Identification of SCAF1 as a key factor affecting VEGF in LIHC and its potential target for therapy hypothesized based on network pharmacology and transcriptomics

doi:10.21203/rs.3.rs-4117141/v1

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Identification of SCAF1 as a key factor affecting VEGF in LIHC and its potential target for therapy hypothesized based on network pharmacology and transcriptomics

https://doi.org/10.21203/rs.3.rs-4117141/v1

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Introduction:

Liver hepatocellular carcinoma (LIHC) is a highly vascularized entity closely associated with immune functions, characterized by high incidence, elusive early detection, high malignancy, and poor prognosis. SCAF1 participates in the immune regulation mechanisms of various cancers (gliomas, breast cancer, etc.) and is involved in regulating the level of gene transcription. Nevertheless, there is currently no research focusing on the multiple mechanisms of SCAF1 in LIHC, including angiogenesis promotion and immunomodulation.

Materials and Methods:

In this study, we obtained TCGA data and utilized Weighted Gene Co-expression Network Analysis (WGCNA) to explore hub genes, followed by evaluating the prognostic and clinical significance of SCAF1. Functional identification of SCAF1 in LIHC was performed through enrichment analysis. Subsequently, the immune therapeutic effects of SCAF1 were explored using TIMER and TISIDB. Spatial transcriptomics and single-cell sequencing analysis based on GEO data were conducted to assess heterogeneity tissue within the tumor microenvironment. Finally, molecular docking predictions were performed using Perl to evaluate pharmacological effects.

Results:

We identified a significant upregulation of SCAF1 in LIHC, and its overexpression may lead to decreased patient survival rates, enhanced levels of angiogenesis, invasion, and migration capabilities in LIHC. Chemokine analysis results demonstrated that the up-regulation of SCAF1 expression could inhibit the expression of cell factors such as CCL19. Experimental results demonstrated that genistein could downregulate SCAF1 and VEGFA in LIHC and inhibit cell invasion and migration levels.

Conclusion:

SCAF1 can influence angiogenesis in LIHC and affect tumor progression and therapeutic outcomes in LIHC patients through angiogenesis regulation.

SCAF1

biomarker

liver hepatocellular carcinoma

angiogenesis

chemokine

pharmacology

Liver hepatocellular carcinoma (LIHC) is a solid tumor with poor prognosis and fast development due to its high vascularization [6, 7]. Its five-year survival rate is merely 20% [8]. Vascular endothelial growth factor (VEGF) is a signaling pathway capable of triggering downstream cellular pathways through phosphorylation cascades, ultimately leading to endothelial proliferation and migration. It is closely associated with tumor angiogenesis, rapid growth, and dissemination. The VEGF signaling pathway is collectively regulated by various angiogenesis-related factors. Among these VEGFs, VEGFA is produced by tumor-associated macrophages (TAMs) and manipulates tumor cell invasion and migration by enhancing VEGFA signaling transduction and bioavailability [9, 10].

An increasing body of research indicates that numerous chemokines can modulate tumor angiogenesis levels [11]. Chemokines constitute a superfamily composed of small proteins capable of specifically binding to downstream cell G-protein-coupled receptors, altering cell secretion activity, and thereby regulating various cellular functions. As a result, chemokines are widely involved in the development, metastasis, and angiogenesis of tumors. [12, 13]. Chemokine CC ligand 19 (CCL19), also known as macrophage inflammatory protein 3-beta (MIP-3b), has been shown in recent studies to suppress the expression level of VEGFA in colorectal cancer, thereby inhibiting tumor occurrence, metastasis, and angiogenesis [14]. It's not evident, nevertheless, if CCL19 controls tumor angiogenesis in LIHC.

Human SR-related CTD-associated factor 1 (SCAF1), also known as SR-A1, is a new member of the human SR (Ser/Arg-rich) pre-mRNA splicing factor superfamily [15]. It participates in the pre-mRNA splicing process, thereby affecting the level of interferon regulatory factor 3 (IRF3) in serum, subsequently influencing the incidence and progression of cancer. Evidence suggests that elevated SCAF1 expression significantly increases the grading and staging of ovarian tumors and lowers ovarian cancer patients' overall survival (OS) and progression-free survival (PFS), leading to a poorer prognosis [16]. Furthermore, research has indicated that elevated levels of SCAF1 can lead to decreased disease-free survival (DFS) in colorectal cancer patients, leading to a dismal outlook for those with colorectal cancer [17]. However, there are no reports on the expression and related regulatory mechanisms of SCAF1 in LIHC.

In this study, we identified the hub gene SCAF1. By using immunohistochemistry, western blot, HE staining, and quantitative reverse transcription (qRT)-PCR, we discovered that SCAF1 was elevated in LIHC relative to normal liver tissue. Furthermore, we discovered a correlation between the clinical pathological characteristics and patient survival and the expression level of SCAF1. Furthermore, by encouraging angiogenesis, our research showed that SCAF1 might improve the invasive and migrating capacities of HCCLM3 cells. Chemokine experiments showed that SCAF1 could downregulate the expression of chemokines such as CCL19 and promote angiogenesis. Meanwhile, we also screened out the potential small molecule genistein that can block VEGF. According to our research, genistein can stop HCCLM3 cells from proliferating and lower VEGFA expression levels by reducing SCAF1 expression. This prevents HCCLM3 cells from being invasive and migrating. In summary, our research has identified a new biomarker associated with angiogenesis and invasion in LIHC, which can be used for the diagnosis of LIHC patients. Additionally, we have identified genistein, a small molecule that can effectively inhibit LIHC angiogenesis.

Data Acquisition and Processing:

The TCGA and ICGC databases provided the clinical samples and mRNA expression data for liver hepatocellular carcinoma (LIHC). In this work, 50 normal samples and 374 LIHC samples were chosen for gene expression profile analysis from The Cancer Genome Atlas (TCGA) database, while 202 normal samples and 243 LIHC samples were chosen from the International Cancer Genome Consortium (ICGC) database. Additionally, clinical data from 377 LIHC patients were collected for clinical-pathological feature analysis.

Weighted Gene Co-expression Network Analysis (WGCNA):

WGCNA is an R package that identifies a group of genes exhibiting synchronous changes [1]. Initially, the optimal soft-thresholding power (β) was set to 18 to follow a scale-free network distribution. Gene modules were determined using hierarchical clustering. Subsequently, key modules were selected based on the correlation analysis of clinical samples. The genetic connectivity, measuring the degree of correlation between one gene and another, was calculated. Core genes were those with high connectivity within the main module.

TIMER Database Analysis:

TIMER (https://cistrome.shinyapps.io/timer/), an integrated database, is used to analyze tumor immune infiltration [2]. The associations between immune cell infiltration, SCAF1 mRNA expression, and copy number changes in LIHC samples were predicted using the "Gene" and "SCNA" modules. Gene co-expression was displayed via the "Correlation" module. We also looked at the connection between different immune cell infiltrations in pan-cancer tissues and SCAF1.

Gene Set Enrichment Analysis (GSEA):

GSEA is a gene set enrichment analysis method based on a set of genes [3]. RNA sequencing data related to LIHC were obtained from TCGA. Using the following fundamental threshold values, we ranked the samples and obtained normalized enrichment scores (NES) by splitting them into two groups based on the expression of SCAF1 using the GSEA program (version 4.0.3): 0.05 FDR q-value and 0.05 P value.

TCMSP:

TCMSP (https://old.tcmsp-e.com/tcmsp.php, Traditional Chinese Medicine Systems Pharmacology) is built upon the framework of traditional Chinese medicine pharmacology [4].It contains 499 Chinese medications with 29,384 chemicals, 3,311 targets, and 837 associated disorders that are listed in the Chinese Pharmacopoeia. Based on this, we searched for herbal ingredients capable of treating LIHC by inhibiting angiogenesis: genistein, rutaecarpine, bifendate, hirsutasideB, and genistein.

PubChem:

PubChem (https://pubchem.ncbi.nlm.nih.gov/) gathers chemical information from hundreds of data integration sources (as of September 6, 2022, 872 sources). Most of the chemicals contained in PubChem are small molecules, and their chemical structures are provided. We obtained the chemical structures of these 5 herbal ingredients from PubChem for further analysis.

Protein Structure and Docking Analysis:

The RCSB Protein Data Bank (https://mcule.com/dashboard/) collected three-dimensional structural information about proteins. We obtained the molecular structure of SCAF1 protein from this database. Using the 1-Click Docking web server, we investigated the binding modes of SCAF1 with the molecules of 5 traditional Chinese medicine ingredients and used PYMOL to visualize, analyze, and map them.

TISIDB:

TISIDB (http://cis.hku.hk/TISIDB/) is a tumor immune analysis database that integrates data from five major types of tumor immune-related data [5]. Based on this, we investigated the association of SCAF1 with six immune system components (lymphocytes, immune modulators, convergent factors, etc.) in LIHC.

Statistical Analysis:

The R program (version 4.3.0) was used for statistical analysis. Differential expression of SCAF1 was detected by a run-sum test using the "limma" and "beeswarm" packages. The "survival" and "survminer" packages were used to conduct multivariate Cox regression analysis in order to identify significant predictors (p < 0.05). ROC curves were created using the SurvivalROC package (version 3.3.1) to assess the ability of SCAF1 expression levels to predict 1, 3, and 5-year survival rates. Survival scenarios for SCAF1 were created in prevalent cancers using the "Survival" and "SorvMiner" packages. The tumor mutation burden (TMB) of each tumor was calculated using the TMB function in the MAfTools package. The "pheatmap" package was used to investigated the relationship between SCAF1 expression and immune checkpoint genes. Unique states of tumor mutation burden were revealed by combining sample TMB and gene expression data.

Cell Culture:

Huh7, HCCLM3, and HepG2 LIHC cell lines were acquired from the National Collection of Authenticated Cell Cultures. Except for HCCLM3 cells, which were grown in RPMI-1640 media, all cell lines were grown in DMEM enhanced with 10% FBS and 1% penicillin-streptomycin. Every cell was grown in an incubator with 5% CO2 and a humidifier set at 37°C.

Western Blot Analysis and Antibodies:

Prepare the total protein extracts according to the method described previously. Using RIPA buffer (Beyotime, Shanghai, China) to extract protein, a buffer mixture containing protease and inhibitors (Termo Fisher Scientific, New York, USA). The monoclonal antibodies used in the experiment were: anti-SCAF1 (1:1000, Solarbio, K112765P); anti-VEGFA (1:1000, Abcam, ab46154); and anti-Tubulin (1:1000, Proteintech, 11224-1-AP).

Construction of WGCNA and Expression of SCAF1 in LIHC:

To identify gene modules associated with LIHC, we constructed a LIHC-related heatmap, where the turquoise module exhibited the strongest correlation with LIHC (Figure 1.a). Subsequently, we intersected VEGF-related genes, focal adhesion-related genes, and EMT-related genes with genes in the turquoise module, resulting in 20 genes identified through a Venn diagram (Figure 1.b). To select suitable hepatocellular carcinoma cell lines for subsequent experiments, we conducted Western blot experiments on three hepatocellular carcinoma cell lines and one normal cell line. The hepatocellular carcinoma cell lines Huh7, HCCLM3, and HepG2 were compared to the normal liver tissue cell line HL-7702 to determine the expression levels of SCAF1. We discovered that the expression level of SCAF1 was greatest in HCCLM3 (Figure 1.c), indicating that this cell line is suitable for subsequent experiments. To explore the expression of SCAF1 in LIHC, we obtained statistical information from the TCGA and ICGC websites and constructed box plots. The results consistently showed high expression of SCAF1 in LIHC (Supplementary Figure 1.a–b). Subsequently, to validate the above conclusions, we performed mRNA detection and WB experiments on SCAF1, demonstrating that LIHC tissues had greater levels of SCAF1 mRNA and protein expression than nearby tissues (Figure 1.e). Furthermore, to further verify the relationship between SCAF1 expression level and LIHC at the cellular level, we conducted HE staining and immunohistochemistry experiments on SCAF1 expression. The findings demonstrated that HCCLM3 cells expressed more SCAF1 than nearby tissues (Figure 1.f), further indicating the close association of high SCAF1 expression with LIHC.

Clinical Predictive Significance of SCAF1:

In order to investigate the relationship between clinical pathological characteristics and SCAF1, we observed changes in SCAF1 expression in LIHC samples with different clinical pathological features. The results showed that as clinical staging, pathological staging, and histological staging increased, the overall expression of SCAF1 also increased (Figure 2.a–c), indicating a close relationship between the clinical pathological characteristics of LIHC patients and SCAF1 expression. We also examined the effect of SCAF1 expression on patient prognosis and utilized the Kaplan-Meier survival technique to estimate the OS, DSS, and PFI of LIHC patients. The findings demonstrated that, in comparison to the low-expression group, the high-expression group of SCAF1 had reduced survival rates at each time (Figure 2. e–f), suggesting that high SCAF1 expression may be associated with a poor prognosis in LIHC patients. Furthermore, we created a prediction nomogram in which T stage was the most significant contributor to OS in order to reliably forecast the survival rate of LIHC patients (Figure 2.g). We created a prognosis ROC curve, where the AUC values for 1, 3, and 5 years were all larger than 0.5, to further assess the precision of gene prediction (Figure 2.h), confirming the high specificity and sensitivity of SCAF1 in predicting LIHC prognosis and suggesting that SCAF1 expression is a key factor affecting the prognosis of LIHC patients.

Potential Functions of SCAF1 in LIHC:

Given the significant upregulation of SCAF1 expression levels in LIHC, we aimed to study the regulatory mechanisms involving SCAF1 in LIHC. According to Figure 3.a–b's GSEA analysis, the elevated DEGs linked to SCAF1 were primarily enriched in pathways pertaining to adhesion junctions and angiogenesis. This suggests that there may be a correlation between the expression of SCAF1 and the levels of metastasis and angiogenesis in LIHC. In response to this conjecture, we carried out transwell assays to evaluate the effect of SCAF1 knockdown on the invasive migration of LIHC cells. We discovered that the SCAF1 knockdown group's HCCLM3 cells' capacity for migration and invasion was greatly diminished (Figure 3.c). Previous research has demonstrated that angiogenesis plays a major role in the invasion and migration processes of tumor cells [18]. Combining our predicted results, we confirmed through WB experiments and mRNA detection that knocking down SCAF1 could reduce the degree of VEGFA expression in LIHC (Figure 3.d), and there was a notable decrease in the cells' capacity to produce tubes in the angiogenesis experiment (Figure 3.e). Lowering SCAF1 may suppress the invasive migration of LIHC cells by altering key signals in the VEGF pathway (VEGFA).

Relationship between SCAF1 and the Immune Microenvironment:

Chemokines and their receptors, a superfamily of secreted small molecules, are closely associated with the development of LIHC [19]. Chemokines can regulate LIHC cells by affecting the expression of VEGF [20]. To explore the relationship between the SCAF1 gene in LIHC cells and chemokines, we used the TISIDB website to generate heatmaps for analysis, revealing that SCAF1 in LIHC cells was associated with multiple chemokines, including CCL19, CCL14, and CCL11, and there was a negative correlation found between the expression levels of SCAF1 and the three chemokines. Knocking down the expression of SCAF1 could upregulate the expression levels of CCL19, CCL14, and CCL11. This implies that SCAF1 may influence LIHC by controlling the expression of these three chemokines, which in turn influences the production of VEGF. Malignant tumor genesis, growth, and metastasis are all dependent on the tumor microenvironment (TME), which is made up of elements including VEGF and immune cells that have infiltrated the tumor [21, 22]. To further explore the ability of SCAF1 expression to regulate the tumor immune microenvironment and evaluate the relationship between immunity and VEGF, we scored SCAF1 for immunity, stroma, and estimate. We found that all three scores were negatively correlated with SCAF1 expression levels (Figures 5.a–c). Next, we investigated the connection between immune cell infiltration and SCAF1 expression in LIHC using the TIMER database. The findings demonstrated that elevated SCAF1 expression may raise the degree of immune cell infiltration, including B cells, CD8+ T cells, CD4+ T cells, neutrophils, macrophages, and dendritic cells. Subsequently, we investigated the connection between SCAF1 expression levels and immune cell surface markers. The results indicated that there was a positive correlation between SCAF1 expression levels and TAM, B cells, monocytes, Th1, Th2, and DC cell surface indicators (Figure 5.d-j). Combination therapy involving VEGF blockade therapy and immune checkpoint-targeted immunotherapy is becoming increasingly important and has become a first-line choice for various cancer treatments [23]. We then studied the correlation between immune checkpoints and SCAF1 in LIHC, and the outcomes demonstrated a negative correlation between the expression of SCAF1 and a number of immunological checkpoints, including CTLA-4 and PD-1(Supplementary Figure 1.c). Ultimately, we discovered that immunotherapy was not appropriate for individuals exhibiting elevated expression of SCAF1(Supplementary Figure 1.d–e). To investigate how tumor treatment affects VEGFA and SCAF1 expression, we performed principal component analysis and dimensionality reduction clustering on tissue cells, simulating tumor heterogeneity changes over time(Supplementary Figure 3.b–c). We arranged the expression levels of SCAF1 and cell types on the pseudo-time axis, and the results showed that as the pseudo-time axis progressed, the expression levels of SCAF1 increased (Supplementary Figure 3.d). The distribution of VEGFA and SCAF1 expression after immunotherapy is shown in Supplementary Figure 4.a–b, and after immunotherapy, the expression of VEGFA and SCAF1 was obviously downregulated, suggesting some mechanisms of immunotherapy.

Small molecule drugs targeting SCAF1:

Through network pharmacology analysis, we explored small-molecule drugs associated with the treatment of hepatocellular carcinoma (LIHC) and drugs targeting VEGFA. By searching the TCMSP database and cross-analyzing LIHC therapeutic molecules with drugs targeting VEGFA, we identified 16 small molecules (Figure 6.a). Using molecular docking techniques, we modeled the interactions between these small molecules and the SCAF1 protein. Genistein exhibited the strongest binding affinity with SCAF1, interacting with three amino acid residues of SCAF1 (85Glu, 84Thr, and 83Val) through hydrogen bonding, demonstrating stronger binding affinity compared to other molecules (Figure 6.b). Cell viability assays showed that cell proliferation significantly slowed down upon genistein treatment, while Western blot experiments demonstrated that genistein markedly downregulated the expression levels of SCAF1 and VEGFA (Figure 6.c–d). Furthermore, the migration and invasion capabilities of LIHC cells were markedly reduced upon genistein treatment (Figure 6.e). These findings suggest that genistein inhibits the occurrence and development of LIHC by suppressing the expression levels of SCAF1, thereby downregulating key molecules in the angiogenesis process.

Hepatocellular carcinoma (LIHC) is a common cancer and ranks second in terms of mortality globally. While the incidence of LIHC has been somewhat controlled recently and remains relatively stable, the prognosis for patients still remains concerning. Due to LIHC's typical highly vascularized and arterialized solid tumor nature, anti-angiogenic therapies have been considered effective strategies in its treatment. Drugs targeting VEGF, for example sorafenib, have been widely utilized in clinical practice for LIHC patients [24]. However, in diagnostic practice, due to the lack of biomarkers predicting VEGF, both OS and PFS for patients have not been effectively improved. Consequently, there is an urgent need to establish new biomarkers related to angiogenesis in LIHC [25, 26].

In our study, we predicted key genes correlated with LIHC progression through WGCNA, followed by exploration of key modules associated with angiogenesis, focal adhesions, and Epithelial-Mesenchymal Transition (EMT). We identified the hub gene SCAF1, which we believe plays a role in promoting angiogenesis in LIHC, possibly promoting tumor cell invasion and migration. We then conducted expression, clinicopathological, survival, and functional analyses of SCAF1. Our results indicate that SCAF1 is highly expressed in LIHC tissues, and high expression of SCAF1 is correlated with poor prognosis and higher cancer grades in patients, and it participates in processes related to angiogenesis and tumor cell metastasis.

It is known that VEGF can heighten the invasion and migration ability of LIHC through various regulatory axes [27, 28, 29]. Our results suggest that SCAF1 not only promotes angiogenesis in LIHC but also enhances the migration and invasion levels of LIHC. We speculate that SCAF1 may increase cancer cell metastasis through the VEGF pathway.

In previous studies, the production status of chemokines in the TME provided a predictive means for VEGF levels in cancer [11, 30]. For example, CCL19 inhibits angiogenesis in colorectal cancer by inhibiting the Met/ERK/Elk-1/HIF-1α/VEGF-A pathway [14, 31]. Our experimental results indicate that knocking down SCAF1 can promote the expression of CCL19, CCL14, and CCL11. We speculate that high expression of SCAF1 may lead to the highly vascularized neovascularization in LIHC by suppressing the levels of anti-angiogenic cytokines in LIHC.

Additionally, the level of immune infiltration in the TME can affect the angiogenesis level in LIHC. Immunosuppressive cells such as regulatory T cells and TAMs can exert immunosuppressive activity, regulate downstream signaling pathways, and drive angiogenesis [32]. SCAF1 may be involved in multiple tumor immune mechanisms [33], such as inducing the expression of SCAF1 in GBMLGG can promote the M2 polarization of macrophages, thereby shifting macrophage subtypes unfavorably for patient survival. In our study, we used immune scores, stromal scores, and ESTIMATE scores to quantify in situ cell infiltration [34]. The results point out that high expression of SCAF1 reduces the immune scores of LIHC and contributes to the recruitment of CD8 + T cells, macrophages, and other immune cells. Using the TIMER database, we analyzed the expression of SCAF1 and immune cell markers in LIHC. As expected, the expression of SCAF1 is positively associated with various immune regulatory cells (TAMs, B cells, Th1, Th2, dendritic cells), indicating that SCAF1 may drive the angiogenesis pathway by inducing anti-immune activity of these cells.

Small molecule-related heterologous therapies have been preliminarily applied in the treatment of LIHC patients [35, 36, 37], and patients treated with traditional Chinese medicine as adjunctive therapy have shown relatively significant improvements in prognosis. genistein is a common precursor for the synthesis of antimicrobial and antitumor phytoalexins in plants of the Leguminosae family. It has a range of potential health benefits, including chemoprevention of LIHC, breast cancer, and prostate cancer [38, 39, 40]. Guo et al. showed that genistein exerts anti-tumor effects in prostate cancer by inhibiting angiogenesis [41], but reports on the anti-tumor mechanism of genistein in LIHC are incomplete. In our study, we found that genistein can form stable docking with the SCAF1 molecule and inhibit the proliferation of HCCLM3 cells. Furthermore, genistein can inhibit the expression of SCAF1 and VEGFA, as well as the invasion and migration capabilities of LIHC cells. We speculate that genistein may inhibit angiogenesis in LIHC by binding to SCAF1 and suppressing its expression, thereby suppressing the occurrence and development of LIHC.

Although our results have conducted meta-analyses of multiple datasets from TCGA, ICGC, and GEO, and obtained some prospective results on clinical treatment, the clinical efficacy of the identified small molecule drugs still needs further confirmation, and the therapeutic effect of VEGF blockade predicted by SCAF1 should be further confirmed in patient cohort analyses. Although our study confirms the temporal and spatial distribution status of SCAF1 in liver tissues, further in vivo validation is needed in our future research to optimize treatment.

In summary, we have identified a biomarker, SCAF1, which can affect the angiogenesis status of LIHC patients, and found that SCAF1 can act as an oncogene leading to high-stage grading and poor prognosis of LIHC patients. High expression of SCAF1 in LIHC downregulates immune scores and the expression levels of multiple pro-angiogenic cytokines, suggesting poor immunotherapeutic effects, and closely interacts with various effective components of anti-tumor angiogenesis in Chinese medicine. These results all indicate that SCAF1 can serve as a diagnostic and therapeutic biomarker for LIHC patients, providing reference for updating the treatment plan for LIHC patients.

Data Availability Statement

Publicly available datasets were analyzed in this study. The data are accessible in TCGA, ICGC and GEO databases. Further inquiries can be directed to the corresponding author.

Ethics Statement

The patient’s informed consent was obtained and this study was permitted ethically by the ethics committee of Second Afflliated Hospital of Nanchang University.

Author Contributions

Liangyun Guo, Gen Chen contributed to the conception and design of the study. Zichuan Yu, Hao Zheng, Shengwei Tang, Conceptualization, Methodology, Software, Validation, Formal analysis, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Supervision, Project administration. Xuanrui Zhou, Minqin Zhou: Conceptualization, Methodology, Software, Validation, Formal analysis, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Supervision, Project administration. Xitong Geng, Yanting Zhu, Shuhan Huang, Yiyang Gong, Yike Jiang: Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

This study was supported by grants from Natural Science Foundation of Jiang xi Province (20232BAB206119) and Science and Technology Project of Jiangxi Provincial Health Commission (202310039)

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SupplementaryFigure1.pdf
Supplementary Figure 1. a, b Analysis of SCAF1 expression in tumor and normal tissues utilizing TCGA and ICGC databases. c Correlation between SCAF1 and various immune checkpoints in LIHC. d Relationship between SCAF1 and TMB. e High SCAF1 expression was associated with high TIDE scores.
SupplementaryFigure2.pdf
Supplementary Figure 2. Relationship of SCAF1 expression with gene markers of immune cells in LIHC. a M1; b Natural killer cell; c Neutrophils; dTreg; e Tfh; f Th17; g Resting Treg; h Effector Treg T-cell; i Naïve T-cell; j Effector T-cell; kExhausted T-cell; l Th1-like; m Memory T-cell; n Effector memory T-cell; o Resident memory T-cell.
SupplementaryFigure3.pdf
Supplementary Figure 3. Spatial transcriptomics and single-cell sequencing. a Liver tissue sections and cell reclustering by UMAP method. b Cells were classified into six phenotypes based on the specific expressed genes in each cluster. c Macrophages were further divided into six cell types based on SCAF1 expression. d Changes in SCAF1 expression levels and cell types in pseudotime.
SupplementaryFigure4.pdf
Supplementary Figure 4. Further study of the post-immunotherapy tumor microenvironment in patients with LIHC. a SCAF1 and VEGFA expression in LIHC cell lines. b SCAF1 and VEGFA’s expression in LIHC cell lines after immunotherapy. c tSNE cell cluster analysis was carried out on the cells after treatment. d Further clustering of one of the cell types into six clusters. e Changes in SCAF1 expression levels and cell types using pseudotime.
SupplementaryFigure5.pdf
Supplementary Figure 5. Molecular docking analysis of SCAF1 and the main ingredients of traditional Chinese medicines. a Beta-carotene. b Progesterone. c Baicalein. d Luteolin
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Identification of SCAF1 as a key factor affecting VEGF in LIHC and its potential target for therapy hypothesized based on network pharmacology and transcriptomics

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