At a session on sex differences she was joined by colleagues from the Lerner Research Institute at the Cleveland Clinic, the Mayo Clinic, and the Washington University School of Medicine, St. Louis, who together offered a comprehensive view of the most current research on sex-specific differences in gliomas, with a focus on sex-specific differences in incidence, survival, genetics, microenvironment, imaging, and therapeutic response. Barnholtz-Sloan summarized her work, in establishing that gliomas and other malignant brain and CNS tumors occur more frequently in males who also have lower overall survival rates. At the molecular level, biological pathways associated with glioma risk and with outcomes also vary by sex.
“Large studies with vast amounts of data, require collaboration across dozens of research centers,” said Barnholtz-Sloan. “Differences by sex in brain tumor incidence, overall survival and risk profile have come to light over many years of collaborative work, although the research community continues to search for the biological underpinnings to explain these sex-specific differences.”
Barnholtz-Sloan’s collaborative work has leveraged multiple types of large data sets – from clinical trials, electronic medical records including pathology and imaging reports, to genetic sequence and genetic pathway information. Her second presentation at the annual meeting, walked colleagues through some of the pragmatic issues in using big data collected across various institutions for clinical research with a focus on brain tumors.
“Researchers looking broadly at multiple variables in brain tumor research recognize that health system electronic medical records offer a wealth of information about disease onset, treatment, co-morbidities and clinical outcomes,” she continued. “The research community is at an important juncture given the ability to leverage clinically based E.M.R. data in concert with large scale data sets that offer detailed molecular characterization of brain tumors. Managing the volume and variety of data while respecting health system requirements about data use and data security, means that biomedical researchers have to navigate the realities of the health care market landscape and the proprietary nature of systems’ data.”
Barnholtz-Sloan, on the leadership team of the Cleveland Institute for Computational Biology, is directing several initiatives to rationalize and use health systems’ E.M.R. data in northeastern Ohio, as a proving ground for this volume and complexity of data intersection.