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Scientists identify biomarker for progression, drug response in brain cancer

Accurately subtyping glioblastoma tumors could lead to diagnostics, precision therapy

Date:
October 16, 2017
Source:
The Mount Sinai Hospital / Mount Sinai School of Medicine
Summary:
Scientists have reported results from a glioblastoma study in which they validated a biomarker indicative of a patient's prognosis and likely response to specific therapies.
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Scientists at the Icahn School of Medicine at Mount Sinai, Sema4, and collaborating institutions including Colorado State University and Fred Hutchinson Cancer Center reported results today from a glioblastoma study in which they validated a biomarker indicative of a patient's prognosis and likely response to specific therapies. The article appeared in the October 15 issue of Cancer Research.

Glioblastoma is a highly aggressive and heterogeneous form of brain cancer, with a median survival time from diagnosis of just one year. Previous efforts to classify glioblastoma tumors into molecular subtypes for precision treatment have been largely unsuccessful. In this study, scientists developed an innovative computational method to classify tumors based on their dependency on a molecule, known as BUB1B, that some glioblastomas need to survive. The project revealed new tumor subtypes and found that BUB1B-sensitive tumors had significantly worse prognosis but were more likely to respond to many drugs already in clinical use.

"It was truly remarkable to see our predictive model yield a new set of molecular subtypes, which appear to be far more indicative of prognosis and therapeutic response than existing subtypes," said Jun Zhu, PhD, Head of Data Sciences at Sema4, Professor of Genetics and Genomic Sciences at Mount Sinai, and senior author of the paper. "For patients who receive the grim diagnosis of glioblastoma, this signals new hope for tailored treatment more likely to be effective against their cancer."

"This research is an outstanding example of how theoreticians working with complex datasets, and clinicians on the frontlines of patient care, can collaborate to uncover new insights into cancer biology that will directly impact clinical decision-making," said Raymund Yong, MD, Assistant Professor of Neurosurgery and Assistant Professor of Oncological Sciences at the Icahn School of Medicine at Mount Sinai, who made a significant contribution to tumor samples, glioma stem cells, and in vitro experiments in the paper.

Eric Schadt, PhD, Sema4 CEO and Dean for Precision Medicine at Mount Sinai, added: "These findings underscore the significant potential we see to improve patient outcomes by investing in predictive modeling of even the most complex types of cancer. We look forward to building on this collaborative project and moving toward development of a diagnostic test that could help physicians better understand and treat their patients' glioblastoma cases."


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Materials provided by The Mount Sinai Hospital / Mount Sinai School of Medicine. Note: Content may be edited for style and length.


Journal Reference:

  1. Eunjee Lee, Margaret Pain, Huaien Wang, Jacob A. Herman, Chad M. Toledo, Jennifer G. DeLuca, Raymund L. Yong, Patrick Paddison, Jun Zhu. Sensitivity to BUB1B Inhibition Defines an Alternative Classification of Glioblastoma. Cancer Research, 2017; 77 (20): 5518 DOI: 10.1158/0008-5472.CAN-17-0736

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The Mount Sinai Hospital / Mount Sinai School of Medicine. "Scientists identify biomarker for progression, drug response in brain cancer." ScienceDaily. ScienceDaily, 16 October 2017. <www.sciencedaily.com/releases/2017/10/171016102835.htm>.
The Mount Sinai Hospital / Mount Sinai School of Medicine. (2017, October 16). Scientists identify biomarker for progression, drug response in brain cancer. ScienceDaily. Retrieved April 14, 2024 from www.sciencedaily.com/releases/2017/10/171016102835.htm
The Mount Sinai Hospital / Mount Sinai School of Medicine. "Scientists identify biomarker for progression, drug response in brain cancer." ScienceDaily. www.sciencedaily.com/releases/2017/10/171016102835.htm (accessed April 14, 2024).

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