title: Imaging genomic mapping of an invasive MRI phenotype predicts patient outcome and metabolic dysfunction: a TCGA glioma phenotype research group project.
abstract: BACKGROUND
  Invasion of tumor cells into adjacent brain parenchyma is a major cause of treatment failure in glioblastoma. Furthermore, invasive tumors are shown to have a different genomic composition and metabolic abnormalities that allow for a more aggressive GBM phenotype and resistance to therapy. We thus seek to identify those genomic abnormalities associated with a highly aggressive and invasive GBM imaging-phenotype.
  
  
  METHODS
  We retrospectively identified 104 treatment-naïve glioblastoma patients from The Cancer Genome Atlas (TCGA) whom had gene expression profiles and corresponding MR imaging available in The Cancer Imaging Archive (TCIA). The standardized VASARI feature-set criteria were used for the qualitative visual assessments of invasion. Patients were assigned to classes based on the presence (Class A) or absence (Class B) of statistically significant invasion parameters to create an invasive imaging signature; imaging genomic analysis was subsequently performed using GenePattern Comparative Marker Selection module (Broad Institute).
  
  
  RESULTS
  Our results show that patients with a combination of deep white matter tracts and ependymal invasion (Class A) on imaging had a significant decrease in overall survival as compared to patients with absence of such invasive imaging features (Class B) (8.7 versus 18.6 months, p < 0.001). Mitochondrial dysfunction was the top canonical pathway associated with Class A gene expression signature. The MYC oncogene was predicted to be the top activation regulator in Class A.
  
  
  CONCLUSIONS
  We demonstrate that MRI biomarker signatures can identify distinct GBM phenotypes associated with highly significant survival differences and specific molecular pathways. This study identifies mitochondrial dysfunction as the top canonical pathway in a very aggressive GBM phenotype. Thus, imaging-genomic analyses may prove invaluable in detecting novel targetable genomic pathways.
authors.affiliation: Department of Diagnostic Radiology, M, D, Anderson Cancer Center, 1400 Pressler St; Unit 1482, Rm # FCT 16,5037, Houston, TX 77030, USA. rcolen@mdanderson.org.
authors.forename: Rivka R
authors.initials: RR
authors.lastname: Colen
authors.forename: Mark
authors.initials: M
authors.lastname: Vangel
authors.forename: Jixin
authors.initials: J
authors.lastname: Wang
authors.forename: David A
authors.initials: DA
authors.lastname: Gutman
authors.forename: Scott N
authors.initials: SN
authors.lastname: Hwang
authors.forename: Max
authors.initials: M
authors.lastname: Wintermark
authors.forename: Rajan
authors.initials: R
authors.lastname: Jain
authors.forename: Manal
authors.initials: M
authors.lastname: Jilwan-Nicolas
authors.forename: James Y
authors.initials: JY
authors.lastname: Chen
authors.forename: Prashant
authors.initials: P
authors.lastname: Raghavan
authors.forename: Chad A
authors.initials: CA
authors.lastname: Holder
authors.forename: Daniel
authors.initials: D
authors.lastname: Rubin
authors.forename: Eric
authors.initials: E
authors.lastname: Huang
authors.forename: Justin
authors.initials: J
authors.lastname: Kirby
authors.forename: John
authors.initials: J
authors.lastname: Freymann
authors.forename: Carl C
authors.initials: CC
authors.lastname: Jaffe
authors.forename: Adam
authors.initials: A
authors.lastname: Flanders
authors.forename: Pascal O
authors.initials: PO
authors.lastname: Zinn
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001932:Brain Neoplasms / Q000235:genetics* / Q000378:metabolism* / Q000473:pathology; D004805:Ependyma / Q000473:pathology; D005260:Female; D015894:Genome, Human / Q000235:genetics*; D005910:Glioma / Q000235:genetics* / Q000378:metabolism* / Q000473:pathology; D006801:Humans; D053208:Kaplan-Meier Estimate; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D008928:Mitochondria / Q000235:genetics; D008954:Models, Biological; D010641:Phenotype; D016016:Proportional Hazards Models; D015398:Signal Transduction / Q000235:genetics; D014157:Transcription Factors / Q000378:metabolism; D016896:Treatment Outcome; D055815:Young Adult
chemical_list: D014157:Transcription Factors