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Los Alamos simulation tests innovative cancer treatment approach

More than 30 percent of human cancers have mutations in a small, specific group of genes, but attempts to design drugs specifically for these cancers have been unsuccessful.
July 25, 2018
Rule-based model of RAS-to-ERK cascad

Rule-based model of RAS-to-ERK cascade.

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More than 30 percent of human cancers have mutations in a small, specific group of genes, but attempts to design drugs specifically for these cancers have been unsuccessful.

Known as Ras genes, named for the specific protein family called Rat Sarcoma, for which the genes code, the Ras-regulated signal pathways control such processes as actin cytoskeletal integrity, cell proliferation, cell differentiation, cell adhesion, apoptosis and cell migration.

There are drugs available that target a similar protein, Raf, from Rapidly Accelerated Fibrosarcoma, which is in the same signaling pathway as Ras. Unfortunately these drugs (called RAF inhibitors) are ineffective in Ras-mutant tumors, and even RAF-mutant tumors quickly develop resistance to RAF inhibitors.

The international collaboration’s aim was to identify combinations of RAF inhibitors that would be able to effectively treat both Ras- and RAF-mutant tumors.

They built a mathematical model of the RAS signaling pathway using BioNetGen, a rule-based modeling language that was developed at LANL. Using this model, they could simulate treatment of diverse cell types with different types of RAF inhibitors.

The simulations predicted that specific combinations of inhibitors would have a synergistic effect, where the drug combination is stronger than expected (e.g., 1+1 = 3). The best pairing of drugs, which combined a Type II and a Type I 1/2 RAF inhibitor, was synergistic in cell lines with RAS mutation, RAF mutation, or both.

“We tested the model predictions in experiments with melanoma cell lines, and confirmed the the combinations were synergistic,” said Keesha Erickson, a Los Alamos researcher on the project. The Type II + Type I 1/2 drug combinations were able to markedly inhibit signaling through the pathway and dramatically reduce cancer cell growth.

These findings are interesting, she said, because a typical drug combination strategy is to use two drugs with different targets to impair tumor growth. “Here, we are actually recommending to hit the same target (RAF), but with two different drugs. This works because different types of RAF inhibitor recognize different conformations of RAF. The Type II RAF inhibitor binds strongly to RAF in one conformation, while the Type I 1/2 drug binds RAF when it is in a different conformation. Together, these drugs can better inhibit RAF than with either single drug alone, since more possible conformations are recognized by the pair of drugs.”

“The next step is to test these drug combinations in xenograft experiments. Potential collaborations at the National Cancer Institute could be an important step before these combinations could be evaluated in clinical trials, and hopefully eventually help a large proportion of cancer patients,” Erickson said.

The Paper: Dissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling, Cell Systems, DOI: https://doi.org/10.1016/j.cels.2018.06.002

Authors:
Oleksii S. Rukhlenko, Systems Biology Ireland, University College Dublin
Fahimeh Khorsand, Systems Biology Ireland, University College Dublin
Aleksandar Krstic, Systems Biology Ireland, University College Dublin
Jan Rozanc, University of Luxembourg, Luxembourg, ProtATonce Ltd, Athens, Greece Leonidas G. AlexopoulosUniversity of Luxembourg, Luxembourg, ProtATonce Ltd, Athens, Greece
Nora Rauch, Systems Biology Ireland, University College Dublin
Keesha E. Erickson, Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos
William S. Hlavacek, Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory
Richard G. Posner, Department of Biological Sciences, Northern Arizona University
Silvia Gómez-Coca, Department of Chemistry, King's College London
Edina Rosta, Department of Chemistry, King's College London
Cheree Fitzgibbon, Systems Biology Ireland, University College Dublin
David Matallanas, Systems Biology Ireland, University College Dublin
Jens Rauch, Systems Biology Ireland, University College Dublin
Walter Kolch, Systems Biology Ireland, University College Dublin; Conway Institute of Biomolecular & Biomedical Research, University College Dublin; School of Medicine and Medical Science, University College Dublin
Boris N. Kholodenko, Systems Biology Ireland, University College Dublin; Conway Institute of Biomolecular & Biomedical Research, University College Dublin; School of Medicine and Medical Science, University College Dublin; Department of Pharmacology, Yale University School of Medicine