Effects of Anticancer Agents on Immune Responses

Les thérapies anticancéreuses ont apporté un gain largement reconnu en matière de réduction de la charge tumorale, de survie des patients et d’amélioration de leur qualité de vie, dans un certain nombre de cancers. Hélas, ces thérapies exercent un effet immunosuppresseur en détruisant les effecteurs ou en bloquant l’activité de certains facteurs biologiques impliqués dans le recrutement des acteurs du système immunitaire. D’autre part, plusieurs travaux ont permis de démontrer que ces traitements pouvaient avoir un effet contraire en générant ou en favorisant l’induction d’une réponse immunitaire anti-tumorale, soit par effet direct sur le recrutement et l’activation des effecteurs de l’immunité, soit en potentialisant les interactions cellulaires par des mécanismes biologiques. Ces derniers faisant intervenir les cytokines, la stimulation des TLR, l’augmentation des interactions entre cellules du SI; ce qui permet de passer d’une anergie immunologique vers un véritable système d’éradication des cellules cancéreuses.Dans notre laboratoire, nous avons essayé d’évaluer l’implication du système immunitaire dans la réponse thérapeutique induite par des agents cytotoxiques conventionnels. Ici, nous décrivons les effets d’un inhibiteur de cyclines kinases multi-cibles « CDKi PHA-793 887 » testé dans un essai de phase I mené sur deux sites en Europe. C’est le constat inattendu que 6 des 15 patients, traités par ce médicament (PHA-793887) ont développé de graves infections bactériennes et virales et que 6 d’entre eux ont présenté la réactivation du virus de l’herpès qui nous a conduit à étudier ces effets sur le système immunitaire et en particulier sur le dialogue entre cellules dendritiques (CD) et cellules natural killer (NK). Ce travail met en évidence que ce médicament inhibe le signalling des récepteurs toll-like (TLR) réduisant par conséquent l’interaction CD/NK in vitro. Enfin la stimulation des cellules des patients sous traitement démontre une réduction importante de ce signalling ex-vivo. Ainsi, cet effet immunosuppresseur inattendu a permis une réactivation virale chez 40% des patients. La deuxième partie de ce travail, concerne les effets du cyclophosphamide (CTX) utilisé à faible dose. L’injection d'une faible dose chez la souris ou d’un dosage métronomique chez l'homme, promeut la différenciation des cellules lymphocytaires vers Th17 (sécrétant de l’interleukine-17 (IL-17)) et Th1 (sécrétant de l’interféron-γ (IFN)). Ceux-ci ont été retrouvés dans le sang et dans des ascites carcinomateuses de patients. Ainsi, le CTX pourrait participer à la génération de réponses anti-tumorale via la différenciation Th 17 comme cela fut suggéré par de récentes études précliniques montrant l’existence d’une corrélation étroite entre le taux des lymphocytes Th17 infiltrant la tumeur et la destruction tumorale.Cancer therapies have made a gain widespread recognition in the reduction of tumor burden, patient survival and improved quality of life in a number of cancers. Unfortunately, these therapies exert an immunosuppressive effect by killing effectors or blocking the activity of certain biological factors involved in recruiting of the immune system. On the other hand, several studies have shown that these treatments could have the opposite effect by generating or promoting the induction of antitumor immune response, either by direct effect on the recruitment and activation of effectors immunity, either by potentiating cellular interactions by biological mechanisms. The latter involving cytokines, TLR stimulation, increased interactions between cells of the IS; which toggles between immunological anergy to a real system to eradicate cancer cells. In our laboratory, we tried to evaluate the involvement of the immune system in the therapeutic response induced by conventional cytotoxic agents. Here, we describe the effects of an inhibitor of cyclin kinases multi-target "CDKIs PHA-793887" tested in a phase I trial conducted at two sites in Europe. This unexpected finding is that 6 of 15 patients treated with this drug (PHA-793887) developed severe bacterial and viral infections and six of them showed reactivation of the herpes virus that has led us to study these effects on the immune system and in particular on the dialogue between dendritic (DCs) and natural killer (NK) cells. This work shows that this drug inhibits the signaling of toll-like receptor (TLR) thereby reducing the interaction DC / NK in vitro. Finally, stimulation of the cells of treated patients demonstrated a significant reduction of this signaling ex vivo. Thus, this immunosuppressive effect has an unexpected viral reactivation in 40% of patients. The second part of this work concerns the effects of metronomic dose of cyclophosphamide (CTX). The injection of a low dose in mice or metronomic dosing in humans, markedly promotes the differentiation of CD4+ T helper 17 (Th17) cells that can be recovered in both blood and tumor beds. However, CTX does not convert regulatory T cells into Th17 cells and promotes cell differentiation into Th17 lymphocytes (secreting interleukin-17 (IL-17)) and Th1 (secreting interferon-γ (IFN)). These were found in blood and in ascites carcinoma patients. Thus, CTX may participate in the generation of antitumor responses through Th 17 differentiation as was suggested by recent preclinical studies showing the existence of a correlation between the rate of Th17 lymphocytes infiltrating the tumor and tumor destruction

Traitement anticancéreux et modulation du système immunitaire

Les thérapies anticancéreuses ont apporté un gain largement reconnu en matière de réduction de la charge tumorale, de survie des patients et d amélioration de leur qualité de vie, dans un certain nombre de cancers. Hélas, ces thérapies exercent un effet immunosuppresseur en détruisant les effecteurs ou en bloquant l activité de certains facteurs biologiques impliqués dans le recrutement des acteurs du système immunitaire. D autre part, plusieurs travaux ont permis de démontrer que ces traitements pouvaient avoir un effet contraire en générant ou en favorisant l induction d une réponse immunitaire anti-tumorale, soit par effet direct sur le recrutement et l activation des effecteurs de l immunité, soit en potentialisant les interactions cellulaires par des mécanismes biologiques. Ces derniers faisant intervenir les cytokines, la stimulation des TLR, l augmentation des interactions entre cellules du SI; ce qui permet de passer d une anergie immunologique vers un véritable système d éradication des cellules cancéreuses.Dans notre laboratoire, nous avons essayé d évaluer l implication du système immunitaire dans la réponse thérapeutique induite par des agents cytotoxiques conventionnels. Ici, nous décrivons les effets d un inhibiteur de cyclines kinases multi-cibles CDKi PHA-793 887 testé dans un essai de phase I mené sur deux sites en Europe. C est le constat inattendu que 6 des 15 patients, traités par ce médicament (PHA-793887) ont développé de graves infections bactériennes et virales et que 6 d entre eux ont présenté la réactivation du virus de l herpès qui nous a conduit à étudier ces effets sur le système immunitaire et en particulier sur le dialogue entre cellules dendritiques (CD) et cellules natural killer (NK). Ce travail met en évidence que ce médicament inhibe le signalling des récepteurs toll-like (TLR) réduisant par conséquent l interaction CD/NK in vitro. Enfin la stimulation des cellules des patients sous traitement démontre une réduction importante de ce signalling ex-vivo. Ainsi, cet effet immunosuppresseur inattendu a permis une réactivation virale chez 40% des patients. La deuxième partie de ce travail, concerne les effets du cyclophosphamide (CTX) utilisé à faible dose. L injection d'une faible dose chez la souris ou d un dosage métronomique chez l'homme, promeut la différenciation des cellules lymphocytaires vers Th17 (sécrétant de l interleukine-17 (IL-17)) et Th1 (sécrétant de l interféron-g (IFN)). Ceux-ci ont été retrouvés dans le sang et dans des ascites carcinomateuses de patients. Ainsi, le CTX pourrait participer à la génération de réponses anti-tumorale via la différenciation Th 17 comme cela fut suggéré par de récentes études précliniques montrant l existence d une corrélation étroite entre le taux des lymphocytes Th17 infiltrant la tumeur et la destruction tumorale.Cancer therapies have made a gain widespread recognition in the reduction of tumor burden, patient survival and improved quality of life in a number of cancers. Unfortunately, these therapies exert an immunosuppressive effect by killing effectors or blocking the activity of certain biological factors involved in recruiting of the immune system. On the other hand, several studies have shown that these treatments could have the opposite effect by generating or promoting the induction of antitumor immune response, either by direct effect on the recruitment and activation of effectors immunity, either by potentiating cellular interactions by biological mechanisms. The latter involving cytokines, TLR stimulation, increased interactions between cells of the IS; which toggles between immunological anergy to a real system to eradicate cancer cells. In our laboratory, we tried to evaluate the involvement of the immune system in the therapeutic response induced by conventional cytotoxic agents. Here, we describe the effects of an inhibitor of cyclin kinases multi-target "CDKIs PHA-793887" tested in a phase I trial conducted at two sites in Europe. This unexpected finding is that 6 of 15 patients treated with this drug (PHA-793887) developed severe bacterial and viral infections and six of them showed reactivation of the herpes virus that has led us to study these effects on the immune system and in particular on the dialogue between dendritic (DCs) and natural killer (NK) cells. This work shows that this drug inhibits the signaling of toll-like receptor (TLR) thereby reducing the interaction DC / NK in vitro. Finally, stimulation of the cells of treated patients demonstrated a significant reduction of this signaling ex vivo. Thus, this immunosuppressive effect has an unexpected viral reactivation in 40% of patients. The second part of this work concerns the effects of metronomic dose of cyclophosphamide (CTX). The injection of a low dose in mice or metronomic dosing in humans, markedly promotes the differentiation of CD4+ T helper 17 (Th17) cells that can be recovered in both blood and tumor beds. However, CTX does not convert regulatory T cells into Th17 cells and promotes cell differentiation into Th17 lymphocytes (secreting interleukin-17 (IL-17)) and Th1 (secreting interferon-g (IFN)). These were found in blood and in ascites carcinoma patients. Thus, CTX may participate in the generation of antitumor responses through Th 17 differentiation as was suggested by recent preclinical studies showing the existence of a correlation between the rate of Th17 lymphocytes infiltrating the tumor and tumor destruction.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Crack recognition automation in concrete bridges using Deep Convolutional Neural Networks

Using Unmanned Aerial Systems (UASs) for bridge visual inspection automation necessitates the implementation of Deep Convolutional Neural Networks (DCNNs) to process efficiently the large amount of data collected by the UASs sensors. However, these networks require massive training datasets for the defects recognition and detection tasks. In an effort to expand existing concrete defects datasets, particularly concrete cracks in bridges, this paper proposes a public benchmark annotated image dataset containing over 6900 images of cracked and non cracked concrete bridges and culverts. The presented dataset includes some challenging surface conditions and covers concrete cracks with different sizes and patterns. The authors analyzed the proposed dataset using three state of the art DCNNs in Transfer Learning mode. The three models were used to classify the cracked and non cracked images and the best testing accuracy obtained reached 95.89%. The experimental results showcase the potential use of this dataset to train deep networks for concrete crack recognition in bridges. The dataset is publicly available at https://github.com/MCBDD-ZRE/Concrete-Bridge-Crack-Dataset

Concrete Bridge Crack Image Classification Using Histograms of Oriented Gradients, Uniform Local Binary Patterns, and Kernel Principal Component Analysis

Bridges deteriorate over time, which requires the continuous monitoring of their condition. There are many digital technologies for inspecting and monitoring bridges in real-time. In this context, computer vision has extensively studied cracks to automate their identification in concrete surfaces, overcoming the conventional manual methods that rely on human judgment. The general framework of vision-based techniques consists of feature extraction using different filters and descriptors and classifier training to perform the classification task. However, training can be time-consuming and computationally expensive, depending on the dimension of the features. To address this limitation, dimensionality reduction techniques are applied to extracted features, and a new feature subspace is generated. This work used histograms of oriented gradients (HOGs) and uniform local binary patterns (ULBPs) to extract features from a dataset containing over 3000 uncracked and cracked images covering different patterns of cracks and concrete surface representations. Nonlinear dimensionality reduction was performed using kernel principal component analysis (KPCA), and three machine learning classifiers were implemented to conduct the classification. The experimental results show that the classification scheme based on the support-vector machine (SVM) model and feature-level fusion of the HOG and ULBP features after KPCA application provided the best results as an accuracy of 99.26% was achieved by the proposed classification framework

Concrete Bridge Crack Image Classification Using Histograms of Oriented Gradients, Uniform Local Binary Patterns, and Kernel Principal Component Analysis

Bridges deteriorate over time, which requires the continuous monitoring of their condition. There are many digital technologies for inspecting and monitoring bridges in real-time. In this context, computer vision has extensively studied cracks to automate their identification in concrete surfaces, overcoming the conventional manual methods that rely on human judgment. The general framework of vision-based techniques consists of feature extraction using different filters and descriptors and classifier training to perform the classification task. However, training can be time-consuming and computationally expensive, depending on the dimension of the features. To address this limitation, dimensionality reduction techniques are applied to extracted features, and a new feature subspace is generated. This work used histograms of oriented gradients (HOGs) and uniform local binary patterns (ULBPs) to extract features from a dataset containing over 3000 uncracked and cracked images covering different patterns of cracks and concrete surface representations. Nonlinear dimensionality reduction was performed using kernel principal component analysis (KPCA), and three machine learning classifiers were implemented to conduct the classification. The experimental results show that the classification scheme based on the support-vector machine (SVM) model and feature-level fusion of the HOG and ULBP features after KPCA application provided the best results as an accuracy of 99.26% was achieved by the proposed classification framework

Concrete Bridge Defects Identification and Localization Based on Classification Deep Convolutional Neural Networks and Transfer Learning

Conventional practices of bridge visual inspection present several limitations, including a tedious process of analyzing images manually to identify potential damages. Vision-based techniques, particularly Deep Convolutional Neural Networks, have been widely investigated to automatically identify, localize, and quantify defects in bridge images. However, massive datasets with different annotation levels are required to train these deep models. This paper presents a dataset of more than 6900 images featuring three common defects of concrete bridges (i.e., cracks, efflorescence, and spalling). To overcome the challenge of limited training samples, three Transfer Learning approaches in fine-tuning the state-of-the-art Visual Geometry Group network were studied and compared to classify the three defects. The best-proposed approach achieved a high testing accuracy (97.13%), combined with high F1-scores of 97.38%, 95.01%, and 97.35% for cracks, efflorescence, and spalling, respectively. Furthermore, the effectiveness of interpretable networks was explored in the context of weakly supervised semantic segmentation using image-level annotations. Two gradient-based backpropagation interpretation techniques were used to generate pixel-level heatmaps and localize defects in test images. Qualitative results showcase the potential use of interpretation maps to provide relevant information on defect localization in a weak supervision framework