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Digital Biomarker Assay Identifies Breast Cancer Patients with Low Expression of HER2 Protein

By LabMedica International staff writers
Posted on 05 Jul 2022
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Image: New digital biomarker assay identifies patients with expression of HER2 in breast cancer (Photo courtesy of Paige)
Image: New digital biomarker assay identifies patients with expression of HER2 in breast cancer (Photo courtesy of Paige)

Human epidermal growth factor receptor 2 (HER2) is a protein that promotes breast cancer cell growth, and breast cancer cells with excess levels of HER2 are called HER2-positive. Targeted therapies for HER2-positive tumors have been a mainstay of cancer treatment over the past two decades. Recent evidence suggests there may be a subgroup of patients who are considered HER2-negative through standard immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) testing but may actually have low or ultra-low levels of HER2, and therefore may be responsive to particular investigative therapies. It has been challenging to identify these patients reliably and reproducibly using conventional methods, calling for the development of novel ways to assess a patient’s HER2 status that are more accurate and sensitive than traditional assays, which were designed and optimized to detect high levels of HER2 expression. Now, a new artificial intelligence (AI) software can identify patients with breast cancer whose tumors have expressions of HER2 protein.

In contrast to traditional IHC tests for HER2, Paige’s (New York, NY, USA) HER2Complete AI software is deployed to detect HER2 expression based on protein and mRNA levels on digital images of H&E-stained tissue samples, with results generated rapidly at the click of a button. In a recent study, HER2Complete was able to detect levels of HER2 expression in HER2-negative (IHC-0) and HER2-low (IHC1+/2+) hematoxylin and eosin (H&E)-stained tissue samples, making it the first and only AI biomarker assay capable of doing so. This approach complements existing IHC testing to potentially identify true HER2-expressing breast cancers without the need for special staining approaches and with a very rapid turnaround using only the diagnostic biopsy or resection slides.

Further, HER2Complete has been used to detect true HER2-negative disease, whose definitive identification based on a lack of IHC and mRNA HER2 expression may accelerate efforts for developing new therapies for this important group of patients who may not benefit from HER2 targeted therapies. This approach does not require any special labeling of the tissue sample and can be done rapidly and easily on standard tissue preparations using methods that already exist in labs across the globe. Paige has received CE-IVD and UKCA marks for HER2Complete, making it the first CE-IVD and UKCA designated tool to explore the novel space of HER2-low.

“AI brings a transformational approach to diagnostics and allows us to identify low levels of HER2 in tissue that we would not be able to detect using current assays,” said David Klimstra, M.D., Founder and Chief Medical Officer at Paige. “We are working to enable the next generation of HER2 testing to provide the information physicians need to guide the use of next generation HER2 therapy. We believe that this assay will allow us to reliably identify increased likelihood of HER2 expression, even on samples where HER2 expression was misclassified by legacy diagnostics as low or null.”

“Our product is potentially a very targeted and cost-effective solution to identify a subset of patients who have previously been unidentified,” said Jill Stefanelli, Ph.D., President and Chief Business Officer at Paige. “Paige is developing an end-to-end solution to detect and further characterize breast cancer so that pathologists and oncologists get comprehensive insights into an individual’s cancer. We look forward to assessing the clinical utility with multiple potential partners in order to link this test to treatment outcomes.”

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