Downregulated miR-23b-3p expression acts as a predictor of hepatocellular carcinoma progression: A study based on public data and RT-qPCR verification

Abstract

Mounting evidence has shown that miR-23b-3p, which is associated with cell proliferation, invasion, and apoptosis, acts as a biomarker for diagnosis and outcomes in numerous cancers. However, the clinicopathological implication of miR-23b-3p in hepatocellular carcinoma (HCC) remains unclear. Our study evaluated the role of miR-23b-3p in HCC and investigated its potential application as a marker for preliminary diagnosis and therapy in HCC. High-throughput data from the NCBI Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were collected and analyzed. One hundred and one tissue sections of HCC were paired with adjacent non-cancerous HCC as further supplements. miR-23b-3p expression was detected using quantitative real-time PCR. Additionally, the relationship between miR-23b-3p expression and HCC progression and Time-to-recurrence (months) was explored. Ten algorithms were applied to predict the prospective target genes of miR-23b-3p. Next, we conducted bioinformatics analysis for further study. miR-23b-3p expression was pronouncedly decreased in HCC tissues in contrast with their paired adjacent non-cancerous HCC (P<0.001) with RT-qPCR. In total, 405 targets, acquired with consistent prediction from at least five databases, were used for the bioinformatics analysis. According to the Gene Ontology (GO) analysis, all targets were classified into biological processes, cellular components and molecular functions. In the pathway analysis, targets of miR-23b-3p were primarily enriched in the signaling pathways of renal cell carcinoma, hepatitis B and pancreatic cancer (corrected P-value <0.05). In the protein-protein interaction (PPI) network for miR-23b-3p, a total of 8 targets, including SRC, AKT1, EGFR, CTNNB1, BCL2, SMAD3, PTEN and KDM6A, were located in the key nodes with high degree (>35). In conclusion, this study provides impressive illumination of the potential role of miR-23b-3p in HCC tumorigenesis and progression. Furthermore, miR-23b-3p may act as a predictor of HCC and could be a new treatment target.

Figure 1

Meta-analysis of miR-23b-3p expression in hepatocellular carcinoma (HCC) patients and healthy controls retrieved from Gene Expression Omnibus (GEO) datasets. (A) Forest plot. The center dot and the horizontal line represent the standard mean difference (SMD) and 95% confidence interval (CI), respectively. The pooled SMD and its corresponding 95% CI are presented below the list of studies; (B) Begg's funnel plot. Hazard ratios are presented on a logarithmic scale. (C) Egger's publication bias plot. Hazard ratios are presented on a logarithmic scale; (D) sensitivity analysis.

Figure 2

Meta-analysis of removing a single study from Gene Expression Omnibus (GEO) datasets. (A) Forest plot. The center dot and the horizontal line represent the standard mean difference (SMD) and 95% confidence interval (CI), respectively. The pooled SMD and its corresponding 95% CI are presented below the list of studies; (B) Begg's funnel plot. Hazard ratios are presented on a logarithmic scale. (C) Egger's publication bias plot. Hazard ratios are presented on a logarithmic scale; (D) sensitivity analysis. Pooled SMDs and 95% CIs by eliminating each study.

Figure 3

Meta-analysis of the relationships between miR-23b-3p and clinicopathological parameters in hepatocellular carcinoma (HCC) patients. (A) Invasion; (B) age; (C) sex; (D) HBV infection; (E) metastasis. Pooled standard mean differences (SMDs) and 95% confidence intervals (CIs) by eliminating each study.

Figure 4

miR-23b-3p expression in hepatocellular carcinoma (HCC) tissues from The Cancer Genome Atlas (TCGA). (A) The difference in relevant miR-23b-3p expression between HCC and adjacent non-cancerous HCC; (B) ROC curve to distinguish HCC from normal tissues. Error bars represented standard deviation (SD).

Figure 5

The relationship between miR-23b-3p expression and clinicopathological parameters of hepatocellular carcinoma (HCC) patients from The Cancer Genome Atlas (TCGA). (A) hepatitis B; (B) smoking history; (C) vascular invasion; (D) N status. Error bars represent standard deviation (SD).

Figure 6

Diagnostic significance between miR-23b-3p and different parameters on hepatocellular carcinoma (HCC) tissues from The Cancer Genome Atlas (TCGA). (A) Hepatitis B; (B) smoking history; (C) vascular invasion; (D) N status. Error bars represented standard deviation (SD).

Figure 7

Kaplan-Meier curve for overall survival (months) of hepatocellular carcinoma (HCC) patients included in The Cancer Genome Atlas (TCGA) and grouped by the level of miR-23b-3p expression. There was no significant association between miR-203 expression and survival times in patients with HCC (P=0.061). Error bars represented standard deviation (SD).

Figure 8

Expression of miR-23b-3p in hepatocellular carcinoma (HCC) and adjacent non-cancerous HCC. Quantitative real-time PCR was performed to detect the expression of miR-23b-3p. (A) The difference of relevant miR-23b-3p expression between HCC and adjacent non-cancerous HCC; (B) ROC curve of miR-23b-3p expression to distinguish HCC from comparative cancerous liver. Error bars represent standard deviation (SD).

Figure 9

The relationship between miR-23b-3p expression and clinicopathological parameters of hepatocellular carcinoma (HCC). (A) tumor nodes, (B) metastasis; (C) portal vein tumor embolus. Error bars represent standard deviation (SD).

Figure 10

Diagnostic significance between miR-23b-3p and various parameters for hepatocellular carcinoma (HCC). (A) tumor nodes; (B) metastasis; (C) portal vein tumor embolus. Error bars represent standard deviation (SD).

Figure 11

Kaplan-Meier curve for recurrence-free survival in hepatocellular carcinoma (HCC) patients grouped by the level of miR-23b-3p expression. There was no significant association between miR-203 expression and recurrence free survival in patients with HCC (P=0. 401). Error bars represented standard deviation (SD).

Figure 12

Meta-analysis of miR-23b-3p expression in hepatocellular carcinoma (HCC) patients and healthy controls retrieved from Gene Expression Omnibus (GEO) datasets, The Cancer Genome Atlas (TCGA) datasets and PCR data. (A) Forest plot. The center dot and the horizontal line represent the standard mean difference (SMD) and 95% confidence interval (CI), respectively. The pooled SMD and its corresponding 95% CI are presented below the list of studies; (B) Begg's funnel plot. Hazard ratios are presented on a logarithmic scale. (C) Egger's publication bias plot. Hazard ratios are presented on a logarithmic scale; (D) sensitivity analysis. Pooled SMDs and 95% CIs by eliminating each study.

Figure 13

Meta-analysis of removing PCR data from all the studies. (A) Forest plot. The center dot and the horizontal line represent the standard mean difference (SMD) and 95% confidence interval (CI), respectively. The pooled SMD and its corresponding 95% CI are presented below the list of studies; (B) Begg's funnel plot. Hazard ratios are presented on a logarithmic scale. (C) Egger's publication bias plot. Hazard ratios are presented on a logarithmic scale; (D) sensitivity analysis. Pooled SMDs and 95% CIs by eliminating each study.

Figure 14

GO analysis for target genes of miR-23b-3p. The length of horizontal column represents the number of genes and their color stand for P-value.

Figure 15

Network analysis with the prospective target genes of miR-23b-3p. Network nodes represent proteins. Colored nodes, query proteins and first shell of interactors; white nodes, second shell of interactors. Small nodes, protein of unknown 3D structure; large nodes, some 3D structure is known or predicted.