Design and characterization of α-melanotropin peptide analogs cyclized through rhenium and technetium metal coordination

α-Melanocyte stimulating hormone (α-MSH) analogs, cyclized through site-specific rhenium (Re) and technetium (Tc) metal coordination, were structurally characterized and analyzed for their abilities to bind α-MSH receptors present on melanoma cells and in tumor-bearing mice. Results from receptor-binding assays conducted with B16 F1 murine melanoma cells indicated that receptor-binding affinity was reduced to approximately 1% of its original levels after Re incorporation into the cyclic Cys4,10, d-Phe7–α-MSH4-13 analog. Structural analysis of the Re–peptide complex showed that the disulfide bond of the original peptide was replaced by thiolate–metal–thiolate cyclization. A comparison of the metal-bound and metal-free structures indicated that metal complexation dramatically altered the structure of the receptor-binding core sequence. Redesign of the metal binding site resulted in a second-generation Re–peptide complex (ReCCMSH) that displayed a receptor-binding affinity of 2.9 nM, 25-fold higher than the initial Re–α-MSH analog. Characterization of the second-generation Re–peptide complex indicated that the peptide was still cyclized through Re coordination, but the structure of the receptor-binding sequence was no longer constrained. The corresponding 99mTc- and 188ReCCMSH complexes were synthesized and shown to be stable in phosphate-buffered saline and to challenges from diethylenetriaminepentaacetic acid (DTPA) and free cysteine. In vivo, the 99mTcCCMSH complex exhibited significant tumor uptake and retention and was effective in imaging melanoma in a murine-tumor model system. Cyclization of α-MSH analogs via 99mTc and 188Re yields chemically stable and biologically active molecules with potential melanoma-imaging and therapeutic properties.

Radiometal labeling of recombinant proteins by a genetically engineered minimal chelation site: technetium-99m coordination by single-chain Fv antibody fusion proteins through a C-terminal cysteinyl peptide.

We describe a method to facilitate radioimaging with technetium-99m (99mTc) by genetic incorporation of a 99mTc chelation site in recombinant single-chain Fv (sFv) antibody proteins. This method relies on fusion of the sFv C terminus with a Gly4Cys peptide that specifically coordinates 99mTc. By using analogues of the 26-10 anti-digoxin sFv as our primary model, we find that addition of the chelate peptide, to form 26-10-1 sFv', does not alter the antigen-binding affinity of sFv. We have demonstrated nearly quantitative chelation of 0.5-50 mCi of 99mTc per mg of 26-10-1 sFv' (1 Ci = 37 GBq). These 99mTc-labeled sFv' complexes are highly stable to challenge with saline buffers, plasma, or diethylenetriaminepentaacetic acid. We find that the 99mTc-labeled 741F8-1 sFv', specific for the c-erbB-2 tumor-associated antigen, is effective in imaging human ovarian carcinoma in a scid mouse tumor xenograft model. This fusion chelate methodology should be applicable to diagnostic imaging with 99mTc and radioimmunotherapy with 186Re or 188Re, and its use could extend beyond the sFv' to other engineered antibodies, recombinant proteins, and synthetic peptides.

In vivo detection and imaging of phosphatidylserine expression during programmed cell death

One of the earliest events in programmed cell death is the externalization of phosphatidylserine, a membrane phospholipid normally restricted to the inner leaflet of the lipid bilayer. Annexin V, an endogenous human protein with a high affinity for membrane bound phosphatidylserine, can be used in vitro to detect apoptosis before other well described morphologic or nuclear changes associated with programmed cell death. We tested the ability of exogenously administered radiolabeled annexin V to concentrate at sites of apoptotic cell death in vivo. After derivatization with hydrazinonicotinamide, annexin V was radiolabeled with technetium 99m. In vivo localization of technetium 99m hydrazinonicotinamide-annexin V was tested in three models: fuminant hepatic apoptosis induced by anti-Fas antibody injection in BALB/c mice; acute rejection in ACI rats with transplanted heterotopic PVG cardiac allografts; and cyclophosphamide treatment of transplanted 38C13 murine B cell lymphomas. External radionuclide imaging showed a two- to sixfold increase in the uptake of radiolabeled annexin V at sites of apoptosis in all three models. Immunohistochemical staining of cardiac allografts for exogenously administered annexin V revealed intense staining of numerous myocytes at the periphery of mononuclear infiltrates of which only a few demonstrated positive apoptotic nuclei by the terminal deoxynucleotidyltransferase-mediated UTP end labeling method. These results suggest that radiolabeled annexin V can be used in vivo as a noninvasive means to detect and serially image tissues and organs undergoing programmed cell death.

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.