Lab-Grown Organs Help Predict Tumor Response to Treatment

A team at UC San Francisco figured out a method to predict how breast cancer responds to different drugs. They used patient data and lab-grown mini tumors. This could help doctors create more personalized care, especially for a tough, aggressive type called triple-negative breast cancer.

Growing Tumors in a Lab

The team took tumor cells from patients and placed them in a special gel. Over a few weeks, the cells formed tiny spheres called organoids. These clusters were so small you needed a microscope to see them, but they acted just like the original tumors.

This allowed the researchers to test different treatments safely in the lab.

“The breast tumor organoids modeled how corresponding patient tumors responded to therapies and identified candidate combination therapies for cancers that don’t respond to standard treatment,” Jennifer M. Rosenbluth, MD, PhD, a medical oncologist at UCSF, explained. “These findings support organoid modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer.”

The team looked closely at triple-negative breast cancer, which often resists standard chemotherapy. They took one highly resistant mini tumor and tested 386 different drugs on it and found that combining a chemotherapy drug called cisplatin with another drug called ABT-263 worked incredibly well against the resistant cells.

“The breast cancer organoids were found to express important cancer biomarkers — many of which can be targeted with drugs,” Tam Binh V. Bui, MD, MSc, the study’s first author, added. “These organoids allowed us to study the effects of drugs directly in human tissue and prioritize the most promising therapies for this subtype.”

The Limits and What’s Next

While promising, the lab-grown tumors aren’t perfect. They lack blood vessels, immune cells, and the full complexity of a human body. The team also didn’t test how these treatment choices hold up over long periods of time.

Even with those limits, this might work for patients down the road as a way to get custom 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 explained. “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.”