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Structure, Function, and Resistance in Chronic Myeloid Leukemia

Cancer Cell, 3, 26, pages 305 - 306

Refers to article:

BCR-ABL1 Compound Mutations Combining Key Kinase Domain Positions Confer Clinical Resistance to Ponatinib in Ph Chromosome-Positive Leukemia

Matthew S. Zabriskie, Christopher A. Eide, Srinivas K. Tantravahi, Nadeem A. Vellore, Johanna Estrada, Franck E. Nicolini, Hanna J. Khoury, Richard A. Larson, Marina Konopleva, Jorge E. Cortes, Hagop Kantarjian, Elias J. Jabbour, Steven M. Kornblau, Jeffrey H. Lipton, Delphine Rea, Leif Stenke, Gisela Barbany, Thoralf Lange, Juan-Carlos Hernández-Boluda, Gert J. Ossenkoppele, Richard D. Press, Charles Chuah, Stuart L. Goldberg, Meir Wetzler, Francois-Xavier Mahon, Gabriel Etienne, Michele Baccarani, Simona Soverini, Gianantonio Rosti, Philippe Rousselot, Ran Friedman, Marie Deininger, Kimberly R. Reynolds, William L. Heaton, Anna M. Eiring, Anthony D. Pomicter, Jamshid S. Khorashad, Todd W. Kelley, Riccardo Baron, Brian J. Druker, Michael W. Deininger and Thomas O’Hare

Received 10 March 2014, Revised 30 April 2014, Accepted 10 July 2014

Chronic myeloid leukemia (CML) is effectively treated by tyrosine kinase inhibitors (TKIs). Rarely, CML cases develop TKI resistance through acquisition of compound mutations. In this issue ofCancer Cell, Zabriskie and colleagues study how structural changes caused by compound mutations cause clinically relevant changes in TKI sensitivity.

Chronic myeloid leukemia (CML) is effectively treated by tyrosine kinase inhibitors (TKIs). Rarely, CML cases develop TKI resistance through acquisition of compound mutations. In this issue ofCancer Cell, Zabriskie and colleagues study how structural changes caused by compound mutations cause clinically relevant changes in TKI sensitivity.

Main Text

Chronic myeloid leukemia (CML) is a rare clonal myeloproliferative disease, occurring roughly in 2 of 100,000 persons, but it has dramatically shaped the world of molecular oncology and targeted therapy. CML was the first disease in which a unique chromosomal translocation, t(9;22), the so called “Philadelphia chromosome” (because it was discovered at the Winstar Institute in Philadelphia), was discovered. At the genetic level, it was established that the translocation resulted in theBCR-ABLchimeric gene; this unique and universal event (because all CML cases have the rearrangedBCR-ABL) then became a target for therapy and a sensitive marker for disease monitoring.

The aberrant activity of the tyrosine kinase ABL, when placed in the chimeric BCR-ABL context, drives the pathogenesis of CML. The development of tyrosine kinase inhibitors (TKIs) that inhibit ABL has dramatically altered the natural history of CML. Before TKIs, the median survival of newly diagnosed CML patients was roughly 5 years; with TKI therapy, the 10 year survival rate is >80% ( Druker et al., 2006 ). Indeed, the therapy is so effective that some patients become free of any detectable disease, and, in some patients, TKI therapy can be discontinued without relapse. The evolution of treatment strategies in CML in a little over a decade is nothing short of remarkable, and the success of TKI therapy is the benchmark against all other targeted therapy is judged.

There are several TKIs now in clinical use for treating CML. Nonetheless, some CML patients do become resistant to TKI therapy ( Apperley 2007 ). Often, TKI resistance is caused by single amino acid mutations in the ABL domain of the BCR-ABL, which changes the protein conformation to limit or exclude the TKI binding. Some of these point mutations have different sensitivities to different TKIs, for example, insensitive to imatinib but still sensitive to dasatinib. However, the T315I mutation is resistant across a broad range of TKIs and is only effectively inhibited by the recently Food and Drug Administration approved ponatinib, which has activity against all known single amino acid ABL mutations that are resistant to clinical TKIs (Cortes et al, 2012 and O’Hare et al, 2009).

As the Borg will ruefully acknowledge, resistance isnotfutile, and, in CML, the strong selective pressures of ponatinib have led to cases of resistance involving compound mutations in ABL (Khorashad et al, 2013 and Soverini et al, 2013). These are multiple point mutations occurring in the sameBCR-ABLallele, as opposed to multiple clones with different mutations. This phenomenon has been seen in other diseases treated with targeted therapy ( Smith et al., 2013 ) and may become an increasing common phenomenon as more cancers are treated with targeted therapy and tumors develop cleaver tactics to evade selective pressure. In this issue ofCancer Cell, Zabriskie et al. (2014) study a series of CML cases with compound mutations, and, in a series of logical, thoughtful, and well-executed experiments, build a solid understanding of how the structure and function of these mutations drive drug susceptibility and, ultimately, patient response to therapy.

The authors first surveyed the landscape of compound mutations to understand the patterns of mutations, because one would expect that only certain combination of mutations would cause sufficient structural change in BCR-ABL to prevent kinase inhibition by TKIs. While >100 different kinase point mutations have been reported, only 12 positions have been involved in the vast majority of compound mutations. The authors then looked at over 400 patients enrolled in a phase 2 trial of ponatinib for patients who were resistant or intolerant to the “second generation” TKIs dasatinib or nilotinib or had the resistant T315I mutation. Many of these patients had failed two different TKIs before being in the study, so their diseases had already passed through a rigid test of natural selection, thus enriching for complicated kinase dependent or independent mechanisms of resistance. Sixteen patients had compound mutations evident at the end of treatment (3 cases ended treatment because of toxicity, 13 from lack of efficacy of ponatinib), and, remarkably, the compound mutations involved at least 2 of the key positions in all but one case.

To further understand the relationship of compound mutations and sensitivity to TKIs, the authors then performed proliferation assays, comparing the growth of Ba/F3 cells expressing ectopic wild-type BCR-ABL to those expressing ectopic BCR-ABL containing a spectrum of single and compound mutations. While ponatinib inhibited the growth of cells expressing any single mutations (including the T315I), its effectiveness was greatly decreased in T315I-containing compound mutations. This was borne out in the experience of patients in the clinical trial, where patients whose CML had baselineBCR-ABLcompound mutations involving T315I or a baselineBCR-ABLT315I mutation and evolved a clone containing an additionalBCR-ABLmutation showed clinical resistance to ponatinib. However, 22 cases of compound mutations without T315I patterns of variable effectiveness was demonstrated across the panel of TKIs, which suggests that early detection of compound mutations could be combined with sensitivity studies to shape a therapeutic change in TKIs and thus abort the emergence of resistant clones.

Computer modeling suggested the impact of compound mutations on TKI activity. The proliferation studies noted above found that, for compound mutations not containing T315I, ponatinib and dasatinib had similar activities, except with the Y253H/E55V compound mutation, where dasatinib is considerably more active. The binding sites of ponatinib and dasatinib are known to be different; can modeling explain the difference? Indeed, it can; molecular dynamic simulations showed that Y253H and E255V mutations force a shift in the P loop of the ABL kinase domain, obstructing the ponatinib binding site. Similar simulations suggested poor ponatinib activity in clinically relevant disease evolution, such as the difference in the binding domains of a single T315I and the resistant T315I/E255V mutation. Thus, the authors elegantly followed the interplay of structure, in vitro and in vivo function.

Why is this study important? First, it is a demonstration of how clinical material, wet bench work, and computer modeling can be melded to develop a clear understanding of clinically important biology. Second, it provides a clear roadmap of how future studies can be performed to understand disease resistance. As “targeted therapy” becomes an increasing reality in cancer care, it will become increasingly important to understand and anticipate how Darwinian selection will select for resistance. This manuscript helps prepare us for that future.


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1 Fred Hutchinson Cancer Research Center, Seattle, WA 98104, USA

Corresponding author