Tunable Scaffolding Better Mimics Tumor Microenvironments

A research team in Atlanta has developed a way to generate breast tumor models faster, more reliably, and with less immune variability than existing models. Their findings could speed development of immunotherapy treatments and also help explain why patients with the same type of breast cancer respond differently to treatment.

A discrepancy between preclinical advances in breast cancer immunotherapy and poor patient outcomes is rooted in the limitations of current breast cancer models, which often fail to mimic complex interactions between cancer cells and key immune cells present in the tumor microenvironment. One type of model involves injecting human tumor cells into mice that lack a complete immune system, but this complicates the study of immune-targeting therapies. In a different approach, mice are manipulated at the genome level to make them prone to cancer, but the rate of tumor development is highly variable.

The most common way to generate breast cancer models for immunotherapy research is by injecting mouse breast cancer cells directly into healthy mice. This method is affordable and scalable, but sometimes up to 80% of mice in an experiment will not grow tumors. To address this, breast cancer researchers began to inject the tumor cells alongside Matrigel, a commercially available protein mixture derived from mouse cells that helps tumors grow reliably. The problem with the mixture, however, is that its composition varies from batch to batch. Using the mixture therefore creates more unknown variables, affecting a mouse’s immune response in unpredictable ways.

The newly developed method, published recently in Advanced Materials, uses a gel-like matrix as a scaffold to grow breast cancer tumors and allowed the team to modulate how immune cells filter into a tumor’s microenvironment. They injected triple negative breast cancer (TNBC) cells, the most aggressive type of breast cancer, into a synthetic matrix they developed. They found that their breast cancer tumors formed at a rate of 100% and did so faster and with lower variability in growth than when using Matrigel. The team also created different formulations of the gel matrix by incorporating biomolecular tags readily recognized by immune cells. The tags are made of peptides and serve to recruit key immune cells to the microenvironment. Incorporating the tags enabled them to model different subtypes of immune environments often seen in treatment-resistant TNBC.

They then tested two of the most common types of immunotherapy drugs—vaccines and immune checkpoint blockade therapy—on the different subsets of cancer microenvironments. “When we used different matrix components, we saw different effects of these drugs on the same type of cancer,” says Susan N. Thomas, an associate professor in the George W. Woodruff School of Mechanical Engineering. “There is a lot of variability related to why some patients respond to therapy or not, and until now there was no way to incorporate that into our mouse models when developing drugs.”

The findings demonstrate the essential role a patient’s tumor immune microenvironment plays in the success of immunotherapies and has broad potential for pre-screening immunotherapy drugs for individual patients. Hypothetically, for the average cancer patient, a clinician could do a simple biopsy, determine what immune cells are present, and choose a better therapy.