Lab-grown mini tumors help scientists predict breast cancer treatment success

Researchers at UC San Francisco have developed a new method to predict how different types of breast cancer will respond to treatment, using patient data from the I-SPY2 breast cancer trial and rapid testing on lab-grown mini tumors.

The advance could hasten more personalized treatments for breast cancer, including the triple negative type, which is especially aggressive and hard to treat.

Since many of the organoids were derived from triple-negative breast cancer tumors, those organoids were chosen to validate a model predicting response to veliparib-platinum chemotherapy (VP). Platinum chemotherapies and combination therapies like VP are often prescribed to patients with triple-negative breast cancer (TNBC) – even though TNBC can be highly treatment resistant.

With the aim of finding alternative treatment strategies to overcome tumors' resistance to platinum chemotherapy, the researchers selected tumor organoid TORG40, with the highest predicted and subsequently validated resistance to VP. The team performed a drug screen of 386 small-molecule inhibitors on this organoid, including ABT-263, a type of drug that helps to eliminate damaged cells. They then compared ABT-263 alone with ABT-263 in combination with the chemotherapy drug cisplatin. This drug combination in the organoid enhanced activity against resistant tumor cells, having a uniquely potent effect on TORG40.

But the researchers hope that one day physicians may be able to use patient-derived organoids to develop personalized approaches to cancer care.

"By combining computational analyses of large molecular and clinical datasets with organoid model systems, this proof-of-principle study demonstrated the utility of matching I-SPY2 resistance biomarkers and signatures to residual disease tumor organoid cultures," Rosenbluth said. "Our findings highlight the value of a reverse translational approach that integrates patient-level clinical trial data and testing in organoid models to inform drug discovery and future personalized treatment strategies for patients."

Source:

University of California San Francisco Medical Center

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