Vascular endothelial growth factor A is a potential prognostic biomarker and correlates with immune cell infiltration in hepatocellular carcinoma

Abstract Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer‐related deaths among cancer patients. Vascular endothelial growth factor A (VEGFA) is involved in regulating biological processes, such as angiogenesis and vascular permeability, and is very closely related to the pathogenesis of various tumours, especially vascular‐rich, solid tumours. Clinical data of patients with HCC and other tumours were analysed through public databases, such as the TCGA database, Gene Expression Omnibus database, Human Protein Atlas database, STRING, Tumour Immune Estimation Resource and Kaplan–Meier Plotter. The tumour tissues and adjacent normal tissues of patients with HCC from Hunan Provincial People's Hospital were collected to verify the expression of VEGFA by immunohistochemistry, immunofluorescence, Western blotting and qPCR. VEGFA expression is elevated in multiple tumour types and correlates with the prognosis of tumour patients. VEGFA is involved in regulating the tumour microenvironment and immune cell function in tumour development. Inhibition of VEGFA reduces proliferation, invasion, and migration and promotes apoptosis in HCC cells. VEGFA is a potential predictive biomarker for the diagnosis and prognosis of HCC.


| BACKG ROU N D
Hepatocellular carcinoma (HCC) is one of the most common malignancy and is currently one of the leading causes of cancer-related death. [1][2][3] More than 700,000 people die of HCC every year worldwide. 4 China has the greatest number of cases of HCC in the world. 3,5 The most important risk factors for HCC include chronic infection with hepatitis B virus or hepatitis C virus and exposure to aflatoxin. [5][6][7] Surgical resection is the most effective treatment for patients with HCC, 8,9 but the risk of recurrence 5 years after surgical resection is as high as 70%; further, relapse within 2 years is more likely. 10,11 Moreover, most patients with HCC miss the opportunity for radical surgery because they are usually diagnosed as intermediate and advanced stages. 11,12 Comprehensive treatment, including radiotherapy, interventional therapy, targeted therapy and immunotherapy, is very important for postoperative recurrence and inoperable HCC. In recent years, an increasing number of clinical studies have explored the efficacy of immunotherapy for HCC. 13,14 However, our understanding of immunotherapy for HCC is still insufficient. Therefore, it is of great significance to find biomarkers related to the prognosis and immune infiltration of HCC.
It is believed that tumour growth is controlled by tumour angiogenesis. 15 Angiogenesis is one of the malignant features of tumours. 16 The switch of tumour angiogenesis is induced by angiogenic factors secreted by tumour cells or stromal cells, and VEGF is the strongest angiogenesis stimulator. 17,18 There are five kinds of VEGF, namely VEGFA, VEGFB, VEGFC, VEGFD and PIGF. 19,20 The combination of Vascular endothelial growth factor A (VEGFA) and VEGFR2 is mainly involved in the regulation of angiogenesis. 21 VEGFA combined with VEGFR2 triggers signalling cascade pathways and ultimately induces endothelial cell proliferation, survival and migration to promote tumour progression. 22,23 Sorafenib, a commonly used targeted drug in HCC, also inhibits angiogenesis as an important mechanism. 24,25 Recent studies have illustrated that VEGFA is highly expressed in malignant tumours, including HCC. 26,27 The expression and predictive significance of VEGFA in HCC need to be further studied.
In this study, the expression of VEGFA and its relationship with The results demonstrated that VEGFA could play an important role in the prognosis of HCC. This finding also suggested that VEGFA might regulate the infiltration of immune cells in HCC.

| Analysis of survival data and drawing of ROC curve
The Gepia2 website (http://gepia2.cance r-pku.cn/) was applied to analyse the survival data related to different cancer patients in the GTEx database (www.gtexp ortal.org). The influence of the VEGFA gene expression level on the prognosis of each tumour was analysed.

| Univariate and multivariate logistic regression analysis
The variables including age, T stage, N stage, M stage, pathologic stage, histologic grade, adjacent hepatic tissue inflammation, vascular invasion, sex and VEGFA were input to further analyse the influence of clinicopathological features on the prognosis of HCC.
The hazard rate (95% CI) was analysed by the survival package using univariate and multivariate analyses, and p values were calculated.
Finally, prognostic predictors on patients with HCC were obtained.

| GSEA and GO KEGG analysis
In this study, we analysed the correlation between VEGFA mRNA expression and all other genes. The clusterProfiler package was applied for GSEA, and the org.Hs.e.g.db package and clusterProfiler package were used for gene ontology (GO) Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. |ES| > 1, p < 0.05 and FDR < 0.25 were considered statistically significant.

| Analysis of the protein interaction network
The STRING website (https://strin g-db.org) is a database to predict protein-protein interactions (PPIs) (including at least 6k proteins).
The PPI network information map was obtained by entering the VEGFA gene into the search bar. A combined score >0.7 was considered a close relationship.

| Analysis of tumour-related immune infiltration
The Tumour Immune Estimation Resource Web Server (TIMER) is a comprehensive resource for systematic analysis of immune infiltration in different cancer types. To analyse the correlation between the expression of VEGFA and immune infiltration in HCC tissues, the first six types of immune cells, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages and dendritic cells, were obtained from the TIMER database. Next, CD8+ T cell, CD4+ T cell and T regulatory cell infiltration and VEGFA expression were calculated through this website. Then, the relationship between each immune cell marker and VEGFA expression was analysed. Additionally, the coefficient value (R) and corresponding p value of the correlation between VEGFA and immune cell markers were obtained from GEPIA.

| Cell culture and transfection
The human normal liver cell line (L02) and HCC cell lines (HepG2, HepG3B, Huh7, SNU449 and PLC) were cultured in DMEM supplemented with 10% foetal bovine serum (FBS, Corning) at 37°C and 5% CO 2 . Short interfering (si)RNA targeting vascular endothelial growth Factor A (si-VEGFA) and siRNA negative control (si-NC) were purchased from Guangzhou Sagene Biotech Co. Si-VEGFA was transfected using lentivirus followed by subsequent experiments 48-72 h later.

| RNA isolation, reverse transcription and qRT-PCR analysis
Total RNA was isolated from samples using TRIzol reagent (Invitrogen), and cDNA was obtained by using TransScript First-Strand cDNA Synthesis SuperMix (TransGen). TransStart Green Q-PCR SuperMix (TransGen) was used to perform quantitative realtime PCR (qRT-PCR) according to the manufacturer's protocol as described in a previous study. 29 The primers for the real-time PCR were designed by Sangon Biotech. The primers used were 5′-GCGGA TCA AAC CTC ACCAAG-3′ and 5′-GCTTT CGT TTT TGC CCC TTTC-3′ for VEGFA and 5′-AATCC CAT CAC CAT CTTCCA-3′ and 5′-CCTGC TTC ACC ACC TTCTTG-3′ for GAPDH. Relative mRNA expression levels were normalized to GAPDH levels.

| Protein extraction and immunoblottingtechniques
Protein extraction and immunoblotting were performed as described in a previous study. 30 Briefly, RIPA lysis buffer was added to tissue or cell samples to obtain total protein. Then, 5× SDS buffer was added to quantify the protein samples at 99°C for 10 min to desaturate the protein. The proteins were separated by SDS-PAGE electrophoresis, transferred to PVDF membranes, blocked with 3% nonfat dry milk (PBST) for 1 h, incubated with a VEGFA antibody (AF5131, Affinity Biosciences) overnight at 4°C, washed three times with PBST, incubated with a secondary antibody for 90 min at room temperature and washed three times with PBST. Finally, chemiluminescence imaging was performed to detect protein expression levels on the membranes.

| Immunohistochemistry
Immunohistochemistry (IHC) was performed as described in a previous study. 31 Briefly, the tissue blocks were fixed with 4% polychloroformaldehyde, rinsed, dehydrated with gradient ethanol, embedded in paraffin and prepared into paraffin sections with a thickness of 4 μm for staining. Then, the paraffin sections were dewaxed with xylene, dehydrated with gradient ethanol, incubated with antibodies (primary antibody, secondary antibody), dehydrated, cleared, mounted and observed under a microscope.

| Immunofluorescence technique
Paraffin sections were deparaffinized for antigen retrieval, blocked with hydrogen peroxide, and serum blocked. CD86 primary antibody (DF6332, Affinity Biosciences) was added overnight followed by secondary antibody incubation. After FITC-TSA treatment and microwave treatment, CTLA4 primary antibody (DF6793, Affinity Biosciences) was added overnight followed by secondary antibody incubation. The nuclei were stained with DAPI, and the glass was mounted. Finally, the images were observed and collected under a fluorescence microscope.

| Detection of apoptotic rate by flowcytometry
All the supernatant and adherent cells were collected. Annexin V/ FITC staining was performed according to the instructions of the Annexin V/FITC Apoptosis Kit.

| Transwell chamber experiment to detect the number of migrating cells
The cells were trypsinized, and 2.5 × 10 4 cells were seeded into the upper chamber of the Transwell. Meanwhile, 500 μl of complete medium containing 10% FBS was added to the lower chamber. The cells were cultured for another 48 h. After that, the chamber was removed and washed with PBS. Next, the cells were fixed with 4% paraformaldehyde for 15 min, washed three times with PBS, stained with 0.1% crystal violet for 10 min and washed three times with PBS. Then, the pictures were selected randomly under a microscope. The number of migrated cells was counted. The experiments were repeated in triplicate.  The results from TCGA data showed that the expression of VEGFA mRNA in most tumour tissues was significantly higher than that

| VEGFA has good diagnostic sensitivity in HCC
In this study, we assessed the diagnostic value of VEGFA in HCC by generating ROC curves from the TCGA database. The results showed that the area under the curve (AUG) of VEGFA was 0.731 ( Figure 3A), and to some extent, the diagnostic performance of VEGFA was no less than that of AFP. In addition, we also analysed the  Figure 3H). All of these data support that VEGFA might be a potential new biomarker.

| Higher expression levels of VEGFA mRNA are associated with worse prognosis
The GEPIA2 website was applied to comprehensively analyse the information of the TCGA database and GTEx database. The results showed that a high VEGFA mRNA expression level was associated with shorter overall survival of CESC, GBM, KIRP and LIHC (p < 0.05; Figure 4A). Moreover, a high expression level of VEGFA mRNA was associated with shorter disease-free survival in COAD, KIRP, LGG, LIHC and UVM (p < 0.05; Figure 4B). Unexpectedly, low VEGFA mRNA expression was associated with shorter overall survival in BLCA (p < 0.05; Figure 4A).  Table 2). Finally, the above results were verified again by using the Kaplan-Meier Plotter website to synthesize the GEO, EGA and TCGA databases ( Figure 4F-H).

| Network enrichment analysis identifies VEGFA functions, associated signalling pathways and genes
Through GSEA, it was shown that VEGFA was involved in the two pathways of GPCR ligand binding and rho GTPases ( Figure 5A,B).
The results of GO KEGG analysis showed the signalling pathway,

Tregs, Tems, mast cells, NK infiltration of CD58dim cells, B cells, iDCs, neutrophils, T cells, Tgd cells, pDCs, cytotoxic cells and DCs)
in HCC tissues were also analysed ( Figure 6E). To further understand the correlation between VEGFA and immunotherapy, we an- and CTLA4 suggesting that VEGFA was related to the immunosuppressive microenvironment ( Figure 6I).

| Inhibition of VEGFA reduces proliferation, invasion and migration and promotes apoptosis in HCC cells
To explore the effect of VEGFA in HCC, we transfected si-VEGFA into HCC cells ( Figure 7A) and detected the proliferation ability of the cells by CCK8. The results showed that inhibition of VEGFA could significantly inhibit the proliferation of HCC ( Figure 7B). Next, the cell migration ability was assessed by transwell assay, and the results suggested that the inhibition of VEGFA could significantly inhibit the migration ability of HCC ( Figure 7C). Furthermore, cell apoptosis was calculated by FCM, and the results showed that inhibiting VEGFA could induce increased apoptosis. (Figure 7D). Cumulative evidence has shown that VEGF plays an important role in cancer progression. 33,34 In this study, we found that VEGFA was overexpressed in HCC tissues compared to normal tissues. Moreover, our results indicate that VEGFA is a potential prognostic biomarker and correlates with immune cell infiltration in HCC. This finding provides new insight into the combination of immunotherapy for HCC.
It is well known that AFP is an important tumour marker for the diagnosis of HCC. 35,36 In this study, we also found that VEGFA had a diagnostic specificity for HCC similar to that of AFP. This re- Considering that higher expression of VEGFA is mostly associated with more advanced-stage tumours and that advanced-stage tumours often lose the opportunity for surgery, VEGFA is a good therapeutic target for these patients. Sorafenib is a multitarget antitumor drug that can also inhibit the VEGFR signalling pathway and angiogenesis. 37 The SHARP Investigators Study Group found that sorafenib monotherapy for advanced HCC was significantly better than placebo. 38 [54][55][56] In this study, we also found that VEGFR played an important role in GPCR ligand binding and rho GTPases.
A PPI study showed that VEGFA might have a close interaction with HIF1A, FLT1, FN1 and FGF2. All these molecules can promote HCC development by activating various pro-tumour signals. 57 angiogenesis. Therefore, VEGFA is an important factor that promotes HCC and may be used as a diagnostic indicator that is similar to AFP in the future. Additionally, it can predict the prognosis of HCC, and its high expression has a worse prognosis. Furthermore, it is also related to immune infiltration suggesting that targeted inhibition of VEGFA and combined immune treatment is a viable strategy.

| CON CLUS ION
In this study, we found that VEGFA is a potential predictive biomarker for the diagnosis and prognosis of HCC through the TCGA database and further molecular biology experiments. Although this finding is valuable, the specific mechanism by which VEGFA affects HCC immunotherapy was not explored in depth in this study. In future studies, we will focus on clarifying the possibility of VEGFA as a biomarker for HCC immunotherapy.

CO N FLI C T O F I NTER E S T S TATEM ENT
The authors confirm that there are no conflicts of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available from the corresponding author upon reasonable request.

I N FO R M ED CO N S ENT
Written informed consent for publication was obtained from all participants.