard-Jones Collection and assembly of data: All authors Data analysis and interpretation: Tasnim Chagtai, Christina Zill, Linda Dainese, Jenny Wegert, Gordan Vujanić, Yves Le Bouc, Peter F. Ambros, Annick Blaise, Marry M. van den Heuvel-Eibrink, Harm van Tinteren, Aurore Coulomb, Manfred Gessler, Richard Dafydd Williams, Kathy Pritchard-Jones Manuscript writing: All authors Final approval of manuscript: All authors

Data analysis and interpretation: Tasnim Chagtai, Christina Zill, Linda Dainese, Jenny Wegert, Gordan Vujanić, Yves Le Bouc, Peter F. Ambros, Annick Blaise, Marry M. van den Heuvel-Eibrink, Harm van Tinteren, Aurore Coulomb, Manfred Gessler, Richard Dafydd Williams, Kathy Pritchard-Jones Manuscript writing: All authors Final approval of manuscript: All authors AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST Gain of 1q As a Prognostic Biomarker in Wilms Tumors (WTs) Treated With Preoperative Chemotherapy in the International Society of Paediatric Oncology (SIOP) WT 2001 Trial: A SIOP Renal Tumours Biology Consortium Study The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO's conflict of interest policy, please refer to www.asco.org/rwc or jco.ascopubs.org/site/ifc. Tasnim Chagtai No relationship to disclose Christina Zill Employment: Roche Diagnostics Deutschland Honoraria: Roche Diagnostics Deutschland Travel, Accommodations, Expenses: Roche Diagnostics Deutschland Linda Dainese No relationship to disclose Jenny Wegert No relationship to disclose Suvi Savola Employment: MRC-Holland Sergey Popov No relationship to disclose William Mifsud No relationship to disclose Gordan Vujanić No relationship to disclose Neil Sebire No relationship to disclose Yves Le Bouc Honoraria: Ipsen, Sandoz Consulting or Advisory Role: Sandoz

Linda Dainese No relationship to disclose Jenny Wegert No relationship to disclose Suvi Savola Employment: MRC-Holland Sergey Popov No relationship to disclose William Mifsud No relationship to disclose Gordan Vujanić No relationship to disclose Neil Sebire No relationship to disclose Yves Le Bouc Honoraria: Ipsen, Sandoz Consulting or Advisory Role: Sandoz Speakers' Bureau: Ipsen Research Funding: Sandoz (Inst) Peter F. Ambros No relationship to disclose Leo Kager Travel, Accommodations, Expenses: Novartis Maureen J. O'Sullivan No relationship to disclose Annick Blaise No relationship to disclose Christophe Bergeron No relationship to disclose Linda Holmquist Mengelbier No relationship to disclose David Gisselsson Consulting or Advisory Role: Spago Nanomedical Marcel Kool No relationship to disclose Godelieve A.M. Tytgat No relationship to disclose Marry M. van den Heuvel-Eibrink No relationship to disclose Norbert Graf No relationship to disclose Harm van Tinteren No relationship to disclose Aurore Coulomb No relationship to disclose Manfred Gessler No relationship to disclose Richard Dafydd Williams No relationship to disclose Kathy Pritchard-Jones No relationship to disclose