Influence of inputs for bone lesion segmentation in longitudinal 18F-FDG PET/CT imaging studies.

In metastatic breast cancer, bone metastases are prevalent and associated with multiple complications. Assessing their response to treatment is therefore crucial. Most deep learning methods segment or detect lesions on a single acquisition while only a few focus on longitudinal studies. In this work, 45 patients with baseline (BL) and follow-up (FU) images recruited in the context of the EPICUREseinmeta study were analyzed. The aim was to determine if a network trained for a particular timepoint can generalize well to another one, and to explore different improvement strategies. Four networks based on the same 3D U-Net framework to segment bone lesions on BL and FU images were trained with different strategies and compared. These four networks were trained 1) only with BL images 2) only with FU images 3) with both BL and FU images 4) only with FU images but with BL images and bone lesion segmentations registered as input channels. With the obtained segmentations, we computed the PET Bone Index (PBI) which assesses the bone metastases burden of patients and we analyzed its potential for treatment response evaluation. Dice scores of 0.53, 0.55, 0.59 and 0.62 were respectively obtained on FU acquisitions. The under-performance of the first and third networks may be explained by the lower SUV uptake due to treatment response in FU images compared to BL images. The fourth network gives better results than the second network showing that the addition of BL PET images and bone lesion segmentations as prior knowledge has its importance. With an AUC of 0.86, the difference of PBI between two acquisitions could be used to assess treatment response. Clinical relevance- To assess the response to treatment of bone metastases, it is crucial to detect and segment them on several acquisitions from a same patient. We proposed a completely automatic method to detect and segment these metastases on longitudinal 18F-FDG PET/CT images in the context of metastatic breast cancer. We also proposed an automatic PBI to quantitatively assess the evolution of the bone metastases burden of patient and to automatically evaluate their response to treatment.

Deformable image registration with deep network priors: a study on longitudinal PET images.

Objective.This paper proposes a novel approach for the longitudinal registration of PET imaging acquired for the monitoring of patients with metastatic breast cancer. Unlike with other image analysis tasks, the use of deep learning (DL) has not significantly improved the performance of image registration. With this work, we propose a new registration approach to bridge the performance gap between conventional and DL-based methods: medical image registration method regularized by architecture (MIRRBA).Approach.MIRRBAis a subject-specific deformable registration method which relies on a deep pyramidal architecture to parametrize the deformation field. Diverging from the usual deep-learning paradigms,MIRRBAdoes not require a learning database, but only a pair of images to be registered that is used to optimize the network's parameters. We appliedMIRRBAon a private dataset of 110 whole-body PET images of patients with metastatic breast cancer. We used different architecture configurations to produce the deformation field and studied the results obtained. We also compared our method to several standard registration approaches: two conventional iterative registration methods (ANTs and Elastix) and two supervised DL-based models (LapIRN and Voxelmorph). Registration accuracy was evaluated using the Dice score, the target registration error, the average Hausdorff distance and the detection rate, while the realism of the registration obtained was evaluated using Jacobian's determinant. The ability of the different methods to shrink disappearing lesions was also computed with the disappearing rate.Main results.MIRRBA significantly improved all metrics when compared to DL-based approaches. The organ and lesion Dice scores of Voxelmorph improved by 6% and 52% respectively, while the ones of LapIRN increased by 5% and 65%. Regarding conventional approaches, MIRRBA presented comparable results showing the feasibility of our method.Significance.In this paper, we also demonstrate the regularizing power of deep architectures and present new elements to understand the role of the architecture in DL methods used for registration.

Prognostic Value of Metabolic, Volumetric and Textural Parameters of Baseline [18F]FDG PET/CT in Early Triple-Negative Breast Cancer.

(1) Background: triple-negative breast cancer (TNBC) remains a clinical and therapeutic challenge primarily affecting young women with poor prognosis. TNBC is currently treated as a single entity but presents a very diverse profile in terms of prognosis and response to treatment. Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose ([18F]FDG) is gaining importance for the staging of breast cancers. TNBCs often show high [18F]FDG uptake and some studies have suggested a prognostic value for metabolic and volumetric parameters, but no study to our knowledge has examined textural features in TNBC. The objective of this study was to evaluate the association between metabolic, volumetric and textural parameters measured at the initial [18F]FDG PET/CT and disease-free survival (DFS) and overall survival (OS) in patients with nonmetastatic TBNC. (2) Methods: all consecutive nonmetastatic TNBC patients who underwent a [18F]FDG PET/CT examination upon diagnosis between 2012 and 2018 were retrospectively included. The metabolic and volumetric parameters (SUVmax, SUVmean, SUVpeak, MTV, and TLG) and the textural features (entropy, homogeneity, SRE, LRE, LGZE, and HGZE) of the primary tumor were collected. (3) Results: 111 patients were enrolled (median follow-up: 53.6 months). In the univariate analysis, high TLG, MTV and entropy values of the primary tumor were associated with lower DFS (p = 0.008, p = 0.006 and p = 0.025, respectively) and lower OS (p = 0.002, p = 0.001 and p = 0.046, respectively). The discriminating thresholds for two-year DFS were calculated as 7.5 for MTV, 55.8 for TLG and 2.6 for entropy. The discriminating thresholds for two-year OS were calculated as 9.3 for MTV, 57.4 for TLG and 2.67 for entropy. In the multivariate analysis, lymph node involvement in PET/CT was associated with lower DFS (p = 0.036), and the high MTV of the primary tumor was correlated with lower OS (p = 0.014). (4) Conclusions: textural features associated with metabolic and volumetric parameters of baseline [18F]FDG PET/CT have a prognostic value for identifying high-relapse-risk groups in early TNBC patients.

The mitochondrially-localized nucleoside diphosphate kinase D (NME4) is a novel metastasis suppressor.

BACKGROUND: Mitochondrial nucleoside diphosphate kinase (NDPK-D, NME4, NM23-H4) is a multifunctional enzyme mainly localized in the intermembrane space, bound to the inner membrane. RESULTS: We constructed loss-of-function mutants of NDPK-D, lacking either NDP kinase activity or membrane interaction and expressed mutants or wild-type protein in cancer cells. In a complementary approach, we performed depletion of NDPK-D by RNA interference. Both loss-of-function mutations and NDPK-D depletion promoted epithelial-mesenchymal transition and increased migratory and invasive potential. Immunocompromised mice developed more metastases when injected with cells expressing mutant NDPK-D as compared to wild-type. This metastatic reprogramming is a consequence of mitochondrial alterations, including fragmentation and loss of mitochondria, a metabolic switch from respiration to glycolysis, increased ROS generation, and further metabolic changes in mitochondria, all of which can trigger pro-metastatic protein expression and signaling cascades. In human cancer, NME4 expression is negatively associated with markers of epithelial-mesenchymal transition and tumor aggressiveness and a good prognosis factor for beneficial clinical outcome. CONCLUSIONS: These data demonstrate NME4 as a novel metastasis suppressor gene, the first localizing to mitochondria, pointing to a role of mitochondria in metastatic dissemination.

Metastasis-suppressor NME1 controls the invasive switch of breast cancer by regulating MT1-MMP surface clearance.

Membrane Type 1 Matrix Metalloprotease (MT1-MMP) contributes to the invasive progression of breast cancers by degrading extracellular matrix tissues. Nucleoside diphosphate kinase, NME1/NM23-H1, has been identified as a metastasis suppressor; however, its contribution to local invasion in breast cancer is not known. Here, we report that NME1 is up-regulated in ductal carcinoma in situ (DCIS) as compared to normal breast epithelial tissues. NME1 levels drop in microinvasive and invasive components of breast tumor cells relative to synchronous DCIS foci. We find a strong anti-correlation between NME1 and plasma membrane MT1-MMP levels in the invasive components of breast tumors, particularly in aggressive histological grade III and triple-negative breast cancers. Knockout of NME1 accelerates the invasive transition of breast tumors in the intraductal xenograft model. At the mechanistic level, we find that MT1-MMP, NME1 and dynamin-2, a GTPase known to require GTP production by NME1 for its membrane fission activity in the endocytic pathway, interact in clathrin-coated vesicles at the plasma membrane. Loss of NME1 function increases MT1-MMP surface levels by inhibiting endocytic clearance. As a consequence, the ECM degradation and invasive potentials of breast cancer cells are enhanced. This study identifies the down-modulation of NME1 as a potent driver of the in situ-to invasive transition during breast cancer progression.

Automatic Segmentation of Metastatic Breast Cancer Lesions on 18F-FDG PET/CT Longitudinal Acquisitions for Treatment Response Assessment.

Metastatic breast cancer patients receive lifelong medication and are regularly monitored for disease progression. The aim of this work was to (1) propose networks to segment breast cancer metastatic lesions on longitudinal whole-body PET/CT and (2) extract imaging biomarkers from the segmentations and evaluate their potential to determine treatment response. Baseline and follow-up PET/CT images of 60 patients from the EPICUREseinmeta study were used to train two deep-learning models to segment breast cancer metastatic lesions: One for baseline images and one for follow-up images. From the automatic segmentations, four imaging biomarkers were computed and evaluated: SULpeak, Total Lesion Glycolysis (TLG), PET Bone Index (PBI) and PET Liver Index (PLI). The first network obtained a mean Dice score of 0.66 on baseline acquisitions. The second network obtained a mean Dice score of 0.58 on follow-up acquisitions. SULpeak, with a 32% decrease between baseline and follow-up, was the biomarker best able to assess patients' response (sensitivity 87%, specificity 87%), followed by TLG (43% decrease, sensitivity 73%, specificity 81%) and PBI (8% decrease, sensitivity 69%, specificity 69%). Our networks constitute promising tools for the automatic segmentation of lesions in patients with metastatic breast cancer allowing treatment response assessment with several biomarkers.

Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer.

18FDG PET/CT imaging is commonly used in diagnosis and follow-up of metastatic breast cancer, but its quantitative analysis is complicated by the number and location heterogeneity of metastatic lesions. Considering that bones are the most common location among metastatic sites, this work aims to compare different approaches to segment the bones and bone metastatic lesions in breast cancer.Two deep learning methods based on U-Net were developed and trained to segment either both bones and bone lesions or bone lesions alone on PET/CT images. These methods were cross-validated on 24 patients from the prospective EPICUREseinmeta metastatic breast cancer study and were evaluated using recall and precision to measure lesion detection, as well as the Dice score to assess bones and bone lesions segmentation accuracy.Results show that taking into account bone information in the training process allows to improve the precision of the lesions detection as well as the Dice score of the segmented lesions. Moreover, using the obtained bone and bone lesion masks, we were able to compute a PET bone index (PBI) inspired by the recognized Bone Scan Index (BSI). This automatically computed PBI globally agrees with the one calculated from ground truth delineations.Clinical relevance- We propose a completely automatic deep learning based method to detect and segment bones and bone lesions on 18FDG PET/CT in the context of metastatic breast cancer. We also introduce an automatic PET bone index which could be incorporated in the monitoring and decision process.

Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images.

Semi-automatic measurements are performed on 18FDG PET-CT images to monitor the evolution of metastatic sites in the clinical follow-up of metastatic breast cancer patients. Apart from being time-consuming and prone to subjective approximation, semi-automatic tools cannot make the difference between cancerous regions and active organs, presenting a high 18FDG uptake.In this work, we combine a deep learning-based approach with a superpixel segmentation method to segment the main active organs (brain, heart, bladder) from full-body PET images. In particular, we integrate a superpixel SLIC algorithm at different levels of a convolutional network. Results are compared with a deep learning segmentation network alone. The methods are cross-validated on full-body PET images of 36 patients and tested on the acquisitions of 24 patients from a different study center, in the context of the ongoing EPICUREseinmeta study. The similarity between the manually defined organ masks and the results is evaluated with the Dice score. Moreover, the amount of false positives is evaluated through the positive predictive value (PPV).According to the computed Dice scores, all approaches allow to accurately segment the target organs. However, the networks integrating superpixels are better suited to transfer knowledge across datasets acquired on multiple sites (domain adaptation) and are less likely to segment structures outside of the target organs, according to the PPV.Hence, combining deep learning with superpixels allows to segment organs presenting a high 18FDG uptake on PET images without selecting cancerous lesion, and thus improves the precision of the semi-automatic tools monitoring the evolution of breast cancer metastasis.Clinical relevance- We demonstrate the utility of combining deep learning and superpixel segmentation methods to accurately find the contours of active organs from metastatic breast cancer images, to different dataset distributions.

Prognostic Impact of Pretherapeutic FDG-PET in Localized Anal Cancer.

Due to the heterogeneity of tumour mass segmentation methods and lack of consensus, our study evaluated the prognostic value of pretherapeutic positron emission tomography with fluorodeoxyglucose (FDG-PET) metabolic parameters using different segmentation methods in patients with localized anal squamous cell carcinoma (SCC). Eighty-one patients with FDG-PET before radiochemotherapy were retrospectively analyzed. Semiquantitative data were measured with three fixed thresholds (35%, 41% and 50% of Maximum Standardized Uptake Value (SUVmax)) and four segmentation methods based on iterative approaches (Black, Adaptive, Nestle and Fitting). Metabolic volumes of primary anal tumour (P-MTV) and total tumour load (T-MTV: P-MTV+ lymph node MTV) were calculated. The primary endpoint was event-free survival (EFS). Seven multivariate models were created to compare FDG-PET tumour volumes prognostic impact. For all segmentation thresholds, PET metabolic volume parameters were independent prognostic factor and T-MTV variable was consistently better associated with EFS than P-MTV. Patient's sex was an independent variable and significantly correlated with EFS. With fixed threshold segmentation methods, 35% of SUVmax threshold seemed better correlated with EFS and the best cut-off for discrimination between a low and high risk of event occurrence was 40 cm3. Determination of T-MTV by FDG-PET using fixed threshold segmentation is useful for predicting EFS for primary anal SCC. If these data are confirmed in larger studies, FDG-PET could contribute to individualized patient therapies.

The mitochondrial nucleoside diphosphate kinase (NDPK-D/NME4), a moonlighting protein for cell homeostasis.

Mitochondrial nucleoside diphosphate kinase (NDPK-D; synonyms: NME4, NM23-H4) represents the major mitochondrial NDP kinase. The homohexameric complex emerged as a protein with multiple functions in bioenergetics and phospholipid signaling. It occurs at different but precise mitochondrial locations and can affect among other mitochondrial shapes and dynamics, as well as the specific elimination of defective mitochondria or cells via mitophagy or apoptosis. With these various functions in cell homeostasis, NDPK-D/NME4 adds to the group of so-called moonlighting (or gene sharing) proteins.

Comparison of Immuno-PET of CD138 and PET imaging with 64CuCl2 and 18F-FDG in a preclinical syngeneic model of multiple myeloma.

PURPOSE: Although recent data from the literature suggest that PET imaging with [18]-Fluorodeoxyglucose (18F-FDG) is a promising technique in multiple myeloma (MM), the development of other radiopharmaceuticals seems relevant. CD138 is currently used as a standard marker in many laboratories for the identification and purification of myeloma cells, and could be used in phenotype tumor imaging. In this study, we evaluated a 64Cu-labeled anti-CD138 murine antibody (64Cu-TE2A-9E7.4) and a metabolic tracer (64CuCl2) for PET imaging in a MM syngeneic mouse model. EXPERIMENTAL DESIGN AND RESULTS: 64Cu-TE2A-9E7.4 antibody and 64CuCl2 were evaluated via PET imaging and biodistribution studies in C57BL / KaLwRij mice bearing either 5T33-MM subcutaneous tumors or bone lesions. These results were compared to 18F-FDG-PET imaging. Autoradiography and histology of representative tumors were secondly conducted. In biodistribution and PET studies, 64Cu-TE2A-9E7.4 displayed good tumor uptake of subcutaneous and intra-medullary lesions, greater than that demonstrated with 18F-FDG-PET. In control experiments, only low-level, non-specific uptake of 64Cu-labeled isotype IgG was observed in tumors. Similarly, low activity concentrations of 64CuCl2 were accumulated in MM lesions. Histopathologic analysis of the immuno-PET-positive lesions revealed the presence of plasma cell infiltrates within the bone marrow. CONCLUSIONS: 64Cu-labeled anti-CD138 antibody can detect subcutaneous MM tumors and bone marrow lesions with high sensitivity, outperforming 18F-FDG-PET and 64CuCl2 in this preclinical model. These data support 64Cu-anti-CD138 antibody as a specific and promising new imaging radiopharmaceutical agent in MM.

The NDPK/NME superfamily: state of the art.

Nucleoside diphosphate kinases (NDPK) are nucleotide metabolism enzymes encoded by NME genes (also called NM23). Given the fact that not all NME-encoded proteins are catalytically active NDPKs and that NM23 generally refers to clinical studies on metastasis, we use here NME/NDPK to denote the proteins. Since their discovery in the 1950's, NMEs/NDPKs have been shown to be involved in multiple physiological and pathological cellular processes, but the molecular mechanisms have not been fully determined. Recent progress in elucidating these underlying mechanisms has been presented by experts in the field at the 10th International Congress on the NDPK/NME/AWD protein family in October 2016 in Dubrovnik, Croatia, and is summarized in review articles or original research in this and an upcoming issue of Laboratory Investigation. Within this editorial, we discuss three major cellular processes that involve members of the multi-functional NME/NDPK family: (i) cancer and metastasis dissemination, (ii) membrane remodeling and nucleotide channeling, and iii) protein histidine phosphorylation.

Transcriptome Analysis of Human Reninomas as an Approach to Understanding Juxtaglomerular Cell Biology.

Renin, a key component in the regulation of blood pressure in mammals, is produced by the rare and highly specialized juxtaglomerular cells of the kidney. Chronic stimulation of renin release results in a recruitment of new juxtaglomerular cells by the apparent conversion of adjacent smooth muscle cells along the afferent arterioles. Because juxtaglomerular cells rapidly dedifferentiate when removed from the kidney, their developmental origin and the mechanism that explains their phenotypic plasticity remain unclear. To overcome this limitation, we have performed RNA expression analysis on 4 human renin-producing tumors. The most highly expressed genes that were common between the reninomas were subsequently used for in situ hybridization in kidneys of 5-day-old mice, adult mice, and adult mice treated with captopril. From the top 100 genes, 10 encoding for ligands were selected for further analysis. Medium of human embryonic kidney 293 cells transfected with the mouse cDNA encoding these ligands was applied to (pro)renin-synthesizing As4.1 cells. Among the ligands, only platelet-derived growth factor B reduced the medium and cellular (pro)renin levels, as well as As4.1 renin gene expression. In addition, platelet-derived growth factor B-exposed As4.1 cells displayed a more elongated and aligned shape with no alteration in viability. This was accompanied by a downregulated expression of α-smooth muscle actin and an upregulated expression of interleukin-6, suggesting a phenotypic shift from myoendocrine to inflammatory. Our results add 36 new genes to the list that characterize renin-producing cells and reveal a novel role for platelet-derived growth factor B as a regulator of renin-synthesizing cells.

Phase II Study of a Radiotherapy Total Dose Increase in Hypoxic Lesions Identified by 18F-Misonidazole PET/CT in Patients with Non-Small Cell Lung Carcinoma (RTEP5 Study).

See an invited perspective on this article on page 1043.This multicenter phase II study investigated a selective radiotherapy dose increase to tumor areas with significant 18F-misonidazole (18F-FMISO) uptake in patients with non-small cell lung carcinoma (NSCLC). Methods: Eligible patients had locally advanced NSCLC and no contraindication to concomitant chemoradiotherapy. The 18F-FMISO uptake on PET/CT was assessed by trained experts. If there was no uptake, 66 Gy were delivered. In 18F-FMISO-positive patients, the contours of the hypoxic area were transferred to the radiation oncologist. It was necessary for the radiotherapy dose to be as high as possible while fulfilling dose-limiting constraints for the spinal cord and lungs. The primary endpoint was tumor response (complete response plus partial response) at 3 mo. The secondary endpoints were toxicity, disease-free survival (DFS), and overall survival at 1 y. The target sample size was set to demonstrate a response rate of 40% or more (bilateral α = 0.05, power 1-ß = 0.95). Results: Seventy-nine patients were preincluded, 54 were included, and 34 were 18F-FMISO-positive, 24 of whom received escalated doses of up to 86 Gy. The response rate at 3 mo was 31 of 54 (57%; 95% confidence interval [CI], 43%-71%) using RECIST 1.1 (17/34 responders in the 18F-FMISO-positive group). DFS and overall survival at 1 y were 0.86 (95% CI, 0.77-0.96) and 0.63 (95% CI, 0.49-0.74), respectively. DFS was longer in the 18F-FMISO-negative patients (P = 0.004). The radiotherapy dose was not associated with DFS when adjusting for the 18F-FMISO status. One toxic death (66 Gy) and 1 case of grade 4 pneumonitis (>66 Gy) were reported. Conclusion: Our approach results in a response rate of 40% or more, with acceptable toxicity. 18F-FMISO uptake in NSCLC patients is strongly associated with poor prognosis features that could not be reversed by radiotherapy doses up to 86 Gy.

Metastasis suppressor NM23 limits oxidative stress in mammals by preventing activation of stress-activated protein kinases/JNKs through its nucleoside diphosphate kinase activity.

NME1 (nonmetastatic expressed 1) gene, which encodes nucleoside diphosphate kinase (NDPK) A [also known as nonmetastatic clone 23 (NM23)-H1 in humans and NM23-M1 in mice], is a suppressor of metastasis, but several lines of evidence-mostly from plants-also implicate it in the regulation of the oxidative stress response. Here, our aim was to investigate the physiologic relevance of NDPK A with respect to the oxidative stress response in mammals and to study its molecular basis. NME1-knockout mice died sooner, suffered greater hepatocyte injury, and had lower superoxide dismutase activity than did wild-type (WT) mice in response to paraquat-induced acute oxidative stress. Deletion of NME1 reduced total NDPK activity and exacerbated activation of the stress-related MAPK, JNK, in the liver in response to paraquat. In a mouse transformed hepatocyte cell line and in primary cultures of normal human keratinocytes, MAPK activation in response to H2O2 and UVB, respectively, was dampened by expression of NM23-M1/NM23-H1, dependent on its NDPK catalytic activity. Furthermore, excess or depletion of NM23-M1/NM23-H1 NDPK activity did not affect the intracellular bulk concentration of nucleoside di- and triphosphates. NME1-deficient mouse embryo fibroblasts grew poorly in culture, were more sensitive to stress than WT fibroblasts, and did not immortalize, which suggested that they senesce earlier than do WT fibroblasts. Collectively, these results indicate that the NDPK activity of NM23-M1/NM23-H1 protects cells from acute oxidative stress by inhibiting activation of JNK in mammal models.-Peuchant, E., Bats, M.-L., Moranvillier, I., Lepoivre, M., Guitton, J., Wendum, D., Lacombe, M.-L., Moreau-Gaudry, F., Boissan, M., Dabernat, S. Metastasis suppressor NM23 limits oxidative stress in mammals by preventing activation of stress-activated protein kinases/JNKs through its nucleoside diphosphate kinase activity.

Correction: New synthesis of phenyl-isothiocyanate C-functionalised cyclams. Bioconjugation and (64)Cu phenotypic PET imaging studies of multiple myeloma with the te2a derivative.

Correction for 'New synthesis of phenyl-isothiocyanate C-functionalised cyclams. Bioconjugation and 64Cu phenotypic PET imaging studies of multiple myeloma with the te2a derivative' by Zakaria Halime et al., Org. Biomol. Chem., 2015, 13, 11302-11314.

New synthesis of phenyl-isothiocyanate C-functionalised cyclams. Bioconjugation and (64)Cu phenotypic PET imaging studies of multiple myeloma with the te2a derivative.

Azamacrocyclic bifunctional chelating agents (BCAs) are essential for the development of radiopharmaceuticals in nuclear medicine and we wish to prove that their bioconjugation by a function present on a carbon atom of the macrocyclic skeleton is a solution of choice to maintain their in vivo inertness. Based on our very recent methodology using a bisaminal template and selective N-alkylation approach, a new synthesis of conjugable C-functionalised teta, te2a and cb-te2a has been developed. These chelators have indeed a growing interest in nuclear medicine for positron emission tomography (PET) and radioimmunotherapy (RIT) where they show in several cases better complexation properties than dota or dota-like macrocycles, especially with (64)Cu or (67)Cu radioisotopes. Chelators are bearing an isothiocyanate grafting function introduced by C-alkylation to avoid as much as possible a critical decrease of their chelating properties. The synthesis is very efficient and yields the targeted ligands, teta-Ph-NCS, te2a-Ph-NCS and cb-te2a-Ph-NCS without fastidious work-up and could be easily extended to other cyclam based-BCAs. The newly synthetised te2a-Ph-NCS has been conjugated to an anti mCD138 monoclonal antibody (mAb) to evaluate its in vivo behavior and potentiality as BCA and to explore a first attempt of PET-phenotypic imaging in multiple myeloma (MM). Mass spectrometry analysis of the immunoconjugate showed that up to 4 chelates were conjugated per 9E7.4 mAb. The radiolabeling yield and specific activity post-purification of the bioconjugate 9E7.4-CSN-Ph-te2a were 95 ± 2.8% and 188 ± 27 MBq mg(-1) respectively and the immunoreactivity of (64)Cu-9E7.4-CSN-Ph-te2a was 81 ± 7%. Animal experiments were carried out on 5T33-Luc(+) tumor bearing mice, either in subcutaneous or orthotopic. To achieve PET imaging, mice were injected with (64)Cu-9E7.4-CNS-Ph-te2a and acquisitions were conducted 2 and 20 h post-injection (PI). A millimetric bone uptake was localised in a sacroiliac of a MM orthotopic tumor. Nonspecific uptakes were observed at 2 h PI but, unlike for the tumor, a significant decrease was observed at 20 h PI which improves the contrast of the images.

General lysosomal hydrolysis can process prorenin accurately.

Renin, an aspartyl protease that catalyzes the rate-limiting step of the renin-angiotensin system, is first synthesized as an inactive precursor, prorenin. Prorenin is activated by the proteolytic removal of an amino terminal prosegment in the dense granules of the juxtaglomerular (JG) cells of the kidney by one or more proteases whose identity is uncertain but commonly referred to as the prorenin-processing enzyme (PPE). Because several extrarenal tissues secrete only prorenin, we tested the hypothesis that the unique ability of JG cells to produce active renin might be explained by the existence of a PPE whose expression is restricted to JG cells. We found that inducing renin production by the mouse kidney by up to 20-fold was not associated with the concomitant induction of candidate PPEs. Because the renin-containing granules of JG cells also contain several lysosomal hydrolases, we engineered mouse Ren1 prorenin to be targeted to the classical vesicular lysosomes of cultured HEK-293 cells, where it was accurately processed and stored. Furthermore, we found that HEK cell lysosomes hydrolyzed any artificial extensions placed on the protein and that active renin was extraordinarily resistant to proteolytic degradation. Altogether, our results demonstrate that accurate processing of prorenin is not restricted to JG cells but can occur in classical vesicular lysosomes of heterologous cells. The implication is that renin production may not require a specific PPE but rather can be achieved by general hydrolysis in the lysosome-like granules of JG cells.

Membrane trafficking. Nucleoside diphosphate kinases fuel dynamin superfamily proteins with GTP for membrane remodeling.

Dynamin superfamily molecular motors use guanosine triphosphate (GTP) as a source of energy for membrane-remodeling events. We found that knockdown of nucleoside diphosphate kinases (NDPKs) NM23-H1/H2, which produce GTP through adenosine triphosphate (ATP)-driven conversion of guanosine diphosphate (GDP), inhibited dynamin-mediated endocytosis. NM23-H1/H2 localized at clathrin-coated pits and interacted with the proline-rich domain of dynamin. In vitro, NM23-H1/H2 were recruited to dynamin-induced tubules, stimulated GTP-loading on dynamin, and triggered fission in the presence of ATP and GDP. NM23-H4, a mitochondria-specific NDPK, colocalized with mitochondrial dynamin-like OPA1 involved in mitochondria inner membrane fusion and increased GTP-loading on OPA1. Like OPA1 loss of function, silencing of NM23-H4 but not NM23-H1/H2 resulted in mitochondrial fragmentation, reflecting fusion defects. Thus, NDPKs interact with and provide GTP to dynamins, allowing these motor proteins to work with high thermodynamic efficiency.

Laparoscopic sentinel lymph node versus hyperextensive pelvic dissection for staging clinically localized prostate carcinoma: a prospective study of 200 patients.

UNLABELLED: Lymph node metastasis is an important prognostic factor in prostate cancer (PC). The aim of this prospective study was to validate, through laparoscopic surgery, the accuracy of the isotopic sentinel lymph node (SLN) technique correlated with hyperextensive pelvic resection (extended pelvic lymphadenectomy dissection) in patients with localized PC, candidates for local curative treatment. METHODS: A transrectal ultrasound-guided injection of (99m)Tc-sulfur rhenium colloid (0.3 mL/100 MBq) in each prostatic lobe was performed the day before surgery. Detection was performed intraoperatively with a laparoscopic probe, followed by extensive resection. SLN counts were performed in vivo and confirmed ex vivo. Histologic analysis was performed by hematoxylin-phloxine-safran staining, followed by immunohistochemistry if the SLN was free of metastasis. RESULTS: Two hundred three patients with PC at intermediate or high risk of lymph node metastases were included. The intraoperative detection rate was 96% (195/203). Thirty-five patients had lymph node metastases, 19 only in the SLN. The false-negative rate was 8.5% (3/35). Unilateral surgical SLN detection did not validate bilateral pelvic lymph node status, and extended pelvic lymphadenectomy dissection was necessary on the opposite side of detection to minimize the false-negative rate (2.8% [1/35]). A significant metastatic sentinel invasion in the common iliac region existed (9.3%) but was always associated with other metastatic node areas. The internal iliac region was the primary metastatic site (40.7%). Finally, this series invalidated any justification for a standard or limited dissection, which would have missed 51.9% and 74.1% of lymph node metastases, respectively. CONCLUSION: The radioisotope SLN identification method up to the common iliac region is successful to identify sentinel nodes during laparoscopic surgery per hemipelvis to be acceptably considered as an isolated procedure and should be validated for intermediate- and high-risk patients.