Scientists studying the genetic changes in skin tissue linked to a life-threatening skin cancer, or melanoma, will soon have new analysis tools and more research data at their fingertips thanks to a collaboration with the Renaissance Computing Institute (RENCI), a multidisciplinary institute affiliated with the University of North Carolina at Chapel Hill, Duke and North Carolina State universities.
Dr. William Kaufmann, a professor of pathology and laboratory medicine at UNC’s School of Medicine, is working with a RENCI team led by Dr. Xiaojun Guan on overcoming some of the thorniest technical challenges in understanding melanoma; their work could lead to better treatments for the deadly disease. Those challenges include pulling together biological data from disparate databases and experiments, merging data sets into comprehensive data visualizations, and developing standard methods for visualizing genetic pathways, which is the series of interactions that take place among related genes that lead to mutations and the development of cancer cells.
“These scientists work with data from their own research subjects and from databases of protein interactions that are accessed through the Internet,” said Guan. “Very often the data are in different formats and use their own nomenclatures, which makes it difficult to do the large-scale comparative studies that are needed in this field.”
Kaufmann’s research looks at the genetic changes in skin cells brought about by ultraviolet radiation. Radiation damage, often triggered by something as common as sunburn, is a known risk factor in developing melanoma. Researchers know that prolonged or extreme exposure to radiation can trigger protein interactions that change the structure and function of skin cells. If they can zero in on the genes involved in these interactions, they will be a step closer to developing more effective strategies for prevention and treatment of melanoma.
“The sophisticated computational tools being generated at RENCI will provide us with the ability to rapidly monitor the system of response to DNA damage, which is known to suppress the development of cancer and is often a target of chemotherapy,” said Kaufman. “By comparing the system in normal and malignant melanocytes, we will be able to identify the molecular changes in cells that underlie development of the disease and that make melanomas resistant to standard chemotherapy.”
With funding from the National Center for Supercomputing Applications (NCSA) at the University of Illinois, the RENCI group is developing software that will allow the researchers to merge data obtained from their own research subjects and from databases distributed over the Internet into one unified format, a process called data federation. Guan also is incorporating Cytoscape, an open source visualization tool, into the new set of research tools. Cytoscape is a collaborative project of the Institute for Systems Biology, the University of California at San Diego, Memorial Sloan-Kettering Cancer Center and the Institut Pasteur.
Once the RENCI team develops a way to merge and visualize the data, the researchers will be able to take advantage of a suite of data mining tools developed at NCSA called Data to Knowledge (D2K). D2K can perform a wide range of data analysis functions, from sifting through the “noise” in large datasets to find meaningful patterns to showing correlations to developing predictive models. According to Guan, the RENCI software developed for Kaufmann’s group will be the prototype for a toolkit that in time will be made available to research teams worldwide to help them integrate and visualize data.
“This project is a good example of what RENCI is all about,” said Dr. Daniel A. Reed, director of the institute. “We bring together people who can benefit from cross-disciplinary collaborations. In this case at RENCI, the Carolina medical school and NCSA to solve problems that couldn’t be resolved by one group working alone. The end result, we hope, is real progress in the effort to understand and treat a serious disease.”
