A Children's Oncology Group and TARGET initiative exploring the genetic landscape of Wilms tumor

Abstract

We performed genome-wide sequencing and analyzed mRNA and miRNA expression, DNA copy number, and DNA methylation in 117 Wilms tumors, followed by targeted sequencing of 651 Wilms tumors. In addition to genes previously implicated in Wilms tumors (WT1, CTNNB1, AMER1, DROSHA, DGCR8, XPO5, DICER1, SIX1, SIX2, MLLT1, MYCN, and TP53), we identified mutations in genes not previously recognized as recurrently involved in Wilms tumors, the most frequent being BCOR, BCORL1, NONO, MAX, COL6A3, ASXL1, MAP3K4, and ARID1A. DNA copy number changes resulted in recurrent 1q gain, MYCN amplification, LIN28B gain, and MIRLET7A loss. Unexpected germline variants involved PALB2 and CHEK2. Integrated analyses support two major classes of genetic changes that preserve the progenitor state and/or interrupt normal development.

Figure 1. Genetic Landscape of Favorable Histology Wilms Tumor

Data variables of interest (rows) for 76 FHWT samples (columns) are separated into six clusters according to gene expression. Upper panel: Rows 2, 3, 4 provide NMF cluster according to gene expression, DNA methylation, or microRNA expression, respectively. Row 5 provides gene expression subset according to expression patterns previously reported [1]. These are followed by the most highly recurrently mutated genes, copy number changes, and methylation status at 11p15 as determined by 450K data. The predominant pre-treatment histological classification of the tumor (blastemal, stromal, or epithelial for those showing these patterns in >66% of the tumor represented in all slides, and mixed for those lacking a predominant histologic pattern), and the presence of accompanying nephrogenic rests (perilobar, PLNR, and intralobar, ILNR) are also provided. Lower panel: Illustrates the expression of genes of interest, with red and blue indicating relatively high and low expression, respectively. Genes present in the top 100 GSEA ranked list for each cluster that overlapped with genes from lists significantly enriched by GSEA in the same cluster are illustrated. Also provided are genes associated with the pre-induction and post-induction metanephric mesenchyme (MM) and genes associated with Wnt signalling in the early developing kidney.

Figure 2. 11p15 ICR1 and ICR2 methylation and select miRNA expression patterns

A. 11p15 Imprinting Status: Graphical representation of the average DNA methylation beta values for 11p15 imprinting control region 1 (ICR1; x axis) and ICR2 (y axis) in 78 FHWT. Retention of imprinting (ROI) is defined as ICR1 and ICR2 average beta values of 0.3–0.7; loss of imprinting (LOI) is defined as 0.8–1 for ICR1 and 0.3–0.7 for ICR2; loss of heterozygosity (LOH) is defined as 0.8–1 for ICR1 and 0–0.2 for ICR2. B. miRNA-10a and -10b expression: Box plots representing miRNA-10a (top panel) and -10b (bottom panel) expression in FHWT. The maximum (top whisker), the 75th, median, and 25th percentiles (box), and minimum expression values (bottom whisker) were calculated for FHWT with MLLT1 mutation (n = 7) and FHWT without MLLT1 mutation (n = 71) by using miRNAseq reads per kilobase of transcript per million mapped reads (RPKM) data. Two-tailed p-values were calculated by using unpaired t-tests assuming unequal variance. Upper panel: p = 4.2×10^-7, t = 5.531, df = 76. Lower panel: p = 3.7×10^-6, t = 4.987, df = 76. C. Let7a expression: Box plots representing let7a expression in FHWT in gene expression clusters 1 and 2 (N=38) compared with clusters 3 and 4 (N=28). The maximum, 75th percentile, median, 25th percentile, and minimum expression values were calculated by using microRNAseq RPKM data (top) or using RT-PCR to measure mature let7a normalized to RNU44 previously reported [3] (bottom). Two-tailed p-values were calculated by using unpaired t-tests assuming unequal variance. Upper panel: p = 0.01, t = 2.654, df = 64. Lower panel: p = 0.002, t = 3.22, df = 64.