Trial reportCell reports. Medicine2026
Biomarker-guided responses in patient-derived organoids predict effective therapies in breast cancer.
Trial report in Cell reports. Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01042379 (I-SPY Trial), which is not on this map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
I-SPY Trial (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging And moLecular Analysis 2)
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
21 authors.
Funding
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.
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