Downregulating ER-α expression may be a potential treatment regimen for cervical cancer patients and will be of great significance for patients with cervical cancer who are receiving conventional treatment for nonsurgical treatments.

Background: rLj-RGD3, a new member of RGD-motif toxin protein family derived from Lampetra japonica by means of DNA recombinant technique, has been demonstrated to be a platelet fibrinogen receptor antagonist. Researches over the years have shown that rLj-RGD3 has great value in developing as a useful antithrombotic and antitumor agent. Therefore, the study of pharmacokinetics is essential, so its quantification in plasma becomes a prerequisite. The present article aims to report a validated highly sensitive and specific double sandwich biotin-avidin enzyme linked immunosorbent assay (BA-ELISA) in order to provide a bio-analytical method for its pharmacokinetic (PK) study. Results: The concentration of rLj-RGD3 in rat plasma was measured at a picogram level by the developed BA-ELISA method, which used two different mouse anti-rLj-RGD3 monoclonal antibodies as capture antibody and detection antibody, respectively, directed at different epitopes. The method was validated to be highly specific (no interference with the detection from blank plasma), precise (within day and between day RSD <10%) and accurate (94%-104%). The absolute recovery was as high as 94%-105%. The calibration curve showed good linearity ranging from 50 to 1600 pg/mL with regression equation of Y = 0.0011X + 0.0328 (r2 = 0.9981), the LOQ was found to be as low as 50 pg/mL. The above validated assay was successfully employed for the assessment of PK disposition of rLj-RGD3 in rats. After i.v. and s.c. dosing 30 µg/kg the rLj-RGD3 plasma concentration declined biexponentially with time, which could be best fitted by the two-compartment model. The drug PK behavior could be characterized by rapid elimination, extensive metabolism and low s.c. bioavailability. Conclusions: The BA-ELISA method reported here was proved to completely meet requirements for PK study of rLj-RGD3, a toxin protein with effective pharmacological dose at µg/kg BW level.

As a step toward understanding complex spatial distribution patterns of prostate cancers, a three-dimensional (3D) master model of the prostate, showing major anatomical structures and probability maps of the location of tumors, has been pilot developed. A virtual environment supported by the 3D master model and in vivo imaging features, will be used to evaluate, simulate, and optimize the image guided needle biopsy and radiation therapy, thus potentiaLly improving the efficacy of prostate cancer diagnosis, staging, and treatment. A deformable graphics algorithm has been developed to reconstruct the graphics models from 200 serially sectioned whole mount radical prostatectomy specimens and to support computerized needle biopsy simulations. For the construction of a generic model, a principal-axes 3D registration technique (single and/or multiple objects) has been developed. Simulated evaluation and real data experiment have shown the satisfactory performance of the method in constructing initial generic model with localized prostate cancer placement. For the construction of statistical model, a blended model registration technique is advanced to perform a non-linear warping of the individual model to the generic model so that the prostate cancer probability distribution maps can be accurately positioned. The method uses a spinesurface model and a linear elastic model to dynamically deform both the surface and volume where object re-slicing is required. For the interactive visualization of the 3D master model, four modes of data display are developed: (1) transparent rendering of the generic model, (2) overlayed rendering of cancer distributions, (3) stereo rendering, and ( 4) true volumetric display, and a model-to-image registration technique using synthetic image phantoms is under investigation. Preliminary results have shown that use of this master model allows correct understanding of prostate cancer distribution patterns and rational optimization of prostate biopsy and radiation therapy strategies.