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      Sexual dimorphism in glioma glycolysis underlies sex differences in survival

      , , , ,
      JCI Insight
      American Society for Clinical Investigation

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          Abstract

          <p class="first" id="d9126060e197">The molecular bases for sex differences in cancer remain undefined and how to incorporate them into risk stratification remains undetermined. Given sex differences in metabolism and the inverse correlation between fluorodeoxyglucose (FDG) uptake and survival, we hypothesized that glycolytic phenotyping would improve glioma subtyping. Using retrospectively acquired lower-grade glioma (LGG) transcriptome data from The Cancer Genome Atlas (TCGA), we discovered male-specific decreased survival resulting from glycolytic gene overexpression. Patients within this high-glycolytic group showed significant differences in the presence of key genomic alterations (i.e., 1p/19q codeletion, <i>CIC</i>, <i>EGFR</i>, <i>NF1</i>, <i>PTEN</i>, <i>FUBP1</i>, and <i>IDH</i> mutations) compared with the low-glycolytic group. Although glycolytic stratification defined poor prognostic males independent of grade, histology, <i>TP53</i>, and <i>ATRX</i> mutation status, we unexpectedly found that females with high-glycolytic gene expression and wild-type <i>IDH</i> survived longer than all other wild-type patients. Validation with an independent metabolomics dataset from grade 2 gliomas determined that glycolytic metabolites selectively stratified males and also uncovered a potential sexual dimorphism in pyruvate metabolism. These findings identify a potential synergy between patient sex, tumor metabolism, and genomic alterations in determining outcome for glioma patients. </p><p class="first" id="d9126060e228">Transcriptome and metabolome-based profiling of glycolysis in gliomas selectively stratifies males and is associated with differences in key genomic alterations. </p>

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              Molecular subgroups of medulloblastoma: an international meta-analysis of transcriptome, genetic aberrations, and clinical data of WNT, SHH, Group 3, and Group 4 medulloblastomas

              Medulloblastoma is the most common malignant brain tumor in childhood. Molecular studies from several groups around the world demonstrated that medulloblastoma is not one disease but comprises a collection of distinct molecular subgroups. However, all these studies reported on different numbers of subgroups. The current consensus is that there are only four core subgroups, which should be termed WNT, SHH, Group 3 and Group 4. Based on this, we performed a meta-analysis of all molecular and clinical data of 550 medulloblastomas brought together from seven independent studies. All cases were analyzed by gene expression profiling and for most cases SNP or array-CGH data were available. Data are presented for all medulloblastomas together and for each subgroup separately. For validation purposes, we compared the results of this meta-analysis with another large medulloblastoma cohort (n = 402) for which subgroup information was obtained by immunohistochemistry. Results from both cohorts are highly similar and show how distinct the molecular subtypes are with respect to their transcriptome, DNA copy-number aberrations, demographics, and survival. Results from these analyses will form the basis for prospective multi-center studies and will have an impact on how the different subgroups of medulloblastoma will be treated in the future. Electronic supplementary material The online version of this article (doi:10.1007/s00401-012-0958-8) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                JCI Insight
                American Society for Clinical Investigation
                2379-3708
                August 3 2017
                August 3 2017
                August 3 2017
                August 3 2017
                August 3 2017
                : 2
                : 15
                Article
                10.1172/jci.insight.92142
                5543918
                28768910
                56b85ff7-8528-4f35-a759-f56d77c1d8a0
                © 2017
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