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Title: Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction
Authors: Chen, Xinsong
Sifakis, Emmanouil G.
Robertson, Stephanie
Neo, Shi Yong
Jun, Seong-Hwan
Tong, Le
Tay, Apple Hui Min
Lövrot, John
Hellgren, Roxanna
Margolin, Sara
Bergh, Jonas
Foukakis, Theodoros
Lagergren, Jens
Lundqvist, Andreas
Ma, Ran
Hartman, Johan
Keywords: Science::Biological sciences
Issue Date: 2023
Source: Chen, X., Sifakis, E. G., Robertson, S., Neo, S. Y., Jun, S., Tong, L., Tay, A. H. M., Lövrot, J., Hellgren, R., Margolin, S., Bergh, J., Foukakis, T., Lagergren, J., Lundqvist, A., Ma, R. & Hartman, J. (2023). Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction. Proceedings of the National Academy of Sciences, 120(1), e2209856120-.
Journal: Proceedings of the National Academy of Sciences 
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.
ISSN: 0027-8424
DOI: 10.1073/pnas.2209856120
Schools: School of Biological Sciences 
Rights: © 2022 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).
Fulltext Permission: open
Fulltext Availability: With Fulltext
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