Justin Drake, PhD, discusses the latest research on a protein-based liquid biopsy to detect early breast cancer

Justin Drake, PhD, chief science officer of Astrin Biosciences, stated that “women, especially women with dense breasts, the screening options for breast cancer are not adequate.” Traditional mammography may detect “up to 50% of lesions in women with dense breasts,” leaving many patients without effective follow-up screening options after a negative mammogram

Drake explained that the investigational test is designed as a supplemental screening strategy following mammography in women with dense breasts. According to Drake, the aim is “to develop a test as a supplemental screening option for these women post mammogram to give them other options.”

Protein-based approach to liquid biopsy

Most early cancer liquid biopsy platforms focus on circulating DNA, RNA, or methylation signals. Drake noted that the Astrin approach “is a protein-based test,” using plasma-based proteomic profiling of “over 9000 proteins on a per patient basis.” The analysis compares protein signatures of healthy individuals with those of individuals with early-stage breast cancer.

Drake reported the results of a study involving “over 1200 women,” using biobank specimens from healthy women and patients with early-stage breast cancer. Machine learning was used to identify classifiers associated with the disease. According to Drake, investigators “are able to detect breast cancer in these women with the sensitivity of greater than 90% and the specificity…greater than 90% as well.”

Potential biologic pathways associated with early disease

Exploratory analysis identified cancer-related signaling patterns, although Drake noted that individual protein markers were not disclosed. “We did do some just standard Hallmark pathway analysis” and observed changes involving “the PI3K, AKT signaling pathway,” epithelial-to-mesenchymal transition, and “some beta catenin and mTOR signaling as well.”

Distinguishing protein-based assays from nucleotide methods

Drake described features of breast cancer biology that may limit DNA-based detection during early disease. Tumor shedding of DNA or RNA may be less robust in early breast cancer than in other cancers, such as lung or colorectal malignancies. As a result, “finding the analyte is more challenging at the nucleotide level,” he said.

In contrast, intercellular signaling mediated by proteins may be detectable even when circulating tumor nucleic acids are minimal. Drake stated that proteins “allow us to find these, you know, very discrete signals that that nucleotide-based assays can’t really find,” and that protein-level communication is “more present and more abundant in the blood versus what you might see with nucleotide-based assays.”

Clinical context and potential use after mammography

Initial findings indicated consistent performance in women with dense and nondense breast tissue, according to Drake. Based on the current data, the company anticipates the test could function as a post-mammogram supplemental tool. Women with a negative result may have “a very high negative predictive value of greater than 99.9%,” which may support routine follow-up. In contrast, a positive result may prompt referral for supplemental imaging or further evaluation.

At present, Drake stated the test is indicated for “women at medium to high risk or moderate to high risk over 40 years of age, and women at high risk under 40 years of age,” with plans for future expansion.

Disclosure

Drake is chief science officer of Astrin Biosciences.

Reference

Horrmann A, Travadi Y, Carey J, et al. Deep Proteomics and AI Classifier for Early Breast Cancer Detection. Poster. Presented at: San Antonio Breast Cancer Symposium. December 9-12, 2025. San Antonio, Texas.