Summary: A new brain cancer atlas maps out comprehensive, visually rich information about the anatomical and genetic bases of glioblastoma, researchers report.
Source: Case Western Reserve.
It takes an “A” team to make headway against glioblastoma, a highly aggressive type of brain cancer. Glioblastoma is the most common type of malignant brain tumor in adults. In addition to the caliber of the researchers involved, in this case “A” also stands for atlas.
A key member of the team, Jill S. Barnholtz-Sloan, PhD, Sally S. Morley Designated Professor in Brain Tumor Research at Case Western Reserve University School of Medicine, and approximately 80 other internationally renowned neurologists, bioinformaticians, and pathologists from the United States and India recently published details of the Ivy Glioblastoma Atlas in Science.
The atlas maps out comprehensive, visually-rich information on the anatomic and genetic bases of glioblastoma at the cellular and molecular levels associated with the disease. It is aimed at helping researchers and physicians improve the diagnosis and treatment of glioblastoma, including finding new drug targets. While Atlas-based data have been previously available, the new paper in Science represents the first published research outlining the project in detail.
According to Barnholtz-Sloan, there are three aims to the venture. The first is to make all the relevant data fully transparent and available. The second is to create a road map of all of the different cells and potential molecular changes that occur in these cells in a glioblastoma. And the third, is to build a better understanding of how much heterogeneity can be found in these tumors.
“Currently we provide the same standard treatment of surgery, followed by radiation plus chemotherapy, for all glioblastoma patients,” says Barnholtz-Sloan, who is also professor and associate director for bioinformatics/translational informatics at CWRU’s School of Medicine. “But the tumors are not all the same. They have different molecular changes, which means that we may need to provide separate, tailored treatments to tackle each one. By identifying unique features of these tumors that may benefit from targeted therapies, the Atlas will enable patients to experience the benefits of precision medicine, increasing the chances for better response to treatment and hence better survival.”
In virtually all cases of glioblastoma, excised tumors are assessed by highly specialized pathologists, who confirm the presence of malignancy and provide details about the unique characteristics of the tumors they examine. For this project, Barnholtz-Sloan assisted the team in developing a study design to assess the concordance between features outlined in the tumors by both these human experts and automated machine-learning techniques. “In many ways it’s a belt and suspenders approach,” she says. “The gold standard is the pathologist. Machine-driven analysis adds value by bringing further information to the findings of the pathologists. In the article we published, we found that the concordance rates were very high; 85-95 percent.”
By way of comparison, Barnholtz-Sloan cites the case of medulloblastoma, a common type of malignant brain tumor mostly seen in children. In medulloblastoma, researchers have been able to group tumors into four distinct molecularly-defined groups, which have specific drugs that would work best within each subtype. The new Atlas hopes to replicate this success in glioblastoma.
“As more new information is added to the Atlas and the associated database for clinical and genomic data, we believe that it will continue to be very valuable research and treatment tool, allowing more refined diagnosis and treatment and enabling researchers to generate potentially life-extending hypotheses about causes and treatments,” said Barnholtz-Sloan.
Funding: Funding for the research provided by Allen Institute for Brain Science, Ben and Catherine Ivy Foundation.
Source: Ansley Gogol – Case Western Reserve
Publisher: Organized by NeuroscienceNews.com.
Image Source: NeuroscienceNews.com image is credited to Case Western Reserve School of Medicine.
Original Research: Abstract for “An anatomic transcriptional atlas of human glioblastoma” by Ralph B. Puchalski, Nameeta Shah, Jeremy Miller, Rachel Dalley, Steve R. Nomura, Jae-Guen Yoon, Kimberly A. Smith, Michael Lankerovich, Darren Bertagnolli, Kris Bickley, Andrew F. Boe, Krissy Brouner, Stephanie Butler, Shiella Caldejon, Mike Chapin, Suvro Datta, Nick Dee, Tsega Desta, Tim Dolbeare, Nadezhda Dotson, Amanda Ebbert, David Feng, Xu Feng, Michael Fisher, Garrett Gee, Jeff Goldy, Lindsey Gourley, Benjamin W. Gregor, Guangyu Gu, Nika Hejazinia, John Hohmann, Parvinder Hothi, Robert Howard, Kevin Joines, Ali Kriedberg, Leonard Kuan, Chris Lau, Felix Lee, Hwahyung Lee, Tracy Lemon, Fuhui Long, Naveed Mastan, Erika Mott, Chantal Murthy, Kiet Ngo, Eric Olson, Melissa Reding, Zack Riley, David Rosen, David Sandman, Nadiya Shapovalova, Clifford R. Slaughterbeck, Andrew Sodt, Graham Stockdale, Aaron Szafer, Wayne Wakeman, Paul E. Wohnoutka, Steven J. White, Don Marsh, Robert C. Rostomily, Lydia Ng, Chinh Dang, Allan Jones, Bart Keogh, Haley R. Gittleman, Jill S. Barnholtz-Sloan, Patrick J. Cimino, Megha S. Uppin, C. Dirk Keene, Farrokh R. Farrokhi, Justin D. Lathia, Michael E. Berens, Antonio Iavarone, Amy Bernard, Ed Lein, John W. Phillips, Steven W. Rostad, Charles Cobbs, Michael J. Hawrylycz, and Greg D. Foltz in Science. Published May 11 2018
An anatomic transcriptional atlas of human glioblastoma
Glioblastoma is an aggressive brain tumor that carries a poor prognosis. The tumor’s molecular and cellular landscapes are complex, and their relationships to histologic features routinely used for diagnosis are unclear. We present the Ivy Glioblastoma Atlas, an anatomically based transcriptional atlas of human glioblastoma that aligns individual histologic features with genomic alterations and gene expression patterns, thus assigning molecular information to the most important morphologic hallmarks of the tumor. The atlas and its clinical and genomic database are freely accessible online data resources that will serve as a valuable platform for future investigations of glioblastoma pathogenesis, diagnosis, and treatment.