The Research Scope
Researchers at Baylor College of Medicine have made significant progress in personalizing treatment for HER2-positive (HER2+) breast cancer, a variant that accounts for approximately one in every five breast cancer cases.
They’ve developed a method that helps predict how a cancer might respond to a specific, less toxic, treatment.
This work is a major stride towards fulfilling the promise of personalized breast cancer therapy.
HER2-Positive Breast Cancer: An Overview
HER2+ breast cancer is characterized by high levels of HER2 proteins, upon which the cancer relies for rapid growth and metastasis.
Historically, patients suffering from HER2+ breast cancer were only treated with chemotherapy, which yielded poor outcomes.
This scenario improved in the late 1990s when anti-HER2 therapy was introduced, transforming the treatment landscape of this disease.
The Dual Anti-HER2 Drug Strategy
The Baylor team found that targeting the HER2 protein with two anti-HER2 drugs, lapatinib and trastuzumab, prior to surgery resulted in a complete response—where all cancer in the breast disappeared—in approximately 25-30% of cases.
This finding suggested that chemotherapy was not necessary for these patients, thereby sparing them the cost and harmful side-effects of chemo.
Predicting Responses with a Molecular Classifier
The challenge was identifying which patients would fall into the responsive 30% at the time of diagnosis. To address this, the team developed a multiparameter molecular classifier.
This test was designed to predict which patients would respond to anti-HER2 treatment alone, as well as to identify those whose tumors might require additional interventions like chemotherapy.
This molecular classifier comprises three components:
- It measures the amount of HER2 gene and protein in the cancer cells and checks whether the expression is homogeneous throughout the tumor.
- It analyzes whether the cancer expresses a set of genes that indicate the cancer’s growth dependence on HER2.
- It investigates the gene PIK3CA for mutations that could provide alternative molecular routes for cancer cell growth when HER2 protein is blocked.
The Path Forward: Precision Medicine
This development enables a shift towards personalized treatment, tailoring the intervention to the patient’s specific needs, thereby minimizing impact on their quality of life.
The team will now evaluate the molecular classifier in a prospective clinical trial for further validation of its clinical utility.
The research team is optimistic that if validated, this classifier could serve as a molecular triaging tool to safely and appropriately select patients with HER2+ breast cancer for treatment de-escalation.
This discovery is the result of many years of dedicated research and presents a significant stride in personalizing cancer treatment.
If you care about cancer, please read studies about a major cause of deadly breast cancer, and new cancer vaccines could prevent cancer recurrence.
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The study was published in Clinical Cancer Research.
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