Thalidomide-like drugs such as lenalidomide are clinically important treatments for multiple myeloma and show promise for other B cell malignancies. The biochemical mechanisms underlying their antitumor activity are unknown. Thalidomide was recently shown to bind to, and inhibit, the cereblon ubiquitin ligase. Cereblon loss in zebrafish causes fin defects reminiscent of the limb defects seen in children exposed to thalidomide in utero. Here we show that lenalidomide-bound cereblon acquires the ability to target for proteasomal degradation two specific B cell transcription factors, Ikaros family zinc finger proteins 1 and 3 (IKZF1 and IKZF3). Analysis of myeloma cell lines revealed that loss of IKZF1 and IKZF3 is both necessary and sufficient for lenalidomide's therapeutic effect, suggesting that the antitumor and teratogenic activities of thalidomide-like drugs are dissociable.

The amount of genomic information about leukemia cells currently far exceeds our overall understanding of the precise genetic events that ultimately drive disease development and progression. Effective implementation of personalized medicine will require tools to distinguish actionable genetic alterations within the complex genetic landscape of leukemia. In this study, we performed kinase inhibitor screens to predict functional gene targets in primary specimens from patients with acute myeloid leukemia (AML) and chronic myelomonocytic leukemia (CMML). Deep sequencing of the same patient specimens identified genetic alterations that were then integrated with the functionally important targets using the HitWalker algorithm to prioritize the mutant genes that most likely explain the observed drug sensitivity patterns. Through this process, we identified Tyrosine Kinase Non-receptor 2 (TNK2) point mutations that exhibited oncogenic capacity. Importantly, the integration of functional and genomic data using HitWalker allowed for prioritization of rare oncogenic mutations that may have been missed through genomic analysis alone. These mutations were sensitive to the multi-kinase inhibitor dasatinib, which antagonizes TNK2 kinase activity, as well as novel TNK2 inhibitors, XMD8-87 and XMD16-5, with greater target specificity. We also identified activating truncation mutations in other tumor types that were sensitive to XMD8-87 and XMD16-5, exemplifying the potential utility of these compounds across tumor types dependent on TNK2. Collectively, our findings highlight a more sensitive approach for identifying actionable genomic lesions that may be infrequently mutated or overlooked, and provide a new method for the prioritization of candidate genetic mutations.

<p>Hitwalker diagram from CMML patient sample 10-210 (S1); EGFR binding domain of Tnk2 (S2).</p>

<div>Abstract<p>The amount of genomic information about leukemia cells currently far exceeds our overall understanding of the precise genetic events that ultimately drive disease development and progression. Effective implementation of personalized medicine will require tools to distinguish actionable genetic alterations within the complex genetic landscape of leukemia. In this study, we performed kinase inhibitor screens to predict functional gene targets in primary specimens from patients with acute myeloid leukemia and chronic myelomonocytic leukemia. Deep sequencing of the same patient specimens identified genetic alterations that were then integrated with the functionally important targets using the HitWalker algorithm to prioritize the mutant genes that most likely explain the observed drug sensitivity patterns. Through this process, we identified tyrosine kinase nonreceptor 2 (TNK2) point mutations that exhibited oncogenic capacity. Importantly, the integration of functional and genomic data using HitWalker allowed for prioritization of rare oncogenic mutations that may have been missed through genomic analysis alone. These mutations were sensitive to the multikinase inhibitor dasatinib, which antagonizes TNK2 kinase activity, as well as novel TNK2 inhibitors, XMD8-87 and XMD16-5, with greater target specificity. We also identified activating truncation mutations in other tumor types that were sensitive to XMD8-87 and XMD16-5, exemplifying the potential utility of these compounds across tumor types dependent on TNK2. Collectively, our findings highlight a more sensitive approach for identifying actionable genomic lesions that may be infrequently mutated or overlooked and provide a new method for the prioritization of candidate genetic mutations. <i>Cancer Res; 76(1); 127–38. ©2015 AACR</i>.</p></div>

<p>Hitwalker diagram from CMML patient sample 10-210 (S1); EGFR binding domain of Tnk2 (S2).</p>

<p>Enzymatic IC50 of potential targets for XMD8-87 and XMD16-5.</p>

<p>Enzymatic IC50 of potential targets for XMD8-87 and XMD16-5.</p>

<div>Abstract<p>The amount of genomic information about leukemia cells currently far exceeds our overall understanding of the precise genetic events that ultimately drive disease development and progression. Effective implementation of personalized medicine will require tools to distinguish actionable genetic alterations within the complex genetic landscape of leukemia. In this study, we performed kinase inhibitor screens to predict functional gene targets in primary specimens from patients with acute myeloid leukemia and chronic myelomonocytic leukemia. Deep sequencing of the same patient specimens identified genetic alterations that were then integrated with the functionally important targets using the HitWalker algorithm to prioritize the mutant genes that most likely explain the observed drug sensitivity patterns. Through this process, we identified tyrosine kinase nonreceptor 2 (TNK2) point mutations that exhibited oncogenic capacity. Importantly, the integration of functional and genomic data using HitWalker allowed for prioritization of rare oncogenic mutations that may have been missed through genomic analysis alone. These mutations were sensitive to the multikinase inhibitor dasatinib, which antagonizes TNK2 kinase activity, as well as novel TNK2 inhibitors, XMD8-87 and XMD16-5, with greater target specificity. We also identified activating truncation mutations in other tumor types that were sensitive to XMD8-87 and XMD16-5, exemplifying the potential utility of these compounds across tumor types dependent on TNK2. Collectively, our findings highlight a more sensitive approach for identifying actionable genomic lesions that may be infrequently mutated or overlooked and provide a new method for the prioritization of candidate genetic mutations. <i>Cancer Res; 76(1); 127–38. ©2015 AACR</i>.</p></div>