title: Somatic intronic microsatellite loci differentiate glioblastoma from lower-grade gliomas.
abstract: Genomic studies of glioma sub-types have amassed new disease specific mutations, yet these only partially explain how mutations are linked to predisposition or progression. We hypothesized that microsatellite variation could expand the understanding of glioma etiology. Furthermore, germline markers for gliomas are typically undetectable; therefore we also hypothesize that the predictability of cancer-associated microsatellite loci in germline DNA may support the current hypothesis of a glioma cell of origin. In this study, "normal" germline exome sequenced DNA from the 1000 Genomes Project (n=390) were compared with exome sequences from germlines of subjects with WHO grade II and III lower-grade glioma (LGG, n=136) and WHO grade IV glioblastoma (GBM, n=252) from The Cancer Genome Atlas to identify microsatellite loci non-randomly associated with glioma. From germline data, we identified 48 GBM-specific loci, 42 Lower-grade glioma specific loci and 29 loci that distinguish GBM from LGG (p≤ 0.01). We then attempted to distinguish WHO grade II glioma (n=67) from GBM resulting in 8 informative loci. Significantly, in all glioma grades, comparisons between tumor and matched germline sequences demonstrated no significant differences in these variants (p≥ 0.01). Therefore, these microsatellite loci are considered to be components of grade-specific signatures for glioma which distinguish germline sequences of individuals with cancer from those of individuals that are "normal". In order to better understand the significance of these loci, we identified biological processes enriched in genes with these variants. Most strikingly, six helicase genes were enriched in the GBM cohort (p≤ 1.0 x10⁻³). The preservation of these glioma-specific loci could therefore serve as valuable diagnostic and therapeutic markers; especially since the heterogeneity of tumor cell populations can obscure the identification of mutations preceding a metastatic phenotype.
authors.affiliation: Virginia Bioinformatics Institute, Medical Informatics and Systems Division; Blacksburg, VA; These authors contributed equally to this work.
authors.forename: Enusha
authors.initials: E
authors.lastname: Karunasena
authors.affiliation: Virginia Bioinformatics Institute, Medical Informatics and Systems Division; Blacksburg, VA; These authors contributed equally to this work.
authors.forename: Lauren J
authors.initials: LJ
authors.lastname: McIver
authors.affiliation: Center for Cancer and Blood Disorders at Children's National Medical Center; Washington, D.C.
authors.forename: Brian R
authors.initials: BR
authors.lastname: Rood
authors.affiliation: Department of Statistics at Virginia Tech; Blacksburg, VA.
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Wu
authors.affiliation: Department of Statistics at Virginia Tech; Blacksburg, VA.
authors.forename: Hongxiao
authors.initials: H
authors.lastname: Zhu
authors.affiliation: Virginia Bioinformatics Institute, Medical Informatics and Systems Division; Blacksburg, VA.
authors.forename: Jasmin H
authors.initials: JH
authors.lastname: Bavarva
authors.affiliation: Virginia Bioinformatics Institute, Medical Informatics and Systems Division; Blacksburg, VA.
authors.forename: Harold R
authors.initials: HR
authors.lastname: Garner
mesh_terms: D001932:Brain Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology*; D002454:Cell Differentiation / Q000235:genetics; D005260:Female; D023281:Genomics; D005909:Glioblastoma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology*; D005910:Glioma / Q000235:genetics* / Q000378:metabolism / Q000473:pathology*; D006801:Humans; D007438:Introns; D008297:Male; D018895:Microsatellite Repeats