Scientists develop gene test to accurately classify brain tumors

February 18, 2014, The Wistar Institute

Scientists at The Wistar Institute 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."

Glioblastoma multiforme is the most lethal of the malignant adult , and accounts for over 50 percent of all cases of . 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 , 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.

Explore further: Multiple 'siblings' from every gene: Alternate gene reading leads to alternate gene products

Related Stories

Multiple 'siblings' from every gene: Alternate gene reading leads to alternate gene products

July 11, 2011
A genome-wide survey by researchers at The Wistar Institute shows how our cells create alternate versions of mRNA transcripts by altering how they "read" DNA. Many genes are associated with multiple gene promoters, the researchers ...

Proteins in histone group might influence cancer development, study shows

September 3, 2013
Spool-like proteins called histones play a crucial role in packaging the nearly seven feet of DNA found in most human cells. A new study shows that a group of histones that are thought to behave the same way actually are ...

Tipping the balance between senescence and proliferation

November 15, 2013
An arrest in cell proliferation, also referred to as cellular senescence, occurs as a natural result of aging and in response to cellular stress. Senescent cells accumulate with age and are associated with many aging phenotypes, ...

Killer cocktail fights brain cancer

November 25, 2013
A novel immune-boosting drug combination eradicates brain cancer in mice, according to a study in The Journal of Experimental Medicine.

Researchers target cancer stem cells in malignant brain tumors

January 6, 2014
Researchers at the Cedars-Sinai Maxine Dunitz Neurosurgical Institute and Department of Neurosurgery identified immune system targets on cancer stem cells – cells from which malignant brain tumors are believed to originate ...

Recommended for you

Researchers develop swallowable test to detect pre-cancerous Barrett's esophagus

January 17, 2018
Investigators at Case Western Reserve University School of Medicine and University Hospitals Cleveland Medical Center have developed a simple, swallowable test for early detection of Barrett's esophagus that offers promise ...

Scientists zoom in to watch DNA code being read

January 17, 2018
Scientists have unveiled incredible images of how the DNA code is read and interpreted—revealing new detail about one of the fundamental processes of life.

Dulling cancer therapy's double-edged sword

January 17, 2018
Researchers have discovered that killing cancer cells can actually have the unintended effect of fueling the proliferation of residual, living cancer cells, ultimately leading to aggressive tumor progression.

Presurgical targeted therapy delays relapse of high-risk stage 3 melanoma

January 17, 2018
A pair of targeted therapies given before and after surgery for melanoma produced at least a six-fold increase in time to progression compared to standard-of-care surgery for patients with stage 3 disease, researchers at ...

T-cells engineered to outsmart tumors induce clinical responses in relapsed Hodgkin lymphoma

January 16, 2018
WASHINGTON-(Jan. 16, 2018)-Tumors have come up with ingenious strategies that enable them to evade detection and destruction by the immune system. So, a research team that includes Children's National Health System clinician-researchers ...

Researchers identify new treatment target for melanoma

January 16, 2018
Researchers in the Perelman School of Medicine at the University of Pennsylvania have identified a new therapeutic target for the treatment of melanoma. For decades, research has associated female sex and a history of previous ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.