By developing advanced algorithms to integrate data from quantitative mass-spectrometry and next generation sequencing of tumor samples, the scientists at the Linding Lab within the BRIC at the University of Copenhagen, have been able to uncover cancer related changes to phospho-signaling networks at a global scale.
The studies are some of the early results of the strategic collaboration between SGI and the Linding Lab at UCPH, and the landmark findings have been published in two back-to-back papers in Cell journal.
Since the human genome was sequenced more than a decade ago, cancer genomics studies have dominated the life sciences worldwide and have been extremely successful at identifying mutations in individual patients and tumors. However, using this knowledge to develop improved cancer therapies has been severely hampered by the inability of researchers to explain and relate this data to proteins: the targets of most pharmaceutical drugs.
"This new breakthrough allows researchers to identify the effects of mutations on the function of proteins in cancer for individual patients, even if those mutations are very rare," said Professor Dr. Rune Linding, lead researcher on the projects from the BRIC.
"The identification of distinct changes within our tissues that help predict and treat cancer is a major step forward and we are confident it can aid in the development of novel therapies and screening techniques.
“In these studies we simulated more than 2.5 million different computer models to find the optimal parameters to interpret cancer genomes. This is a vast computational and big data challenge that requires an extreme degree of computational flexibility.
"There is going to be more and more data available to us, and as scientists trying to lower the cancer burden, technology like SGI's UV system can make sense of all this data. This technology is a real game changer and these findings are a significant discovery from life sciences using a supercomputer, which we hope will make a difference for cancer patients world-wide."
SGI president and CEO, Jorge Titinger, said the studies highlight the importance of big data in cancer biology and underpin the essentiality of large dynamic-range computing platforms such as the SGI UV - SGI's UV server platform offers unique capabilities for research computing, well beyond what is commonly possible with commodity computing hardware. The SGI UV line combines industry-leading shared-memory designs with unmatched data performance capabilities, making it the ideal choice for big data research workflows.
"Thanks to the power of the technology in our supercomputers, SGI supports a broad range of fascinating and history-making research projects that will leave a strong mark in the life sciences and on the medical science community," Titinger said.
"We are honored to be a part of such a monumental research program and are looking forward to continuing to provide the computing power the Linding Lab requires to dive deeper into understanding cancer through genomic research."