A novel computational method developed by the computational genomics group at Barcelona Supercomputing Center (BSC) represents a big leap forward for cancer research as well as genome analysis.
As detailed in the official announcement and the current issue of Nature Biotechnology, SMUFIN – short for Somatic Mutations Finder – pinpoints the genetic alterations responsible for the formation and progression of tumors simply, quickly and precisely. A tumor’s complete genome as well as its mutations can be determined in just a few hours. SMUFIN also goes further than previous solutions, revealing hard-to-detect genetic alterations in aggressive tumors that other tools missed, even when they used weeks of supercomputing cycles.
“This new method is a realistic step towards personalized medicine, in which the genome analysis of each patient will aid diagnosis and allow the selection of treatments which are more effective and less invasive,” notes the BSC release. “SMUFIN represents a new way of analyzing genomes which could also be applied to the study of the genetics underlying many other illnesses prevalent in our society.”
SMUFIN works differently than previous tools that compared genomes taken from the tumor with genomes obtained from healthy cells from the same patient, using a reference human genome as a guide. That was a time-consuming and complex process that did not always have a high degree of success. It also required different computer programs to be used in succession because each one was limited in what it could identify. SMUFIN makes a direct comparison between the genomes of healthy and tumor cells taken from the patient, revealing the location of almost all types of mutations very quickly using one program.
When SMUFIN is used by supercomputing centers, it can identify the mutations of hundreds or thousands of cancer genomes in a few days. This has tremendous implications for cancer research projects such as the global cancer genome initiative. Part of the International Cancer Genome Consortium (ICGC), the effort amasses genome data from thousands of cancer patients so that researchers can assemble profiles for different tumor types.