Matching global mRNA expression profiles were available for 21 of the 42 pediatric tissue samples examined by miRNA microarray. These represented 17 malignant GCTs (10 YSTs, six seminomas, one EC) and four non-malignant controls, comprising one MT and three normal gonads (one pre- and one post-pubertal testis and one post-pubertal ovary) (Supplementary Table S1 ). Profiling had previously been performed using the HG-U133A GeneChip (Affymetrix, Santa Clara, CA), comprising 22,283 probe sets corresponding to 13,042 genes. Data for 16 samples had previously been published (2 (link)); the EC, MT and three normal controls were previously unreported (GEO accession: GSE18155). In addition, we re-analyzed published data from a study of adult TGCTs that also used the HG-U133A GeneChip [(26 (link)); GEO accession: GSE3218], excluding two suboptimal YST samples (K14 and K18) (2 (link)). We used data from 25 such specimens, representing eight pure YSTs, 12 pure seminomas and five normal adult testis controls (26 (link)).
Raw mRNA (.CEL) files were processed and quantile normalized using Robust Multi-array Average (RMA) in R (6 (link), 21 (link), 27 (link)), using the Affymetrix annotation of March 2009. RMA-transformed expression values were analyzed for differential expression (24 ) with significance studied by t-test and adjusted for multiple testing (25 ). Pathway enrichment analysis was performed using the Gene Ontology (GO) algorithm3 , as it permitted comparison of differentially expressed genes (log2 fold-change <−1.5 and adjusted p<0.01) grouped by the presence or absence of the SCR corresponding to the common 2-7nt seed of the miR-372~373 and miR-302a~d clusters. NCBI Entrez Gene identifiers were evaluated for biological process category over-representation within a total gene universe defined by the HG-U133A annotation library, using the hyperGTest function within the Bioconductor GOstats package (28 (link)). GOterms with adjusted p<0.01 (25 ) were considered statistically significant.
Raw mRNA (.CEL) files were processed and quantile normalized using Robust Multi-array Average (RMA) in R (6 (link), 21 (link), 27 (link)), using the Affymetrix annotation of March 2009. RMA-transformed expression values were analyzed for differential expression (24 ) with significance studied by t-test and adjusted for multiple testing (25 ). Pathway enrichment analysis was performed using the Gene Ontology (GO) algorithm