Gregory Z. Ferl

Bruton's tyrosine kinase (Btk) acts downstream of phosphoinositide 3-kinase (PI3K) in a pathway required for B cell receptor (BCR)-dependent proliferation. We used DNA microarrays to determine what fraction of genes this pathway influences and to investigate whether PI3K and Btk mediate distinct gene regulation events. As complete loss-of-function mutations in PI3K and Btk alter B cell subpopulations and may cause compensatory changes in gene expression, we used B cells with partial loss of function in either PI3K or Btk. Only about 5% of the BCR-dependent gene expression changes were significantly affected by reduced PI3K or Btk. The results indicate that PI3K and Btk share target genes, and that PI3K influences additional genes independently of Btk. These data are consistent with PI3K acting through Btk and other effectors to regulate expression of a critical subset of BCR target genes that determine effective entry into the cell cycle.

UNLABELLED: Derivation of the plasma time-activity curve in murine small-animal PET studies is a challenging task when tracers that are sequestered by the myocardium are used, because plasma time-activity curve estimation usually involves drawing a region of interest within the area of the reconstructed image that corresponds to the left ventricle (LV) of the heart. The small size of the LV relative to the resolution of the small-animal PET system, coupled with spillover effects from adjacent myocardial pixels, makes this method reliable only for the earliest frames of the scan. We sought to develop a method for plasma time-activity curve estimation based on a model of tracer kinetics in blood, muscle, and liver. METHODS: Sixteen C57BL/6 mice were injected with (18)F-FDG, and approximately 15 serial blood samples were taken from the femoral artery via a surgically inserted catheter during 60-min small-animal PET scans. Image data were reconstructed by use of filtered backprojection with CT-based attenuation correction. We constructed a 5-compartment model designed to predict the plasma time-activity curve of (18)F-FDG by use of data from a minimum of 2 blood samples and the dynamic small-animal PET scan. The plasma time-activity curve (TACp) was assumed to have 4 exponential components (TAC(P)=A(1)e(lambda(1)t)+A(2)e(lambda(2)t)+A(3)e(lambda(3)t)-(A(1)+A(2)+A(3))e(lambda(4)t)) based on the serial blood samples. Using Bayesian constraints, we fitted 2-compartment submodels of muscle and liver to small-animal PET data for these organs and simultaneously fitted the input (forcing) function to early small-animal PET LV data and 2 blood samples (approximately 10 min and approximately 1 h). RESULTS: The area under the estimated plasma time-activity curve had an overall Spearman correlation of 0.99 when compared with the area under the gold standard plasma time-activity curve calculated from multiple blood samples. Calculated organ uptake rates (Patlak K(i)) based on the predicted plasma time-activity curve had a correlation of approximately 0.99 for liver, muscle, myocardium, and brain when compared with those based on the gold standard plasma time-activity curve. The model was also able to accurately predict the plasma time-activity curve under experimental conditions that resulted in different rates of clearance of the tracer from blood. CONCLUSION: We have developed a robust method for accurately estimating the plasma time-activity curve of (18)F-FDG by use of dynamic small-animal PET data and 2 blood samples.

Monoclonal antibodies (mAb) are being used at an increasing rate in the treatment of cancer, with current efforts focused on developing engineered antibodies that exhibit optimal biodistribution profiles for imaging and/or radioimmunotherapy. We recently developed the single-chain Fv-Fc (scFv-Fc) mAb, which consists of a single-chain antibody Fv fragment (light-chain and heavy-chain variable domains) coupled to the IgG1 Fc region. Point mutations that attenuate binding affinity to FcRn were introduced into the Fc region of the wild-type scFv-Fc mAb, resulting in several new antibodies, each with a different half-life. Here, we describe the construction of a two-tiered physiologically based pharmacokinetic model capable of simulating the apparent biodistribution of both (111)In- and (125)I-labeled scFv-Fc mAbs, where (111)In-labeled metabolites from degraded (111)In-labeled mAbs tend to become trapped within the lysosomal compartment, whereas free (125)I from degraded (125)I-labeled mAbs is quickly eliminated via the urinary pathway. The different concentration-time profiles of (111)In- and (125)I-labeled mAbs permits estimation of the degradation capacity of each organ and elucidates the dependence of cumulative degradation in liver, muscle, and skin on FcRn affinity and tumor mass. Liver is estimated to account for approximately 50% of all degraded mAb when tumor is small (approximately 0.1 g) and drops to about 35% when tumor mass is larger (approximately 0.3 g). mAb degradation in residual carcass (primarily skin and muscle) decreases from approximately 45% to 16% as FcRn affinity of the three mAb variants under consideration increases. In addition, elimination of a small amount of mAb in the kidneys is shown to be required for a successful fit of model to data.