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A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology
Open accessAbstract
Models that recapitulate the complexity of human tumors are urgently needed to develop more effective cancer therapies. We report a bank of human patient-derived xenografts (PDXs) and matched organoid cultures from tumors that represent the greatest unmet need: endocrine-resistant, treatment-refractory and metastatic breast cancers. We leverage matched PDXs and PDX-derived organoids (PDxO) for drug screening that is feasible and cost-effective with in vivo validation. Moreover, we demonstrate the feasibility of using these models for precision oncology in real time with clinical care in a case of triple-negative breast cancer (TNBC) with early metastatic recurrence. Our results uncovered a Food and Drug Administration (FDA)-approved drug with high efficacy against the models. Treatment with this therapy resulted in a complete response for the individual and a progression-free survival (PFS) period more than three times longer than their previous therapies. This work provides valuable methods and resources for functional precision medicine and drug development for human breast cancer.
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“They found that benign organoids carrying mutations in 1–2 genes could not form tumors while more malignant ones with mutations in 4–5 genes were tumorigenic173.”
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Metadata
- Authors
- Guillen, K. P., Fujita, M., Butterfield, A. J., Scherer, S. D., Bailey, M. H., Chu, Z., DeRose, Y. S., Zhao, L., Cortes-Sanchez, E., Yang, C.-H., Toner, J., Wang, G., Qiao, Y., Huang, X., Greenland, J. A., Vahrenkamp, J. M., Lum, D. H., Factor, R. E., Nelson, E. W., Matsen, C. B., Poretta, J. M., Rosenthal, R., Beck, A. C., Buys, S. S., Vaklavas, C., Ward, J. H., Jensen, R. L., Jones, K. B., Li, Z., Oesterreich, S., Dobrolecki, L. E., Pathi, S. S., Woo, X. Y., Berrett, K. C., Wadsworth, M. E., Chuang, J. H., Lewis, M. T., Marth, G. T., Gertz, J., Varley, K. E., Welm, B. E., & Welm, A. L.
- Affiliations
- University of Utah (US)
- Huntsman Cancer Institute (US)
- University of Pittsburgh (US)
- Baylor College of Medicine (US)
- The Jackson Laboratory for Genomic Medicine (US)
- Corresponding author
- Welm, Bryan E.
- Welm, Alana L.
- ORCID
- Fujita, Maihi
- Scherer, Sandra D.
- Bailey, Matthew H.
- Chu, Zhengtao
- Zhao, Ling
- Cortes-Sanchez, Emilio
- Huang, Xiaomeng
- Vahrenkamp, Jeffery M.
- Lum, David H.
- Factor, Rachel E.
- Nelson, Edward W.
- Matsen, Cindy B.
- Beck, Anna C.
- Buys, Saundra S.
- Vaklavas, Christos
- Ward, John H.
- Jensen, Randy L.
- Jones, Kevin B.
- Li, Zheqi
- Oesterreich, Steffi
- Dobrolecki, Lacey E.
- Woo, Xing Yi
- Berrett, Kristofer C.
- Wadsworth, Mark E.
- Chuang, Jeffrey H.
- Lewis, Michael T.
- Gertz, Jason
- Varley, Katherine E.
- Welm, Bryan E.
- Welm, Alana L.
- Venue
- Nature Cancer
- Published
- 2022-02-24
- Volume
- 3
- Issue
- 2
- Pages
- 232-250
- ISSN
- 2662-1347 (ISSN-L)
- PMC
- PMC8882468
- OpenAlex
- W4214507610
- Cited by
- 416
- References
- 69
- Citations by year
- 2026: 87 · 2025: 99 · 2024: 104 · 2023: 78 · 2022: 43
- FWCI
- 33.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature Cancer (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- Funders
- U.S. Department of Defense (W81XWH1210077, W81XWH1410417)
- American Cancer Society (P30 CA042014)
- Breast Cancer Research Foundation
- Cancer Prevention and Research Institute of Texas (CA125123, RP170691)
- University of Utah (P30 CA042014)
- Huntsman Cancer Foundation (P30CA042014)
- Huntsman Cancer Institute (P30CA042014)
- National Institutes of Health (/ NCI R01, CA125123)
- National Human Genome Research Institute (T32HG008962)
- National Cancer Institute (R01CA221303, NCI-CA125123, CA125123, U01CA217617, U54CA224076, U24CA224067, P30CA042014, P30CA125123)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Physical Sciences › Engineering › Biomedical Engineering › 3D Printing in Biomedical Research
- Keywords
- breast cancer, patient-derived xenografts, organoids, endocrine-resistant breast cancer, metastatic breast cancer, triple-negative breast cancer, precision oncology, drug screening, drug repurposing, treatment-refractory cancer
- MeSH terms
- Humans, Organoids, United States, Xenograft Model Antitumor Assays, Drug Discovery, Precision Medicine, Heterografts, Triple Negative Breast Neoplasms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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