CINCINNATI—A multi-institutional team that includes researchers from the University of Cincinnati (UC) College of Medicine Department of Environmental Health today received a five-year, $19.7 million grant from the National Institutes of Health (NIH) to create a data coordination center for an NIH program that will seek insight into how cells react to drugs and toxins.
The grant is part of the NIH’s Big Data to Knowledge (BD2K) initiative, which is projected to have a total investment of nearly $656 million through 2020, pending available funds. Multi-institute awards announced today by the NIH established 12 centers that will each tackle specific data science challenges, constituting an initial investment of nearly $32 million in fiscal year 2014.
UC, along with the Icahn School of Medicine at Mount Sinai in New York and the University of Miami (Florida) will form the BD2K-LINCS Perturbation Data Coordination and Integration Center. (Perturbation refers to disruption by drugs or other factors.) An additional 11 centers will be known as Centers of Excellence for Big Data Computing, charged with developing innovative approaches, methods, software, tools and other resources relevant to big data science.
The BD2K-LINCS Perturbation Data Coordination and Integration Center will receive $2.5 million in funding for the remainder of fiscal year 2014 and $4.3 million annually for the next four years. The principal investigator at UC is Mario Medvedovic, PhD, a professor and the director of the division of biostatistics and informatics in the environmental health department and member of the Center for Environmental Genetics (CEG), which is housed in the department. His collaborators will be Avi Ma’ayan, PhD, at Mount Sinai and Stephan Schürer, PhD, at Miami.
"Today’s announcement reinforces UC as a premier site for bioinformatics,” says Shuk-mei Ho, PhD, Jacob G. Schmidlapp Professor and Chair of Environmental Health at UC, principal investigator of the CEG and director of the Cincinnati Cancer Center, a collaborative initiative of UC, UC Health and Cincinnati Children’s Hospital Medical Center.
The NIH Common Fund’s LINCS (Library of Integrated Network-based Cellular Signatures) program aims to characterize how a variety of cells, tissues and networks respond to disruption by drugs and other factors. The center will support data science research focusing on interpreting and integrating LINCS-generated data from different data types and databases in LINCS-funded projects.
"Our role is to develop new methods to integrate big data, come up with intelligent ways to mine and analyze it, intuitive tools to interact with it and to educate the research community on how to best leverage this trove of information for biomedical research,” says Medvedovic, who along with Jarek Meller, PhD, co-directs the CEG’s bioinformatics core.
Studies generating large amounts of data continue to proliferate, the NIH says, from imaging projects to epidemiological studies examining thousands of participants to large disease-oriented efforts such as the Cancer Genome Atlas, which examines the genomic underpinnings of more than 30 types of cancer. Such efforts have generated billions of data points and provide opportunities for the original researchers and other investigators to use these results in their own work to advance knowledge of biology and biomedicine.
"Data creation in today’s research is exponentially more rapid than anything we anticipated even a decade ago,” says NIH Director Francis S. Collins, MD, PhD. "Mammoth data sets are emerging at an accelerated pace in today’s biomedical research and these funds will help us overcome the obstacles to maximizing their utility. The potential of these data, when used effectively, is quite astounding.”
LINCS signatures aim to capture patterns of genomic and protein global responses within a type of cell to a drug, drug combination or other factors that affect human health, such as environmental toxins. The data integration center will create a computing environment and Web portal where many sources can be shared, combined and jointly analyzed. It will also conduct research into how data is generated, gathered and analyzed, and build an array of statistical and computional models to tease out patterns related to drug response in human cells.
The LINCS project originated 10 years ago with the Broad Institute of Massachusetts Institute of Technology, where researchers created a database of molecular signatures by treating four human cancer cell lines with over 1,000 drugs, then measuring gene expression in the presence of each drug. This dataset proved to be useful for discovering the functions of new drugs by comparing their signatures with existing drugs. The excitement surrounding this first study, called the Connectivity Map, led to the establishment of the LINCS program.
"The ultimate goal,” says Medvedovic, "is to connect the different perturbations that happen due to a disease to the ones that happen due to genetic manipulations or drug treatments and to see what the mechanisms are and whether that can inform us on which drug could effectively treat the disease. This is already happening in the context of ‘precision medicine.’
"On a gross scale, one tumor might look like many other tumors. But when you dig a little deeper and figure out which genes are activated, you find out more about how you should attack it.”