The presentations, led by Shivani Mahajan, PhD, highlight the diagnostic potential of the company’s AI-powered platform, which combines cell-free DNA methylation patterns with protein biomarkers. Clinical data showcased at the symposium point to three specific areas where the blood test may bridge gaps in current surveillance protocols: identifying missed lesions, clarifying ambiguous scans, and providing a lead-time advantage over radiographic detection.
In section Releases
Helio Genomics Debuts Liver Cancer Detection Data at SALCS Symposium
At the San Antonio Liver Cancer Symposium, Irvine-based Helio Genomics is presenting four studies that evaluate the performance of its HelioLiver™ Dx blood test. The research focuses on the platform’s ability to detect hepatocellular carcinoma when traditional ultrasound imaging fails or produces indeterminate results in high-risk patients.
In some cases, the test identified molecular signals up to nine months before a tumor became visible on traditional scans. Hrishikesh Samant, MD, noted that these molecular signals offer physicians a critical secondary metric when imaging findings remain inconclusive. By integrating machine learning with longitudinal modeling, the company aims to move detection into an earlier window, potentially increasing the number of patients eligible for curative interventions. The data suggests that molecular changes often precede the structural tumor growth required for clear radiographic identification.
Comments (0)
No comments yet. Be the first!