Cytoskeletal gene alterations linked to sorafenib resistance in hepatocellular carcinoma

Abstract

Background: Although sorafenib has been consistently used as a first-line treatment for advanced hepatocellular carcinoma (HCC), most patients will develop resistance, and the mechanism of resistance to sorafenib needs further study.

Methods: Using KAS-seq technology, we obtained the ssDNA profiles within the whole genome range of SMMC-7721 cells treated with sorafenib for differential analysis. We then intersected the differential genes obtained from the analysis of hepatocellular carcinoma patients in GSE109211 who were ineffective and effective with sorafenib treatment, constructed a PPI network, and obtained hub genes. We then analyzed the relationship between the expression of these genes and the prognosis of hepatocellular carcinoma patients.

Results: In this study, we identified 7 hub ERGs (ACTB, CFL1, ACTG1, ACTN1, WDR1, TAGLN2, HSPA8) related to drug resistance, and these genes are associated with the cytoskeleton.

Conclusions: The cytoskeleton is associated with sorafenib resistance in hepatocellular carcinoma. Using KAS-seq to analyze the early changes in tumor cells treated with drugs is feasible for studying the drug resistance of tumors, which provides reference significance for future research.

Keywords: Cytoskeleton; Drug resistance; Hepatocellular carcinoma; KAS-seq; Sorafenib.

Fig. 1

A Overview of study design. B Effect of treatment for 24 h with sorafenib on cell proliferation and viability as determined by the CCK-8 assay. Graphs show the effect of various sorafenib concentrations (x-axis, logarithmic values) on relative cell viability (y-axis, net A450 nm using CCK-8 assay). Under sorafenib treatment versus sorafenib-untreated control. Sorafenib concentrations were 1, 3, 6, 8, 12, 16, 32, 64 μM. Graph was obtained from the online tool GR calculator (www.grcalculator.org)

Fig. 2

Characterization of KAS-seq distribution at different time points in SMMC-7721 cells treated with sorafenib. A Distribution of KAS-seq peaks in the gene coding region across the whole genome in different groups; B Distribution of KAS-seq signals at gene-coding regions within the 3000 bp upstream and downstream of the transcription start site (TSS) across different groups; C Heatmap showing the distribution of reads in the gene coding regions of KAS-seq samples treated with Sorafenib at different times; D Density distribution of peaks at promoter regions across different groups; E Density distribution of peaks at exon regions across different groups; F Density distribution of peaks at intron regions across different groups

Fig. 3

Enrichment analysis of differentially expressed genes in SMMC-7721 cells treated with sorafenib for 1 h. A Volcano plot of significantly altered DEGs (|log2 (Fold change) |> 1, p-value < 0.05). Upregulated and downregulated DEGs were highlighted respectively in red and blue using SMMC-7721 cells treated with sorafenib for 1 h vs. untreated SMMC-7721 cells. B GO enrichment analysis and function exploration of upregulated DEGs. C KEGG pathways of upregulated DEGs. D GO enrichment analysis of downregulated DEGs. E KEGG pathways of downregulated DEGs

Fig. 4

Enrichment analysis of efficacy-related differentially expressed genes (ER-DEGs) in hepatocellular carcinoma patients with ineffective and effective sorafenib treatment (GSE109211). A Volcano plot. Significantly altered ERGs (|log2 (Fold change) |> 1, p-value < 0.05) were highlighted in red (up) or blue (down) using non-responder vs. responder. B GO enrichment analysis and function exploration of upregulated ERGs. C KEGG pathways of upregulated ERGs. D GO enrichment analysis of downregulated ERGs. E KEGG pathways of downregulated ERGs

Fig. 5

Selection of hub efficacy-related DEGs. A Venn plot of the 191 upregulated ER-DEGs. B Venn plot of the 92 downregulated ER-DEGs. C Protein–protein interaction (PPI) networks of 283 ER-DEGs with confidence score > 0.4. D Top 10 hub genes selection performed by the MCC Algorithm

Fig. 6

Identification of 10 hub efficacy-related DEGs with prognostic significance using UALCAN. A-J The effect of 10 hub efficacy-related DEGs expression level on liver hepatocellular carcinoma (LIHC) patient survival

Fig. 7

Validation of the expression for 7 hub ERGs. A mRNA expression of 7 hub ERGs using were significantly upregulated in patients with LIHC from the UALCAN database (*P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001). B Representative immunohistochemistry staining of 7 hub ERGs. Protein expression levels of ACTB, CFL1, ACTG1, ACTN1, WDR1, TAGLN2 and HSPA8 in HCC tissue were obtained from the Human Protein Atlas (HPA)

Fig. 8

Investigation of statistically significant pathways for the 7 ERGs. A The gene–gene interaction network of 7 hub ERGs and 20 neighboring genes was constructed using GeneMANIA. B GO enrichment analysis and function exploration of the 27 genes. C KEGG pathways of the 27 genes

Fig. 9

Gene Set Enrichment Analysis (GSEA) was performed using GEO sample data from patients treated solely with sorafenib (GSE109211). A-G The gene sets (according to GSEA normalized enrichment score) for ACTB, CFL1, ACTG1, ACTN1, WDR1, TAGLN2, HSPA8. P-value of < 0.05 was considered statistically significant