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

Sun Young Yim; Nahm Ji Hae; Ji-Hyun Shin; Yun Seong Jeong; Sang-Hee Kang; Young Nyun Park; Soon Ho Um; Ju-Seog Lee

doi:10.1016/j.yexmp.2019.104319

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

Exp Mol Pathol. 2019 Dec:111:104319. doi: 10.1016/j.yexmp.2019.104319. Epub 2019 Oct 30.

Authors

Sun Young Yim¹, Nahm Ji Hae², Ji-Hyun Shin³, Yun Seong Jeong³, Sang-Hee Kang⁴, Young Nyun Park², Soon Ho Um¹, Ju-Seog Lee⁵

Affiliations

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: [email protected].

PMID: 31676327
DOI: 10.1016/j.yexmp.2019.104319

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.

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

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers, Tumor / genetics
Biomarkers, Tumor / metabolism*
Carcinoma, Hepatocellular / diagnosis*
Carcinoma, Hepatocellular / etiology
Carcinoma, Hepatocellular / metabolism
Caveolin 1 / genetics
Caveolin 1 / metabolism*
Cell Proliferation*
Gene Expression Profiling
Humans
Liver Cirrhosis / complications*
Liver Neoplasms / diagnosis*
Liver Neoplasms / etiology
Liver Neoplasms / metabolism
Neoplasm Recurrence, Local / diagnosis*
Neoplasm Recurrence, Local / etiology
Neoplasm Recurrence, Local / metabolism
Prognosis
Protein Array Analysis
Retrospective Studies
Tumor Cells, Cultured

Substances

Biomarkers, Tumor
CAV1 protein, human
Caveolin 1