Hypoxia-selective targeting by the bioreductive prodrug AQ4N in patients with solid tumors: results of a phase 1 study

NoPURPOSE: AQ4N is a novel bioreductive prodrug under clinical investigation. Preclinical evidence shows that AQ4N penetrates deeply within tumors and undergoes selective activation to form AQ4, a potent topoisomerase II inhibitor, in hypoxic regions of solid tumors. This proof-of-principle, phase I study evaluated the activation, hypoxic selectivity, and safety of AQ4N in patients with advanced solid tumors. EXPERIMENTAL DESIGN: Thirty-two patients with cancer (8 glioblastoma, 9 bladder, 8 head and neck, 6 breast, and 1 cervix) received a single 200 mg/m(2) dose of AQ4N before elective surgery. AQ4 and AQ4N levels in 95 tissues (tumor, healthy tissue) were assessed by liquid chromatography-tandem mass spectrometry. Tissue sections were also analyzed for AQ4 fluorescence using confocal microscopy, and for expression of the hypoxia-regulated glucose transporter, Glut-1. RESULTS: Activated AQ4 was detected in all tumor samples with highest levels present in glioblastoma (mean 1.2 microg/g) and head and neck (mean 0.65 microg/g) tumors; 22 of 32 patients had tumor AQ4 concentrations > or = 0.2 microg/g, levels previously shown to be active in preclinical studies. In 24 of 30 tumor samples, AQ4 was detected at higher concentrations than in adjacent normal tissue (tumor to normal ratio range 1.1-63.6); distant skin samples contained very low concentrations of AQ4 (mean 0.037 microg/g). Microscopic evaluation of tumor sections revealed that AQ4 colocalized within regions of Glut-1+ hypoxic cells. CONCLUSIONS: AQ4N was activated selectively in hypoxic regions in human solid tumors. Intratumoral concentrations of AQ4 exceeded those required for activity in animal models and support the evaluation of AQ4N as a novel tumor-targeting agent in future clinical studies

Accuracy of resource selection functions across spatial scales

International audienceResource selection functions (RSFs) can be used to map suitable habitat of a species based on predicted probability of use. The spatial scale may affect accuracy of such predictions. To provide guidance as to which spatial extent or grain is appropriate and most accurate for animals, we used the concept of hierarchical selection orders to dictate extent and grain. We conducted a meta-analysis from 123 RSF studies of 886 species to identify differences in prediction success that might be expected for five selection orders. Many studies do not constrain spatial extent to the grain of the next broader selection order in the hierarchy, mixing scaling effects. Thus, we also compared accuracy of single- vs. multiple-grain RSFs developed at the unconstrained extent of an entire study area. Results suggested that the geographical range of a species was the easiest to predict of the selection orders. At smaller scales within the geographical range, use of a site was easier to predict when environmental variables were measured at a grain equivalent to the home-range size or a microhabitat feature required for reproduction or resting. Selection of patches within home ranges and locations of populations was often more difficult to predict. Multiple-grain RSFs were more predictive than single-grain RSFs when the entire study area was considered available. Models with variables measured at both small and large (> 100 ha) grains were usually most predictive, even for many species with small home ranges. Multiple-grain models may be particularly important for species with moderate dispersal abilities in habitat fragments surrounded by an unsuitable matrix. We recommend studies should no longer address only one grain to map animal species distributions