Tumor organoids in translational cancer research: Models for personalized therapy
Le résumé fourni par la source
BACKGROUND Tumor organoids are 3D cell culture models derived from patient tumor tissues that replicate the complexity of the tumor microenvironment (TME). These models preserve the genetic and phenotypic features of the original tumor, making them superior to traditional 2D cultures and xenografts for cancer research. AIM To explore the role of tumor organoids in translational cancer research, with a focus on their applications in personalized therapy and drug testing. METHODS A comprehensive review of studies was conducted, including articles from PubMed, Scopus, and Web of Science, with a focus on tumor organoid models in cancer research, particularly in preclinical and clinical drug testing, personalized therapy, and biomarker identification. RESULTS Tumor organoids enable high-throughput drug screening, allowing the identification of effective therapies for individual patients. They provide insights into tumor behavior, metastasis, and resistance mechanisms. Additionally, organoids facilitate the evaluation of various therapeutic strategies, including chemotherapy, targeted therapies, and immunotherapies. Despite challenges like inconsistent success rates and ethical concerns with animal-derived matrices, advancements in organoid technology, including AI integration and multi-omics, promise to enhance their clinical applications. CONCLUSION Tumor organoids hold immense potential in precision oncology by providing more accurate, patient-specific models for studying cancer biology and predicting treatment responses. Their integration into clinical decision-making will enhance personalized treatment approaches and improve cancer therapy outcomes.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Tumor organoids in translational cancer research: Models for personalized therapy
- Date Crossref
- 12/02/2026
- Éditeur
- Baishideng Publishing Group Inc.
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.