Hepatocellular carcinoma (HCC) is the second leading cause of cancer mortality worldwide. Early HCC diagnosis increases survival, but the current HCC surveillance tests (ultrasound and serum alpha-fetoprotein) have suboptimal accuracy. We have integrated meta-analysis and microarray data to identify certain methylated cell-free DNA biomarkers for HCC. I will employ giant magnetoresistive biosensor technology to develop a rapid and low-cost multiplexed assay to screen and quantify these biomarkers, and then validate the accuracy of this HCC biomarker diagnostic in a well-characterized multicenter cohort. This interdisciplinary approach of computational modeling, bioinformatics, and biosensing techniques will pave the way to cost-effective and portable HCC surveillance based on highly accurate HCC biomarkers, and will improve HCC survival.