On April 8, 2024 Exai Bio reported new breast cancer data at the American Association for Cancer Research (AACR) (Free AACR Whitepaper) 2024 annual meeting. In a new study, Exai’s novel RNA- and AI-based liquid biopsy platform demonstrated stage I breast cancer detection sensitivity of 90% and ductal carcinoma in situ (DCIS) sensitivity of 88%, both at 90% specificity (Press release, Exai Bio, APR 8, 2024, View Source [SID1234641908]). In addition, the study showed the platform’s unique capability to distinguish low grade, less aggressive DCIS from invasive breast cancer with 87% sensitivity, at 90% specificity using a standard blood sample. More than 55,000 women were diagnosed with DCIS in 2023 in the United States. The current standard of care treatment for the majority of these women is invasive treatment despite the fact that an estimated 60–80% of cases do not progress to cancer. These early data suggest a blood test can become an effective way to not only detect early-stage breast cancer but also monitor low grade DCIS so that more women can have the option of avoiding aggressive or unnecessary treatment.
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"These results further validate the power of Exai’s novel RNA- and AI-based liquid biopsy platform to detect breast cancer at its earliest stages with high sensitivity, overcoming the limitations of DNA-based approaches"
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"These results further validate the power of Exai’s novel RNA- and AI-based liquid biopsy platform to detect breast cancer at its earliest stages with high sensitivity, overcoming the limitations of DNA-based approaches," stated Pat Arensdorf, Chief Executive Officer of Exai Bio. "In addition to strong early detection performance, this study also demonstrated for the first time that our platform can distinguish low grade DCIS from invasive breast cancer with high accuracy. These findings are very promising and indicate the potential for a blood-based test to monitor women who are diagnosed with low grade DCIS."
In addition, Exai announced results from a new breast cancer molecular residual disease (MRD) study conducted in collaboration with the University of Kansas Medical Center. The study demonstrated that Exai’s tumor-naive platform — which does not require sequencing the tumor tissue — can accurately predict survival in the post-adjuvant setting for patients with triple negative breast cancer. These results suggest the potential for Exai’s platform to aid in tailoring adjuvant treatment for individual triple negative breast cancer patients.
Exai’s platform uses RNA sequencing to identify a novel category of cancer-associated, small non-coding RNAs, termed orphan non-coding RNAs (oncRNAs). oncRNAs are actively secreted from living cancer cells and are stable and abundant in the blood of cancer patients. Exai has created a catalog of hundreds of thousands of oncRNAs and thousands of patient oncRNA profiles, spanning all major cancer types. When combined with proprietary artificial intelligence technology, the Exai platform has multiple technical and operational advantages over tests that utilize circulating tumor DNA. These include superior sensitivity and specificity, as well as the ability to reveal dynamic changes in the biology of a patient’s tumor over time. Exai’s universal platform can be used across multiple cancer care settings such as screening and early detection, monitoring, molecular residual disease, and therapy selection.
AACR Presentation Details
Title: Beyond detection: AI-based classification of breast cancer invasiveness using cell-free orphan non-coding RNAs
Abstract Number: 3678
Session: Clinical Research Excluding Trial, Circulating Nucleic Acids 3, Poster Section 41
Authors: M. Karimzadeh, T. Cavazos, N. Chen, N. Tbeileh, D. Siegel, A. Momen-Roknabadi, J. Yen, J. Ku, S. Chen, D. Corti, A. Huang, D. Nguyen, R. Hanna, T. Lam, S. Kilinc, P. Murzynowski, J. Wang, X. Zhao, A. Pohl, B. Behsaz, H. Li, L. Fish, K. Chau, L. Van’t Veer, L. Esserman, P. Arensdorf, H. Goodarzi, F. Hormozdiari, B. Alipanahi
Title: Orphan non-coding RNA (oncRNA) liquid biopsy assay is prognostic for survival in patients with triple-negative breast cancer (TNBC) and residual disease
Abstract Number: 5215
Session: Clinical Research Excluding Trial, Prognostic Biomarkers 1, Poster Section 46
Authors: R. Yoder, J. Yen, M. Karimzadeh, J. Staley, I. Fernandez, A. Heinrich, F. Hormozdiari, J. Gregg, A. Godwin, I. Acerbi, R. Trivedi, B. Alipanahi, S. Stecklein, P. Sharma