Signature can identify hepatocellular carcinoma patients before clinical diagnosis
FRIDAY, July 10, 2020 (HealthDay News) — A viral exposure signature can predict hepatocellular carcinoma (HCC) risk before clinical diagnosis among at-risk patients, according to a study published online June 10 in Cell.
Jinping Liu, Ph.D., of the National Cancer Institute in Bethesda, Maryland, and colleagues used a synthetic human virome technology, VirScan, to perform serological profiling of viral infection history in 899 individuals from a case-control study. A viral exposure signature was developed, and the results were validated in a longitudinal cohort with 173 at-risk patients with long-term follow-up for HCC development.
The researchers found that among at-risk individuals in the validation cohort, the viral exposure signature was significantly associated with HCC status (area under the curve, 0.91 at baseline and 0.98 at diagnosis). The signature was superior to alpha-fetoprotein and identified cancer patients before clinical diagnosis.
“Together with existing screening tests, the new test could play an important role in screening people who are at risk for developing HCC. It could help doctors find and treat HCC early,” a coauthor said in a statement. “The method is relatively simple and inexpensive, and it only requires a small blood sample.”
Several authors are listed as inventors on a U.S. patent application for the viral exposure signature for detection of early-stage HCC.
Urine Cell-Free RNA Shows Promise as Biomarker for Bladder Cancer
Age-, Joint-Specific Ultrasound Reference Values Set for Healthy Joints
Steatotic Liver Disease Risk Scores Compared for Predicting Cirrhosis
Retinal Imaging Can ID Atrial Fibrillation Years Before Diagnosis
U.S. Adults May Not Understand Their Risk for Vascular Disease
NOACs Linked to Slower Cognitive Decline in Patients With A-Fib, Alzheimer Disease
Machine Learning Model IDs Heart Failure With Reduced Ejection Fraction Using Routine Lab Indicators
Addition of CAC to PREVENT-ASCVD Equations May Improve Predictive Utility in Certain Patients