Bridging the Gap Between Preclinical and Clinical Evaluation of Therapeutic Candidates

Keynote Presentation

Cancer Biomarkers: Lessons from Kinase Inhibitors

Charles L. Sawyers, M.D.
Chair, Human Oncology and Pathogenesis Program (HOPP)
Memorial Sloan-Kettering Cancer Center

A central theme that has emerged from the clinical development of kinase inhibitors is the notion of “kinase-dependent” cancer, i.e. those cancers whose growth is driven by a specific kinase or set of kinases. By definition, such cancers should respond (shrink) when exposed to an inhibitor that effectively blocks the enzymatic activity of the responsible kinase. Based on current example, clinical sensitivity to a kinase inhibitor is highly likely if the tumor has a “driver” mutation in the gene encoding the target kinase that alters its biological potency. Discovery of such mutant kinases is a primary rationale for cancer genome resequencing efforts. Once discovered, these mutations can also serve as biomarkers for patient selection.

A growing issue complicating the success of kinase inhibitor therapy of cancer is acquired resistance, defined as disease relapse on continuous therapy after an initial response. First recognized as a significant problem initially in advanced stage CML patients, acquired resistance also occurs in chronic phase CML, GIST (gastrointestinal stromal tumors), HES (hypereosinophilia syndrome) and lung cancer. 85 percent of relapsed CML patients have mutations in the ABL kinase domain that alter drug sensitivity. 38 different ABL mutations have been reported to date. Curiously, only a small number of the mutations occur at contact residues. Rather, the majority occur at residues that appear, based on structural modeling studies, to alter the conformational flexibility of ABL such that it can no longer achieve the closed, inactive conformation required for optimal imatinib binding. These structural insights suggested that second generation ABL kinase inhibitors should bind in a less conformation-dependent fashion to retain activity against most imatinib-resistant mutants. This is the case with the dual SRC/ABL kinase inhibitor dasatinib (BMS-354825), which binds ABL in the active or inactive conformation and was recently approved for treatment of imatinib-resistant CML patients. We have also examined mechanisms of resistance to dasatinib in vitro and in patients treated on these trials. Unlike imatinib, resistance occurs almost exclusively through mutations at drug contact residues, presumably due to less conformation-stringent binding requirements. Some mutations confer resistance to dasatinib but not to imatinib; however, sequential treatment with ABL kinase inhibitors selected for compound mutants (two or more mutations in the same BCR-ABL mRNA) in many patients. Compound mutants limited the ability to respond to re-treatment with imatinib and, in some cases, enhanced the oncogenic fitness of BCR-ABL. These data provide evidence in favor of combination therapy with these two compounds for CML and have implications for other cancers such as GIST, HES and lung cancer where analogous kinase inhibitor resistance mechanisms have been described. Again, these kinase domain mutations have predictive value for patient response.

We are also learning that response to kinase inhibitors can be affected by factors in addition to mutations in the target kinase, such as mutations in other “modifier” genes that reduce kinase dependence. One example is the failure of glioblastoma patients with mutant EGFR (viii EGFR) to response to EGFR inhibitors if the tumor also contains a mutation in the PTEN tumor suppressor gene. Another variable is the blockade of negative feedback loops that can paradoxically lead to hyperactivation of a signaling pathway. This concept is best illustrated by treatment with mTOR inhibitors, which can cause increased activity of Akt in some tumors, and therefore may counteract the intended therapeutic effect. Similar to the problem of acquired resistance, these scenarios may also be solved through appropriately designed combination therapy. A broader implication is that patient-tailored kinase inhibitor therapy is likely to require evaluation of a suite of molecular variables for optimal predictive power.

References

1. Burgess, M. R., Skaggs, B. J., Shah, N. P., Lee, F. Y., and Sawyers, C. L. (2005). Comparative analysis of two clinically active BCR-ABL kinase inhibitors reveals the role of conformation-specific binding in resistance. Proc Natl Acad Sci U S A 102, 3395-3400.
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