Bioinformatics Analysis of the SIRT Family Members and Assessment of Their Potential Clinical Value.

Abstract

BACKGROUND:

Hepatocellular carcinoma (HCC) is a highly malignant and common tumor. Many biomarkers have been identified for HCC. However, the available ones are not accurate enough in term of prognostic value and new markers are needed for the prognosis of this disease. Sirtuins are NAD(+)-dependent histone deacetylases involved in many biological processes of cancers, consisting of family members SIRT1-SIRT7. However, the prognostic value of the SIRTs in HCC remains largely unknown.

METHODS:

Differential expression of SIRTs and survival analysis were assessed in patients with HCC using Oncomine and UALCAN databases. Gene set enrichment analysis (GSEA) was used for pathway analysis. Metascape software was used to construct gene ontologies, metabolic pathways and protein-protein interaction networks. Moreover, a HCC murine model was used to validate the expression levels of SIRT3/6/7 expression.

RESULTS:

Differential expression analysis suggested that SIRT2-7, not SIRT1, were expressed at higher levels in HCC tissues compared to adjacent normal tissues. These SIRTs showed some similarities, as revealed by GO and KEGG pathway. Higher SIRT3/6/7 mRNA expression levels were found to be significantly associated with shorter overall survival (OS) in HCC patients. Both SIRT3/6/7 mRNA and protein levels were highly expressed in HCC. In addition, over-expression of SIRT3/6/7 was associated with tumor stage and grade in HCC patients. Univariate analysis showed that SIRT 6/7 expressions were linked to a shorter OS of HCC patients. Multivariate analysis showed that SIRT7 levels were independently associated with a significantly shorter OS in HCC patients.

CONCLUSION:

Differentially expressed SIRT3/6/7 were significantly associated with tumor stage, grade and OS in HCC patients. In addition, SIRT7 were independently associated with a significantly shorter OS in HCC patients. Thus, SIRT3/6/7 can be used as prognostic biomarkers to predict the survival of HCC patients.

• Authors: Mingjiang Liu, Jingjing Yu, Hu Jin, Sifan Wang, Jin Ding, Hao Xing, Songqing He, Yonglian Zeng
• Journal: OncoTargets and therapy (Onco Targets Ther) Vol. 14 Pg. 2635-2649 ( 2021) ISSN: 1178-6930 [Print] New Zealand
• PMID: 33883907 (Publication Type: Journal Article)
• Copyright: © 2021 Liu et al.