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Biomarkers Can Predict Risk Level for Malignant Glioma Recurrence

2018-04-12
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Researchers have identified specific predictive biomarkers that could help assess the level of risk for recurrence in patients with malignant glioma. The study (“A Distinct DNA Methylation Shift in a Subset of Glioma CpG Island Methylator Phenotypes during Tumor Recurrence”), led by Henry Ford Health System’s Department of Neurosurgery and Department of Public Health Sciences, appears in Cell Reports.

 

“Glioma diagnosis is based on histomorphology and grading; however, such classification does not have predictive clinical outcome after glioblastomas have developed. To date, no bona fide biomarkers that significantly translate into a survival benefit to glioblastoma patients have been identified. We previously reported that the IDH mutant G-CIMP-high subtype would be a predecessor to the G-CIMP-low subtype. Here, we performed a comprehensive DNA methylation longitudinal analysis of diffuse gliomas from 77 patients (200 tumors) to enlighten the epigenome-based malignant transformation of initially lower-grade gliomas. Intra-subtype heterogeneity among G-CIMP-high primary tumors allowed us to identify predictive biomarkers for assessing the risk of malignant recurrence at early stages of disease,” wrote the investigators.

 

“G-CIMP-low recurrence appeared in 9.5% of all gliomas, and these resembled IDH-wild-type primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, mesenchymal stem cell–like epigenomic phenotype, and genomic instability. Molecular abnormalities of longitudinal G-CIMP offer possibilities to defy glioblastoma progression.”

Biomarkers Can Predict Risk Level for Malignant Glioma Recurrence

Previously, their research showed that when there was no change in the DNA methylation, patients had a good clinical outcome. When the DNA methylation was lost, patients had a poor outcome. In this latest study, the authors were able to identify a set of epigenetic biomarkers that can predict, at a patient’s initial diagnosis, which tumors are likely to recur with a more aggressive tumor type.

 

Houtan Noushmehr, Ph.D., of the Hermelin Brain Tumor Center, and senior author of the study, says this discovery could make a huge difference when a patient is first diagnosed.

 

 “To date, we really don’t have any predictive clinical outcomes once a patient is diagnosed with glioma. By pinpointing these molecular abnormalities, we can begin to predict how aggressive a patient’s recurrence will be and that can better inform the treatment path we recommend from the very beginning,” he explains.

 

Of the 200 tissue samples, 10% were found to have a distinct epigenetic alteration at genomic sites known to be functionally active in regulating genes that are known to be associated with aggressive tumors such as glioblastoma.

 

“This research presents a set of testable DNA-methylation biomarkers that may help clinicians predict if someone’s brain tumor is heading in a more or less aggressive direction, essentially illustrating the behavior of a patient’s disease,” says James Snyder, D.O., study co-author and neuro-oncologist. “If we can identify which brain tumors will have a more aggressive course at the point of initial diagnosis then hopefully we can change the disease trajectory and improve care for our patients.”

 

For example, patients predicted to have a more aggressive tumor at recurrence could be monitored more intensively after their initial treatment, or, undergo a more dynamic therapeutic regimen. Conversely, patients predicted to have a less aggressive recurrence might benefit from a reduction or delay of potentially harsh therapies such as standard chemotherapy and radiation.

 

“Right now, this level of molecular analysis is not routinely available in precision medicine testing and that needs to change,” adds Steven N. Kalkanis, M.D., medical director, Henry Ford Cancer Institute, and chair, Department of Neurosurgery. “We need to be examining this level of information for every patient. The hope is that discoveries like this one will lead to clinical trials and increased access and education that make it available for every person who receives a cancer diagnosis.”

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