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. 2022 Mar 29:15:277-300.
doi: 10.2147/PGPM.S349350. eCollection 2022.

Acyl-CoA Binding Domain Containing 4 Polymorphism rs4986172 and Expression Can Serve as Overall Survival Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients After Hepatectomy

Huasheng Huang #  1 , Xiwen Liao #  1 , Guangzhi Zhu  1 , Chuangye Han  1 , Xiangkun Wang  1 , Chengkun Yang  1 , Xin Zhou  1 , Tianyi Liang  1 , Ketuan Huang  1 , Tao Peng  1
Affiliations

Acyl-CoA Binding Domain Containing 4 Polymorphism rs4986172 and Expression Can Serve as Overall Survival Biomarkers for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients After Hepatectomy

Huasheng Huang et al. Pharmgenomics Pers Med. .

Abstract

Background: The aim of our study was to evaluate the potential of expression and single nucleotide polymorphism of Acyl-CoA binding domain containing 4 (ACBD4) gene as prognosis biomarkers in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) after hepatectomy.

Methods: HBV-related HCC patients from the First Affiliated Hospital of Guangxi Medical University and GSE14520 were included in the current study, as well as The Cancer Genome Atlas (TCGA) HCC verification cohort. Prognostic analysis and multiple functional enrichment analysis methods were used to evaluate the prognostic value and potential biological functions of the ACBD4 gene in HBV-related HCC.

Results: We found that ACBD4 gene is highly expressed in normal liver tissues and markedly down-regulated in HBV-related HCC tissues. ACBD4 gene was significantly related to overall survival (OS) of HCC in TCGA and GSE14520 cohorts, and patients with low ACBD4 expression were markedly related to poor OS. Rs4986172 was observed as an OS biomarker after hepatectomy in the Guangxi HBV-related HCC cohort. The OS of rs4986172 GG genotype was worse than that of HCC patients with A allele (AA and AG genotypes). Multifunctional enrichment analysis suggested that ACBD4 gene is closely related to the metabolic, peroxisome proliferator-activated receptor and cytochrome P450 pathway. Through connectivity map, we also identified eight compounds that may be used as targeted therapeutic agents for ACBD4 gene in HBV-related HCC; these compounds were scopoletin, alfaxalone, bephenium hydroxynaphthoate, apramycin, 4,5-dianilinophthalimide, DL-thiorphan, aminohippuric acid and quinidine. Immune microenvironment analysis revealed that there were significant differences in immune scores of HBV-related HCC tumor tissues with different ACBD4 expression levels.

Conclusion: Our study reveals that ACBD4 expression and rs4986172 can be serve as biomarkers of OS in HBV-related HCC patients after hepatectomy.

Keywords: ACBD4; HBV-related HCC; hepatectomy; overall survival; rs4986172.

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Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Violin diagram of ACBD4 gene expression level distribution in normal human organ tissues from GTEx database.
Figure 2
Figure 2
The diagnostic and prognostic values of ACBD4 in GSE14520 HBV-related HCC cohort. (A) Expression distribution of ACBD4 in tumor and adjacent paracancerous tissues; (B) the ROC curve of ACBD4 gene in distinguished tumor and adjacent paracancerous tissues; (C) Kaplan-Meier curve of ACBD4 in HBV-related HCC recurrence-free survival time; (D) Kaplan-Meier curve of ACBD4 in HBV-related HCC overall survival time.
Figure 3
Figure 3
Stratified survival analysis results of ACBD4 gene in GSE14520 HBV-related HCC cohort.
Figure 4
Figure 4
Joint effect survival analysis of ACBD4 expression and clinical parameters in GSE14520 HBV-related HCC patients. (A) Joint effect survival analysis of ACBD4 and tumor size; (B) Joint effect survival analysis of ACBD4 and cirrhosis; (C) Joint effect survival analysis of ACBD4 and BCLC stage; (D) Joint effect survival analysis of ACBD4 and serum AFP.
Figure 5
Figure 5
The nomogram of ACBD4 and clinical parameters in the GSE14520 HBV-related HCC cohort.
Figure 6
Figure 6
Prognostic value of ACBD4 gene in TCGA HCC cohort. (A) Kaplan-Meier curve of ACBD4 in HCC recurrence-free survival time; (B) Kaplan-Meier curve of ACBD4 in HCC overall survival time; (C) Kaplan-Meier curve of ACBD4 in HCC progression-free survival time; (D) Kaplan-Meier curve of ACBD4 in HCC disease-specific survival time.
Figure 7
Figure 7
Prognostic value of ACBD4-rs4986172 in Guangxi HBV-related HCC cohort. (A) Kaplan-Meier curve of AA, AG and GG; (B) Kaplan-Meier curve of AA+AG and GG; (C) Kaplan-Meier curve of AA and AG+GG.
Figure 8
Figure 8
Stratified survival analysis results of ACBD4-rs4986172 in Guangxi HBV-related HCC cohort.
Figure 9
Figure 9
Joint effect survival analysis of ACBD4-rs4986172 and clinical parameters in Guangxi HBV-related HCC patients. (A) Joint effect survival analysis of rs4986172 and serum AFP; (B) Joint effect survival analysis of rs4986172 and BCLC stage; (C) Joint effect survival analysis of rs4986172 and PVTT; (D) Joint effect survival analysis of rs4986172 and radical resection. (E) Joint effect survival analysis of rs4986172 and tumor size; (F) Joint effect survival analysis of rs4986172 and tumor number.
Figure 10
Figure 10
The nomogram of ACBD4-rs4986172 and clinical parameters in the Guangxi HBV-related HCC cohort. (A) AA, AG and GG genotypes in HBV-related HCC; (B) AA+AG and GG genotypes in HBV-related HCC.
Figure 11
Figure 11
Genome-wide co-expression network of ACBD4 gene in HBV-related HCC tumor tissues of patients in GSE14520 cohort.
Figure 12
Figure 12
Volcano plot of DEGs between low- and high-ACBD4 expression groups.
Figure 13
Figure 13
GSEA results between low- and high-ACBD4 expression groups by using c2 reference gene set. (A) nuclear receptor transcription pathway; (B) mTOR signaling up; (C) liver cancer recurrence down; (D) liver cancer poor survival down; (E) PPAR signaling pathway; (F) metabolism cytochrome P450; (G) oxidation by cytochrome P450; (H) bile acid and bile salt metabolism; (I) stress pathway; (J) fatty acid metabolism; (K) tumor invasiveness up; (L) metastasis up.
Figure 14
Figure 14
GSEA results between low- and high-ACBD4 expression groups by using c5 reference gene set. (A) fatty acid metabolic process; (B) polysaccharide catabolic process; (C) bile acid metabolic process; (D) alcohol catabolic process; (E) lipid accumulation in hepatocytes; (F) positive regulation of G protein coupled receptor signaling pathway; (G) fatty acid metabolic process; (H) lipoprotein metabolic process; (I) steroid metabolic process; (J) bile acid and bile salt transport; (K) drug metabolic process; (L) abnormality of hepatobiliary system physiology.
Figure 15
Figure 15
CMap result of ACBD4 in HCC. (A) Chemical construction of scopoletin; (B) Chemical construction of alfaxalone; (C) Chemical construction of bephenium hydroxynaphthoate; (D) Chemical construction of apramycin; (E) Chemical construction of 4,5-dianilinophthalimide; (F) Chemical construction of DL-thiorphan; (G) Chemical construction of aminohippuric acid; (H) Chemical construction of quinidine; (I) Summary table of CMap results.
Figure 16
Figure 16
Drug-gene interaction network of compounds identified by CMap.
Figure 17
Figure 17
Score of ACBD4 gene in HBV-HCC immune microenvironment.
See this image and copyright information in PMC

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