HepatoScore-14: Measures of biological heterogeneity significantly improve prediction of hepatocellular carcinoma risk.

BACKGROUND & AIMS Therapeutic, clinical trial entry and stratification decisions for hepatocellular carcinoma (HCC) are made based on prognostic assessments, using clinical staging systems based on small numbers of empirically selected variables that insufficiently account for differences in biological characteristics of individual patients' disease. APPROACH & RESULTS We propose a novel approach for constructing risk scores from circulating biomarkers that produce a global biological characterization of individual patient's disease. Plasma samples were collected prospectively from 767 HCC patients and 200 controls, and 317 proteins were quantified in a CLIA-certified biomarker testing laboratory. We constructed a circulating biomarker aberration score for each patient, a score between 0 and 1 measuring the degree of aberration of their biomarker panel relative to normal, that we call HepatoScore. We used log-rank tests to assess its ability to sub-stratify patients within existing staging systems/prognostic factors. To enhance clinical application, we constructed a single-sample score, HepatoScore-14, requiring only a subset of 14 representative proteins encompassing the global biological effects. HCC patients were split into 3 distinct groups with low, medium, and high HepatoScore with vastly different prognoses (mOS 38.2/18.3/7.1m; P<0.0001). Further, HepatoScore accurately sub-stratified patients within levels of existing prognostic factors and staging systems (P<0.0001 for nearly all), providing substantial and sometimes dramatic refinement of expected patient outcomes with strong therapeutic implications. These results were recapitulated by HepatoScore-14, rigorously validated in repeated training/test splits, concordant across Myriad RBM and ELISA kits, and established as an independent prognostic factor. CONCLUSIONS HepatoScore-14 augments existing HCC staging systems, dramatically refining patient prognostic assessments and therapeutic decision making and enrollment in clinical trials. The novel underlying strategy provides a global biological characterization of disease, and can be applied broadly to other disease settings and biological media.