Crizotinib-Resistant Mutants of EML4-ALK Identified Through an Accelerated Mutagenesis Screen

Activating gene rearrangements of anaplastic lymphoma kinase (ALK) have been identified as driver mutations in non-small-cell lung cancer, inflammatory myofibroblastic tumors, and other cancers. Crizotinib, a dual MET/ALK inhibitor, has demonstrated promising clinical activity in patients with non-small-cell lung cancer and inflammatory myofibroblastic tumors harboring ALK translocations. Inhibitors of driver kinases often elicit kinase domain mutations that confer resistance, and such mutations have been successfully predicted using in vitro mutagenesis screens. Here, this approach was used to discover an extensive set of ALK mutations that can confer resistance to crizotinib. Mutations at 16 residues were identified, structurally clustered into five regions around the kinase active site, which conferred varying degrees of resistance. The screen successfully predicted the L1196M, C1156Y, and F1174L mutations, recently identified in crizotinib-resistant patients. In separate studies, we demonstrated that crizotinib has relatively modest potency in ALK-positive non-small-cell lung cancer cell lines. A more potent ALK inhibitor, TAE684, maintained substantial activity against mutations that conferred resistance to crizotinib. Our study identifies multiple novel mutations in ALK that may confer clinical resistance to crizotinib, suggests that crizotinib's narrow selectivity window may underlie its susceptibility to such resistance and demonstrates that a more potent ALK inhibitor may be effective at overcoming resistance

INTERVAL ESTIMATION OF WEIBULL DISTRIBUTION BASED ON MODIFIED PIVOTAL VARIABLE METHOD (MT)

To solve the problems of complex calculation and weak applicability of the traditional interval estimation methods such as Weibull distribution with the different parameters, a simple interval estimation method suitable to the conditions of multi-parameters was proposed. Through the expression of Weibull distribution, the pivotal-variable obeying chi-square distribution was obtained and the degrees of freedom were modified. Combined with the point estimation results from maximum likelihood estimation and the empirical estimation shape parameter in the Weibull distribution, the interval estimation method of two parameters in Weibull distribution was established. The confidence of proposed interval estimation method was verified by Monte Carlo simulation, and the applicability of the method on different parameters was also analyzed. Furthermore, comparisons with the results computed from traditional least square and maximum likelihood estimation methods were carried out by using simulation. Simulation results indicated that the modified pivotal-variable method has simple calculation process and small deviation from predefined nominal confidence with the different parameters. Therefore, it can be concluded that proposed method executes the more effective estimation than the traditional methods

The Macrophage Scavenger Receptor SR-AI/II and Lung Defense against Pneumococci and Particles

The class A macrophage scavenger receptor SR-AI/II is implicated as a pattern recognition receptor for innate immunity, but its functional role in lung defense has not been studied. We used mice genetically deficient in SR-AI/II and their wild-type C57BL/6 counterparts to investigate the contribution of this receptor to defense against pneumococcal infection and inhaled particles. SR-AI/II deficiency caused impaired phagocytosis of fluorescent bacteria in vivo, diminished clearance of live bacteria from the lungs, and substantially increased pneumonic inflammation. Survival studies also showed increased mortality in SR-AI/II–deficient mice with pneumococcal lung infection. Similarly, after challenge of the airways with TiO2 particles, SR-AI/II–deficient mice showed increased proinflammatory cytokine levels in lung lavage fluid and a more pronounced neutrophilic inflammation. The data indicate that the lung macrophage class A scavenger receptor SR-AI/II contributes to innate defense against bacteria and inhaled particles