Abstract Background Numerous cancer types present the aberrant TANK-binding kinase 1 (TBK1) expression, which plays an important role in driving inflammation and innate immunity. However, the prognostic role of TBK1 and its relationship with immune cell infiltration in hepatocellular carcinoma (HCC) remain unclear. Methods The expression and prognostic value of TBK1 was analyzed by Tumor Immune Estimation Resource (TIMER), Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and further confirmed in the present cohort of patients with HCC. The association between TBK1 and HCC immune infiltrates, and its potential mechanism were investigated via analyses of the Tumor Immune Estimation Resource, tumor-immune system interactions database (TISIDB), CIBERSORT, STRING, and Metascape. The effect of TBK1 on immune infiltrates and the therapeutic value of targeting TBK1 were further investigated in a HCC mouse model by treatment with a TBK1 antagonist. Results The level of TBK1 expression in HCC was higher than that measured in normal tissues, and associated with poorer overall survival (GEPIA: hazard ratio [HR]=1.80, P=0.038; Kaplan–Meier plotter: HR=1.87, P<0.001; CPTAC: HR=2.23, P=0.007; Our cohort: HR=2.92, P=0.002). In addition, high TBK1 expression was found in HCC with advanced TNM stage and identified as an independent poor prognostic factor for overall survival among patients with HCC. In terms of immune infiltration, tumor tissues from HCC patients with high TBK1 expression had a low proportion of CD8^+ T cells, and TBK1 expression did not show prognostic value in HCC patients with enriched CD8+ T cells. Furthermore, TBK1 expression was positively correlated with the markers of T cell exhaustion and immunosuppressive cells in the HCC microenvironment. Mechanistically, the promotion of HCC immunosuppression by TBK1 was involved in the regulation of inflammatory cytokines. In vivo experiments revealed that treatment with a TBK1 antagonist delayed HCC growth by increasing the number of tumor-infiltrating CD8+ T cells. Conclusions The up-regulated expression of TBK1 may be useful in predicting poor prognosis of patients with HCC. In addition, TBK1, which promotes the HCC immunosuppressive microenvironment, may be a potential immunotherapeutic target for patients with HCC. Keywords: TANK-binding kinase 1, immune infiltration, inflammation, targeted therapy, hepatocellular carcinoma Introduction Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and the fourth leading cause of cancer-related death worldwide ([41]1). More than 50% of patients with HCC are diagnosed with advanced disease ([42]2). Immunotherapy represents a promising strategy for many types of advanced cancer ([43]3). The US Food and Drug Administration approved the use of checkpoint inhibitors (nivolumab and pembrolizumab) as a treatment option for advanced HCC ([44]4). However, as a typically inflammation-associated cancer ([45]5), HCC shows a unique immunosuppressive microenvironment enhanced by inflammation-related stromal cells and cytokines ([46]6). This results in lower response and acquired resistance to checkpoint inhibitors ([47]7). Therefore, it is urgent to identify novel therapeutic targets correlated with the HCC immunosuppressive microenvironment. TANK-binding kinase 1 (TBK1) is a member of the inhibitor of nuclear factor-κB kinase (NF-κB) family ([48]8). Upon receptor-mediated pathogen detection, TBK1 phosphorylation promotes the activation of the NF-κB pathway in the innate immune response ([49]9). An initial study linking TBK1 to cancer found that TBK1 supports oncogenic Ras transformation with coupling innate immune signaling to tumor cell survival ([50]10). Previous studies also demonstrated aberrant TBK1 expression and its pro-tumor effects in multiple cancers, including the promotion of migration and invasion in melanoma ([51]11), AXL-induced epithelial–mesenchymal transition in pancreatic cancer ([52]12), and tamoxifen resistance by increasing the transcriptional activity of estrogen receptor α in breast cancer ([53]13). However, the underlying functions and mechanisms of TBK1 in HCC progression remain uncertain. Recently, it was reported that TBK1 restrains the activation and migration of T cells, which are the main type of lymphocytes involved in the antitumor immune response ([54]14, [55]15). Moreover, TBK1 contributed to tumor immunosuppression by down-regulating the expression of co-stimulatory molecules and decreasing T cell-priming activity in dendritic cells ([56]16). However, another study yielded contrary results indicating that TBK1 participated in the activation of stimulator of the interferon genes pathway, enhancing antitumor immunity in the tumor microenvironment ([57]17). Moreover, TBK1 was identified as a promoter of resistance to immunotherapy ([58]9). Of note, inhibition of TBK1 effectively blocked the release of immune-suppressive cytokines and improved the therapeutic efficacy of anti-programmed death-ligand 1 (anti-PD-L1) ([59]18). These findings prompted us to investigate the effects of TBK1 on the immune microenvironment and its potential value in the treatment of HCC. In the present study, we investigated the correlation of TBK1 expression with prognosis and immune infiltration in patients with HCC. Mechanistically, we constructed TBK1-related gene networks and analyzed their function using bioinformatics tools. Importantly, the roles of TBK1 in HCC progression and immune infiltration were further explored in vivo (in immunodeficient and immunocompetent mice) using the TBK1 antagonist GSK8613. Our data revealed that TBK1 predicted poor prognosis in patients with HCC and may be a therapeutic target by attenuating tumor immunosuppression. Materials and Methods UALCAN and Gene Expression Omnibus (GEO) Database Analysis UALCAN is a comprehensive and interactive resource for analyzing cancer data ([60]http://ualcan.path.uab.edu/index.html) ([61]19). It provides access to publicly available cancer databases, including The Cancer Genome Atlas (TCGA) and MET500 data set. Moreover, it enables researchers to identify the up- or down-regulated genes in tumors compared with normal tissues, and compare the expression of genes of interest in subgroups, as defined by individual cancer stages, tumor grade, gender, age, nodal metastasis status, TP53 mutation status, and tumor histology. GEO2R is an interactive web tool that enables researchers to analyze the different expression of genes in two or more groups of samples across experimental conditions in a GEO series ([62]20). In the present study, we investigated the levels of TBK1 mRNA expression in different types of cancer and corresponding normal tissues using UALCAN and GEO2R. Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan–Meier (KM) Plotter, and Clinical Proteomic Tumor Analysis Consortium (CPTAC) Database Analysis The online database GEPIA is an interactive web server for the analysis of RNA sequencing expression data from the TCGA and Genotype-Tissue Expression projects, which include 9,736 tumors and 8,587 normal samples ([63]21). The KM plotter is an online available tool for exploring the effect of 54,675 genes on survival in 21 types of cancer. Sources for the databases include the GEO, TCGA, and European Genome-phenome Archive ([64]22). We performed the survival analysis based on TBK1 mRNA expression in 33 different types of cancer using GEPIA and in 21 different types of cancer using the KM plotter. According to the mRNA expression of markers of CD4, CD8 and B cell in HCC tissues, the KM-plotter tool divided the HCC cohort from TCGA into enriched and decreased infiltration of the three types of cell. We used the KM-plotter to investigate the survival time of HCC patients based on the content of CD4, CD8 and B cell ([65]https://kmplot.com/analysis/index.php?p=service&cancer=pancancer_r naseq). The tool of “auto select best cutoff” (all possible cut off values between the lower and upper quartiles are computed, and the best performing threshold is used as a cutoff) in GEPIA and KM plotter were used to determine the cut-off values in the survival curves (mRNA level). CPTAC is a database established by The National Cancer Institute to promote the understanding of the molecular basis of cancer by applying large-scale proteomic and genomic analyses, or proteogenomics ([66]23). Survival analysis based on TBK1 protein expression in HCC was also performed via the CPTAC database. The proteomic data of TBK1 in CPTAC (≤ 0.00368 defined as TBK1 low expression; > 0.00368 defined as TBK1 high expression) were analyzed to select the cut-off value in survival curves (protein level). Tumor Immune Estimation Resource (TIMER) Database and Tumor-Immune System Interactions Database (TISIDB) Analysis TIMER is a comprehensive resource for investigating the interactions between genes of interest and tumor immune interactions in more than 30 types of cancer ([67]https://cistrome.shinyapps.io/timer/) ([68]24). It has incorporated 10,897 samples across 32 types of cancer from TCGA to estimate the abundance of immune infiltrates. The TISIDB is a web portal for the analysis of tumor and immune system interaction; it integrates heterogeneous data types, including literature mining results from the PubMed database, high-throughput screening data, RNA sequencing data of patients with immunotherapy, and TCGA ([69]25). In the present study, we investigated the correlation of TBK1 expression with tumor immune infiltration using TIMER and with tumoral activated CD8^+ T cells through the TISIDB in the HCC data set. The abundance profile of tumor-infiltrating immune cells in HCC samples from TCGA was calculated using the CIBERSORT computational method ([70]26). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Enrichment Analysis Metascape is an online portal that integrates multiple bioinformatics knowledge bases to provide a comprehensive gene list annotation and analysis resource, especially for functional enrichment, gene annotation, and construction of protein-protein interaction networks ([71]27). Here, we used Metascape to analyze the molecular and functional characteristics of TBK1 and its related genes Reagents and Chemicals TBK1 inhibitor GSK8612 were purchased from Selleck Chemicals (S8872). For in vitro experiments, GSK8612 were dissolved in DMSO (Sigma-Aldrich, MO, USA) and further diluted to the required concentration. For in vivo experiments, GSK8612 suspension was prepared in 0.5% carboxymethyl cellulose sodium normal saline solution. Antibodies to TBK1 were purchased from Proteintech. Antibodies to α-SMA, CD8α, phospho-TBK1 (p-TBK1) and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) were purchased from Cell Signaling Technology. Cell Proliferation and Migration Assay Hepa1-6 and H22 cell line were gifts from Dr. Limin Zheng (School of Life Sciences, Sun Yat-Sen University, Guangzhou, China). Hepa1-6 cells were cultured in DMEM supplemented with 10% inactivated fetal bovine serum and 1% penicillin-streptomycin (Gibco, USA). Hepa1-6 cells were seeded at 1,000 cells per well in 96-well microplates and incubated in normal growth medium for 24 h. Subsequently, the cells were treated with DMSO or GSK8612 for an additional 24, 48, or 72 h. Cell viability was measured using the Cell Counting Assay Kit-8 (CCK-8; Dojindo, Kumamoto, Japan) according to the manufacturer’s instructions. Cell migration assays were performed on transwell chambers with 8-μm pore-size filters. Cells were trypsinized and resuspended in serum-free medium with DMSO or GSK8612. 250 μl of cell suspension (1 x 10^5 cells) was added to the upper chambers in a transwell insert, and the upper chambers were then placed into the wells of a 24-well plate. 750 μl culture medium containing 20% fetal bovine serum (FBS) was added to the lower chamber. After transwell inserts were cultured at 5% CO2 at 37°C for 24 h, cells on the top of the membrane were removed with a cotton swabs. Cells attached on the underside of the membrane were fixed and stained with 0.1% crystal violet. After washing with phosphate-buffered saline (PBS), the number of cells was counted in three random microscopic fields under the microscope. Histological and Immunohistological Analysis of Liver Sections Liver and tumor tissues were fixed with 10% formalin, embedded in paraffin and cut into 2 mm sections for staining with hematoxylin-eosin (H&E), Sirius red and immunohistochemistry according to standard procedures ([72]28). For immunohistochemistry (IHC), tumor sections were stained with the appropriate antibodies, and both the intensity and extent of immunostaining were taken into consideration when analyzing the data. The intensity was scored as 0 for negative, 1 for weak staining, 2 for moderate staining and 3 for strong staining. The extent of staining was scored as 0, 0.25, 0.50, 0.75, and 1.00 for less than 5%, 6%–25%, 26%–49%, 50%–74%, and 75%–100% positively stained cells, respectively. The final quantitation of each staining was obtained by multiplying these two values (intensity score × extent score) ([73]29). TBK1 expression was classified as high expression if the score was higher than 1.5; if the score was 1.5 or less, the case was classified as low expression. Two different pathologists who specialize in liver cancer evaluated the results of IHC. Western Blotting The total cellular protein and tissue protein was extracted by RIPA Lysis Buffer (Thermo Fisher Scientific, MA, USA) and RIPA Lysis Buffer (Thermo Fisher Scientific) containing protease inhibitors and phosphatase inhibitors (Thermo Fisher Scientific). The protein concentrations of the cell lysates were measured using a Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific) and equalized before loading. Equal amount of protein extracts from HCC cells or tissues were separated by SDS–PAGE, and transferred onto polyvinylidene fluoride membranes (Sigma-Aldrich, MO, USA). Immunoblot analyses were carried out using the appropriate antibodies, and the bands were visualized using an SuperSignal™ West Pico PLUS chemiluminescence Substrate (Thermo Fisher Scientific). Flow Cytometry Fresh mouse liver tissues were finely chopped and dissociated into single-cell suspensions. After removal of red blood cells and liver cells, the leukocytes were further purified using a magnetic-activated cell-sorting separator with CD45 magnetic beads (Miltenyi Biotec, CA, USA). After incubation with V450-labeled CD3, PerCP-Cy™-labeled CD4, and V500-labeled CD8 (BD Biosciences, CA, USA), tumor-infiltrated T cells were detected by a flow cytometer (BD LSRFortessa X-20). Gating strategy for CD4^+ and CD8^+ T-cell in HCC tissues: lymphocytes were gated by forward and side scatter properties, and then CD4^+/CD8^+ T-cells were gated for further analysis ([74]30). Enzyme-Linked Immunosorbent Assay (ELISA) The HCC tissues from mouse model collected above were weighed and homogenized at 4°C. Homogenates were centrifuged at 14,000xg for 10 min at 4°C. Supernatants were transferred to clean microcentrifuge tubes for detection. Specific ELISA kits (Jiangsu Meimian industrial, Jiangsu, China) were used to quantitate IL-6 according to the manufacturer’s instructions. In Vivo Treatment Studies Male immunodeficient (BALB/c nude) and immunocompetent (C57BL/6) mice (aged 4–6 weeks) were subjected to carbon tetrachloride (CCl[4]) gavage (40% in 100 μl of olive oil per mouse, volume/volume) for 4 weeks to induce the inflammatory liver microenvironment. Subsequently, mice were injected with 25 μl of HCC cell/Matrigel solution (containing 1×10^6 Hepa1–6 cells) in the subcapsular region of the liver, and were divided into the control or treatment groups ([75]31). On day 3 following inoculation with tumor cells, the TBK1 antagonist GSK8612 was administered orally at the dose of 5 mg/kg for 7 days. Mice were sacrificed 10 days after HCC implantation. The mice were maintained in the laboratory for animal experimentation in a specific pathogen-free environment with laminar air-flow conditions, a 12-h light-dark cycle, and at a temperature of 22°C–25°C. All animals had free access to standard laboratory mouse food and water. Animal experiments were approved by the Bioethics Committee of Jinan University (China) and performed according to established guidelines. Patients and Specimens Liver samples (n=139) from patients with HCC who underwent hepatectomy were collected in the First Affiliated Hospital of Jinan University. Patient samples were collected and used with the informed written consent of the patient. All liver samples were obtained under protocols approved by the First Affiliated Hospital of Jinan University Office for Protection of Human Subjects. Statistical Analysis The Student’s t test was used to compare values between two groups and the ANOVA was employed to compare between subgroups with more than two groups. Overall survival (OS) was calculated by KM survival analysis and log-rank tests. Data were expressed as the mean ± standard deviation of at least three biological replicates. P < 0.05 denoted statistical significance. All analyses were performed using the SPSS software (Version 23.0; IBM, Armonk, NY, USA). Results TBK1 Expression Was Up-Regulated in HCC Tissues TIMER and UALCAN were used to analyze the transcriptome-sequencing data from TCGA data set to evaluate the differences in TBK1 expression between tumor and normal samples. The results obtained from TIMER revealed that TBK1 expression was up-regulated in nine types of cancer, including liver hepatocellular carcinoma (LIHC), whereas it was down-regulated in only one type of cancer ([76] Figure 1A ). Moreover, the results obtained from UALCAN indicated that TBK1 expression was significantly increased in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), LIHC, lung adenocarcinoma (LUAD), lung squamous cell carcinoma(LUSC), and stomach adenocarcinoma (STAD) ([77] Figure 1B ). Figure 1. [78]Figure 1 [79]Open in a new tab TANK-binding kinase 1 (TBK1) expression levels in human cancer. The levels of TBK1 mRNA expression in different types of human cancer were determined using Tumor Immune Estimation Resource (TIMER) (A) and UALCAN (B). (C) Representative images of immunohistochemistry (IHC) staining with a TBK1 antibody on HCC tissues (n = 138) and corresponding normal tissues (n = 118) in our cohort. ACC, Adrenocortical carcinoma; BLCA, Bladder urothelial carcinoma; BRCA, Breast invasive carcinoma; BRCA-Basal/Her2/Luminal, Breast invasive carcinoma-Basal/Her2/Luminal; CESC, Cervical squamous cell carcinoma and endocervical adenocarcinoma; CHOL, Cholangiocarcinoma; LIHC, Liver hepatocellular carcinoma; COAD, Colon adenocarcinoma; READ, Rectum adenocarcinoma; DLBC, Lymphoid neoplasm diffuse large B-cell lymphoma; LAML, Acute myeloid leukemia; ESCA, Esophageal carcinoma; GBM, Glioblastoma multiforme; LGG, Brain Lower Grade Glioma; HNSC, Head and neck squamous cell carcinoma; HNSC- HPVneg, Head and neck squamous cell carcinoma-HPVneg; KICH, Kidney chromophobe; KIRC, Kidney renal clear cell carcinoma; KIRP, Kidney renal papillary cell carcinoma; LUAD, Lung adenocarcinoma; LUSC, Lung squamous cell carcinoma; MESO, Mesothelioma; OV, Ovarian serous cystadenocarcinoma; PAAD, Pancreatic adenocarcinoma; PCPG, Pheochromocytoma and Paraganglioma; PRAD, Prostate adenocarcinoma; SARC, Sarcoma; SKCM, Skin cutaneous melanoma; SKCM-Metastasis, Skin cutaneous melanoma- Metastasis; STAD, Stomach adenocarcinoma; TGCT, Testicular Germ Cell Tumors; THCA, Thyroid carcinoma; THYM, Thymoma; UCEC, Uterine Corpus Endometrial Carcinoma; UCS, Uterine Carcinosarcoma; UVM, Uveal Melanoma. *P < 0.05; **P < 0.01; ***P < 0.001. We further confirmed the expression of TBK1 in multiple human cancers using microarray data sets from GEO. Higher TBK1 expression was found in the subtype of breast cancer, cervical cancer, colorectal cancer, gastric cancer, head and neck cancer, kidney cancer, leukemia, liver cancer, and pancreatic cancer compared with that measured in normal tissues or cells. Meanwhile, TBK1 expression was lower in the subtype of brain cancer ([80] Table 1 ). In addition, the protein level of TBK1 expression in HCC and liver tissues were also determined with immunohistochemistry staining. TBK1 was mainly expressed in hepatocytes and HCC cells, and were also detected in stromal cells. In line with the results obtained from TCGA and GEO databases, the findings of this study indicate that TBK1 expression was significantly increased in HCC tissues (P<0.001) ([81] Figure 1C ). Table 1. Significant changes in TANK-binding kinase 1 (TBK1) expression in cancer versus normal tissue in GEO the database. Cancer Subtype Fold change P value Adjusted P Value Reference (PMID) GEO accession number Breast Ductal Breast Carcinoma in situ 1.434 <0.001 0.009 19187537 [82]GSE14548 Brain Oligodendroglioma −1.569 <0.001 <0.001 16616334 [83]GSE4290 Cervical Cervical Squamous Cell Carcinoma 1.428 <0.001 <0.001 18191186 [84]GSE7410 Cervical cancer 4.287 <0.001 <0.001 17510386 [85]GSE6791 Colorectal Rectal carcinoma 1.504 <0.001 <0.001 18171984 [86]GSE8671 Gastric Gastric mixed adenocarcinoma 1.727 <0.001 <0.001 19081245 [87]GSE13911 Head and neck Nasopharyngeal carcinoma 1.651 <0.001 <0.001 17119049 [88]GSE12452 Kidney Clear cell renal cell carcinoma 1.784 <0.001 <0.001 17699851 [89]GSE6344 Renal pelvis urothelial carcinoma 1.649 <0.001 <0.001 16115910 [90]GSE15641 Leukemia T-cell prolymphocytic leukemia 2.543 <0.001 0.012 17713554 [91]GSE5788 Liver Hepatocellular carcinoma 1.512 0.006 0.037 22689435 [92]GSE50579 Pancreatic Pancreatic ductal adenocarcinoma 1.656 <0.001 <0.001 19260470 [93]GSE15471 [94]Open in a new tab The data sets used in the current study has been published in relevant references and can be obtained by GEO accession.