Integrated molecular analysis of adult Sonic Hedgehog (SHH)-activated medulloblastomas reveals two clinically relevant tumor subsets with VEGFA as potent prognostic indicator.

BACKGROUND Up to now, adult medulloblastoma (MB) patients are treated according to the protocols elaborated for pediatric MB although these tumors are different in terms of clinical outcomes and biology. Approximately 70% of adult MB disclose a Sonic Hedgehog (SHH) molecular signature in contrast to about 30% in pediatric cohorts. In addition, adult SHH-MB (aSHH-MB) are clinically heterogeneous but there is consensus neither on their optimal treatment nor on risk stratification. Thus, the identification of clinically relevant molecular subsets of aSHH-MB and identification of potential treatment targets remains inconclusive. METHODS We analyzed 96 samples of institutionally diagnosed aSHH-MB through genome-wide DNA methylation profiling, targeted DNA sequencing and RNA sequencing to identify molecular subcategories of these tumors and assess their prognostic significance. RESULTS We defined two aSHH-MB numerically comparable epigenetic subsets with clinical and molecular variability. The subset "aSHH-MBI" (46/48%) was associated with PTCH1/SMO (54%/46%) mutations, "neuronal" transcriptional signatures, and favorable outcomes after combined radio-chemotherapy (5-year PFS = 80% and OS = 92%). The clinically unfavorable "aSHH-MBII" subset (50/52%; 5-year PFS = 24% and OS = 45%) disclosed GLI2 amplifications (8%), loss of 10q (22%), and gene expression signatures associated with angiogenesis and embryonal development. aSHH-MBII tumors revealed strong and ubiquitous expression of VEGFA both at transcript and protein levels that was correlated with unfavorable outcome. CONCLUSIONS 1. The histologically uniform aSHH-MB cohort exhibits clear molecular heterogeneity separating these tumors into two molecular subsets (aSHH-MBI and aSHH-MBII), which are associated with different cytogenetics, mutational landscapes, gene expression signatures, and clinical course. 2. VEGFA appears to be a promising biomarker to predict clinical course, which needs further prospective validation as its potential role in the pathogenesis of this subset.