Genetic test can help identify brain tumors

A genetic test can help determine types of brain tumors which may help doctors pick the most effective form of treatment.

Scientists have developed a mathematical method for classifying forms of glioblastoma, an aggressive and deadly type of brain cancer, through variations in the way these tumor cells 'read' genes. Their system was capable of predicting the subclasses of glioblastoma tumors with 92 percent accuracy. With further testing, this system could enable physicians to accurately predict which forms of therapy would benefit their patients the most.

Their research was performed in collaboration with Donald M. O'Rourke, M.D., a neurosurgeon at the University of Pennsylvania Brain Tumor Center, who provided the glioblastoma samples necessary to validate the Wistar computer model. Their findings were published online in the journal Nucleic Acids Research.

"It has become increasingly obvious that understanding the molecular makeup of each patient tumor is the key to personalizing cancer treatments for individual patients," said Ramana Davuluri, Ph.D., Wistar's Tobin Kestenbaum Family Professor and associate director of Wistar's Center for Systems and Computational Biology. "We have developed a computational model that will allow us to predict a patient's exact variety of glioblastoma based on the transcript variants a given tumor produces."

"A gene can produce multiple variants, in the form of transcript variants and protein-isoforms. We found that when you use the gene expression information at variant/isoform-level, the statistical analyses recaptured the four known molecular subgroups but with a significant survival difference among the refined subgroups." said Davuluri. "Using patient data, we found that certain subgroups when combined with patient age, for example, could predict better outcomes using a given course of therapy."

"As more targeted therapies come into use, this is exactly the sort of information clinicians will need to provide the best hope of survival for their patients," Davuluri said. "In time, we think this could form the basis of a clinical test that will help oncologists decide a patient's course of treatment."

Glioblastomamultiforme is the most lethal of the malignant adult brain tumors, and accounts for over 50 percent of all cases of brain cancer. Even with aggressive combination therapies, the prognosis remains bleak, with median patient survival of 15 months after diagnosis. The disease is also molecularly heterogeneous, that is, composed of subtypes that are not genetically alike or produce the same array of proteins. Genetic data from the Cancer Genome Atlas (TCGA) consortium has led to the identification of four subtypes of glioblastoma, but Davuluri and his researchers sought to find a way to quickly identify which patient was which subtype.

In previous studies, Davuluri and his Wistar colleagues have established how changes in the way a cell reads its own DNA can create multiple variations of a single protein. These variant proteins are called isoforms, and they are produced as cells alter how they transcribe a given gene into RNA. Slight changes in how the cellular machine reads a gene can result in protein isoforms with subtle differences in enzymatic activity or longevity.

For example, their earlier research determined how human brains produce different isoforms of specific proteins throughout their lives. Developing fetal brains produce different isoforms of certain genes than adult brains. They also found that changes that trigger the production of the wrong isoform at the wrong time could lead to cancer.

In the Nucleic Acids Research study, the researchers combined assays of these protein isoforms with a computer model they call PIGExClass, or the Platform-independent Isoform-level Gene-EXpression based Classification-system. To categorize glioblastomas with PIGExClass, Davuluri and his colleagues first began with Cancer Genome Atlas data to develop a set of 121 isoform variants whose combination of differences could denote a specific subtype of the brain cancer. PIGExClass is, essentially, a software that ranks gene isoform data into sets based on a set of pre-determined values. The researchers found that, by using this classification system, they could predict the subtype of glioblastoma in the database with 92 percent accuracy.

"When we knew what combination of isoforms could create a specific signature for each type of glioblastoma, we could then create a simple laboratory assay that would look for these differences in patient samples," Davuluri said. "In this case the test would measure variations in the RNA abundance associated with these 121 isoforms that make up the signature."

With this new assay in hand, the researchers validated their research using 206 independent samples from the University of Pennsylvania Brain Tumor Tissue Bank. According to Davuluri, when you accounted for differences in the makeup of the pools of patients between TCGA and Penn, the accuracy of the assay remained the same.

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Common cause for brain tumors in children

A specific signaling pathway was found to be the common cause for many brain tumors in children.

An overactive signaling pathway is a common cause in cases of pilocytic astrocytoma, the most frequent type of brain cancer in children. This was discovered by a network of scientists coordinated by the German Cancer Research Center (as part of the International Cancer Genome Consortium, ICGC). In all 96 cases studied, the researchers found defects in genes involved in a particular pathway. Hence, drugs can be used to help affected children by blocking components of the signaling cascade.

The findings are published in the latest issue of the journal Nature Genetics.

Brain cancer is the primary cause of cancer mortality in children. Even in cases when the cancer is cured, young patients suffer from the stress of a treatment that can be harmful to the developing brain. In a search for new target structures that would create more gentle treatments, cancer researchers are systematically analyzing all alterations in the genetic material of these tumors. This is the mission of the PedBrain consortium, which was launched in 2010. Led by Professor Stefan Pfister from the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), the PedBrain researchers have now published the results of the first 96 genome analyses of pilocytic astrocytomas.

Pilocytic astrocytomas are the most common childhood brain tumors. These tumors usually grow very slowly. However, they are often difficult to access by surgery and cannot be completely removed, which means that they can recur. The disease may thus become chronic and have debilitating effects for affected children.

In previous work, teams of researchers led by Professor Dr. Stefan Pfister and Dr. David Jones had already discovered characteristic mutations in a major proportion of pilocytic astrocytomas. All of the changes involved a key cellular signaling pathway known as the MAPK signaling cascade. MAPK is an abbreviation for "mitogen-activated protein kinase." This signaling pathway comprises a cascade of phosphate group additions (phosphorylation) from one protein to the next -- a universal method used by cells to transfer messages to the nucleus. MAPK signaling regulates numerous basic biological processes such as embryonic development and differentiation and the growth and death of cells.

"A couple of years ago, we had already hypothesized that pilocytic astrocytomas generally arise from a defective activation of MAPK signaling," says David Jones, first author of the publication. "However, in about one fifth of the cases we had not initially discovered these mutations. In a whole-genome analysis of 96 tumors we have now discovered activating defects in three other genes involved in the MAPK signaling pathway that have not previously been described in astrocytoma."

"Aside from MAPK mutations, we do not find any other frequent mutations that could promote cancer growth in the tumors. This is a very clear indication that overactive MAPK signals are necessary for a pilocytic astrocytoma to develop," says study director Stefan Pfister. The disease thus is a prototype for rare cancers that are based on defects in a single biological signaling process.

In total, the genomes of pilocytic astrocytomas contain far fewer mutations than are found, for example, in medulloblastomas, a much more malignant pediatric brain tumor. This finding is in accordance with the more benign growth behavior of astrocytomas. The number of mutations increases with the age of the affected individuals.

About one half of pilocytic astrocytomas develop in the cerebellum, the other 50 percent in various other brain regions. Cerebellar astrocytomas are genetically even more homogenous than other cases of the disease: In 48 out of 49 cases that were studied, the researchers found fusions between the BRAF gene, a central component of the MAPK signaling pathway, and various other fusion partners.

"The most important conclusion from our results," says study director Stefan Pfister, "is that targeted agents for all pilocytic astrocytomas are potentially available to block an overactive MAPK signaling cascade at various points. We might thus in the future be able to also help children whose tumors are difficult to access by surgery."

The International Cancer Genome Consortium (ICGC), a network of scientists from currently 15 countries, aims to obtain a comprehensive description of genomic and epigenomic changes in all significant types of cancer. Germany takes part with the PedBrain Tumor Project to analyze pediatric brain tumors (medulloblastoma, which in Germany affects approximately 100 children each year; and pilocytic astrocytoma, which is diagnosed in approximately 200 children each year). Within the PedBrain Tumor Project, 300 samples of each tumor type will be analyzed, along with the same number of samples of healthy tissue from the same patients, to identify changes that are cancer-specific.

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