Molecular subtyping of GBM has advanced basic, translational and clinical neuro-oncology. As there are well-recognized sex differences in GBM incidence and outcome, we hypothesized that analysis of merged male and female datasets had previously masked important molecular features of GBM. To test this hypothesis we applied a JIVE algorithm to decompose male and female complete GBM transcriptome datasets (TCGA) accessed through the UCSC Cancer Genomics Browser, to joint and sex-specific components. We sought to determine whether there are shared or distinct GBM molecular subtypes in males and females. Using consensus hierarchical clustering independently on the sex-specific component from the JIVE, we defined five male and five female transcriptome clusters. Most clusters were a mix of samples previously assigned to the four Verhaak subtypes. While driver events were shared between the male and female clusters, they could be distinguished by their expression profiles, pathway analysis, and by their survival. Most notable were the differences between male and female subsets with the best survival. In female GBM, IDH1 mutation alone defined a single cluster with superior survival. Two male subtypes exhibited better survival, and this could not be completely explained by enrichment for IDH mutant tumors. Pathway analyses of genes differentiating a male or female cluster versus the others indicated that the male clusters with better survival were enriched with expression of collagen genes and extracellular matrix components. No similar phenotype was observed in the female subsets. The correlation between the sex-specific GBM clusters and survival was validated in further analyses of the GSE13041 and 16011 datasets. Together these data indicate that important elements of GBM biology and outcome can be discovered through sex-specific analyses and that distinctions between the biology of male and female GBM may need to be incorporated into precision approaches to treatment.