A123 CNON-SHERBROOKE NODE: ADVANCING COLORECTAL CANCER RESEARCH WITH ORGANOIDS
Notice bibliographique
Résumé
Abstract Background Colorectal cancer (CRC) is a major global health issue and the second most common cancer in Canada. Human cancer cell lines have served as the main model for CRC research; however, they do not adequately capture the complexity and heterogeneity of tumors. In the past decade, 3D in vitro models, known as organoids, have emerged as more accurate representations of organs’ structure and function. In cancer research, patient-derived organoids (PDOs) provide an ideal model that mimic the heterogeneity and clinical progression of the disease. However, fine-tuning this model needs numerous optimizations, which differ between laboratories and affect the reproducibility of the data. Additionally, accessing patient tissue for PDOs remains a significant challenge. Aims The Canadian National Organoid Network (CNON), a multicentric (the University of British Colombia, University of Calgary & Université de Sherbrooke) national project supported by the Weston Family Foundation, was established to address these challenges. The Sherbrooke node is focused on building a biobank of CRC PDOs, using both tumor and healthy tissues from each patient to enable comparative studies. These PDOs, grown in various media, demonstrate differing growth patterns reflective of CRC heterogeneity. Methods CNON Sherbrooke node, also focuses on optimizing advanced methodologies for human intestinal organoids to delve deeper into the biology of CRC and its clinical applications. Results CRC arises from the accumulation of genetic mutations, yet the exact role of these mutations in cancer development remains unclear. To address this gap, we refine a comprehensive array of gene-editing tools, including CRISPR/Cas9, base editing, and prime editing, tailored for human intestinal organoids. This approach aims to produce organoids models that accurately reflect the genetic diversity and phenotypes associated with CRC, thereby enhancing the potential for personalized medicine. Furthermore, the tumor microenvironment (TME) plays a crucial role in cancer progression, but its interactions with cancer cells and the immune system are poorly understood. To better simulate the TME, CNON-Sherbrooke node integrates organ-on-a-chip systems that combine multiple cell types. This innovative approach provides a better understanding of the TME’s involvement in the context of CRC for drug screening, and the development of precise therapies. Conclusions In conclusion, the CNON-Sherbrooke node aims at first to enhance the accessibility of CRC-PDOs to the scientific community by optimizing and standardizing culture methods. Additionally, we seek to develop technological tools for CRC-PDOs. By combining organoids with genome editing and microfluidic systems, we aim to contribute to fundamental and translational research, drug discovery, and other CRC-related fields, ultimately enhancing the landscape of personalized medicine. Funding Agencies The Weston Family Foundation, IRCUS (Institut de Recherche sur le Cancer de l’Université de Sherbrooke)
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,000 | 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 tête enseignante, 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 ».