Big data visualization identifies the multidimensional molecular landscape of human gliomas.
We show that visualizing large molecular and clinical datasets enables discovery of molecularly defined categories of highly similar patients. We generated a series of linked 2D sample similarity plots using genome-wide single nucleotide alterations (SNAs), copy number alterations (CNAs), DNA methylation, and RNA expression data. Applying this approach to the combined glioblastoma (GBM) and lower grade glioma (LGG) The Cancer Genome Atlas datasets, we find that combined CNA/SNA data divide gliomas into three highly distinct molecular groups. The mutations commonly used in clinical evaluation of these tumors are regionally distributed in these plots. One of the three groups is a mixture of GBM and LGG that shows similar methylation and survival characteristics to GBM. Altogether, our approach identifies eight molecularly defined glioma groups with distinct sequence/expression/methylation profiles. Importantly, we show that regionally clustered samples are enriched for specific drug targets.
Division of Human Biology, and Solid Tumor and Translational Research, Fred Hutchinson Cancer Research Center (FHCRC), Seattle, WA 98109; HBolouri@fhcrc.org eholland@fhcrc.org.
Hamid
H
Bolouri
Division of Public Health Sciences, FHCRC, Seattle, WA 98109;
Lue Ping
LP
Zhao
Division of Human Biology, and Solid Tumor and Translational Research, Fred Hutchinson Cancer Research Center (FHCRC), Seattle, WA 98109; Department of Neurological Surgery, Alvord Brain Tumor Center, University of Washington, Seattle, WA 98195 HBolouri@fhcrc.org eholland@fhcrc.org.
Eric C
EC
Holland
D014408:Biomarkers, Tumor / Q000235:genetics; D001932:Brain Neoplasms; D003196:Computer Graphics; D057225:Data Mining / Q000379:methods*; D030541:Databases, Genetic; D066264:Datasets as Topic; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005910:Glioma; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D009363:Neoplasm Proteins / Q000235:genetics*; D014584:User-Computer Interface
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins
big data; biomarkers; glioma; precision medicine; visualization