ArticleBreast cancer research : BCR2023
Transcriptomic intratumor heterogeneity of breast cancer patient-derived organoids may reflect the unique biological features of the tumor of origin.
Article in Breast cancer research : BCR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed.
- Organoid technology in cancer research.Molecular biomedicine · 2026Review
- Organoid models: Regulations and prospects for the development of investigational new drugs.Chinese medical journal · 2026Review
- Harnessing Cancer Stem Cells and 3D Organoids in Unravelling Spatial and Cellular Heterogeneity in Cancer.International journal of molecular sciences · 2026Review
- Patient-Derived Organoids from Multiple Sites of a Single Tumor Recapitulates Intratumoral Heterogeneity in Patients with Gastric Cancer.Gut and liver · 2026Article
- Tumor heterogeneity as a driver of drug resistance and its implications for personalized therapy.Cancer drug resistance (Alhambra, Calif.) · 2026Review
- Integrated transcriptomic and immune-associated network analysis of breast cancer patient-derived organoids reveals candidate inflammatory biomarkers.Frontiers in bioengineering and biotechnology · 2026Article
- Endocrine cancer organoids in basic and translational medical research.Science China. Life sciences · 2025Review
- Review
- Plasma exosomes from individuals with type 2 diabetes drive breast cancer aggression in patient-derived organoids.Communications biology · 2025Article
- Axillary adipose tissue-derived lymphatic endothelial cells exhibit distinct transcriptomic signatures reflecting lymphatic invasion status in breast cancer.Breast cancer research : BCR · 2025Article
- A new dawn: Vitalising translational oncology research in Africa with the help of advanced cell culture models.Translational oncology · 2025Article
- Facing the Challenge to Mimic Breast Cancer Heterogeneity: Established and Emerging Experimental Preclinical Models Integrated with Omics Technologies.International journal of molecular sciences · 2025Review
- Dataset of transcriptomic changes induced by naringenin treatment in MCF-7 breast cancer cells.Data in brief · 2025Article
- Dynamic culture system advances the applications of breast cancer organoids for precision medicine.Scientific reports · 2025Article
- Deciphering the dynamic single-cell transcriptional landscape in the ocular surface ectoderm differentiation system.Life medicine · 2024Article
- Patient-Derived Organoids as Therapy Screening Platforms in Cancer Patients.Advanced healthcare materials · 2024Review
- Patient-derived organoids: a promising tool for breast cancer research.Frontiers in oncology · 2024Review
- Culturally responsive strategies and practical considerations for live tissue studies in Māori participant cohorts.Frontiers in research metrics and analytics · 2024Article
- Modeling epithelial-mesenchymal transition in patient-derived breast cancer organoids.Frontiers in oncology · 2024Article
- Complex in vitro Model: A Transformative Model in Drug Development and Precision Medicine.Clinical and translational science · 2023Review
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Abstract
backgroundThe intratumor heterogeneity (ITH) of cancer cells plays an important role in breast cancer resistance and recurrence. To develop better therapeutic strategies, it is necessary to understand the molecular mechanisms underlying ITH and their functional significance. Patient-derived organoids (PDOs) have recently been utilized in cancer research. They can also be used to study ITH as cancer cell diversity is thought to be maintained within the organoid line. However, no reports investigated intratumor transcriptomic heterogeneity in organoids derived from patients with breast cancer. This study aimed to investigate transcriptomic ITH in breast cancer PDOs.
methodsWe established PDO lines from ten patients with breast cancer and performed single-cell transcriptomic analysis. First, we clustered cancer cells for each PDO using the Seurat package. Then, we defined and compared the cluster-specific gene signature (ClustGS) corresponding to each cell cluster in each PDO.
resultsCancer cells were clustered into 3-6 cell populations with distinct cellular states in each PDO line. We identified 38 clusters with ClustGS in 10 PDO lines and used Jaccard similarity index to compare the similarity of these signatures. We found that 29 signatures could be categorized into 7 shared meta-ClustGSs, such as those related to the cell cycle or epithelial-mesenchymal transition, and 9 signatures were unique to single PDO lines. These unique cell populations appeared to represent the characteristics of the original tumors derived from patients.
conclusionsWe confirmed the existence of transcriptomic ITH in breast cancer PDOs. Some cellular states were commonly observed in multiple PDOs, whereas others were specific to single PDO lines. The combination of these shared and unique cellular states formed the ITH of each PDO.
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