Clinical OMICS

JAN-FEB 2017

Healthcare magazine for research scientists, labs, pathologists, hospitals, cancer centers, physicians and biopharma companies providing news articles, expert interviews and videos about molecular diagnostics in precision medicine

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Page 4 of 47 January/February 2017 Clinical OMICs 3 News In Silico Insights Harnessing Bioinformatics to Find New Breast Cancer Drug Combinations Meghaan Ferreira, Contributing Editor C ancer research has progressed rap- idly over the last few decades, with a growing repertoire of drugs to fight the deadly disease. Despite advances, treatment resistance remains a prob- lem, particularly for treating solid tumors such as breast cancer. Drug combinations are one of the most effec- tive ways to fight back, and a group of scientists at the Institute for Research in Biomedicine (IRB) in Barcelona reportedthe successful use of" or "the use of" bioinformatics to uncover pre- viously untested pairs of breast cancer therapeutics. The study appeared in the journal Cancer Research. One way treatment resistance to cancer therapies occurs is when can- cer cells evade destruction by using alternative signaling routes. "What we realized within the literature and by attending talks is that one of the big problems of treatment relapse or resistance is crosstalk between path- ways," says Patrick Aloy, Ph.D., head of IRB's Structural Bioinformatics and Network Biology Lab, and a co-author of the study. To address this issue, Dr. Aloy's group used computational methods to quantify how well various drug com- binations could prevent the signalling crosstalk and increase treatment effi- cacy. " The basic idea behind all this work was to maximize the damage we were incurring to the signalling path- ways in cancer," Dr. Aloy explains. "Impeding this crosstalk or damaging signaling networks could be an effec- tive treatment for cancer." The researchers analyzed 64 breast cancer drugs in silico that were either currently in use or in clinical trials and discovered 390 novel drug com- binations. From these, they chose ten to test in vitro on human breast tumor cells and found high level of synergy in seven of those combinations. As a final step, the group vali- dated one of those pairs, the estro- gen response modifier raloxifene and the c-Met/VEGFR2 kinase inhibi- tor cabozantibib, in a mouse model of breast cancer. Though each drug reduced tumor size on its own, together the drugs had an additive effect, shrinking tumors by an impres- sive 60 percent. Remarkably, they saw this effect with much smaller doses of raloxifene and cabozantibib than used in current treatments, three and 25 times, respectively. "Raloxifene isn't a drug we think of as an excellent breast cancer drug […] so I think that combination sounds interesting, but we would have to really see whether there was clinical activity before coming to a conclusion on that," says Larissa Korde, M.D., an oncologist specializing in breast can- cer treatment research at the Univer- sity of Washington Medical Center. "I think the paper [used] a good strategy, although I would always say that it doesn't matter what happens in silico if it doesn't happen in reality," Dr. Korde adds. "Sometimes things (continued on next page) Patrick Aloy, Ph.D., of the Institute for Research in Biomedicine (IRB), Barcelona, Spain, led a team of researchers that employed bioinformatics approaches to uncover new drug combinations for the treatment of breast cancer. Institute for Research in Biomedicine (IRB)

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