Abstract 5775: A unique 3D tissue-engineered human melanoma model combining lymphatic and blood microvasculature to study cancer cell dissemination
Notice bibliographique
Résumé
Abstract INTRODUCTION: Melanoma is amongst malignancies with constantly increasing incidence in developed countries. One of the underlying causes of death for patients diagnosed with melanoma is metastasis, which can spread through lymphatic or blood vessels. Mechanisms controlling the dissemination paths are poorly understood and relevant models for studying metastasis physiopathology are often inadequate. To address this, we hypothesized that the human tumor microenvironment can be mimicked in vitro by combining tissue-engineered microvascularized skin and melanoma microtissues. METHODS: Tissue-engineered skin was produced using primary dermal, epidermal and microvascular endothelial cells by the self-assembly technique without any exogenous biomaterial. Tumor microtissues were produced using the hanging drop method. Six melanoma cell lines were used originating from primary tumor sites (A375, SK-MEL 28 and WM983a) and from metastatic sites (RPMI 7951, Malme 3M and WM983b). Tumor development and growth were assessed by histology, immunofluorescence and confocal microscopy, while cytokine secretion profiles were determined by ELISA. WM983a and WM983b models were treated for 11 days with vemurafenib. Response to treatment was assessed by counting the ratio of tumor cells positive for Ki67, representative of the tumor proliferation. RESULTS: We obtained a tissue-engineered skin displaying two distinct microvascular networks: a VE-cadherin+ CD31+ blood network, and a PDPN+ LYVE-1+ CD31+ lymphatic network. Blood capillaries were thin and highly connected whereas lymphatic capillaries were larger and presented a distinct morphology. Histological analyses revealed tumor microtissue integration at the dermoepidermal junction within the reconstructed skin. The pro-lymphangiogenic factor and tumor-secreted VEGF-C was detected in conditioned media from the melanoma microtissues (662 pg/ml). Furthermore, CCL21, a chemoattractant known to be secreted by lymphatic endothelial cells, displayed secretion levels that were 10-fold higher in microvascularized tissues compared to the non-microvascularized skin (P ≤ 0.001). Both of these cytokines are involved in the cross-talk between tumor cells and capillaries, and thus in tumor dissemination. The 3D melanoma model responded to vemurafenib with up to a 5-fold decrease of tumor cell proliferation and a partial pigmentation of the tumor. CONCLUSION: This unique 3D in vitro melanoma model mimics tumor microenvironment by combining blood and lymphatic capillaries with melanoma microtissues in a reconstructed skin. Being responsive to treatment such as vemurafenib, it represents a valuable tool for studying mechanisms of metastasis and drug response in a fully human cell and matrix microenvironment, and thus testing anti-metastatic compounds could better predict their safety and efficacy. Citation Format: Jennifer Bourland, Julie Fradette, François A. Auger. A unique 3D tissue-engineered human melanoma model combining lymphatic and blood microvasculature to study cancer cell dissemination [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5775. doi:10.1158/1538-7445.AM2017-5775
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».