Dr. Sol Efroni: Improving Cancer-Related Computation

When a patient is diagnosed with lung cancer, doctors typically examine murky X-ray or CT images to characterize its subtype. But what if it were possible to stratify lung cancer through the crystal clear means of mathematics? This was one question posed by the IMPROVER Diagnostics Signature Challenge, an international competition designed to assess computational approaches to classifying clinical samples.

With some 50 teams in the running, top honors went to BIU Dr. Sol Efroni and his PhD student Rotem Ben-Hamo, for their method of deriving clinically significant information from gene expression data. “Doctors need imaging to direct cancer surgery, but molecular methods are becoming ever more important for determining post-operative treatment,” says Efroni. “Our goal in this competition was to establish predictive ‘signatures’ based on unlabeled gene expression data from tissue samples, and to link a particular computational outcome with a specific tumor type and prognosis.”

Efroni, who joined BIU after completing his post-doc at the National Cancer Institute at the NIH in Maryland, as part of a cohort of retuning scientists BIU continues to bring back from abroad, reversing Israel’s brain drain, is a member of the Institute of Nanotechnology and Advanced Materials (BINA), and a senior lecturer at the Mina and Everard Goodman Faculty of Life Sciences.

Over the years, Efroni has contributed significantly to the field of systems biomedicine, having designed and implemented an approach now known as Reactive Animation that facilitates the visual, computer legible and intuitive simulation of complex multi agent systems through reactive technology of reactive animation. RA allows the experimenter to intervene mid-simulation, suggest new hypotheses for cellular and molecular interactions, apply them to the simulation and observe their resulting outcomes "on-line."

As head of BIU's Systems BioMedicine Lab, Efroni, who holds a PhD from the Weizmann Institute, also performs pioneering systems biology network analysis in order to identify and quantify the network-wide changes that occur during the development of malignant disease. His ultimate goal is to understand the cancer phenotype, in particular breast cancer, ovarian cancer, and liver cancer, and to identify targets for therapeutic intervention.

 “In systems biomedicine, we study not only the genes, but the networks of gene-regulated activity that drives disease,” he says. “We want to see how gene expression forms the basis of connected biological pathways that result in a particular outcome. These pathways, in turn, can point the way toward targeted therapy.” In order to promote research in this field, in 2013 Efroni has launched (and is Editor in Chief of) Systems Biomedicine – a peer-reviewed journal focusing on how the emerging field of systems biology can yield clinically relevant results.
For more on Dr. Efroni click here.