A new test for HER2+ breast cancer allows delivery of more personalized treatment, say researchers at the Baylor College of Medicine in Houston.
The group developed and validated a multiparameter molecular classifier test that predicts which patients with HER2-positive breast cancer are candidates for treatment with targeted anti-HER treatment, and which patients would best be treated with chemotherapy or other targeted therapies.
The findings are reported by Jamunarani Veeraraghavan, MD, and colleagues this week in Clinical Cancer Research.
“HER2+ breast cancer, which represents about 1 of every 5 breast cancers, expresses high levels of HER2 proteins and is physiologically dependent on the abundance of this protein to grow fast and metastasize or spread to other organs,” study co-author Rachel Schiff, MD, explained in a press release highlighting the findings. “Historically, HER2+ breast cancer was treated only by chemotherapy, but patient outcomes were poor. This changed in the late 1990s when the introduction of anti-HER2 therapy, drugs that block the growth effects of HER2, transformed the treatment of this disease.”
Schiff is a professor of medicine and molecular and cellular biology and a member of the Smith Breast Center and the Duncan Comprehensive Cancer Center at Baylor.
The team of investigators has been working for years to identify the most effective approach to treat HER2+ breast cancer. They previously found that targeting the HER2 protein with the anti-HER2 drugs lapatinib (Tykerb) and trastuzumab (Herceptin) before surgery resulted in a complete response in 25%-30% of cases — to the extent that chemotherapy was no longer needed.
The next challenge was to identify those 30% of patients at the time of diagnosis. To that end, they developed the novel molecular classifier test, which includes three components.
“The first component measures how much HER2 gene and protein is in the cancer cells and whether the expression is homogeneous throughout the tumor,” said Veeraraghavan, an assistant professor at Baylor. “All tumor cells must express high levels of HER2 for a higher chance of a complete response.”
The second component assesses whether the cancer is HER2-enriched, and the third focuses on the PIK3CA gene, as mutations in the gene bypass HER2-driven pathways, thereby providing alternative molecular paths that allow cancer cells to grow when the HER2 protein is blocked.
Test validation in the current study used baseline HER2+ breast cancer tumor specimens obtained from patients who participated in the TBCRC023 and PAMELA clinical trials of neoadjuvant lapatinib+trastuzumab (plus endocrine therapy in ER+ tumors).
HER2 protein and gene amplification (ratio), HER2-enriched (HER2-E), and PIK3CA mutation status were assessed by dual gene protein assay (GPA), research-based PAM50, and targeted DNA-sequencing. A decision-tree algorithm was used to construct GPA cutoffs and classifier of response in TBCRC023, and this yielded a positive predictive value (PPV) of 55% and negative predictive value (NPV) of 94%.
Independent validation in the PAMELA trial yielded 47% PPV and 82% NPV. The high NPV underscores the classifier’s ability to accurately identify patients who may not be good candidates for treatment de-escalation, the investigators noted.
“Traditionally, in an effort to eliminate the tumor, we give patients more aggressive treatments, but these also increase the toxicity and affect the patient’s quality of life,” Veeraraghavan explained. “But when we provide a personalized treatment, we are giving patients what they need to treat the tumor, not more, minimizing the consequences on their quality of life. This is an important aspect of precision medicine that we do not want to miss.”
Indeed, “studying the biology of the tumor tells us what would be needed to eliminate the tumor,” added senior author Mothaffar F. Rimawi. “Our findings strongly support that safe treatment de-escalation is possible.”
The team now plans to evaluate the molecular classifier in a prospective clinical trial to further validate its clinical utility, noted Rimawi, professor of medicine, executive medical director, and co-leader of the Breast Cancer Program at the Duncan Cancer Center.
“If validated prospectively, our classifier may function as a molecular triaging tool to safely and appropriately select patients with HER2+ breast cancer for treatment de-escalation,” Rimawi said.
This work was supported by the Department of Defense breast cancer research program breakthrough awards, Breast Cancer Research Foundation, NIH SPORE Grants, Cancer Center Grants, and support to the Translational Breast Cancer Research Consortium from the Breast Cancer Research Foundation. Veeraraghavan reports a patent for PCT/US21/70543 (methods for breast cancer treatment and prediction of therapeutic response) pending to Baylor College of Medicine.
Clinical Cancer Research. Published online June 28, 2023. Abstract
Sharon Worcester, MA, is an award-winning medical journalist based in Birmingham, Alabama, writing for Medscape, MDedge and other affiliate sites. She currently covers oncology, but she has also written on a variety of other medical specialties and healthcare topics. She can be reached at [email protected] or on Twitter: @SW_MedReporter .
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