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Targeting ALK: Precision Medicine Takes on Drug Resistance.

ABSTRACT: Anaplastic lymphoma kinase (ALK) is a validated molecular target in several ALK-rearranged malignancies, including non-small cell lung cancer. However, the clinical benefit of targeting ALK using tyrosine kinase inhibitors (TKI) is almost universally limited by the emergence of drug resistance. Diverse mechanisms of resistance to ALK TKIs have now been discovered, and these basic mechanisms are informing the development of novel therapeutic strategies to overcome resistance in the clinic. In this review, we summarize the current successes and challenges of targeting ALK. SIGNIFICANCE:Effective long-term treatment of ALK-rearranged cancers requires a mechanistic understanding of resistance to ALK TKIs so that rational therapies can be selected to combat resistance. This review underscores the importance of serial biopsies in capturing the dynamic therapeutic vulnerabilities within a patient's tumor and offers a perspective into the complexity of on-target and off-target ALK TKI resistance mechanisms. Therapeutic strategies that can successfully overcome, and potentially prevent, these resistance mechanisms will have the greatest impact on patient outcome. Cancer Discov; 7(2); 137-55. ©2017 AACR.

SUBMITTER: Lin JJ

PROVIDER: S-EPMC5296241 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Targeting ALK: Precision Medicine Takes on Drug Resistance.

Lin Jessica J JJ Riely Gregory J GJ Shaw Alice T AT

Cancer discovery 20170125 2

Anaplastic lymphoma kinase (ALK) is a validated molecular target in several ALK-rearranged malignancies, including non-small cell lung cancer. However, the clinical benefit of targeting ALK using tyrosine kinase inhibitors (TKI) is almost universally limited by the emergence of drug resistance. Diverse mechanisms of resistance to ALK TKIs have now been discovered, and these basic mechanisms are informing the development of novel therapeutic strategies to overcome resistance in the clinic. In thi ...[more]

PMID: 28122866

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Project description:BackgroundAcute myeloid leukemia (AML) remains a devastating disease with a 5-year survival rate of less than 30%. AML treatment has undergone significant changes in recent years, incorporating novel targeted therapies along with improvements in allogeneic bone marrow transplantation techniques. However, the standard of care remains cytarabine and anthracyclines, and the primary hindrance towards curative treatment is the frequent emergence of intrinsic and acquired anticancer drug resistance. In this respect, patients presenting with chemoresistant AML face dismal prognosis even with most advanced therapies. Herein, we aimed to explore the potential implementation of the characterization of chemoresistance mechanisms in individual AML patients towards efficacious personalized medicine.MethodsTowards the identification of tailored treatments for individual patients, we herein present the cases of relapsed AML patients, and compare them to patients displaying durable remissions following the same chemotherapeutic induction treatment. We quantified the expression levels of specific genes mediating drug transport and metabolism, nucleotide biosynthesis, and apoptosis, in order to decipher the molecular mechanisms underlying intrinsic and/or acquired chemoresistance modalities in relapsed patients. This was achieved by real-time PCR using patient cDNA, and could be readily implemented in the clinical setting.ResultsThis analysis revealed pre-existing differences in gene expression levels between the relapsed patients and patients with lasting remissions, as well as drug-induced alterations at different relapse stages compared to diagnosis. Each of the relapsed patients displayed unique chemoresistance mechanisms following similar treatment protocols, which could have been missed in a large study aimed at identifying common drug resistance determinants.ConclusionsOur findings emphasize the need for standardized evaluation of key drug transport and metabolism genes as an integral component of routine AML management, thereby allowing for the selection of treatments of choice for individual patients. This approach could facilitate the design of efficacious personalized treatment regimens, thereby reducing relapse rates of therapy refractory disease.

Project description:BACKGROUND:Alectinib has shown a greater efficacy to ALK-rearranged non-small-cell lung cancers in first-line setting; however, most patients relapse due to acquired resistance, such as secondary mutations in ALK including I1171N and G1202R. Although ceritinib or lorlatinib was shown to be effective to these resistant mutants, further resistance often emerges due to ALK-compound mutations in relapse patients following the use of ceritinib or lorlatinib. However, the drug for overcoming resistance has not been established yet. METHODS:We established lorlatinib-resistant cells harboring ALK-I1171N or -G1202R compound mutations by performing ENU mutagenesis screening or using an in vivo mouse model. We performed drug screening to overcome the lorlatinib-resistant ALK-compound mutations. To evaluate these resistances in silico, we developed a modified computational molecular dynamic simulation (MP-CAFEE). FINDINGS:We identified 14 lorlatinib-resistant ALK-compound mutants, including several mutants that were recently discovered in lorlatinib-resistant patients. Some of these compound mutants were found to be sensitive to early generation ALK-TKIs and several BCR-ABL inhibitors. Using our original computational simulation, we succeeded in demonstrating a clear linear correlation between binding free energy and in vitro experimental IC50 value of several ALK-TKIs to single- or compound-mutated EML4-ALK expressing Ba/F3 cells and in recapitulating the tendency of the binding affinity reduction by double mutations found in this study. Computational simulation revealed that ALK-L1256F single mutant conferred resistance to lorlatinib but increased the sensitivity to alectinib. INTERPRETATION:We discovered lorlatinib-resistant multiple ALK-compound mutations and an L1256F single mutation as well as the potential therapeutic strategies for these ALK mutations. Our original computational simulation to calculate the binding affinity may be applicable for predicting resistant mutations and for overcoming drug resistance in silico. FUND: This work was mainly supported by MEXT/JSPS KAKENHI Grants and AMED Grants.

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Targeting ALK: Precision Medicine Takes on Drug Resistance.

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Targeting ALK: Precision Medicine Takes on Drug Resistance.

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