Mammalian target of rapamycin (mTOR) (a serine/threonine protein kinase) is a major repressor of autophagy, a cell survival mechanism. The specific in vivo mechanism of mTOR signalling in OA ...pathophysiology is not fully characterised. We determined the expression of mTOR and known autophagy genes in human OA cartilage as well as mouse and dog models of experimental OA. We created cartilage-specific mTOR knockout (KO) mice to determine the specific role of mTOR in OA pathophysiology and autophagy signalling in vivo.
Inducible cartilage-specific mTOR KO mice were generated and subjected to mouse model of OA. Human OA chondrocytes were treated with rapamycin and transfected with Unc-51-like kinase 1 (ULK1) siRNA to determine mTOR signalling.
mTOR is overexpressed in human OA cartilage as well as mouse and dog experimental OA. Upregulation of mTOR expression co-relates with increased chondrocyte apoptosis and reduced expression of key autophagy genes during OA. Subsequently, we show for the first time that cartilage-specific ablation of mTOR results in increased autophagy signalling and a significant protection from destabilisation of medial meniscus (DMM)-induced OA associated with a significant reduction in the articular cartilage degradation, apoptosis and synovial fibrosis. Furthermore, we show that regulation of ULK1/adenosine monophosphate-activated protein kinase (AMPK) signalling pathway by mTOR may in part be responsible for regulating autophagy signalling and the balance between catabolic and anabolic factors in the articular cartilage.
This study provides a direct evidence of the role of mTOR and its downstream modulation of autophagy in articular cartilage homeostasis.
Epithelial ovarian cancer (EOC) is the most lethal gynecological cancer. Among the key challenges in developing effective therapeutics is the poor translation of preclinical models used in the drug ...discovery pipeline. This leaves drug attrition rates and costs at an unacceptably high level. Previous work has highlighted the discrepancies in therapeutic response between current in vitro and in vivo models. To address this, we conducted a comparison study to differentiate the carboplatin chemotherapy response across four different model systems including 2D monolayers, 3D spheroids, 3D ex vivo tumors and mouse xenograft models. We used six previously characterized EOC cell lines of varying chemosensitivity and performed viability assays for each model. In vivo results from the mouse model correlated with 2D response in 3/6 cell lines while they correlated with 3D spheroids and the ex vivo model in 4/6 and 5/5 cell lines, respectively. Our results emphasize the variability in therapeutic response across models and demonstrate that the carboplatin response in EOC cell lines cultured in a 3D ex vivo model correlates best with the in vivo response. These results highlight a more feasible, reliable, and cost-effective preclinical model with the highest translational potential for drug screening and prediction studies in EOC.
Predicting patient responses to anticancer drugs is a major challenge both at the drug development stage and during cancer treatment. Tumor explant culture platforms (TECPs) preserve the native ...tissue architecture and are well-suited for drug response assays. However, tissue longevity in these models is relatively low. Several methodologies have been developed to address this issue, although no study has compared their efficacy in a controlled fashion. We investigated the effect of two variables in TECPs, specifically, the tissue size and culture vessel on tissue survival using micro-dissected tumor tissue (MDT) and tissue slices which were cultured in microfluidic chips and plastic well plates. Tumor models were produced from ovarian and prostate cancer cell line xenografts and were matched in terms of the specimen, total volume of tissue, and respective volume of medium in each culture system. We examined morphology, viability, and hypoxia in the various tumor models. Our observations suggest that the viability and proliferative capacity of MDTs were not affected during the time course of the experiments. In contrast, tissue slices had reduced proliferation and showed increased cell death and hypoxia under both culture conditions. Tissue slices cultured in microfluidic devices had a lower degree of hypoxia compared to those in 96-well plates. Globally, our results show that tissue slices have lower survival rates compared to MDTs due to inherent diffusion limitations, and that microfluidic devices may decrease hypoxia in tumor models.
Cancer cell lines are amongst the most important pre-clinical models. In the context of epithelial ovarian cancer, a highly heterogeneous disease with diverse subtypes, it is paramount to study a ...wide panel of models in order to draw a representative picture of the disease. As this lethal gynaecological malignancy has seen little improvement in overall survival in the last decade, it is all the more pressing to support future research with robust and diverse study models. Here, we describe ten novel spontaneously immortalized patient-derived ovarian cancer cell lines, detailing their respective mutational profiles and gene/biomarker expression patterns, as well as their in vitro and in vivo growth characteristics. Eight of the cell lines were classified as high-grade serous, while two were determined to be of the rarer mucinous and clear cell subtypes, respectively. Each of the ten cell lines presents a panel of characteristics reflective of diverse clinically relevant phenomena, including chemotherapeutic resistance, metastatic potential, and subtype-associated mutations and gene/protein expression profiles. Importantly, four cell lines formed subcutaneous tumors in mice, a key characteristic for pre-clinical drug testing. Our work thus contributes significantly to the available models for the study of ovarian cancer, supplying additional tools to better understand this complex disease.
Un défi majeur en oncologie clinique est de caractériser avec précision la réponse des patients aux agents thérapeutiques. Actuellement, il n'existe pas de modèles et de tests fiables capable de ...reproduire précisément une tumeur primaire dans toute sa complexité. Or, ce paramètre est essentiel pour mettre en œuvre une stratégie de médecine personnalisée capable d'identifier le régime de traitement le plus approprié pour un patient particulier dans un délai cliniquement pertinent. Pour répondre à ce besoin, notre groupe a développé un nouveau modèle 3D ex vivo qui repose sur la micro-dissection d'un échantillon de tumeur (MDT) d'un patient et l'utilisation de technologies microfluidiques pour maintenir la viabilité du tissu et le microenvironnement tumoral naturel afin d’évaluer la sensibilité aux traitements dans un délai adapté à la prise de décision clinique. Cette approche permettrait de sélectionner les thérapies les plus efficaces tout en réduisant l'administration de traitements inefficaces associés à des effets secondaires indésirables, ainsi que les coûts de prise en charge des patients.;
Des travaux précédemment publiés par notre équipe ont montré que la viabilité des cellules cancéreuses situées dans notre modèle de tumeur ex vivo pouvait être caractérisée par microscopie confocale sur l’intégralité du MDT ou par cytométrie de flux sur les MDTs après dissociation enzymatique des cellules. Cependant, ces techniques présentent des limitations en termes de résolution visuelle pour la microscopie confocale et de sensibilité et information spatiale pour la cytométrie de flux. Nous proposons ici d’associer notre modèle 3D de MDTs en microfluidiques à des techniques d’immuno-histopathologie, dans le but d’offrir une évaluation moléculaire, spatiale et quantitative de la réponse de la tumeur au traitement. Pour cela, nous avons optimisé une procédure de lithographie en paraffine de nos systèmes microfluidiques, permettant la production de blocs de micro-étalages micro-réseaux de tissus micro-disséqués (MDTMA). afin de permettre une coloration morphologique du tissu et un marquage de protéines spécifiques pour analyser l'architecture tissulaire, la prolifération et l’apoptose cellulaire au sein des échantillons traités. En outre, nous avons montré que le modèle ex vivo est comparable et corrélé au système de modèle de souris in vivo de référence pour l'essai de chimio-sensibilité. Suite à l’optimisation de ce modèle, nous avons collecté 25 échantillons de tumeurs de patientes atteintes de cancer de l’ovaire, pour réaliser des MDTs et des cultures de cellules primaires afin de comparer les profils transcriptomiques de ces deux modèles avec celui de la tumeur d’origine, et d'analyser les réponses aux traitements et le microenvironnement tumoral. ;
Les données transcriptomiques obtenues par micropuces ARN nous ont permis d'effectuer une analyse bio-informatique des voies de signalisation incluant un groupement hiérarchique non supervisé. Nos résultats montrent que les MDT à chaque point de temps (jour 0, 8 et 15) sont génétiquement similaires à la tumeur primaire par opposition aux cultures cellulaires primaires, et que les principales voies dérégulées sont impliquées dans la réponse cellulaire au stress. Nous avons observé une viabilité élevée des cellules au sein des MDT sur une période de culture de 15 jours. En outre, nous avons déterminé qu'un régime de chimiothérapie (carboplatine et paclitaxel) consistant en une induction thérapeutique de 10 heures suivie d'une période de récupération de 14 heures était idéal pour caractériser la réponse au traitement. Notre analyse de prédiction de la réponse des patients montre que nous avons une corrélation positive élevée d'une efficacité de 95 % entre la réponse ex vivo et la réponse clinique pour les patients appariés. En général, nos résultats suggèrent que notre technique fournit un modèle plus sophistiqué et précis pour récapituler la réponse de la tumeur primaire dans un laps de temps cliniquement adapté, et pourrait servir de plateforme pour tester de nouvelles thérapeutiques, et d'outil d'orientation clinique pour la réponse des patients.
A major challenge in clinical oncology is the inability to accurately predict the patients’ response to therapeutic agents. Currently, there are no reliable models and assays available that reiterate the immense complexity of a primary tumor. These factors are important to implement a personalized medicine strategy capable of identifying the most suitable treatment regimen for a particular patient in a clinically relevant timeframe. To answer this need, our group has developed a novel ex vivo 3D model that relies on the micro-dissection of a patient’s tumor specimen and the utilization of microfluidic technologies to monitor drug sensitivity within a time-frame suitable for clinical decision-making. This approach would allow for better selection of effective therapies and limit the administration of ineffective treatments, further improving treatment outcome of patients while reducing cost and drug-induced toxicities.;
Previously published work studied that the viability of cancer cells located within the tumor was characterized using two imaging modalities: confocal microscopy and flow cytometry. However, each technique has its own disadvantage, limiting their ability to molecularly characterize the effect of therapeutic agents on cancer cells. Thus, we hypothesize that our 3D ex vivo tumor-derived model coupled to a pathology-like tool would allow for a more comprehensive approach to evaluate tumor response to treatment, providing a readout system to closely mirror the patient’s response, and evaluating molecular mechanisms involved in response to drugs. To address this hypothesis, we optimized a paraffin-embedding lithography procedure allowing the production of micro-dissected tissue micro-array (MDTMA) block to allow morphological and protein-specific staining to analyze the cellular integrity and tissue architecture of treated samples. In addition, we showed that ex vivo model is comparable and correlated to the gold standard in vivo mouse model system for chemosensitivity assay. Moreover, we collected, following informed consent, 25 post-surgical OC patient tumor samples, to form micro-dissected tissues (MDTs), and primary cell cultures for micro-array analysis and characterization of the TME and response prediction. ;
The micro-array data allowed us to perform unsupervised hierarchical clustering and pathway analysis showing that the MDTs at each time-point (day 0, 8 and 15) are genetically similar to the primary tumor as opposed to the primary cell cultures and that main deregulated pathways are involved in cellular response to stress. We observed a high viability of cells within MDTs over a culture period of 15 days. In addition, we determined that a treatment regimen consisting of a 10-hour therapy induction followed by a 14-hour recovery period was ideal for characterizing carboplatin treatment response. Our response prediction analysis of patients shows that we have a high positive correlation of 95% efficiency between ex vivo and clinical response for matched patients. In general, our results suggest that our ex vivo drug response model provides a more sophisticated model to recapitulate primary tumor response in a clinically suitable timeframe that can be exploited further serving, in part, as a platform to test new therapeutics and as a clinical guidance tool for patient response.
Antidepressants are commonly used during pregnancy, but limited information is available about individual antidepressants and specific birth defect risks.
To examine associations between individual ...antidepressants and specific birth defects with and without attempts to partially account for potential confounding by underlying conditions.
The population-based, multicenter case-control National Birth Defects Prevention Study (October 1997-December 2011) included cases with selected birth defects who were identified from surveillance systems; controls were randomly sampled live-born infants without major birth defects. Mothers of cases and controls participated in an interview after the expected delivery date. The data were analyzed after the completion of the National Birth Defects Prevent Study's data collection.
Self-reported antidepressant exposure was coded to indicate monotherapy exposure to antidepressants.
We used multivariable logistic regression to calculate adjusted odds ratios (aORs) and 95% confidence intervals for associations between maternal antidepressant use and birth defects. We compared early pregnancy antidepressant-exposed women with those without antidepressant exposure and, to partially account for confounding by underlying maternal conditions, those exposed to antidepressants outside of the birth defect development critical period.
This study included 30 630 case mothers of infants with birth defects and 11 478 control mothers (aged 12-53 years). Early pregnancy antidepressant use was reported by 1562 case mothers (5.1%) and 467 control mothers (4.1%), for whom elevated aORs were observed for individual selective serotonin reuptake inhibitors (SSRIs) and selected congenital heart defects (CHD) (eg, fluoxetine and anomalous pulmonary venous return: aOR, 2.56; 95% CI, 1.10-5.93; this association was attenuated after partially accounting for underlying conditions: aOR, 1.89; 95% CI, 0.56-6.42). This pattern was observed for many SSRI-CHD combinations. Associations between SSRIs and non-CHD birth defects often persisted or strengthened after partially accounting for underlying conditions (eg, citalopram and diaphragmatic hernia: aOR, 5.11; 95% CI, 1.29-20.24). Venlafaxine had elevated associations with multiple defects that persisted after partially accounting for underlying conditions (eg, anencephaly and craniorachischisis: aOR, 9.14; 95% CI, 1.91-43.83).
We found some associations between maternal antidepressant use and specific birth defects. Venlafaxine was associated with the highest number of defects, which needs confirmation given the limited literature on venlafaxine use during pregnancy and risk for birth defects. Our results suggest confounding by underlying conditions should be considered when assessing risk. Fully informed treatment decision-making requires balancing the risks and benefits of proposed interventions against those of untreated depression or anxiety.
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