The UCLA Center in Early Detection of Liver Cancer

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Project Summary Liver cancer is the second most frequent cause of cancer deaths. While cancer mortality has been declining overall, liver cancer mortality has been rising steadily due to the increasing incidence of obesity and alcohol abuse. This high mortality is mainly due to challenges in early detection. The goal of this project is to integrate molecular, imaging, and clinical information for the early detection of Hepatocellular Carcinoma (HCC). In the previous grant period, we developed a highly sensitive and cost-effective method of using cell-free DNA methylome for cancer detection, and have successfully validated the technology on a pilot HCC versus cirrhosis cohort. We have also established multiple clinical cohorts to study HCC detection, including a prospective longitudinal HCC screening cohort of patients with cirrhosis or HBV. The availability of blood samples, imaging scans, and comprehensive clinical information of patients in those cohorts provide us with unique opportunities to develop an integrated cancer detection method in the next funding period. The UCLA center includes a multidisciplinary team of clinical and translational researchers, and we have the following foci in the next funding period: (1) Continued expansion of multiple clinical cohorts to facilitate early detection of liver cancer. These cohorts shall provide an invaluable resource for the proposed research and other consortium-wide projects. (2) Continued experimental and computational development to refine the cfDNA methylome assay for early cancer detection. Experimentally, we will address a key challenge in cfDNA-based early cancer detection, namely, the limited cfDNA input, and computationally we will extract additional features, in addition to DNA methylation, from the assay data to enhance cancer detection. (3) We will integrate epigenomic, imaging, and clinical information into a complementary approach for the detection of HCC. We will build etiology-specific models for the multi- modality data to maximize performance. (4) We will contribute to collaborative consortium activities. We have been enthusiastically participating in collaborations within and beyond the consortium. We are an active enrollment site for the consortium-wide clinical cohorts, and we will collaborate with other centers to develop multi-omics and multi-modality markers to exploit the diagnostic potential of blood samples and imaging data.