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.

In their study, which appeared Aug. 6 in Cell Reports Medicine, the researchers found that the organoids were able to mimic a tumor's response to treatment. 

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. These findings support organoid modeling as a bridge between clinical biomarkers and precision treatment strategies in breast cancer." 

Jennifer M. Rosenbluth, MD, PhD, study's senior author, medical oncologist and the Sulochana Pradhan, MD, Endowed Professor in Breast Cancer at UCSF

The researchers created the breast cancer organoids by placing patient-derived tumor cells into a gel designed to support the original tumor's biology. Over several weeks, the cells clustered into tiny spheres that reflected the structure and biology of the original tumor. Each cluster contained up to thousands of cells - too small to see clearly without a microscope - the largest appearing as translucent clusters in the gel.

The researchers then evaluated this biobank of early-stage invasive breast cancer organoids to study mechanisms of therapy resistance. Response predictive subtypes – molecular subtypes developed during the course of the I-SPY2 trial – provided the researchers with a framework of anticipated tumor responses to current therapies, including immunotherapy, PARP-inhibitors, platinum chemotherapy drugs, and dual-HER2 targeted therapies. With access to clinical patient data, they used the response predictive subtypes and the biomarker data of tumors from patients in the I-SPY2 trial to predict treatment responses in organoids. 

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.

The organoid drug screen also revealed other promising hits, including a class of drugs called HSP90 inhibitors; and the researchers were able to link what they observed in the lab to a subset of I-SPY patients who had responded better to these types of drugs. 

"The breast cancer organoids were found to express important cancer biomarkers - many of which can be targeted with drugs," said Tam Binh V. Bui, MD, MSc, the study's first author, who is a PhD candidate at UCSF member of the Rosenbluth Lab and Van 't Veer/I-SPY lab at UCSF. "These organoids allowed us to study the effects of drugs directly in human tissue and prioritize the most promising therapies for this subtype."

The study did not test how organoid-guided treatment decisions would perform over time. And the organoids could not reflect the complexity of a whole organ​ and could not mimic the environment inside the body, which includes blood vessels, immune cells and other processes that influence the signals that the tumor cells receive.​ 

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."