7 results on '"Morel, Mehdi"'
Search Results
2. Adipocytes secretome from normal and tumor breast favor breast cancer invasion by metabolic reprogramming
- Author
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Zaoui, Maurice, Morel, Mehdi, Louadj, Lila, Ferrand, Nathalie, Lamazière, Antonin, Uzan, Catherine, Canlorbe, Geoffroy, Atlan, Michael, and Sabbah, Michèle
- Published
- 2023
- Full Text
- View/download PDF
3. Abstract 5430: Improved colorectal cancer survival prediction with deep learning-based WSI analysis on PETACC8 and PRODIGE13 cohorts
- Author
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Douget, Jean-Eudes Le, primary, Taïeb, Julien, additional, Jacob, Paul, additional, Bibeau, Frédéric, additional, Malicot, Karine Le, additional, Emile, Jean-François, additional, de Reyniès, Aurélien, additional, Morel, Mehdi, additional, Jégou, Simon, additional, Lepage, Côme, additional, and Laurent-Puig, Pierre, additional
- Published
- 2023
- Full Text
- View/download PDF
4. Adipocytes secretome from normal and tumor breast favor breast cancer invasion by metabolic reprogramming
- Author
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Zaoui, Maurice, primary, Morel, Mehdi, additional, Louadj, Lila, additional, Ferrand, Nathalie, additional, Lamazière, Antonin, additional, Uzan, Catherine, additional, Canlorbe, Geoffroy, additional, Atlan, Michael, additional, and Sabbah, Michèle, additional
- Published
- 2022
- Full Text
- View/download PDF
5. Dialogue between mammary tumour cells and adipose cells : involvement of the fatty acid transporter CD36
- Author
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Morel, Mehdi, Centre de Recherche Saint-Antoine (CRSA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Sorbonne Université, Michèle Sabbah, and STAR, ABES
- Subjects
Breast cancer ,Microenvironment ,Acides gras ,[SDV.CAN] Life Sciences [q-bio]/Cancer ,Adipocytes ,Adipose tissue ,[SDV.CAN]Life Sciences [q-bio]/Cancer ,[SDV.BC]Life Sciences [q-bio]/Cellular Biology ,CD36 ,Métastases ,[SDV.BC] Life Sciences [q-bio]/Cellular Biology ,Cancer du sein ,Microenvironnement - Abstract
Breast cancer is the most common cancer in women worldwide.The breast consists of a mammary gland organised into ducts and lobules and surrounded by a stromal fraction, mostly composed of adipose tissue. Breast tumours derive from epithelial cells of the mammary gland, and develop in a stroma, rich in adipose tissue, with which there is dynamic and reciprocal communication via secreted factors.Many risk factors increase the incidence of breast cancer. Using breast adipocytes from human samples, differentiated in vitro, we show in this work that obesity, menopausal status, and breast density have no local effect in the dialogue between breast adipocytes and breast tumour cells. We also show that mammary adipocytes release fatty acids which can be captured by mammary tumour cells, via the CD36 transporter, stimulating their growth and invasion. Our work also shows that the expression of CD36 is sufficient to induce these effects, and to activate the fatty acid oxidation pathway in vitro. Understanding the mechanisms induced by CD36 on the aggressiveness of tumour cells will allow us to consider this protein as a biomarker or a therapeutic target in breast cancer., Le cancer du sein est le cancer le plus fréquent chez la femme dans le monde. Le sein se compose d’une glande mammaire organisée en canaux et lobules et entourée d’une fraction stromale, majoritairement composée de tissu adipeux. Les tumeurs mammaires dérivent des cellules épithéliales de la glande mammaire, et se développent dans un stroma riche en tissu adipeux, avec lequel il existe une communication dynamique et réciproque via des facteurs secrétés. De nombreux facteurs de risque augmentent l’incidence des cancers du sein. En utilisant des adipocytes mammaires issus de prélèvement humains, différenciés in vitro, nous montrons dans ces travaux que l’obésité, le statut ménopausique, et la densité mammaire, n’ont pas d’effet local dans le dialogue entre adipocytes mammaires et cellules tumorales mammaires. Nous montrons également que les adipocytes mammaires libèrent des acides gras qui peuvent être captés par les cellules tumorales mammaires, via le transporteur CD36, stimulant leur croissance et leur invasion. Nos travaux montrent aussi que l’expression de CD36 suffit à induire ces effets, et à activer la voie d’oxydation des acides gras in vitro. La compréhension des mécanismes qu’induit CD36 sur l’agressivité des cellules tumorales permettra d’envisager cette protéine comme un biomarqueur ou une cible thérapeutique dans les cancers du sein.
- Published
- 2021
6. Breast-Associated Adipocytes Secretome Induce Fatty Acid Uptake and Invasiveness in Breast Cancer Cells via CD36 Independently of Body Mass Index, Menopausal Status and Mammary Density
- Author
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Zaoui, Maurice, Morel, Mehdi, Ferrand, Nathalie, Fellahi, Soraya, Bastard, Jean-Philippe, Lamazière, Antonin, Larsen, Annette Kragh, Béréziat, Véronique, Atlan, Michael, Sabbah, Michèle, Centre de Recherche Saint-Antoine (CR Saint-Antoine), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Service de biochimie et hormonologie [CHU Tenon], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire des biomolécules (LBM UMR 7203), Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Département de Chimie - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Chimie Moléculaire de Paris Centre (FR 2769), Institut de Chimie du CNRS (INC)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Paris - Chimie ParisTech-PSL (ENSCP), Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), and Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
adiposity ,breast cancer ,[SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology ,[SDV.CAN]Life Sciences [q-bio]/Cancer ,body mass index ,mammary density ,fatty acid ,[SDV.MHEP.GEO]Life Sciences [q-bio]/Human health and pathology/Gynecology and obstetrics ,CD36 ,Article ,ComputingMilieux_MISCELLANEOUS ,menopausal status - Abstract
International audience; Breast adiposity is correlated with body mass index, menopausal status and mammary density. We here wish to establish how these factors influence the cross-talk between breast adipocytes and normal or malignant breast cells. Adipocyte-derived stem cells (ASCs) were obtained from healthy women and classified into six distinct groups based on body mass index, menopausal status and mammary density. The ASCs were induced to differentiate, and the influence of their conditioned media (ACM) was determined. Unexpectedly, there were no detectable differences in adipogenic differentiation and secretion between the six ASC groups, while their corresponding ACMs had no detectable influence on normal breast cells. In clear contrast, all ACMs profoundly influenced the proliferation, migration and invasiveness of malignant breast cells and increased the number of lipid droplets in their cytoplasm via increased expression of the fatty acid receptor CD36, thereby increasing fatty acid uptake. Importantly, inhibition of CD36 reduced lipid droplet accumulation and attenuated the migration and invasion of the breast cancer cells. These findings suggest that breast-associated adipocytes potentiate the invasiveness of breast cancer cells which, at least in part, is mediated by metabolic reprogramming via CD36-mediated fatty acid uptake.
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- 2019
- Full Text
- View/download PDF
7. MYCRearrangement Prediction From LYSA Whole Slide Images in Large B-Cell Lymphoma: A Multicentric Validation of Self-supervised Deep Learning Models
- Author
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Syrykh, Charlotte, Di Proietto, Valentina, Brion, Eliott, Copie-Bergman, Christiane, Jardin, Fabrice, Dartigues, Peggy, Gaulard, Philippe, Molina, Thierry Jo, Briere, Josette, Oberic, Lucie, Haioun, Corine, Tilly, Hervé, Maussion, Charles, Morel, Mehdi, Schiratti, Jean-Baptiste, and Laurent, Camille
- Abstract
Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYCgene rearrangement (MYC-R) is associated with a poor prognosis, prompting the recommendation for more intensive treatment. MYC-R detection relies on fluorescence in situ hybridization method which is time consuming, expensive, and not available in all laboratories. Automating MYC-R detection on hematoxylin-and-eosin–stained whole slide images of LBCL would decrease the need for costly molecular testing and improve pathologists’ productivity. We developed an interpretable deep learning algorithm to detect MYC-R considering recent advances in self-supervised learning and providing an extensive comparison of 7 feature extractors and 6 multiple instance learning models, themselves. Four different multicentric cohorts, including 1247 patients with LBCL, were used for training and validation. The best deep learning model reached an average area under the receiver operating characteristic curve score of 81.9% during crossvalidation on the largest LBCL cohort, and area under the receiver operating characteristic curve scores ranging from 62.2% to 74.5% when evaluated on other unseen cohorts. In addition, we demonstrated that using this model as a prescreening tool (with a false-negative rate of 0%), fluorescence in situ hybridization testing would be avoided in 35% of cases. This work demonstrates the feasibility of developing a medical device to efficiently detect MYCgene rearrangement on hematoxylin-and-eosin–stained whole slide images in daily practice.
- Published
- 2024
- Full Text
- View/download PDF
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