Pediatric primary central nervous system germ cell tumors of different prognosis groups show characteristic miRNome traits and chromosome copy number variations

Abstract

Background: Intracranial pediatric germ cell tumors (GCTs) are rare and heterogeneous neoplasms and vary in histological differentiation, prognosis and clinical behavior. Germinoma and mature teratoma are GCTs that have a good prognosis, while other types of GCTs, termed nongerminomatous malignant germ cell tumors (NGMGCTs), are tumors with an intermediate or poor prognosis. The second group of tumors requires more extensive drug and irradiation treatment regimens. The mechanisms underlying the differences in incidence and prognosis of the various GCT subgroups are unclear.

Results: We identified a distinct mRNA profile correlating with GCT histological differentiation and prognosis, and also present in this study the first miRNA profile of pediatric primary intracranial GCTs. Most of the differentially expressed miRNAs were downregulated in germinomas, but miR-142-5p and miR-146a were upregulated. Genes responsible for self-renewal (such as POU5F1 (OCT4), NANOG and KLF4) and the immune response were abundant in germinomas, while genes associated with neuron differentiation, Wnt/beta-catenin pathway, invasiveness and epithelial-mesenchymal transition (including SNAI2 (SLUG) and TWIST2) were abundant in NGMGCTs. Clear transcriptome segregation based on patient survival was observed, with malignant NGMGCTs being closest to embryonic stem cells. Chromosome copy number variations (CNVs) at cytobands 4q13.3-4q28.3 and 9p11.2-9q13 correlated with GCT malignancy and clinical risk. Six genes (BANK1, CXCL9, CXCL11, DDIT4L, ELOVL6 and HERC5) within 4q13.3-4q28.3 were more abundant in germinomas.

Conclusions: Our results integrate molecular profiles with clinical observations and provide insights into the underlying mechanisms causing GCT malignancy. The genes, pathways and microRNAs identified have the potential to be novel therapeutic targets.

Figure 1

MiRNome analysis of childhood CNS GCTs. (A) Overall survival rates of GCTs of different histological subtypes. In total, 161 patients were followed up for up to 20 years. These were then subjected to Kaplan-Meier survival analysis. Numbers in parentheses are case numbers of each tumor subtype. Vertical lines indicate the censored survival observations. (B) Principal component analysis (PCA) using the filtered miRNAs (p < 0.05 and fold change ≧2). Each spot represents a single array. (C) A heat map shows the miRNAs enriched in the different prognostic groups. MiRNAs in red showed increased expression, while those in blue showed decreased. (D-E) Validation of miRNA array results by real-time PCR. The mean expression levels of the target miRNAs are compared to that of the U6 small nuclear RNA control. Results are expressed as the mean ± standard deviation (SD) (E). The miRNAs' array hybridization signals are also shown (D).

Figure 2

Gene expression analysis of the different GCT subgroups. (A) A multidimensional scaling (MDS) plot containing the differentially expressed genes (690 probe sets, q < 0.001). Each spot represents a single array. (B) A comparison of the transcriptome traits between ESCs and NGMGCTs by principal component analysis (PCA). (C) Relationships between ESCs, germinomas and NGMGCTs. Average linkage Euclidean distances between the tissues and ESC were calculated using genes distinguishing the filtrated 690-probe set. The confidence limits shown represent the standard error. (D) A heat map shows genes enriched in the ESCs and in the different prognostic groups (q < 0.001). (E-F) Real-time PCR validation of the microarray data. Mean expression levels of the examined genes were compared to that of the GAPDH control. Each bar represents a different individual (F). The genes' array hybridization signals are also shown (E).

Figure 3

Altered functional modules in the different pediatric GCT prognostic groups. (A-B) Gene set enrichment analysis according to the Gene Ontology (GO) classification. Probe sets differentiating good prognostic CNS GCTs from intermediate/poor prognostic CNS GCTs were subjected to the GO database search via the DAVID 2008 interface. The number of genes, gene symbols, their percentages and the p values for each category that show significance (p < 0.05) and are enriched in either the good (A) or the intermediate/poor (B) prognostic group are listed. (C) KEGG pathways significantly enriched in the TW NGMGCT genes. The number of genes, their percentages in terms of total genes, and the p values for pathways that are significantly over-represented (p < 0.05 by the DAVID 2008 tool) are listed. (D) Distribution of signature genes on the chromosome cytobands.

Figure 4

Chromosomal aberrations in the TW germinomas, mature teratomas (MTs) and NGMGCTs. The red bars on the right side of the chromosome idiograms indicate gain in these chromosomal regions, while blue bars indicate chromosomal loss. Two common copy number variation (CNV) regions (S1 & S2) in 3 out of 5 NGMGCT cases are highlighted.