Detailed new information about diffuse glioma has come from an international collaborative study. This raises hopes for improved clinical outcomes from the better understanding of the disease. The findings were published in Cell.1
Diffuse glioma represents approximately 80% of adult malignant brain tumors and is currently classified by histological criteria into 4 groups (oligodendroglioma, olioastrocytoma, astrocytoma, and glioblastoma).
The study, led by researchers at The University of Texas MD Anderson Cancer Center in Houston, Texas; Columbia University Medical Center, New York; and the University of Sao Paulo Ribeirao Preto Medical School, Brazil, analyzed data from 1122 samples of diffuse glioma from lower to higher grades. The dataset came from The Cancer Genome Atlas (TCGA).
“TCGA data allowed us to identify diffuse glioma subgroups with distinct molecular and clinical features and shed light on mechanisms driving disease progression,” said Roel Verhaak, PhD, associate professor, Bioinformatics and Computational Biology at MD Anderson.
The study comprehensively analyzed molecular profiling data from TCGA. It found that telomere length and maintenance are defined by somatic alterations; telomeres are the repetitive DNA pieces at the end of chromosomes that protect the end of the chromosome from alteration.
When the study profiled DNA methylation, it revealed subtypes of the IDH-mutant and IDH-wild-type gliomas. The study describes 7 subtypes of glioma (3 under IDH-mutant and 4 under IDH-wild-type), and it includes clinical features for each subtype.
In addition, the study integrated molecular analysis of the progression from low- to high-grade disease. Currently, pathologists determine if a glioma is low-grade or high-grade based on microscopic evaluation of tumor tissue appearance.
“While this approach is generally good at distinguishing between gliomas that are clearly very aggressive and those that are relatively slow-growing, it misses the mark in a significant percentage of cases, leading to inappropriate treatment,” said Antonio Iavarone, MD, professor of Neurology and Pathology and Cell Biology at Columbia University Medical Center. “By looking at the molecular makeup of these tumors, we now have a much more precise way of predicting which tumors are more likely to grow rapidly and can prescribe treatments accordingly.”
The researchers explained that the data from this study will allow accurate determinations of which patients will have the best and worst clinical outcomes. This will allow treatments to be prescribed accordingly, explained Houtan Noushmehr, PhD, assistant professor of Epigenomics and Bioinformatics at University of Sao Paolo in Brazil.
The new knowledge about glioma classification will aid the development of therapies.
“This study has expanded our knowledge of the glioma somatic alteration landscape, emphasized the relevance of DNA methylation profiles as a method for clinical classification, and has linked TERT (telomerase reverse transcriptase) pathway alterations to telomere maintenance,” said Verhaak. “Combined, these findings are an important step forward in our understanding of glioma as discrete disease subsets, and the mechanism driving glioma formation and progression.”
1. Ceccarelli M, Barthel FP, Malta TM, et al. Molecular profiling reveals biologically discrete subsets and pathways of progression in diffuse glioma. Cell. 2016;164(3):550-563. doi:10.1016/j.cell.2015.12.028.