Lynda Chin, MDWhen The Cancer Genome Atlas (TCGA) launched its extremely collaborative approach to organ-by-organ genomic analysis of cancers, the brain had both the benefit, and the challenge, of being first on the list.
TCGA ganged up on glioblastoma multiforme (GBM), the most common and lethal of brain tumors, with more than 100 scientists from 14 institutions tracking down the genomic abnormalities that drive GBM.
Five years later, older, and wiser, TCGA revisited glioblastoma, producing a broader, deeper picture of the drivers–and potential therapeutic targets–of the disease published in the October 10 issue of Cell.
“The first paper in 2008 characterized glioblastoma in important new ways and illuminated the path for all TCGA organ studies that have followed,” says senior author Lynda Chin, MD, professor and chair of genomic medicine and scientific director, Institute for Applied Cancer Science, The University of Texas MD Anderson Cancer Center, Houston.
“Our new study reflects major improvements in technology applied to many more tumor samples to more completely characterize the landscape of genomic alterations in glioblastoma,” says Chin, who was also co-senior author of the first paper while she was on the faculty of Dana-Farber Cancer Institute, Boston.
“Information generated by this unbiased, data-driven analysis presents new opportunities to discover genomics-based biomarkers, understand disease mechanisms, and generate new hypotheses to develop better, targeted therapies,” Chin says.
About 23,000 new cases of GBM are predicted in the United States during 2013 and more than 14,000 people are expected to die of the disease. Most patients die within 15 months of diagnosis.
New information about genetic mutations, deletions, and amplifications; gene expression and epigenetic regulation; structural changes due to chromosomal alterations, proteomic effects, and the molecular networks that drive GBM make for a deep, broad dataset that will underpin research and clinical advances for years to come.
“Our main contribution is this tremendous resource for the GBM research community, which is already heavily relying on the earlier TCGA study,” says co-lead author Roeland Verhaak, PhD, assistant professor, bioinformatics and computational biology, MD Anderson. “Whatever new treatments people come up with for GBM, I’m very confident that their discovery and development will in some way have benefited from this rich and detailed data set.”
The Cell paper describes analysis of tumor samples and molecular data from 599 patients at 17 study sites. Detailed clinical information, including treatment and survival, was available for almost all cases.
In addition to confirming significantly mutated genes discovered earlier, such as the tumor suppressors TP53, PTEN, and RB1 and the oncogene PIK3CA, the analysis identified 61 new mutated genes. The most frequent mutations occurred in from 1.7% to 9% of cases.
Two of these, BRAF and FGFR, might have more immediate clinical relevance, Verhaak notes. MD Anderson neuro-oncologists are checking to see if patients have these mutations. Drugs are available to address those variations now, Verhaak adds. The BRAF point mutation in GBM is the same commonly found in melanoma, which is treated by a new class of drugs.
The larger data set and an improved analytical algorithm allowed major refinement of gene amplification and deletion information. For example, common amplification events were found to occur more frequently than previously known, including amplification of the epidermal growth factor receptor (EGFR) on chromosome 7.
EGFR is both amplified and mutated frequently in GBM; yet therapeutic efforts targeting EGFR so far have failed. “We found EGFR is more frequently altered than we already thought,” Verhaak says.
Overall, the EGFR gene was mutated, rearranged, amplified, or otherwise altered in 57% of tumors. Increased EGFR protein levels in GBM cells correlated with the many mechanisms of EGFR alteration, Verhaak says.
A treatment based on EGFR still has great potential, he notes. But strategies to target EGFR will need to address the likelihood that different alterations of EGFR might be present in the same tumor and affect the impact of targeted drugs.
Verhaak and other researchers have, in recent years, begun to classify GBM tumors by gene expression. Four such subgroups—neural, proneural, mesenchymal, and classical—were further characterized by DNA methylation pattern, signaling pathway activity, and by clinical measures such as survival and treatment response. Methylation of a gene turns it off.
Understanding the subgroups could establish biomarkers to guide treatment and identify new therapeutic targets.
The team found, for example, that the survival advantage of the proneural subtype depends on a specific DNA methylation pattern known as G-CIMP and that DNA methylation of the MGMT gene may serve as a biomarker of treatment response in the classical subtype.
Co-authors with Chin and Verhaak are 56 investigators from 39 institutions on behalf of the TCGA Research Network. MD Anderson co-authors include Wei Zhang, PhD, of the Pathology Department. Zhang, is among the leaders or co-leaders of three of the seven TCGA Genome Analysis Centers.
TCGA is a joint project of the National Cancer Institute and the National Human Genome Research Institute of the National Institutes of Health.
[Source: MD Anderson]
