Semi-quantitative and quantitative dynamic contrast-enhanced (DCE) MRI parameters as prostate cancer imaging biomarkers for biologically targeted radiation therapy

Background Biologically targeted radiation therapy treatment planning requires voxel-wise characterisation of tumours. Dynamic contrast enhanced (DCE) DCE MRI has shown promise in defining voxel-level biological characteristics. In this study we consider the relative value of qualitative, semi-quantitative and quantitative assessment of DCE MRI compared with diffusion weighted imaging (DWI) and T2-weighted (T2w) imaging to detect prostate cancer at the voxel level. Methods Seventy prostate cancer patients had multiparametric MRI prior to radical prostatectomy, including T2w, DWI and DCE MRI. Apparent Diffusion Coefficient (ADC) maps were computed from DWI, and semi-quantitative and quantitative parameters computed from DCE MRI. Tumour location and grade were validated with co-registered whole mount histology. Kolmogorov–Smirnov tests were applied to determine whether MRI parameters in tumour and benign voxels were significantly different. Cohen’s d was computed to quantify the most promising biomarkers. The Parker and Weinmann Arterial Input Functions (AIF) were compared for their ability to best discriminate between tumour and benign tissue. Classifier models were used to determine whether DCE MRI parameters improved tumour detection versus ADC and T2w alone. Results All MRI parameters had significantly different data distributions in tumour and benign voxels. For low grade tumours, semi-quantitative DCE MRI parameter time-to-peak (TTP) was the most discriminating and outperformed ADC. For high grade tumours, ADC was the most discriminating followed by DCE MRI parameters Ktrans, the initial rate of enhancement (IRE), then TTP. Quantitative parameters utilising the Parker AIF better distinguished tumour and benign voxel values than the Weinmann AIF. Classifier models including DCE parameters versus T2w and ADC alone, gave detection accuracies of 78% versus 58% for low grade tumours and 85% versus 72% for high grade tumours. Conclusions Incorporating DCE MRI parameters with DWI and T2w gives improved accuracy for tumour detection at a voxel level. DCE MRI parameters should be used to spatially characterise tumour biology for biologically targeted radiation therapy treatment planning

Transcriptional Profiling of Chondrodysplasia Growth Plate Cartilage Reveals Adaptive ER-Stress Networks That Allow Survival but Disrupt Hypertrophy

Metaphyseal chondrodysplasia, Schmid type (MCDS) is characterized by mild short stature and growth plate hypertrophic zone expansion, and caused by collagen X mutations. We recently demonstrated the central importance of ER stress in the pathology of MCDS by recapitulating the disease phenotype by expressing misfolding forms of collagen X (Schmid) or thyroglobulin (Cog) in the hypertrophic zone. Here we characterize the Schmid and Cog ER stress signaling networks by transcriptional profiling of microdissected mutant and wildtype hypertrophic zones. Both models displayed similar unfolded protein responses (UPRs), involving activation of canonical ER stress sensors and upregulation of their downstream targets, including molecular chaperones, foldases, and ER-associated degradation machinery. Also upregulated were the emerging UPR regulators Wfs1 and Syvn1, recently identified UPR components including Armet and Creld2, and genes not previously implicated in ER stress such as Steap1 and Fgf21. Despite upregulation of the Chop/Cebpb pathway, apoptosis was not increased in mutant hypertrophic zones. Ultrastructural analysis of mutant growth plates revealed ER stress and disrupted chondrocyte maturation throughout mutant hypertrophic zones. This disruption was defined by profiling the expression of wildtype growth plate zone gene signatures in the mutant hypertrophic zones. Hypertrophic zone gene upregulation and proliferative zone gene downregulation were both inhibited in Schmid hypertrophic zones, resulting in the persistence of a proliferative chondrocyte-like expression profile in ER-stressed Schmid chondrocytes. Our findings provide a transcriptional map of two chondrocyte UPR gene networks in vivo, and define the consequences of UPR activation for the adaptation, differentiation, and survival of chondrocytes experiencing ER stress during hypertrophy. Thus they provide important insights into ER stress signaling and its impact on cartilage pathophysiology

The distribution of the apparent diffusion coefficient as an indicator of the response to chemotherapeutics in ovarian tumour xenografts

Cancer Council of Queensland and a mobility grant (Personalized Medicine) from the German Academic Exchange Service (DAAD)

Physiologically Based Pharmacokinetic Modeling of TransporterMediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats

[Image: see text] Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (K(m,u)) of gadoxetate was 106 μM (17%) (n = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI

Conserved roles of C. elegans and human MANFs in sulfatide binding and cytoprotection

MANF is a secreted ER stress-inducible protein that protects neurons, pancreatic β cells and cardiomyocytes from cell death under oxidative stress, hypoxic or ischemic conditions. Here the authors show that MANF confers cytoprotection through direct binding to sulfatide followed by cellular uptake in both C. elegans and mammalian cells