“Tumor Avatars” Could Help Identify Effective Cancer Treatments
By Mike Howie
Finding an effective cancer treatment isn’t always easy. While immunotherapy is popular and can be highly effective, it doesn’t work for every patient. To care for their patients, doctors must first find the right treatment, a process that can be tiring and discouraging for someone with such a serious illness. But that process might soon be easier.
Researchers from the Netherlands Cancer Institute (NKI) have devised a method of identifying effective cancer treatments in the lab with a tumor sample, leaving patients out of what can be a rigorous process.
The method, described by Daniela Thommen, a cancer researcher at NKI, is simple in concept: "We first cut patient tumor samples into small pieces and then treat these 'tumor avatars' outside the patient's body with different therapies to see which one works."
The idea behind the process is so simple that it may sound obvious, but there was reason to question the accuracy of the approach. It’s possible that tumors could react differently once removed from the body, meaning that successful treatment in the lab wouldn’t necessarily translate to successful treatment in the patient. But the team’s results were encouraging.
“We’ve solved a major problem many scientists had been facing,” Thommen said, “preserving a tumor’s original composition and structure outside of the patient in the lab.”
"We’ve solved a major problem many scientists had been facing," Thommen said.
The study focused on a type of immunotherapy called a PD-1 blockade. As with other immunotherapies, a
PD-1 blockade uses T-cells to find and destroy cancer cells. However, some cancer cells are able to inactivate T-cells and evade destruction. To prevent this, a PD-1 blockade uses inhibitors to stop cancer cells from inactivating T-cells. This type of therapy has proven effective against some forms of melanoma, kidney cancer, lung cancer, and some other cancers. After linking lab and clinical results of 38 patients, the researchers found that the response of tumor avatars successfully predicted how the patient would respond to therapy.
“These results confirm that we have now a very powerful model system in place which we can use to develop new diagnostics, and in this way personalize immunotherapy,” Thommen said. The team also found some unknown predictors of whether a tumor will respond to or resist immunotherapy, including three subgroups of tumors that do not respond, and discovered that responsive tumors had been infiltrated by specific immune cells and formed tertiary lymphoid structures. These markers can now be tested to verify how well they can predict a therapy’s effectiveness.
More work must be done before this method of identifying a cancer treatment can be widely used, but for now the results — published July 8, 2021, in Nature Medicine — are promising.
Mike Howie is a Thermo Fisher Scientific staff writer.
