Abstract 217: Establishment of a spatially defined co-culture model of non-small cell lung cancer organoids and cancer-associated fibroblasts to investigate phenotypic heterogeneity
Notice bibliographique
Résumé
Abstract Background: Cancer-associated fibroblasts (CAFs) are heterogeneous, with CAF subtypes being localized in spatially defined areas of tumors. However, it remains unclear which CAF subsets specifically play a role in fundamental processes such as tumor growth, invasion, and response to therapy. This study aims to establish a novel in vitro model that recapitulates the in vivo tumor-stroma spatial relationship to investigate CAF heterogeneity and its impact on tumor cell growth in non-small cell lung cancer (NSCLC). Methods: The in vitro model was established using NSCLC patient-derived CAFs and tumor organoids as a 6:1 ratio. Tumor cells originating from xenograft-derived organoids (XDOs) were embedded in a hydrogel containing CAFs (Day 0) and co-cultured for 5 days. Confocal microscopy was utilized to characterize and measure the proliferation of the XDO tumor cells in the co-culture setup, and the proliferation rate was defined as differences in tumor spheroid area between Day 1 and 5. Single-cell RNA-sequencing (scRNAseq) and gene set enrichment analysis (GSEA) were then used to assess the gene expression and signaling pathways dominant in mono- and co-culture to characterize CAF heterogeneity in this model. Results: Initially, the culture media formulations and the matrix for the growth of both CAFs and tumor cells were screened to assess the compatibility of different culture elements. Both CAFs and XDO tumor cells proliferated well in reduced organoid media (M27RD). This reduced medium and the novel matrix composition (50% Matrigel/50% Rat Tail type I collagen) also allowed for maintaining CAF contractility and XDO proliferation. Utilizing these harmonized media and matrix conditions, a spatially defined co-culture model, which incorporated XDOs as a central cluster surrounded by CAFs, was generated. In confocal microscopy, the proliferation rate of tumor cells was significantly higher in co-cultures with CAFs (adjusted p-value < 0.01), while not significant in mono-culture of tumor cells. The GSEA using the Hallmark gene sets on scRNAseq data generated in three co-cultures identified the heterogeneity among CAFs: two CAFs showed significantly higher effect on tumor cell proliferation with the most highly differential expressed genes (DEGs) enriched with inflammation and mitosis and the top high DEGs associated with epithelial-mesenchymal transition, while the other CAF has no effect. Conclusion: The harmonized co-culture conditions for NSCLC organoids and CAFs enabled the characterization of both cell phenotypes and the building of an informed model architecture to study tumor-stroma communication. The presence of CAFs increased tumor cell growth with enrichment in secreted proteins involved in epithelial-mesenchymal transition. Citation Format: Cheol-Kyu Park, Roya Navab, Elisa D'Arcangelo, Quan Li, Hiroyuki Ogawa, Nikolina Radulovich, Nhu-An Pham, Ming-Sound Tsao. Establishment of a spatially defined co-culture model of non-small cell lung cancer organoids and cancer-associated fibroblasts to investigate phenotypic heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 217.
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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».