Literature DB >> 32931023

HepatoScore-14: Measures of Biological Heterogeneity Significantly Improve Prediction of Hepatocellular Carcinoma Risk.

Jeffrey S Morris1, Manal M Hassan2, Ye Emma Zohner3, Zeya Wang3,4, Lianchun Xiao5, Asif Rashid6, Abedul Haque7, Reham Abdel-Wahab8, Yehia I Mohamed8, Karri L Ballard9, Robert A Wolff8, Bhawana George7, Liang Li5, Genevera Allen3,10, Michael Weylandt3, Donghui Li8, Wenyi Wang4, Kanwal Raghav8, James Yao8, Hesham M Amin7, Ahmed Omar Kaseb8.   

Abstract

BACKGROUND AND 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 AND
RESULTS: We propose an 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 patients with HCC and 200 controls, and 317 proteins were quantified in a Clinical Laboratory Improvement Amendments-certified biomarker testing laboratory. We constructed a circulating biomarker aberration score for each patient, a score between 0 and 1 that measures the degree of aberration of his or her biomarker panel relative to normal, which we call HepatoScore. We used log-rank tests to assess its ability to substratify patients within existing staging systems/prognostic factors. To enhance clinical application, we constructed a single-sample score, HepatoScore-14, which requires only a subset of 14 representative proteins encompassing the global biological effects. Patients with HCC were split into three distinct groups (low, medium, and high HepatoScore) with vastly different prognoses (medial overall survival 38.2/18.3/7.1 months; P < 0.0001). Furthermore, HepatoScore accurately substratified 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 (Austin, TX) and enzyme-linked immunosorbent assay 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 underlying strategy provides a global biological characterization of disease, and can be applied broadly to other disease settings and biological media.
© 2020 by the American Association for the Study of Liver Diseases.

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Year:  2021        PMID: 32931023      PMCID: PMC7956911          DOI: 10.1002/hep.31555

Source DB:  PubMed          Journal:  Hepatology        ISSN: 0270-9139            Impact factor:   17.298


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Review 10.  The inflammatory microenvironment in hepatocellular carcinoma: a pivotal role for tumor-associated macrophages.

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  2 in total

1.  Bayesian Edge Regression in Undirected Graphical Models to Characterize Interpatient Heterogeneity in Cancer.

Authors:  Zeya Wang; Ahmed O Kaseb; Hesham M Amin; Manal M Hassan; Wenyi Wang; Jeffrey S Morris
Journal:  J Am Stat Assoc       Date:  2022-01-05       Impact factor: 4.369

2.  Disruption of Growth Hormone Receptor Signaling Abrogates Hepatocellular Carcinoma Development.

Authors:  Abedul Haque; Vishal Sahu; Jamie Lynne Lombardo; Lianchun Xiao; Bhawana George; Robert A Wolff; Jeffrey S Morris; Asif Rashid; John J Kopchick; Ahmed O Kaseb; Hesham M Amin
Journal:  J Hepatocell Carcinoma       Date:  2022-08-15
  2 in total

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