Journal article
Whole-Genome Multi-omic Study of Survival in Patients with Glioblastoma Multiforme
G3 (Bethesda, Md.), Vol.8(11), pp.3627-3636
11/06/2018
DOI: 10.1534/g3.118.200391
PMCID: PMC6222579
PMID: 30228192
Abstract
Glioblastoma multiforme (GBM) has been recognized as the most lethal type of malignant brain tumor. Despite efforts of the medical and research community, patients' survival remains extremely low. Multi-omic profiles (including DNA sequence, methylation and gene expression) provide rich information about the tumor. These profiles are likely to reveal processes that may be predictive of patient survival. However, the integration of multi-omic profiles, which are high dimensional and heterogeneous in nature, poses great challenges. The goal of this work was to develop models for prediction of survival of GBM patients that can integrate clinical information and multi-omic profiles, using multi-layered Bayesian regressions. We apply the methodology to data from GBM patients from The Cancer Genome Atlas (TCGA, n = 501) to evaluate whether integrating multi-omic profiles (SNP-genotypes, methylation, copy number variants and gene expression) with clinical information (demographics as well as treatments) leads to an improved ability to predict patient survival. The proposed Bayesian models were used to estimate the proportion of variance explained by clinical covariates and omics and to evaluate prediction accuracy in cross validation (using the area under the Receiver Operating Characteristic curve, AUC). Among clinical and demographic covariates, age (AUC = 0.664) and the use of temozolomide (AUC = 0.606) were the most predictive of survival. Among omics, methylation (AUC = 0.623) and gene expression (AUC = 0.593) were more predictive than either SNP (AUC = 0.539) or CNV (AUC = 0.547). While there was a clear association between age and methylation, the integration of age, the use of temozolomide, and either gene expression or methylation led to a substantial increase in AUC in cross-validaton (AUC = 0.718). Finally, among the genes whose methylation was higher in aging brains, we observed a higher enrichment of these genes being also differentially methylated in cancer.
Details
- Title: Subtitle
- Whole-Genome Multi-omic Study of Survival in Patients with Glioblastoma Multiforme
- Creators
- Yeni L Bernal Rubio - Department of Epidemiology and BiostatisticsAgustin González-Reymúndez - Institute for Quantitative Health Science and EngineeringKuan-Han H Wu - Department of Public Health Sciences, Henry Ford Health System, Detroit, Michigan, 48202Corinne E Griguer - Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, Alabama, 35294Juan P Steibel - Department of Animal Science and Department of Fisheries and WildlifeGustavo de Los Campos - Department of Statistics and ProbabilityAndrea Doseff - Department of Pharmacology and Toxicology, Michigan State University, East Lansing, Michigan, 48823Kathleen Gallo - Department of PhysiologyAna I Vazquez - Institute for Quantitative Health Science and Engineering
- Resource Type
- Journal article
- Publication Details
- G3 (Bethesda, Md.), Vol.8(11), pp.3627-3636
- DOI
- 10.1534/g3.118.200391
- PMID
- 30228192
- PMCID
- PMC6222579
- NLM abbreviation
- G3 (Bethesda)
- ISSN
- 2160-1836
- eISSN
- 2160-1836
- Publisher
- United States
- Grant note
- R01 GM101219 / NIGMS NIH HHS P30 DK079626 / NIDDK NIH HHS R01 CA160821 / NCI NIH HHS
- Language
- English
- Date published
- 11/06/2018
- Academic Unit
- Radiation Oncology
- Record Identifier
- 9984047976402771
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