ArticleProceedings of the National Academy of Sciences of the United States of America2023
Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Breast Cancer Multicellular Spheroid Models-A Tool for Studying Cancer Biology; a Possible Platform for Drug Screening and Personalized Medicine.International journal of molecular sciences · 2026Review
- Developing Mammary Gland Models for Biomedical Applications.Research (Washington, D.C.) · 2026Review
- Fast-adapting graph neural network with prior knowledge for drug response prediction across preclinical and clinical data.Journal of pharmaceutical analysis · 2025Article
- Deciphering Breast Tumor Heterogeneity Through Patient-Derived Organoids and Circulating Tumor Cells.Journal of personalized medicine · 2025Review
- Establishing predictive machine learning models for drug responses in patient derived cell culture.NPJ precision oncology · 2025Article
- Zebrafish Avatar testing preclinical study predicts chemotherapy response in breast cancer.NPJ precision oncology · 2025Article
- Patient-derived glioblastoma organoids as real-time avatars for assessing responses to clinical CAR-T cell therapy.Cell stem cell · 2025Article
- Review
- Patient-derived response estimates from zero-passage organoids of luminal breast cancer.Breast cancer research : BCR · 2024Article
- A phenotypic screening approach to target p60AmotL2-expressing invasive cancer cells.Journal of experimental & clinical cancer research : CR · 2024Article
- Patient-derived response estimates from zero-passage organoids of luminal breast cancer.bioRxiv : the preprint server for biology · 2024Article
- Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms.Frontiers in immunology · 2024Review
- ExoDS: a versatile exosome-based drug delivery platform to target cancer cells and cancer stem cells.Frontiers in bioengineering and biotechnology · 2024Article
- Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
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Authors and funding
16 authors.
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Abstract
Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.
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