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Biomarkers of hepatocellular synthesis predict mortality in patients with decompensated cirrhosis

ABSTRACT: Background & Aims: Since liver hepatocytes produce the majority of serum proteins, liver cirrhosis displays a massive alteration in serum proteome. The aim of the current study was to characterize these alterations and to study the prognostic usefulness of hepatocellular proteins available in routine clinical testing. Methods: Sera from 29 healthy controls and 43 cirrhotic subjects were subjected to untargeted proteomic analysis. The data were analyzed by Perseus program, R and unsupervised hierarchical clustering. The prognostic usefulness potential of selected biomarkers was tested in 61 controls and 285 cirrhotic individuals. Ingenuity pathway analysis (IPA) was employed to determine the upstream regulators that were further validated in 9 control and 9 cirrhotic livers. Results: Proteomics uncovered 65 down- and 16 upregulated hepatocellular serum proteins that are significantly down- respectively upregulated in cirrhotic subjects versus controls. Hierarchical clustering revealed two main clusters and 6 subclusters, while IPA identified HNF4α and IL6 as the two major upstream regulators that were confirmed in gene expression analyses. Pseudocholinesterase (AUROC 0.618; P=0.002), transferrin (AUROC 0.594; P=0.013), and transthyretin (TTR; AUROC 0.586; P=0.023) but not albumin serum levels discriminated between 90 days transplant-free survivors vs. non-survivors. Tree learning decision algorithm identified transthyretin as a biomarker that improved the prediction of death or transplant in the subset of patients with acute-on-chronic liver failure (ACLF). TTR≤58 mg/dl conferred an increased risk in both univariate (HR 1.75; 95% CI 1.14-2.67; P=0.01) and multivariable analysis (aHR 1.59; 95% CI 1.04-2.24; P=0.033). Conclusion: Our study uncovers the changes in hepatocellular serum proteins as well as the underlying transcriptional factors and suggest that transthyretin may constitute an useful prognostic adjunct in ACLF subjects.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Liver Cirrhosis

SUBMITTER: Christian Preisinger

LAB HEAD: Pavel Strnad

PROVIDER: PXD035024 | Pride | 2023-11-20

REPOSITORIES: Pride

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			Action	DRS
	MQ_output.zip	Other
	OR2_2021_08_13_PaStr_cirr_serum_ctrl29_1.raw	Raw
	OR2_2021_08_13_PaStr_cirr_serum_ctrl29_2.raw	Raw
	OR2_2021_08_13_PaStr_cirr_serum_ctrl29_3.raw	Raw
	OR2_2021_08_13_PaStr_cirr_serum_ctrl29_4.raw	Raw

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Project description:BACKGROUND & AIMS: In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona-Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. METHODS: We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. RESULTS: Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. CONCLUSIONS: We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses. Center and peripheral portions of hepatocellular carcinoma tumors as well as surrounding non-tumor cirrhotic liver tissues were obtained from fresh frozen surgically resected tissues, and isolated total RNA samples were analyzed for genome-wide expression profiles.

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Biomarkers of hepatocellular synthesis predict mortality in patients with decompensated cirrhosis

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