New Technique Predicts Tumor’s Responsiveness to Breast Cancer Treatment

Breast cancer is the most common cancer among women worldwide, with 2.3 million new cases diagnosed each year. In the era of personalized medicine, targeted therapies for different types of breast cancer are now available. However, despite these advancements, some tumors remain difficult to treat. As a result, even with significant progress in early diagnosis and treatment options, 670,000 women worldwide still die from breast cancer annually. Historically, predicting how well a patient's tumor will respond to available treatments has been challenging. This uncertainty means some patients undergo ineffective and unpleasant treatments. There is a need for more accurate lab testing methods to help doctors improve clinical outcomes. Researchers have now developed a technique that could predict how well certain breast cancer patients will respond to chemotherapy and antibody-directed treatments.

In their study, researchers at the University of Leicester (Leicester, UK) applied advanced digital pathology and multi-immunofluorescent techniques to examine changes in patient tumor samples in the lab. Building on their previous work with non-small cell lung cancer and endometrial cancer patient-derived explants (PDEs), the team discovered a significant link between explant responses to chemotherapy drugs and patient outcomes. This finding set the stage for their current research. Published in Nature Scientific, the new study involved measuring the stability of tumor explants from 55 breast cancer patients over time. The tumors were 'treated' with either chemotherapy or the HER2 antibody therapy trastuzumab in the lab.

The results showed that using the PDE technique, the tumor architecture was preserved for up to 72 hours during testing, and the immune microenvironment remained intact. This was particularly encouraging, as other testing methods have struggled with maintaining these characteristics, providing the researchers with confidence that their testing was meaningful. The team then compared their observations of the tumor explants' response to treatment in the lab with the clinical progression of the same patients. They found a similar pattern in the explant's response to treatment and the patient's progression. This is especially promising, as it suggests that the tumor explant in the lab responded in a manner similar to the patient's tumor in the clinic.

“Our findings suggest that our patient derived explant technique could be a suitable preclinical testing platform for some breast cancer patients,” said Gareth Miles, Lecturer in Cancer Patient Derived Explant Technology at the University of Leicester. “It could provide a more accurate method to predict how they may respond to particular treatments. Doctors can avoid giving ineffective treatments, saving time and ultimately improving a patient’s clinical outcome.”

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