Skip to main content
An official website of the United States government

Modeling Treatments for Ras and Raf Cancers

, by Boris Kholodenko

Boris Kholodenko, Ph.D.

Trained as a biophysicist, Boris Kholodenko did postdoctoral training with A. Zhabotinsky (known for the oscillatory Belousov-Zhabotinsky reaction). His career has focused on mathematical and experimental analysis of biological networks. Together with Walter Kolch he now co-directs Systems Biology Ireland (SBI) at University College Dublin.

Mutations in the first two proteins of the MAP kinase pathway, Ras and its downstream effector Raf, drive millions of cases of human cancer each year. Ras proteins (K-Ras, H-Ras, and N-Ras) are small GTPases that signal through effectors when they are in the GTP-bound state, but decades of effort to target mutant Ras proteins directly have not resulted in any approved drugs. The Raf proteins A-Raf, B-Raf, and C-Raf however are kinases and are much more amenable to inhibition by small molecules. Early on there was much optimism that Raf inhibitors would be effective treatments for not only mutant Raf cancers (melanomas, thyroid and ovarian cancers) but also cancers driven by mutant Ras (pancreatic, colon, lung, bladder, leukemia, melanoma). Unfortunately Raf inhibitors have failed to help patients with Ras cancers, and patients with mutant Raf cancers that respond initially inevitably develop resistance.

Understanding these failures has led to a much deeper appreciation of the complexities of MAPK (Ras -> Raf -> Mek -> Erk) signaling and the mechanisms of Raf kinase activation (Durrant and Morrison, 2017). The lack of response of Ras-mutant melanomas to clinically-used Raf inhibitors is related to the increase in homo- and heterodimerization of Raf kinases, which is driven by oncogenic Ras and also leads to the paradoxical activation of ERK signaling by Raf inhibitors. For melanomas carrying wild type Ras and mutant BRafV600E, Raf inhibitors such as dabrafenib and vemurafenib, often given in combination with MEK inhibitors such as trametinib, result in a good initial response. Unfortunately, resistance inevitably develops, in most cases driven by the increase in Raf homo- and hetero-dimerization or by acquisition of oncogenic Ras mutations.

Drug resistance and thermodynamic principles

We have now gained insights into how to overcome the drug resistance caused by kinase dimerization through mathematical modeling. It appears that the resistance of Raf dimers to drugs is consistent with fundamental thermodynamic principles (Kholodenko, 2015). Mutant Ras and current clinically used Raf inhibitors induce Raf dimers, in which the protomers acquire different conformations (Jambrina et al., 2016). In this constellation one protomer is drug bound and allosterically activates the other drug-free protomer, conferring resistance. Overcoming this enhanced Raf dimerization, especially in Ras-mutant cancers, and the resulting resistance is a challenge for drug design. For instance, paradox breaker Raf inhibitors that do not increase Raf dimerization have been developed, yet they do not inhibit Raf dimers (Zhang, C. et al., 2015; Karoulia et al., 2016). All other Raf inhibitors that are able to inhibit Raf dimers also induce paradoxical ERK activation at some doses. Exploiting thermodynamic principles, we showed how two Raf inhibitors, ineffective on their own, can inhibit Raf homo- or heterodimers when combined at lower doses than either inhibitor applied alone (Kholodenko, 2015).

Mechanistic models to predict ways to effectively inhibit oncogenic Ras-driven MAPK signaling, while disabling or delaying signal recovery, growth, and drug resistance, have to account for both i) conformational selectivity of kinase inhibitors – affecting structural, thermodynamic and kinetic properties of Raf/MEK/ERK kinases; and ii) emergent network properties determined by cell-specific protein levels, mutations, and regulatory loops. Our team has developed a mathematical model that integrates the protein-protein interaction and network architectures of melanomas, and also includes the thermodynamics and kinetics of drug-protein interactions, spontaneous intra-molecular motions of proteins, structural conformations of the protein targets and inhibitors, and post-translational modifications of the signaling molecules (Rukhlenko et al., 2018). By taking into account conformational preferences of inhibitors (stabilization of active, inactive, or distorted kinase conformations) and their thermodynamic and kinetic properties, this model demonstrates a number of unexpected features of network responses to different types of Raf inhibitors. For individual protein-abundance and mutational profiles, the model predicted and experiments corroborated synergistic combinations of conformation-selective Raf inhibitors, which effectively suppressed not only oncogenic Raf, but also oncogenic Ras signaling, cancer cell proliferation and focus formation.

We suggest that targeting an enzyme with two structurally different small molecule inhibitors that bind to the same pocket in the target can be a new widely applicable strategy to overcome resistance induced by enzyme dimerization or oligomerization. We also present an approach to develop mathematical models to optimize drug combinations for each case. For example, our computational models and experiments predict synergy between different conformation-selective ERBB inhibitors in HER2-positive breast cancer cells, and different conformation-selective JAK inhibitors in IL7R-mutant T-cell acute lymphoblastic leukemia cells. The theoretical and experimental data also suggest novel potential treatment options for RASopathies (developmental disorders caused by germline mutations in the components of the Ras/Raf/MEK/ERK pathway). Modeling predicts inhibitor doses that would modulate the ERK pathway activity while minimizing toxicity. Finally, populating next-generation mechanistic models with specific cellular protein abundance and mutational profiles, information about conformation selective inhibitors, and mechanisms of emerging resistance to single drugs, will allow researchers to model and understand how to target other Ras-mutant cancers, such as pancreatic cancer.

Selected References
  1. Durrant DE, Morrison DK, 2018. Targeting the Raf kinases in human cancer: the Raf dimer dilemma. Br J Cancer

    [PubMed Abstract]
  2. Jambrina PG, et al., 2016. Phosphorylation of RAF Kinase Dimers Drives Conformational Changes that Facilitate Transactivation. Angew Chem Int Ed Engl

    [PubMed Abstract]
  3. Karoulia Z, et al., 2016. An Integrated Model of RAF Inhibitor Action Predicts Inhibitor Activity against Oncogenic BRAF Signaling. Cancer Cell

    [PubMed Abstract]
  4. Kholodenko BN, 2015. Drug Resistance Resulting from Kinase Dimerization Is Rationalized by Thermodynamic Factors Describing Allosteric Inhibitor Effects. Cell Reports

    [PubMed Abstract]
  5. Rukhlenko OS, et al., 2018. Dissecting RAF Inhibitor Resistance by Structure-based Modeling Reveals Ways to Overcome Oncogenic RAS Signaling. Cell Systems

    [PubMed Abstract]
  6. Zhang C, et al., 2015. RAF inhibitors that evade paradoxical MAPK pathway activation. Nature

    [PubMed Abstract]
< Older Post

The Stroma of Pancreatic Cancer Supports Proliferation of Tumor Cells

Newer Post >

Covalent Inhibitors of RAS