Abstract
Modeling of genomic profiles from the Cancer Genome Atlas (TCGA) by using recently developed mathematical frameworks has associated a genome-wide pattern of DNA copy-number alterations with a shorter, roughly one-year, median survival time in glioblastoma (GBM) patients. Here, to experimentally test this relationship, we whole-genome sequenced DNA from tumor samples of patients. We show that the patients represent the U.S. adult GBM population in terms of most normal and disease phenotypes. Intratumor heterogeneity affects and profiling technology and reference human genome specifics affect <1% of the classifications of the tumors by the pattern, where experimental batch effects normally reduce the reproducibility, i.e., precision, of classifications based upon between one to a few hundred genomic loci by >30%. With a 2.25-year Kaplan–Meier median survival difference, a 3.5 univariate Cox hazard ratio, and a 0.78 concordance index, i.e., accuracy, the pattern predicts survival better than and independent of age at diagnosis, which has been the best indicator since 1950. The prognostic classification by the pattern may, therefore, help to manage GBM pseudoprogression. The diagnostic classification may help drugs progress to regulatory approval. The therapeutic predictions, of previously unrecognized targets that are correlated with survival, may lead to new drugs. Other methods missed this relationship in the roughly 3B-nucleotide genomes of the small, order of magnitude of 100, patient cohorts, e.g., from TCGA. Previous attempts to associate GBM genotypes with patient phenotypes were unsuccessful. This is a proof of principle that the frameworks are uniquely suitable for discovering clinically actionable genotype–phenotype relationships.
Highlights
The prognostics, diagnostics, and therapeutics of glioblastoma (GBM), which is the most prevalent as well as most aggressive brain cancer in adults, have remained largely unchanged for decades
Two additional biomarkers have progressed from omic studies to GBM standard of care, both of which have already been used as indicators of survival in other types of cancer, i.e., the mutation of the gene isocitrate dehydrogenase 1 (IDH1) and, most recently, the mutation of the promoter of the gene telomerase reverse transcriptase (TERT), which is correlated with the messenger RNA expression of the gene.[6,7,8,9]
The distribution of the age at diagnosis of the 8001 Surveillance, Epidemiology, and End Results (SEER) patients between ! 50 years and 0.05 (Table S1). These distributions, describe statistically significantly older populations at diagnosis than that of the the Cancer Genome Atlas (TCGA) patients, whose average of 58 years reflects a bias against surgical resections in patients >65 years old
Summary
The prognostics, diagnostics, and therapeutics of glioblastoma (GBM), which is the most prevalent as well as most aggressive brain cancer in adults, have remained largely unchanged for decades. I.e., the alkylating agent temozolomide, has progressed from clinical trials to standard of care since 1980, modestly improving the median life expectancy of patients treated by surgical resection and radiation to roughly 15 months.[1,2,3] A biomarker of response to earlier alkalyting agents in different types of cancer, i.e., the methylation of the promoter of the gene O6-methylguanine-DNA methyltransferase (MGMT), is being used today to predict GBM response to temozolomide and indicate survival.[4,5] Only two additional biomarkers have progressed from omic studies to GBM standard of care, both of which have already been used as indicators of survival in other types of cancer, i.e., the mutation of the gene isocitrate dehydrogenase 1 (IDH1) and, most recently, the mutation of the promoter of the gene telomerase reverse transcriptase (TERT), which is correlated with the messenger RNA (mRNA) expression of the gene.[6,7,8,9] Efforts to conclusively associate outcome, e.g., survival, with GBM-specific mRNA expression of between a few to a few hundred genes, have been unsuccessful, and have not been translated into clinical use.[10,11,12] Despite advances in profiling technologies, including an authorization by the Food and Drug Administration (FDA) for non-disease-specific applications of next-generation sequencing,[13] and the growing numbers of publicly available (gen)omic datasets, age at diagnosis has remained the best indicator of GBM survival in clinical practice since 1950.14–16
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