Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer

Tam Binh V Bui; Denise M Wolf; Michael C Bruck; Kaitlin Moore; Jessica Lien; Sarah D W Choi; Shruti Warhadpande; Amirabbas Parizadeh; Deborah Dillon; Beth Overmoyer; Filipa Lynce; Lamorna Brown-Swigart; Gillian L Hirst; Christina Yau; Isaac J Nijman; Boudewijn M T Burgering; Isaac S Harris; Laura J Esserman; Laura J van 't Veer; Jennifer M Rosenbluth

doi:10.1016/j.xcrm.2026.102973

Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer

Tam Binh V Bui
, Denise M Wolf
, Michael C Bruck
, Kaitlin Moore
, Jessica Lien
, Sarah D W Choi
, Shruti Warhadpande
, Amirabbas Parizadeh
, Deborah Dillon
, Beth Overmoyer
, Filipa Lynce
, Lamorna Brown-Swigart
, Gillian L Hirst
, Christina Yau
, Isaac J Nijman
, Boudewijn M T Burgering
, Isaac S Harris
, Laura J Esserman
, Laura J van 't Veer^*
, Jennifer M Rosenbluth^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Poor therapeutic response in subsets of breast cancer (BC) patients poses an ongoing challenge. Here, we present a biomarker-guided characterization of 40 patient-derived BC organoids, with the aim of modeling resistant disease with greater fidelity and developing an in vitro system grounded in clinical data for testing alternative treatment strategies. We utilize patient data from the I-SPY2 clinical trial (NCT01042379) to develop predictive models of response to a range of therapies, using only organoid-detectable biomarkers as input, and validate a model predicting response to veliparib-platinum chemotherapy (VP) in triple-negative BC (TNBC) organoids. A drug screen in VP-resistant TNBC organoids reveals combination treatments that overcome resistance to cisplatin, including pro-apoptotic therapies. Another class of hits, HSP90 inhibitors, links organoid drug sensitivity to improved recurrence-free survival in a biomarker-defined patient subset. These findings establish organoid-based functional modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer.

Original language	English
Article number	102973
Journal	Cell reports. Medicine
Volume	7
Issue number	8
Early online date	6 Aug 2026
DOIs	https://doi.org/10.1016/j.xcrm.2026.102973
Publication status	Published - 18 Aug 2026

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1-s2.0-S2666379126003903Final published version, 8.21 MBLicence: CC BY

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Bui, T. B. V., Wolf, D. M., Bruck, M. C., Moore, K., Lien, J., Choi, S. D. W., Warhadpande, S., Parizadeh, A., Dillon, D., Overmoyer, B., Lynce, F., Brown-Swigart, L., Hirst, G. L., Yau, C., Nijman, I. J., Burgering, B. M. T., Harris, I. S., Esserman, L. J., van 't Veer, L. J. (2026). Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer. Cell reports. Medicine, 7(8), Article 102973. https://doi.org/10.1016/j.xcrm.2026.102973

@article{d735d4c334b04263a5432334f8350848,

title = "Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer",

abstract = "Poor therapeutic response in subsets of breast cancer (BC) patients poses an ongoing challenge. Here, we present a biomarker-guided characterization of 40 patient-derived BC organoids, with the aim of modeling resistant disease with greater fidelity and developing an in vitro system grounded in clinical data for testing alternative treatment strategies. We utilize patient data from the I-SPY2 clinical trial (NCT01042379) to develop predictive models of response to a range of therapies, using only organoid-detectable biomarkers as input, and validate a model predicting response to veliparib-platinum chemotherapy (VP) in triple-negative BC (TNBC) organoids. A drug screen in VP-resistant TNBC organoids reveals combination treatments that overcome resistance to cisplatin, including pro-apoptotic therapies. Another class of hits, HSP90 inhibitors, links organoid drug sensitivity to improved recurrence-free survival in a biomarker-defined patient subset. These findings establish organoid-based functional modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer.",

author = "Bui, \{Tam Binh V\} and Wolf, \{Denise M\} and Bruck, \{Michael C\} and Kaitlin Moore and Jessica Lien and Choi, \{Sarah D W\} and Shruti Warhadpande and Amirabbas Parizadeh and Deborah Dillon and Beth Overmoyer and Filipa Lynce and Lamorna Brown-Swigart and Hirst, \{Gillian L\} and Christina Yau and Nijman, \{Isaac J\} and Burgering, \{Boudewijn M T\} and Harris, \{Isaac S\} and Esserman, \{Laura J\} and \{van 't Veer\}, \{Laura J\} and Rosenbluth, \{Jennifer M\}",

year = "2026",

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doi = "10.1016/j.xcrm.2026.102973",

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Bui, TBV, Wolf, DM, Bruck, MC, Moore, K, Lien, J, Choi, SDW, Warhadpande, S, Parizadeh, A, Dillon, D, Overmoyer, B, Lynce, F, Brown-Swigart, L, Hirst, GL, Yau, C, Nijman, IJ, Burgering, BMT, Harris, IS, Esserman, LJ, van 't Veer, LJ, Rosenbluth, JM 2026, 'Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer', Cell reports. Medicine, vol. 7, no. 8, 102973. https://doi.org/10.1016/j.xcrm.2026.102973

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AU - Bui, Tam Binh V

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AU - Bruck, Michael C

AU - Moore, Kaitlin

AU - Lien, Jessica

AU - Choi, Sarah D W

AU - Warhadpande, Shruti

AU - Parizadeh, Amirabbas

AU - Dillon, Deborah

AU - Overmoyer, Beth

AU - Lynce, Filipa

AU - Brown-Swigart, Lamorna

AU - Hirst, Gillian L

AU - Yau, Christina

AU - Nijman, Isaac J

AU - Burgering, Boudewijn M T

AU - Harris, Isaac S

AU - Esserman, Laura J

AU - van 't Veer, Laura J

AU - Rosenbluth, Jennifer M

PY - 2026/8/18

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N2 - Poor therapeutic response in subsets of breast cancer (BC) patients poses an ongoing challenge. Here, we present a biomarker-guided characterization of 40 patient-derived BC organoids, with the aim of modeling resistant disease with greater fidelity and developing an in vitro system grounded in clinical data for testing alternative treatment strategies. We utilize patient data from the I-SPY2 clinical trial (NCT01042379) to develop predictive models of response to a range of therapies, using only organoid-detectable biomarkers as input, and validate a model predicting response to veliparib-platinum chemotherapy (VP) in triple-negative BC (TNBC) organoids. A drug screen in VP-resistant TNBC organoids reveals combination treatments that overcome resistance to cisplatin, including pro-apoptotic therapies. Another class of hits, HSP90 inhibitors, links organoid drug sensitivity to improved recurrence-free survival in a biomarker-defined patient subset. These findings establish organoid-based functional modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer.

AB - Poor therapeutic response in subsets of breast cancer (BC) patients poses an ongoing challenge. Here, we present a biomarker-guided characterization of 40 patient-derived BC organoids, with the aim of modeling resistant disease with greater fidelity and developing an in vitro system grounded in clinical data for testing alternative treatment strategies. We utilize patient data from the I-SPY2 clinical trial (NCT01042379) to develop predictive models of response to a range of therapies, using only organoid-detectable biomarkers as input, and validate a model predicting response to veliparib-platinum chemotherapy (VP) in triple-negative BC (TNBC) organoids. A drug screen in VP-resistant TNBC organoids reveals combination treatments that overcome resistance to cisplatin, including pro-apoptotic therapies. Another class of hits, HSP90 inhibitors, links organoid drug sensitivity to improved recurrence-free survival in a biomarker-defined patient subset. These findings establish organoid-based functional modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer.

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DO - 10.1016/j.xcrm.2026.102973

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SN - 2666-3791

VL - 7

JO - Cell reports. Medicine

JF - Cell reports. Medicine

IS - 8

M1 - 102973

ER -

Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer

Abstract

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