AKR1B10 expression characteristics in hepatocellular carcinoma and its correlation with clinicopathological features and immune microenvironment

Abstract

Hepatocellular carcinoma (HCC) represents a major global health threat with diverse and complex pathogenesis. Aldo-keto reductase family 1 member B10 (AKR1B10), a tumor-associated enzyme, exhibits abnormal expression in various cancers. However, a comprehensive understanding of AKR1B10's role in HCC is lacking. This study aims to explore the expression characteristics of AKR1B10 in HCC and its correlation with clinicopathological features, survival prognosis, and tumor immune microenvironment, further investigating its role and potential regulatory mechanisms in HCC. This study conducted comprehensive analyses using various bioinformatics tools and databases. Initially, differentially expressed genes related to HCC were identified from the GEO database, and the expression of AKR1B10 in HCC and other cancers was compared using TIMER and GEPIA databases, with validation of its specificity in HCC tissue samples using the HPA database. Furthermore, the relationship of AKR1B10 expression with clinicopathological features (age, gender, tumor size, staging, etc.) of HCC patients was analyzed using the TCGA database's LIHC dataset. The impact of AKR1B10 expression levels on patient prognosis was evaluated using Kaplan-Meier survival analysis and the Cox proportional hazards model. Additionally, the correlation of AKR1B10 expression with tumor biology-related signaling pathways and tumor immune microenvironment was studied using databases like GSEA, Targetscan, and others, identifying microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) that regulate AKR1B10 expression to explore potential regulatory mechanisms. Elevated AKR1B10 expression was significantly associated with gender, primary tumor size, and fibrosis stage in HCC tissues. High AKR1B10 expression indicated poor prognosis and served as an independent predictor for patient outcomes. Detailed mechanism analysis revealed a positive correlation between high AKR1B10 expression, immune cell infiltration, and pro-inflammatory cytokines, suggesting a potential DANCR-miR-216a-5p-AKR1B10 axis regulating the tumor microenvironment and impacting HCC development and prognosis. The heightened expression of AKR1B10 in HCC is not only related to significant clinical-pathological traits but may also influence HCC progression and prognosis by activating key signaling pathways and altering the tumor immune microenvironment. These findings provide new insights into the role of AKR1B10 in HCC pathogenesis and highlight its potential as a biomarker and therapeutic target.

Keywords: AKR1B10; Clinical-pathological features; Hepatocellular carcinoma; Immune microenvironment; Regulatory mechanisms; Survival prognosis.

Figure 1

High expression of AKR1B10 in hepatocellular carcinoma: (a) significantly overexpressed differentially expressed genes in six datasets, (b) significantly underexpressed differentially expressed genes in six datasets, (c) expression of AKR1B10 in various cancers, (d) differential expression of AKR1B10 in liver cancer tissues compared to non-cancerous tissues in non-paired samples, (e) Differential expression of AKR1B10 in liver cancer tissues compared to non-cancerous tissues in paired samples.

Figure 2

Expression of AKR1B10 at the Tissue Level in the HPA Database: (a–c) IHC shows no detection of AKR1B10 expression in normal liver tissues, (d–f) High levels of AKR1B10 expression observed in liver cancer tissues, (g–i) IF demonstrates the localization of AKR1B10 in HepG2 liver cancer cells.

Figure 3

Correlation between AKR1B10 expression and clinicopathological features in hepatocellular carcinoma patients: (a) correlation with gender, (b) correlation with T stage, (c) correlation with tissue grading, (d) correlation with postoperative tissue margin status, (e) correlation with inflammation in adjacent tissues, (f) correlation with Ishak fibrosis score.

Figure 4

Correlation between AKR1B10 expression and prognosis in liver cancer patients in the GSCA database: (a) correlation of AKR1B10 with the prognosis of patients with six types of cancer: CHOL, LIHC, LUAD, LUSC, PRAD, UCEC; (b–e) correlation between the prognosis of liver cancer patients and the expression level of AKR1B10.

Figure 5

GSEA functional enrichment analysis of genes associated with AKR1B10 (a–d).

Figure 6

AKR1B10 functional clustering and interaction network analysis of AKR1B10-related genes: (a) heatmap showing the top 25 genes in LIHC that were positively related to AKR1B10, (b) heatmap showing the top 25 genes in LIHC that were negatively related to AKR1B10, (c) Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of AKR1B10-related genes in LIHC, (d) Venn diagram of AKR1B10-related genes and survival-related genes in LIHC, (e) GO term and KEGG pathway analyses of AKR1B10-related genes and survival-related genes in LIHC, (f) AKR1B10-survival-related gene interaction in chord diagram, (g) Gene coexpression matrix.

Figure 7

Analysis of the correlation between AKR1B10 and the tumor immune microenvironment: (a) analysis of tumor-related immune cell infiltration between high and low AKR1B10 expression groups based on public data, (b,c) analysis of the correlation between AKR1B10 and immune-promoting factors, (d) analysis of the correlation between AKR1B10 and immune-inhibitory factors.

Figure 8

Predicted ceRNAs Interacting with AKR1B10: (a) miRNAs predicted from three datasets, (b–e) correlation analysis between AKR1B10 and miRNAs, (f) LncRNAs predicted from three datasets.

Figure 9

Correlation Analysis of LncRNAs in LIHC: (a–e) correlation analysis of the five predicted LncRNAs with the overall survival rate of liver cancer patients, (f) expression differences of DANCR in liver cancer tissues compared to non-cancerous tissues in unpaired samples.