Preclinical derivation and imaging of autologously transplanted canine induced pluripotent stem cells

Derivation of patient-specific induced pluripotent stem cells (iPSCs) opens a new avenue for future applications of regenerative medicine. However, before iPSCs can be used in a clinical setting, it is critical to validate their in vivo fate following autologous transplantation. Thus far, preclinical studies have been limited to small animals and have yet to be conducted in large animals that are physiologically more similar to humans. In this study, we report the first autologous transplantation of iPSCs in a large animal model through the generation of canine iPSCs (ciPSCs) from the canine adipose stromal cells and canine fibroblasts of adult mongrel dogs. We confirmed pluripotency of ciPSCs using the following techniques: (i) immunostaining and quantitative PCR for the presence of pluripotent and germ layer-specific markers in differentiated ciPSCs; (ii) microarray analysis that demonstrates similar gene expression profiles between ciPSCs and canine embryonic stem cells; (iii) teratoma formation assays; and (iv) karyotyping for genomic stability. Fate of ciPSCs autologously transplanted to the canine heart was tracked in vivo using clinical positron emission tomography, computed tomography, and magnetic resonance imaging. To demonstrate clinical potential of ciPSCs to treat models of injury, we generated endothelial cells (ciPSC-ECs) and used these cells to treat immunodeficient murine models of myocardial infarction and hindlimb ischemia.     

Comparison of Deconvolution Filters for Photoacoustic Tomography

In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT). We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain. All subjects were scanned using an imaging system with a rotatable hemispherical bowl, into which 128 ultrasound transducer elements were embedded in a spiral pattern. We characterized the frequency response of each deconvolution method, compared the final image quality achieved by each deconvolution technique, and evaluated each method’s robustness to noise. The frequency response was quantified by measuring the accuracy with which each filter recovered the ideal flat frequency spectrum of an experimentally measured impulse response. Image quality under the various scenarios was quantified by computing noise versus resolution curves for a point source phantom, as well as the full width at half maximum (FWHM) and contrast-to-noise ratio (CNR) of selected image features such as dots and linear structures in additional imaging subjects. It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum), achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise. While the Wiener filter achieved a similar image resolution, it tended to underrepresent the lower frequency content of the deconvolved signals, and hence of the reconstructed images after backprojection. In addition, its robustness to noise was poorer than that of the Tikhonov filter. The performance of the Fourier filter was found to be the poorest of all three methods, based on the reconstructed images’ lowest resolution (blurriest appearance), generally lowest contrast-to-noise ratio, and lowest robustness to noise. Overall, the Tikhonov filter was deemed to produce the most desirable image reconstructions.     

Pilot Preclinical and Clinical Evaluation of (4S)-4-(3-[18F]Fluoropropyl)-L-Glutamate (18F-FSPG) for PET/CT Imaging of Intracranial Malignancies

Purpose

(S)-4-(3-[¹⁸F]Fluoropropyl)-L-glutamic acid (18F-FSPG) is a novel radiopharmaceutical for Positron Emission Tomography (PET) imaging. It is a glutamate analogue that can be used to measure x_C^- transporter activity. This study was performed to assess the feasibility of 18F-FSPG for imaging orthotopic brain tumors in small animals and the translation of this approach in human subjects with intracranial malignancies.

Experimental Design

For the small animal study, GS9L glioblastoma cells were implanted into brains of Fischer rats and studied with 18F-FSPG, the 18F-labeled glucose derivative 18F-FDG and with the 18F-labeled amino acid derivative 18F-FET. For the human study, five subjects with either primary or metastatic brain cancer were recruited (mean age 50.4 years). After injection of 300 MBq of 18F-FSPG, 3 whole-body PET/Computed Tomography (CT) scans were obtained and safety parameters were measured. The three subjects with brain metastases also had an 18F-FDG PET/CT scan. Quantitative and qualitative comparison of the scans was performed to assess kinetics, biodistribution, and relative efficacy of the tracers.

Results

In the small animals, the orthotopic brain tumors were visualized well with 18F-FSPG. The high tumor uptake of 18F-FSPG in the GS9L model and the absence of background signal led to good tumor visualization with high contrast (tumor/brain ratio: 32.7). 18F-FDG and 18F-FET showed T/B ratios of 1.7 and 2.8, respectively. In the human pilot study, 18F-FSPG was well tolerated and there was similar distribution in all patients. All malignant lesions were positive with 18F-FSPG except for one low-grade primary brain tumor. In the 18F-FSPG-PET-positive tumors a similar T/B ratio was observed as in the animal model.

Conclusions

18F-FSPG is a novel PET radiopharmaceutical that demonstrates good uptake in both small animal and human studies of intracranial malignancies. Future studies on larger numbers of subjects and a wider array of brain tumors are planned.

Trial Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01186601","term_id":"NCT01186601"}}NCT01186601     

Integrating noninvasive molecular imaging into molecular medicine: an evolving paradigm

Molecular imaging is a rapidly emerging field, providing noninvasive visual quantitative representations of fundamental biological processes in intact living subjects. Fundamental biomedical research stands to benefit considerably from advances in molecular imaging, with improved molecular target selection, probe development and imaging instrumentation. The noninvasiveness of molecular imaging technologies will also provide benefit through improved patient care. Molecular imaging endpoints can be quantified, and therefore are particularly useful for translational research. Integration of the two disciplines of molecular imaging and molecular medicine, combined with systems-biology approaches to understanding disease complexity, promises to provide predictive, preventative and personalized medicine that will transform healthcare.     

Creating self-illuminating quantum dot conjugates

Semiconductor quantum dots are inorganic fluorescent nanocrystals that, because of their unique optical properties compared with those of organic fluorophores, have become popular as fluorescent imaging probes. Although external light excitation is typically required for imaging with quantum dots, a new type of quantum dot conjugate has been reported that can luminesce with no need for external excitation. These self-illuminating quantum dot conjugates can be prepared by coupling of commercially available carboxylate-presenting quantum dots to the light-emitting protein Renilla luciferase. When the conjugates are exposed to the luciferase's substrate coelenterazine, the energy released by substrate catabolism is transferred to the quantum dots through bioluminescence resonance energy transfer, leading to quantum dot light emission. This protocol describes step-by-step procedures for the preparation and characterization of these self-illuminating quantum dot conjugates. The preparation process is relatively simple and can be done in less than 2 hours. The availability of self-illuminating quantum dot conjugates will provide many new possibilities for in vivo imaging and detection, such as monitoring of in vivo cell trafficking, multiplex bioluminescence imaging and new quantum dot-based biosensors.     

Quantitative micro positron emission tomography (PET) imaging for the in vivo determination of pancreatic islet graft survival

Islet transplantation is an attractive approach for treating type-1 diabetes, but there is a massive loss of transplanted islets. It is currently only possible to estimate islet mass indirectly, through measurement of circulating C-peptide and insulin levels. This type of estimation, however, is not sufficiently sensitive or reproducible for follow-up of individuals who have undergone islet transplantation. Here we show that islet graft survival could be assessed for 1 month in diabetic NOD mice using 9-(4-[(18)F]-fluoro-3-hydroxymethylbutyl)guanine ([(18)F]FHBG)-positron emission tomography (PET) technology, the PET signal reflecting insulin secretory capacity of transplanted islets. Expression of the gene encoding viral interleukin-10 (vIL-10), was measurable in real time with PET scanning. Additionally, we addressed the clinical potential of this approach by visualizing transplanted islets in the liver, the preferred clinical transplantation site. We conclude that quantitative in vivo PET imaging is a valid method for facilitating the development of protocols for prolonging islet survival, with the potential for tracking human transplants.     

Near-infrared fluorescent RGD peptides for optical imaging of integrin alphavbeta3 expression in living mice

Near-infrared fluorescence optical imaging is a powerful technique for studying diseases at the molecular level in preclinical models. We recently reported that monomeric RGD peptide c(RGDyK) conjugated to the NIR fluorescent dye specifically targets integrin receptor both in cell culture and in living subjects. In this report, Cy5.5-conjugated mono-, di-, and tetrameric RGD peptides were evaluated in a subcutaneous U87MG glioblastoma xenograft model in order to investigate the effect of multimerization of RGD peptide on integrin avidity and tumor targeting efficacy. The binding affinities of Cy5.5-conjugated RGD monomer, dimer, and tetramer for alpha(v)beta(3) integrin expressed on U87MG cell surface were determined to be 42.9 +/- 1.2, 27.5 +/- 1.2, and 12.1 +/- 1.3 nmol/L, respectively. All three peptide-dye conjugates had integrin specific uptake both in vitro and in vivo. The subcutaneous U87MG tumor can be clearly visualized with each of these three fluorescent probes. Among them, tetramer displayed highest tumor uptake and tumor-to-normal tissue ratio from 0.5 to 4 h postinjection. Tumor-to-normal tissue ratio for Cy5.5-conjugated RGD monomer, dimer, and tetramer were found to be 3.18 +/- 0.16, 2.98 +/- 0.05, and 3.63 +/- 0.09, respectively, at 4 h postinjection. These results suggest that Cy5.5-conjugated monomeric, dimeric, and tetrameric RGD peptides are all suitable for integrin expression imaging. The multmerization of RGD peptide results in moderate improvement of imaging characteristics of the tetramer, compared to that of the monomer and dimeric counterparts.     

An Integrated Computational/Experimental Model of Lymphoma Growth

Non-Hodgkin''s lymphoma is a disseminated, highly malignant cancer, with resistance to drug treatment based on molecular- and tissue-scale characteristics that are intricately linked. A critical element of molecular resistance has been traced to the loss of functionality in proteins such as the tumor suppressor p53. We investigate the tissue-scale physiologic effects of this loss by integrating in vivo and immunohistological data with computational modeling to study the spatiotemporal physical dynamics of lymphoma growth. We compare between drug-sensitive Eμ-myc Arf-/- and drug-resistant Eμ-myc p53-/- lymphoma cell tumors grown in live mice. Initial values for the model parameters are obtained in part by extracting values from the cellular-scale from whole-tumor histological staining of the tumor-infiltrated inguinal lymph node in vivo. We compare model-predicted tumor growth with that observed from intravital microscopy and macroscopic imaging in vivo, finding that the model is able to accurately predict lymphoma growth. A critical physical mechanism underlying drug-resistant phenotypes may be that the Eμ-myc p53-/- cells seem to pack more closely within the tumor than the Eμ-myc Arf-/- cells, thus possibly exacerbating diffusion gradients of oxygen, leading to cell quiescence and hence resistance to cell-cycle specific drugs. Tighter cell packing could also maintain steeper gradients of drug and lead to insufficient toxicity. The transport phenomena within the lymphoma may thus contribute in nontrivial, complex ways to the difference in drug sensitivity between Eμ-myc Arf-/- and Eμ-myc p53-/- tumors, beyond what might be solely expected from loss of functionality at the molecular scale. We conclude that computational modeling tightly integrated with experimental data gives insight into the dynamics of Non-Hodgkin''s lymphoma and provides a platform to generate confirmable predictions of tumor growth.     

Sequential Modelling of the Effects of Mass Drug Treatments on Anopheline-Mediated Lymphatic Filariasis Infection in Papua New Guinea

Background

Lymphatic filariasis (LF) has been targeted by the WHO for global eradication leading to the implementation of large scale intervention programs based on annual mass drug administrations (MDA) worldwide. Recent work has indicated that locality-specific bio-ecological complexities affecting parasite transmission may complicate the prediction of LF extinction endpoints, casting uncertainty on the achievement of this initiative. One source of difficulty is the limited quantity and quality of data used to parameterize models of parasite transmission, implying the important need to update initially-derived parameter values. Sequential analysis of longitudinal data following annual MDAs will also be important to gaining new understanding of the persistence dynamics of LF. Here, we apply a Bayesian statistical-dynamical modelling framework that enables assimilation of information in human infection data recorded from communities in Papua New Guinea that underwent annual MDAs, into our previously developed model of parasite transmission, in order to examine these questions in LF ecology and control.

Results

Biological parameters underlying transmission obtained by fitting the model to longitudinal data remained stable throughout the study period. This enabled us to reliably reconstruct the observed baseline data in each community. Endpoint estimates also showed little variation. However, the updating procedure showed a shift towards higher and less variable values for worm kill but not for any other drug-related parameters. An intriguing finding is that the stability in key biological parameters could be disrupted by a significant reduction in the vector biting rate prevailing in a locality.

Conclusions

Temporal invariance of biological parameters in the face of intervention perturbations indicates a robust adaptation of LF transmission to local ecological conditions. The results imply that understanding the mechanisms that underlie locally adapted transmission dynamics will be integral to identifying points of system fragility, and thus countermeasures to reliably facilitate LF extinction both locally and globally.