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Mutation testing is becoming mainstream to personalized cancer treatment, but for the vast variations of breast cancer, it is challenging to identify treatments based on genetic mutations alone.
More and more studies suggest that functional testing may have distinct advantages over mutation testing alone to personalize treatment. Functional precision medicine is a strategy where live tumor cells from a patient are directly tested with a drug to provide immediate information that can inform personalized treatment.
One way scientists try to test drugs on patient’s breast tumors is to implant human tumor biopsies into the mouse mammary gland. These mice are called human patient-derived xenografts, or PDX models. Scientists can use PDXs to see how they respond to treatments, and the mice’s responses are a good model of how people will respond. PDXs can also show scientists how tumors grow and spread. Hundreds of PDX mouse models have been developed for breast cancer. However, the generation and maintenance of PDX mouse models is slow and expensive, which makes it difficult to test a large number of drugs and doses on each patient tumor to find the optimal treatment.
Scientists need to develop models of breast cancer that represent the complexity of human tumors and are easier to grow for drug screening to find effective treatments for each type of breast cancer.
American Cancer Society (ACS) grantee Katherine Varley, PhD, co-wrote a published study in Nature Cancer with lead investigator Alana Welm, PhD, about their development of mouse and organoid models to test breast cancer drugs.
This collaborative study implanted tumor specimens from patients into mice to create PDX models, and then they use samples from those mice to create PDX-derived organoids, or PDxO models, that could be grown in a dish.
The ability to grow patient tumor cells in a dish allows us to accelerate personalized medicine. We can now test a large number of drugs on diverse tumors from people with breast cancer and use genomic analysis to learn which differences in gene expression between patients’ tumors are associated with the response to each drug.”
Katherine Varley, PhD
Huntsman Cancer Institute, University of Utah
American Cancer Society Research Grantee
When they tested potential drugs, they found that organoids grown in a dish (in vitro) had similar results as the live PDX mice with human cancers (in vivo). They were able to uncover both experimental and FDA-approved drugs that worked very well to kill the cancer cells in the PDxO organoid in the lab (an example of in vitro testing) and verify their findings with the PDX live mouse with the human cancer (an example of in vivo testing). They also used genomic analysis to demonstrate that the different mutations and gene expression signatures found in each patient tumor were preserved when the tumors were grown in mice (PDX) and in a dish (PDxO).
They extended their work to personalize treatment for a patient with a recurrence of triple-negative breast cancer. The treatment selected based on the PDxO drug testing of the patient’s tumor resulted in a complete response (no signs of cancer) and the patient had a period of progression-free survival that was 3 times longer than people who’d received other treatments.
These findings demonstrate that PDxO models can be used to accelerate the testing of a large number of drugs on patient tumors to prioritize more effective treatments. Additionally, the genomic analysis of these diverse PDxO models will allow researchers to identify gene expression differences between patients that are associated with response to different drugs. In the future, the research team hopes to use this information to predict which drug will be most effective for each patient based on the gene expression of the patient’s tumor.
Varley’s collaborative research results are an example of functional precision medicine —a pre-clinical research platform where scientists take live tumor cells from patients to identify new drugs for breast cancer, including the identification of biomarkers to personalize the use of these drugs. These new functional tools can also be used to accelerate the discovery of new drugs against tough-to-treat breast cancers and identify patient tumors that are most likely to respond to each treatment option.