SOX9 Promotes Hepatocellular Carcinoma Progression through Targeted Regulation of HSPA1B

Jiangbo Shao1, Donglai Zhu2, Shengqiang Zou1, Guohong Ge1 and Ju Huang1*

1Department of Hepatosis, The Third People’s Hospital of Zhenjiang Affiliated Jiangsu University, Zhenjiang, Jiangsu 212005, China

2Department of Clinical Laboratory, The Third People’s Hospital of Zhenjiang Affiliated Jiangsu University, Zhenjiang, Jiangsu 212005, China

Jiangbo Shao and Donglai Zhu contributed equally to this work.

ABSTRACT

Recent studies have demonstrated that SOX9 was highly expressed and played critical roles in increasing cancer stem cell expansion as well as decreasing sensitivity to the sorafenib therapy in hepatocellular carcinoma. In this study, the potential functions and mechanisms of SOX9 in promoting hepatocellular carcinoma progression were investigated through comprehensive bioinformatics analysis. We found that SOX9 mainly participated in heat stress response, protein folding as well as metabolism and biosynthesis of amino acid. SOX9 correlated with HSPA1B were negative to the progression in hepatocellular carcinoma patients. These results suggest that SOX9 participated in hepatocellular carcinoma progression through targeted regulation of HSPA1B that might provide novel insights in hepatocellular carcinoma therapy.

Article Information

Received 14 September 2021

Revised 18 October 2021

Accepted 06 November 2021

Available online 09 February 2022

(early access)

Published 22 October 2022

Authors’ Contribution

JS, DZ and JH designed the study, performed the research and wrote the paper. SZ and GG did part of the analyses and interpreted the results. All authors discussed the data and revised the manuscript.

Key words

SOX9, HSPA1B, Hepatocellular carcinoma, Bioinformatic analyses, Biomarker

DOI: https://dx.doi.org/10.17582/journal.pjz/20210914160920

* Corresponding author: [email protected]

0030-9923/2023/0001-139 $ 9.00/0

Copyright 2023 by the authors. Licensee Zoological Society of Pakistan.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

INTRODUCTION

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death worldwide, which seriously threats the physical and mental health of patients (Forner et al., 2018; El-Serag, 2020; Siegel et al., 2020). Early stage HCC can be treated with partial resection, liver transplantation or radiofrequency ablation (Grandhi et al., 2016; Liver, 2018). However, as limitations in the sensitivity and specificity of diagnosis, most patients are diagnosed at an advanced stage. At this stage, palliative therapy such as radiotherapy or chemotherapy is the only option (Balogh et al., 2016; Yang et al., 2019). Sorafenib, a small-molecule multikinase inhibitor of antiangiogenic drug, was the first-line systemic treatment of patients with advanced-stage HCC. Sorafenib has been proved for significantly suppressing tumor cell proliferation as well as effectively prolonging the survival of HCC patients (Wilhelm et al., 2006; Llovet et al., 2008). Unfortunately, most patients treated with sorafenib eventually show resistance and disease progression (Keating, 2017; Zhu et al., 2017).

Sex determining region Y-related high mobility group box gene 9 (SOX9), a member of the sex determining region Y box gene superfamily, is required for cartilage, formation respiratory epithelium development and melanocyte differentiation (Bi et al., 1999). Accumulating evidence has revealed that the up-regulated SOX9 was associated to drug resistance and recurrence in a number of tumors (Lü et al., 2008; Song et al., 2014; Ma et al., 2016). In HCC research, recent studies have demonstrated that SOX9 was highly expressed and played critical roles in increasing cancer stem cell expansion as well as decreasing sensitivity to the sorafenib therapy (Huang et al., 2017; Xiao et al., 2019; Wang et al., 2020). However, there was still little research about functions or molecular mechanisms of SOX9 in HCC.

In this study, we deeply analyzed the raw data of GSE143477 from GEO database and comprehensively explored the potential functions and mechanisms of SOX9 in promoting hepatocellular carcinoma progression, which will provide novel insights in HCC therapy.

Materials and methods

Microarray, Metascape, JASPAR, TIMER and Kaplan Meier plotter were used for that present study. The gene expression profiles chip (GSE143477) was downloaded from GEO database and was checked by an Agilent Bioanalyzer 2100 (Agilent technologies, Santa Clara, CA, US) (Barrett et al., 2005). This microarray included three SOX9 knockdown and three scrambled control HepG2 cell samples (Wang et al., 2020). Genes with adjusted |log2FC|≥1 and p value < 0.05 were obtained as the differentially expressed genes.

Metascape (https://metascape.org) is a comprehensive online analysis tool for inputted genes (Zhou et al., 2019). In this study, Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, PPI analysis and mCODE enrichment analysis of differentially expressed genes were performed by Metascape.

JASPAR (http://jaspar.genereg.net/) is a database for derivation of eukaryotic potential transcription factor binding sites (Sandelin et al., 2004). In this study, we explored the possible target gene and binding sequence to SOX9 in HCC with JASPAR.

TIMER (https://cistrome.shinyapps.io/timer/) is an online web server for providing information for differential gene expression in tumor/normal tissue and correlations between genes (Li et al., 2017).

Kaplan Meier plotter (http://kmplot.com/analysis/) is a reliable tool for a meta-analysis based discovery and validation of survival biomarkers (Nagy et al., 2018). In this study, prognostic analysis was performed using a Kaplan-Meier curve.

Results

Differentially expressed genes of GSE143477

We firstly performed analysis of SOX9 and its correlated genes in HCC. The gene expression profiles of GSE143477 included three SOX9 knockdown and three scrambled control HepG2 cell samples. Genes with adjusted |log2FC|≥1 and p value < 0.05 were obtained. Heat map Figure 1 shows a total of 676 differentially expressed genes were identified, including 212 up-regulated and 464 down-regulated genes.

Functions of SOX9 and HCC

To further explore the potential functions of SOX9 and its correlated genes in HCC, Metascape was utilized for analysis of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Table I shows the top 10 enrichment functions of the 212 up-regulated and 464 down-regulated genes, respectively. As presented in the table, the up-regulated genes were significantly enriched in heat stress response and protein folding. While the down-regulated genes were significantly enriched in metabolism and biosynthesis of amino acid.

 

 

To deeply understand the correlation between SOX9 and HCC, the protein–protein interaction (PPI) network was analyzed. Two mCODE components were identified in the up-regulated genes list and mainly associated with HSP90 chaperone cycle for steroid hormone receptors (SHR), selective autophagy and metabolism of RNA (Fig. 2A). In addition, one mCODE component was identified in the down-regulated genes list and related to alcoholism, HDACs deacetylate histones and RHO GTPases activate PKNs (Fig. 2B).

 

Table I. Enrichment analysis of 676 differentially expressed genes in different samples.

Category	Gene function	-Log P
Up-regulated genes
GO	response to heat	8.8
GO	cellular response to heat	7.8
GO	regulation of cellular response to heat	7.4
GO	response to temperature stimulus	7.3
GO	protein folding	6.6
GO	chaperone-mediated protein folding	5.7
GO	response to unfolded protein	5.6
GO	response to topologically incorrect protein	5.2
KEGG	protein processing in endoplasmic reticulum	5.0
GO	regulation of protein complex assembly	4.8
Down-regulated genes
GO	alpha-amino acid metabolic process	9.1
GO	cellular amino acid metabolic process	8.7
KEGG	biosynthesis of amino acids	7.4
GO	serine family amino acid biosynthetic process	7.3
GO	cellular amino acid biosynthetic process	6.9
GO	alpha-amino acid biosynthetic process	6.8
GO	L-serine metabolic process	6.6
GO	serine family amino acid metabolic process	5.7
GO	cysteine biosynthetic process via cystathionine	5.7
KEGG	cysteine biosynthesis	5.7

 

 

To find the core gene of the mCODE components, we explored the possible target gene and binding sequence of SOX9 in HCC using JASPAR. We found that ATTGTT could be the core binding sequence to SOX9 transcriptional factor and there were twelve potential binding sites in HSPA1B promoter region (Fig. 3, Table II).

 

Table II. Binding site sequences to SOX9 transcriptional factor in HSPA1B promoter region.

Model ID	Model name	Score	Start	End	Predicted site sequence
MA0077.1	SOX9	7.650	19	27	CTATAGTTG
MA0077.1	SOX9	6.315	702	710	ATATTGTTA
MA0077.1	SOX9	7.874	859	867	ATATTGTTA
MA0077.1	SOX9	7.105	909	917	CATTTGTTT
MA0077.1	SOX9	6.222	994	1002	CAATTGAGC
MA0077.1	SOX9	6.944	1087	1095	CTATTTTTT
MA0077.1	SOX9	7.222	1140	1148	CTATTGCTT
MA0077.1	SOX9	8.391	1179	1187	CCTTTGTTA
MA0077.1	SOX9	9.086	1219	1227	CCTTTGTTT
MA0077.1	SOX9	8.316	1425	1433	GAATTGTTT
MA0077.1	SOX9	6.113	1524	1532	TTTTTGTTT
MA0077.1	SOX9	6.964	1530	1538	CTGTTGTTT

 

We finally assessed the expression levels and association of SOX9 and HSPA1B in HCC tumor and normal tissues with TIMER (Fig. 4A, B). As expected, the expression levels of SOX9 and HSPA1B in HCC were significantly elevated and there was a positive correlation between them (p=0.0241). Subsequently, correlation between differently expressed SOX9/HSPA1B and the overall survival of HCC patients were assessed (Fig. 4C). As a result, HCC patients with low transcriptional levels of SOX9 or HSPA1B were associated with longer survival. These data suggest that SOX9 might play critical roles in the progression and prognosis of HCC via targeted regulation of HSPA1B.

Discussion

The SOX family consists of more than 20 members and have regulatory functions in specific biological processes. Over-expression of SOX9 in HCC clinical samples significantly associates with tumor progression and poor prognosis of HCC (Guo et al., 2012). Inhibiting SOX9 could effectively suppress HCC tumorigenicity, proliferation, invasion and sorafenib resistance, which suggested that SOX9 was involved in multiple biological functional regulations (Liu et al., 2016; Xiao et al., 2019; Wang et al., 2020). In this study, we explored the gene expression profiles chip of SOX9 knockdown HCC cell line and performed the differential gene enrichment analysis. The data suggested that SOX9 was mainly participated in heat stress response, protein folding as well as metabolism and biosynthesis of amino acid in HCC. Recently, SOX9 was found to be involved in sorafenib resistance in HCC. Wang et al. (2020) reported that sorafenib treatment increased the proportion of SOX9+ HCC cell. Overexpression of exogenous SOX9 in HCC increased sorafenib resistance both in vitro and in vivo, whereas down-regulation led to inhibition of sorafenib resistance, which indicated that SOX9 enhanced sorafenib resistance (Wang et al., 2020). However, the mechanism needs to be further explored.

 

Heat shock proteins (HSPs) 70, as one of the molecular markers of HCC, is significantly over-expressed in advanced stage (Chuma et al., 2003). HSPA1B is the member of the HSP70 family, but the role and its prognostic implication in HCC are unknown. Recently, a case-control study elucidated that single nucleotide polymorphism (SNP) in 1267 allele of HSPA1B increased the risk and threated prognosis of HCC (Jeng et al., 2008), which indicated that HSPA1B played important roles in the development of HCC. In our study, HSPA1B was predicted as the possible target gene and binding sites of SOX9. Besides, we investigated the high-expression and prognostic value of SOX9 and its target HSPA1B in clinical HCC patients from TCGA datasets. All these results also suggested that HSPA1B might participate in the development of HCC.

Limitations of this research should not be ignored. The different expressed genes correlated with SOX9 in HCC were investigated by constructing SOX9 knockdown cell line. Whether these genes expressed in clinical samples remains to be further confirmed. In addition, this study only evaluated the potential functions and mechanisms of SOX9 through bioinformatics analysis. Future studies should further verify these results both in vitro and in vivo.

In conclusion, our research indicated that SOX9 was high-expressed in HCC and mainly participated in heat stress response, protein folding as well as metabolism and biosynthesis of amino acid through targeted regulation of HSPA1B, which were associated with poor prognosis in HCC patients. These will provide novel insights in SOX9 research and HCC therapy.

Acknowledgement

This work was supported by grant from Science and Technological Development Foundation of Zhenjiang (SH2020035).

Statement of conflict interest

The authors have declared no conflict of interest.

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