Identification of prognostic biomarker in predicting hepatocarcinogenesis from cirrhotic liver using protein and gene signatures. - PubMed - NCBI

Identification of prognostic biomarker in predicting hepatocarcinogenesis from cirrhotic liver using protein and gene signatures. - PubMed - NCBI

Exp Mol Pathol. 2019 Oct 30;111:104319. doi: 10.1016/j.yexmp.2019.104319. [Epub ahead of print]

Identification of prognostic biomarker in predicting hepatocarcinogenesis from cirrhotic liver using protein and gene signatures.

Yim SY1, Hae NJ2, Shin JH3, Jeong YS3, Kang SH4, Park YN2, Um SH1, Lee JS5.

Author information

1

Department of Internal Medicine, University College of Medicine, Republic of Korea.

2

Department of Pathology, Yonsei University College of Medicine, Republic of Korea.

3

Department of Systems Biology, Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

4

Department of Surgery, Korea University College of Medicine, Seoul, Republic of Korea.

5

Department of Systems Biology, Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address: jlee@mdanderson.org.

Abstract

INTRODUCTION:

Cirrhosis primes the liver for hepatocellular carcinoma (HCC) development. However, biomarkers that predict HCC in cirrhosis patients are lacking. Thus, we aimed to identify a biomarker directly from protein analysis and relate it with transcriptomic data to validate in larger cohorts.

MATERIAL AND METHOD:

Forty-six patients who underwent hepatectomy for HCC that arose from cirrhotic liver were enrolled. Reverse-phase protein array and microarray data of these patients were analyzed. Clinical validation was performed in two independent cohorts and functional validation using cell and tissue microarray (TMA).

RESULTS:

Systematic analysis performed after selecting 20 proteins from 201 proteins with AUROC >70 effectively categorized patients into high (n = 20) or low (n = 26) risk HCC groups. Proteome-derived late recurrence (PDLR)-gene signature comprising 298 genes that significantly differed between high and low risk groups predicted HCC well in a cohort of 216 cirrhosis patients and also de novo HCC recurrence in a cohort of 259 patients who underwent hepatectomy. Among 20 proteins that were selected for analysis, caveolin-1 (CAV1) was the most dominant protein that categorized the patients into high and low risk groups (P < .001). In a multivariate analysis, compared with other clinical variables, the PDLR-gene signature remained as a significant predictor of HCC (HR 1.904, P = .01). In vitro experiments revealed that compared with mock-transduced immortalized liver cells, CAV1-transduced cells showed significantly increased proliferation (P < .001) and colony formation in soft agar (P < .033). TMA with immunohistochemistry showed that tissues with CAV1 expression were more likely to develop HCC than tissues without CAV1 expression (P = .047).

CONCLUSION:

CAV1 expression predicts HCC development, making it a potential biomarker and target for preventive therapy.

Copyright © 2019. Published by Elsevier Inc.

KEYWORDS:

Caveolin-1; Hepatocellular carcinoma; Liver cirrhosis; Reverse-phase protein array

PMID:

 

31676327

 

DOI:

 

10.1016/j.yexmp.2019.104319