Biomarker panel can guide future therapeutic decisions for glioma patients

In an article published April 10th in the journal Cell Reports, researchers at the University of São Paulo (USP) describe a biomarker panel that could tell physicians which patients diagnosed with glioma, a type of brain cancer, will tend to progress to a more aggressive form of the disease in the event of relapse.

According to principal investigator Houtan Noushmehr, a professor at USP's Ribeirão Preto Medical School (FMRP-USP), between 80% and 90% of patients diagnosed with brain cancer develop a second tumor after surgical removal of the original lesion.

In most cases the epigenetic profile of the tumor cells remains the same, meaning that gene expression is not altered. This suggests a favorable prognosis with good longevity. In 10% of patients with tumor relapse, however, the cancer cells acquire a more aggressive phenotype, reducing their overall survival.

"At the time of the primary diagnosis [discovery of the first tumor] our biomarker panel could show whether the patient is among these 10% who tend to progress to a more severe condition. This knowledge would help the physician decide whether more aggressive treatment is appropriate in order to prevent progression of the disease," Noushmehr said.

With support by the Sao Paulo Research Foundation - FAPESP, the study was based on an analysis of 200 samples of glioma, a type of cancer that originates in glial cells (such as astrocytes, oligodendrocytes and microglia), which mediate immune responses in the central nervous system (CNS) and support the functioning of neurons. The work was carried out during the postdoctoral research of Camila Ferreira de Souza, partly conducted in the United States at the Henry Ford Hospital, thanks to a FAPESP scholarship for a research internship abroad.

Gliomas are the most common group of CNS tumors, accounting for some 80% of cases, with a mortality rate of about 92%. The degree of histopathological aggressiveness (based on tissue characteristics) ranges from 1 to 4. The higher the number, the worse the prognosis.

"We analyzed samples from 77 patients, from both the primary tumor and the first and second relapse, or even the third in some cases. This is the largest case series survey ever of primary and recurrent gliomas from the same patients," Noushmehr said.

Some of the samples analyzed were collected from patients treated at FMRP-USP and Henry Ford Hospital in Detroit (USA). The rest of the data was obtained from studies published in the last three years.

Analysis of the samples focused on epigenetic mechanisms, the chemical processes that modulate genome functioning (to adapt to environmental stimuli) and hence cell phenotype by activating or deactivating gene expression.

More precisely, in this study the group chose a specific epigenetic regulation mechanism known as DNA methylation, a chemical reaction that adds a methyl group (made up of hydrogen and carbon atoms) to the DNA base cytosine, potentially altering the expression of certain genes.

Glioma subtypes

In an article published in the journal Cell in 2016, the group led by Noushmehr had identified seven different glioma subtypes on the basis of tumor epigenetic profiles - among them a more aggressive profile, which they called subtype G-CIMP-low, and one with a more favorable prognosis called G-CIMP-high.

"What we show in this new paper is that only 10% of patients who develop a second tumor progress from subtype G-CIMP-high to subtype G-CIMP-low," Noushmehr explained.

The group analyzed DNA methylation in the 200 tumor samples by microarray, a methodology that can identify and characterize millions of sites and functional genomic elements simultaneously.

As the authors explain, the process whereby a methyl group is added to DNA typically occurs in the base cytosine that usually precedes a guanine (dinucleotide CpG). Microarray analysis shows whether the CpG regions studied, including genes and regulatory elements in the genome, are more or less methylated.

The microarray datasets were processed with the aid of machine learning algorithms, a form of artificial intelligence. These algorithms sift through masses of data using advanced statistical techniques in search of patterns on which to base determinations or predictions.

"In this way we identified seven genomic sites where the level of DNA methylation serves as a biomarker of the risk of evolution from the G-CIMP-high phenotype to the G-CIMP-low phenotype. This is how we produced the biomarker panel," Noushmehr said.

Today, he added, all patients diagnosed with glioma are prescribed practically the same treatment. "You have to wait for the cancer to return, undergo another operation and find out whether it has progressed," he said. "If we know from the outset whether there's a risk of progression to the G-CIMP-low phenotype, we can plan treatment accordingly."

For Souza, the development of personalized therapies for glioma patients is "suboptimized".

"This is due in part to the fact that diagnosis is based mainly on traditional histopathological criteria, meaning the degree of tumor malignancy," she said.

The present study, she added, identified epigenetic vulnerabilities that serve to stratify with high levels of sensitivity and specificity phenotypes associated with recurrent gliomas and with distinct clinical prognoses that could not be predicted merely by neurohistopathological grading of tumor biopsies.

"We expect the panel of clinical biomarkers identified to pave the way for a refinement of our current clinical classification scheme," Souza said. "This will help guide future therapeutic decisions before recurrent malignant gliomas become symptomatic. It will also avoid unnecessarily exposing patients with gliomas that are not highly aggressive to toxic radiation therapy and chemotherapy protocols."

Noushmehr and Souza stressed, however, that the biomarker panel must be validated in a clinical trial and that completion of this process typically takes several years.

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