High expression of BMP pathway genes distinguishes a subset of atypical teratoid/rhabdoid tumors associated with shorter survival

Abstract

Molecular profiling of tumors has proven to be a valuable tool for identification of prognostic and diagnostic subgroups in medulloblastomas, glioblastomas, and other cancers. However, the molecular landscape of atypical teratoid/rhabdoid tumors (AT/RTs) remains largely unexplored. To address this issue, we used microarrays to measure the gene expression profiles of 18 AT/RTs and performed unsupervised hierarchical clustering to determine molecularly similar subgroups. Four major subgroups (clusters) were identified. These did not conform to sex, tumor location, or presence of monosomy 22. Clusters showed distinct gene signatures and differences in enriched biological processes, including elevated expression of some genes associated with choroid plexus lineage in cluster 4. In addition, survival differed significantly by cluster, with shortest survival (mean, 4.7 months) in both clusters 3 and 4, compared with clusters 1 and 2 (mean, 28.1 months). Analysis showed that multiple bone morphogenetic protein (BMP) pathway genes were upregulated in the short survival clusters, with BMP4 showing the most significant upregulation (270-fold). Thus, high expression of BMP pathway genes was negatively associated with survival in this dataset. Our study indicates that molecular subgroups exist in AT/RTs and that molecular profiling of these comparatively rare tumors may be of diagnostic, prognostic, and therapeutic value.

Fig. 1.

Hierarchical clustering of AT/RTs. (A) Molecular profiling was performed using gene expression microarrays to measure 19,667 genes in 18 AT/RT tumor samples. The top 10% of genes, as ranked by variance across samples, were used as input to an agglomerative hierarchical clustering algorithm. Four clusters are defined on the resulting dendrogram, marked clusters 1–4. (B) Principal component analysis (PCA) of the AT/RTs in (A) using the same top 10% of high variance genes in (A).

Fig. 2.

Survival analysis of AT/RTs based on molecular classification. (A) Kaplan-Meier survival plot of 17 patients with AT/RT, using the clusters identified by hierarchical clustering of 18 patients with AT/RT (see Fig. 1). One patient included in the clustering was lost to follow-up and is not included in the survival analysis. The difference between the 4 clusters was statistically significant (log rank P value <.001). Vertical ticks indicate censored survival observations. (B) Multivariate survival model (Cox regression analysis) was used with the same patients in (A) to assess the importance of cluster membership and diagnostic age in AT/RT survival.

Fig. 3.

BMP4 gene expression in AT/RT samples. (A) Expression of BMP4 mRNA in 18 AT/RT samples grouped by the molecular clusters defined in Fig. 1. Gene expression was measured by Affymetrix U133 Plus2 GeneChips. (B) The same BMP4 expression values as (A), plotted against survival time for the 17 patients included in the survival analysis (Fig. 2) (one patient was lost to follow-up).

Fig. 4.

Differentially expressed BMP signaling genes. Heatmap of expression data for all genes from BMP signaling geneset #2 that showed differential expression (P < .05) in clusters 3 and 4 (short survival group), compared with clusters 1 and 2 (longer survival group). Eighteen genes were upregulated, and 7 were downregulated. Gene expression was measured by Affymetrix U133 Plus2 GeneChips.

Fig. 5.

Top-scoring Ingenuity pathways analysis functional network. The 193 genes differentially expressed between the short survival group (clusters 3 and 4) and the longer survival group (clustera 1 and 2) were input to Ingenuity pathway analysis for functional network generation. The top-scoring network is shown here. The intensity of the node color indicates the degree of upregulation (red) or downregulation (green) of genes differentially expressed in the dataset being examined.