Loss of FGL1 induces epithelial‑mesenchymal transition and angiogenesis in LKB1 mutant lung adenocarcinoma
- Authors:
- Published online on: July 15, 2019 https://doi.org/10.3892/ijo.2019.4838
- Pages: 697-707
Abstract
Introduction
Lung cancer is the leading cause of cancer-related death worldwide and results in >1 million deaths annually (1). The most common type of lung cancer is the non-small cell lung cancer (NSCLC), which mainly comprises lung adenocarcinoma and squamous cell carcinoma (2). Lung adenocarcinoma is the most common form of lung cancer, and its 5-year survival rate is only 15% (3). Although many treatment modalities exist for lung adenocarcinoma, such as surgery, radiotherapy, chemotherapy and targeted treatment, the prognosis for patients with lung cancer is poor because of various complications and diagnosis at late stages (4,5). The present study explored potential novel biomarkers in liver kinase b1 (LKB1) mutant lung adenocarcinoma. Bioinformatic data mining and experimental verification revealed that FGL1 was highly expressed in LKB1 mutant lung adenocarcinoma. Then, the functional role of FGL1 in LKB1 mutant lung adenocarcinoma was further explored.
LKB1, also known as serine/threonine kinase 11 (STK11), is a gene encoding the serine/threonine kinase LKB1, which was originally identified as the tumor suppressor gene for the inherited cancer disorder Peutz-Jeghers syndrome (6). The inactivated mutation frequency of LKB1 in NSCLC is ~20% (7). The most common target of LKB1 is AMP-activated protein kinase (AMPK), which is directly phosphorylated and activated by LKB1 under conditions of low cellular ATP (8). LKB1 can activate AMPK-related family kinases to regulate many aspects of cell metabolism, growth, autophagy and polarity (8,9). LKB1 mutations can lead to tumor initiation and confer invasive and metastatic behavior in genetically engineered mouse models of cancer (10,11). The present study focused on LKB1 mutant lung adenocarcinoma and explored novel biomarkers to diagnose and treat this subcategory of patients.
Fibrinogen-like protein 1 (FGL1), also termed HRFEP-1 or hepassocin, is a predominantly liver-expressed protein that functions as both a hepatoprotectant and a hepatocyte mitogen. In 1993, Yamamoto et al (12) isolated FGL1 from a cDNA library constructed from the mRNA of a hepatocellular carcinoma specimen using subtractive and differential cDNA cloning and demonstrated that this gene was important in the development of hepatocellular carcinoma. Rijken et al (13) concluded that FGL1, a protein with liver cell growth regulatory properties, was found in plasma and was strongly associated with fibrin and possibly fibrinogen. Nayeb-Hashemi et al (14) reported that FGL1 was a tumor suppressor in hepatocellular carcinoma, and its loss correlated with a poorly differentiated phenotype. Although several studies have shown an association of FGL1 with liver cancer, few studies have investigated the role of FGL1 in lung cancer.
In the present study, data mining of The Cancer Genome Atlas (TCGA) (15) and the Gene Expression Omnibus (GEO) (16) databases revealed that FGL1 expression was significantly increased in LKB1 mutant lung adenocarcinoma. The association between LKB1 and FGL1 was explored via functional experiments and gene set enrichment analysis (GSEA); the results confirmed that FGL1 regulated epithelial-mesenchymal transition (EMT) and angiogenesis in LKB1 mutant lung adenocarcinoma. The present study demonstrated that FGL1 may serve as a potential novel biomarker for diagnosis and prognosis in patients with LKB1 mutated lung adenocarcinoma.
Materials and methods
Database source and gene expression
Using the TCGA database, lung adenocarcinoma information on 230 patients with LKB1 mutations were acquired (7). Separate differential gene expression analyses were conducted using the edgeR and DESeq packages in R software (r-project.org/, R ×64 3.4.3), and the intersection of the differentially expressed genes [|logFC|>1 and false discovery rate (FDR) <0.05] from these two packages was obtained. Two GEO databases (GSE72094 and GSE75037) (17,18) were then used to validate these differentially expressed genes and the intersected/validated genes from TCGA and the two GEO databases were finally selected. Fig. 1 illustrates a flow-chart for the gene screening process.
Patient selection
Tissue samples from 30 patients (13 male, 17 female) with lung adenocarcinoma who underwent surgery at Shandong Provincial Hospital affiliated to Shandong University in 2018 were enrolled in this study. Tumor tissue was collected from patients that met the following inclusion criteria: The patient has only one cancer, lung cancer; there is only one lesion and the pathological diagnosis is simple lung adenocarcinoma; tumor size 2-4 cm; the range of age is 40-60 years old; the specific surgery dates were between October to December 2018. Patients that did not meet the inclusion criteria were excluded. Informed consent was obtained from all participants included in the study. All procedures conformed to the ethical guidelines of the 1975 Declaration of Helsinki and were in accordance with the ethical standards of the Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong University. The Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong University approved all experimental protocols.
Cell cultures and antibodies
The LKB1 mutant lung adenocarcinoma cell lines (A549 and H157), the LKB1 mutant large cell lung cancer cell line (H460) and 293T cells were purchased from the American Type Culture Collection. A549, H157 and H460 cells were cultured in RPMI-1640 medium and 293T cells were cultured in high glucose DMEM (both from HyClone; GE Healthcare Life Sciences) supplemented with 10% (FBS; Biological Industries). Cells were grown at 37°C in a humidified atmosphere with 5% CO2. Mouse monoclonal antibody against GAPDH (cat. no. sc-166545), mouse monoclonal antibody against FGL1 (cat. no. sc-514057), mouse monoclonal antibody against N-cadherin (CDH2; cat. no. sc-59987, for IHC), mouse monoclonal antibody against vascular endothelial growth factor (VEGF)A (cat.no. sc-152) and mouse monoclonal antibody against LKB1 (cat. no. sc-32245) were purchased from Santa Cruz Biotechnology, Inc. Rabbit monoclonal antibodies against E-cadherin (CDH1; cat. no. 3195s) and vimentin (VIM; cat. no. 5741P) were purchased from Cell Signaling Technology, Inc. Rabbit monoclonal antibody against CDH2 (cat. no. ab76011; used for western blotting) was purchased from Abcam.
Construction of the LKB1 cell line
HEK293T cells were transfected with virus packaging plasmid (psPAX2; Addgene, Inc.; cat. no. 12260; pMD2.G, Addgene, Inc.; cat. no. 12259) and pLenti-EF1a-mcherry-P2A-Puro-CMV-MCS-3Flag (control) or pLenti-EF1a-mcherry-P2A-Puro-CMV-LKB1 [encoding the wild-type LKB1 protein; made by OBiO Technology (Shanghai) Corp., Ltd.] stable plasmids using transfection reagent (jetPRIME® in vitro DNA and siRNA transfection reagent; Polyplus-transfection® SA). After the HEK293T cells were transfected for 48 h, the supernatant was collected and added to infect A549 cells for 24 h. A549 cells were then subjected to puromycin selection (4 ng/μl) for 1 to 2 weeks, and puromycin-resistant stable clones were collected. Expression of LKB1 in the established stably transfected A549 cells was validated via western blotting.
Small interfering RNA (siRNA)
Transfection was performed using transfection reagent (jetPRIME® in vitro DNA and siRNA transfection reagent; Polyplus-transfection® SA). Cells in 6-well plates were grown to ~50% confluence, then the media was replaced with fresh complete culture medium prior to transfection. Cells were then transfected with four different FGL1-targeting sequences (50 nM) (TranSheepBio), following the manufacturer's instructions. The sequences of the siRNAs are as follows: Negative Control, sense, 5′-UUCUCCGAACGUGUCACGUdTdT-3′ and antisense, 5′-ACGUGACACGUUCGGAGAAdTdT-3′; FGL1-1, sence, 5′-GAAGUCCAGUUCCUUGAUAdTdT-3′ and antisense, 5′-UAUCAAGGAACUGGACUUCdTdT-3′; FGL1-2, sense, 5′-GCCGUUAUGCACAAUAUAAdTdT-3′ and antisense, 5′-UUAUAUUGUGCAUAACGGCdTdT-3′; FGL1-3, 5′-CUAGUCACCAAAGAAUGAAdTdT-3′ and antisense, 5′-UUCAUUCUUUGGUGACUAGdTdT-3′; FGL1-4, sense, 5′-GGGCUAGUCACCAAAGAAUdTdT-3′ and antisense, 5′-AUUCUUUGGUGACUAGCCCdTdT-3′. The transfected cells were incubated for 24 h, then the medium was replaced with complete medium. A 48 h post-transfection, the cells were divided into two dishes, to avoid overconfluency. At 72 h post-transfection, the efficiency of the siRNAs was examined by reverse transcription-quantitative PCR (RT-qPCR), and the most effective siRNAs were used for subsequent functional experiments.
RT-qPCR
RNAiso Plus (Takara Bio, Inc.) was used to lyse the cultured cells and extracted and amplified the RNA from the cells using a cellular RNA extraction kit (PrimeScript™ RT reagent Kit with gDNA Eraser). The genomic DNA removal reaction and the RNA RT reaction were performed in accordance with the instruction of the cellular RNA extraction kit. mRNA expression was examined via RT-qPCR with the LightCycler 480 Real-time PCR System, using SYBR Premix Dimer Eraser (Takara Bio, Inc.) reagent in a 20 μl reaction volume. Cycling conditions for qPCR were as follows: Denaturation, 95°C for 30 sec (1 cycle); PCR, 95°C for 5 sec, 55°C for 30 sec, 72°C for 30 sec (40 cycles); melting, 95°C for 5 sec, 60°C for 1 min, 95°C (1 cycle); cooling, 50°C for 30 sec (1 cycle). The qPCR primers were designed using Primer3 (primer3.ut.ee/). Primer sequences are listed in Table I. Each sample was repeated in triplicate and normalized to 18S ribosomal RNA expression. The results were evaluated using the comparative threshold cycle value method (2−ΔΔCq) (19) for relative quantification of gene expression.
Colony formation assay
After transfecting cells with FGL1 siRNAs for 48 h, the cells were suspended with pancreatin (0.25% Trypsin-EDTA 1X; Gibco; Thermo Fisher Scientific, Inc.) and plated in 60 mm dishes (1,000 cells/dish) containing 5 ml of culture medium. The dishes were maintained at 37°C with 5% CO2 and saturated humidity for 7-14 days. The cultivation was terminated when macroscopic colonies appeared in the dishes. After removing the supernatant, the colonies were carefully washed with phosphate-buffered saline (PBS). The cells were then fixed with 4% paraformaldehyde for 30 min (25°C) and stained with 0.1% crystal violet for 30 min (25°C). Finally, the excess dye was washed with running water, and the cells were observed using an optical microscope (×40 and ×100; Leica Microsystems Gmbh). Images of the clone formation were obtained by scanning the cell culture dishes.
Wound healing assay
A wound healing assay was performed to investigate the effect of FGL1 on A549 cell migration. Cell suspensions were prepared and seeded into a 6-well plate with ~5×105 cells/well. After culturing for 24 h, the wounds were induced with a 100-μl micropipette tip. Then, the complete RPMI-1640/10% FBS medium was changed to RPMI-1640 medium with 1% FBS. The wound widths were photographed using an optical light microscope (Leica Microsystems GmbH) at 0, 6, 12, 24, 36 and 48 h post-scratching.
Immunofluorescence analysis
Cells were grown on slides for 24 h to 50% confluence. The medium was aspirated and washed twice with PBS. Cells were fixed in 4% formaldehyde for 10 min (25°C), then washed two or three times with PBS. Permeabilization treatment with 0.5% Triton X-100 was applied for 5 min, then cells were washed two or three times with PBS. Tetramethylrhodamine (TRITC)-labeled phalloidin was applied to the cells at room temperature for 30 min in the dark, then washed three times with PBS. Nuclei were counterstained with 200 μl of DAPI solution (100 nM), washed and covered with PBS, and observed under a fluorescence microscope.
Western blot analysis
Cells were lysed in lysis buffer and the protein concentration was determined via the bicinchoninic acid protein assay. Equal amounts of protein (15 μg protein per lane in the gel) from each cell lysate were subjected to SDS-PAGE (upper layer of gel 5% concentration; lower layer of gel 10% concentration) and transferred onto polyvinylidene difluoride membranes. The membranes were blocked in 5% bovine serum albumin for 1 h at room temperature and then probed with primary antibodies against LKB1 (dilution 1:2,000), GAPDH (dilution 1:1,500), CDH1 (dilution 1:1,000), CDH2 (dilution 1:5,000) or VIM (dilution 1:1,000) in Tris-buffered saline containing 0.2% Tween-20 and 5% fat-free dry milk overnight at 4°C. After washing, the membrane was incubated with horseradish peroxidase-conjugated secondary antibodies (dilution 1:10,000; cat. no. ZB-2305 for goat anti-mouse; cat. no. ZB-2301 for goat anti-rabbit) (both from OriGene Technologies, Inc.) for 1 h at room temperature. Immunoreactive bands were visualized using enhanced chemiluminescence detection reagent (WesternBright™ ECL; cat. no. 180805-33; Advansta, Inc.), as per the manufacturer's instructions.
Immunohistochemistry (IHC) staining
Tissue sections (4 μm thick) were cut from formalin-fixed (10% formalin-fixed at 25°C for 24h) paraffin blocks, and used for IHC staining. Anti-LKB1, anti-FGL1, anti-CDH2 and anti-VEGFA (all dilution 1:200; Santa Cruz Biotechnology, Inc.) were used as the primary antibodies. Sections were dewaxed and subjected to antigen retrieval (high pressure method for 3 min in saline sodium citrate), then incubated with 3% H2O2 for 30 min at 25°C to quench endogenous peroxidase activity. Subsequently, 7% goat serum (OriGene Technologies, Inc.; cat. no. SPN-9001 for goat anti-rabbit kit; cat. no. SPN-9002 for goat anti-mouse kit) was used to block cross-reactivity at 25°C for 30 min. Biotin-labelled antibody (1:200; OriGene Technologies, Inc.; cat. no. SPN-9001 for goat anti-rabbit kit; cat. no. SPN-9002 for goat anti-mouse kit), streptavidin-biotin complex (OriGene Technologies, Inc.; cat. no. SPN-9001 for goat anti-rabbit kit; cat. no. SPN-9002 for goat anti-mouse kit) and diaminobenzidine (DAB) were added to the samples after the primary antibodies and incubated at 4°C overnight. The same steps were used for the control group, except the primary antibody was substituted with PBS. After dyeing, two observers selected five fields (×400) randomly and scored these specimens according to the intensity of dyed color. The intensity of staining was graded as: 0, no color; 1, light yellow; 2, light brown; 3, deep brown. Each observer's scores of five view fields were averaged, and the two observers' scores were also averaged. Scores 0-1 were defined as low expression, and score ≥2 were defined as high expression.
GSEA
GSEA was used to explore selected gene functions. Using the TCGA database, lung adenocarcinoma information on 592 patients were acquired for GSEA analysis. GSEA software (20,21) provides scores based on gene expression and acquired pathways associated with gene function. The presents study used two gene set databases, c5.all.v6.2.symbols. gmt (gene ontology gene sets) and c2.cp.kegg.v6.2.symbols. gmt [curated gene sets, gene sets derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database], to analyze the target genes using GSEA 3.0.
Statistical analysis
Data were analyzed using GraphPad Prism 7 (GraphPad Software, Inc.) and three independent experiments were performed. The data are presented as the mean ± standard deviation. Comparison between two sets of data was performed using unpaired Student's t-test. One-way ANOVA, followed by Dunnett's multiple comparisons test, was used for statistical analysis of >2 groups. All P-values were two-sided and P<0.05 was considered to indicate a statistically significant difference.
Results
mRNA expression profiling
Gene expression information from 230 patients (including 43 LKB1 mutant patients and 187 LKB1 wild-type patients) with lung adenocarcinoma was obtained using TCGA. Next, a differential gene expression analysis was conducted between the LKB1 mutant and wild-type groups using R software. The results revealed 2,369 and 165 differentially expressed genes using the edgeR and DESeq packages, respectively. Of these, 161 genes were intersected in both the edgeR and DESeq analyses (Fig. 2A). A volcano plot was constructed using the gene information from the DESeq package (Fig. 2B). The red points indicate the significantly differentially expressed genes, using the criteria of |logFC|>1 and FDR<0.05. Next, two GEO databases (GSE72094 and GSE75037) of patients with lung adenocarcinoma were used to further validate the differentially expressed genes using the limma package in R software. The results revealed 84 and 218 significantly differentially expressed genes for the GSE72094 and GSE75037 databases, respectively. Finally, by comparing the TCGA and GEO database results, 11 genes were identified to be significantly differentially expressed in all the aforementioned analyses (Fig. 2C). Fig. 1 illustrates the flow-chart for the study design. Table II lists the detailed gene expression information for these 11 genes. A heat map was constructed using the expression information for these 11 genes (Fig. 2D). To better analyze the differential expression data for these genes, scatter plots were created using GraphPad Prism 7 (Fig. 2E).
Gene expression validation
A stably transfected A549 cell line overexpressing wild-type LKB1 was constructed and confirmed via western blot analysis (Fig. 2F). The results demonstrated that the A549 cells transfected with the wild-type LKB1 plasmid had markedly higher wild-type LKB1 protein expression levels compared with cells transfected with empty vector. Next, the expression levels of the 11 significantly differentially expressed genes were examined by RT-qPCR in A549 cells transfected with wild-type LKB1 plasmid and cells transfected with empty vector. FGL1 was selected as the research object for subsequent experiments. RT-qPCR results indicated that FGL1 mRNA expression levels were significantly decreased in A549 cells transfected with LKB1 plasmid compared with cells transfected with empty vector (P<0.0001; Fig. 2G). FGL1 expression was also verified in using Gene Expression Profiling Interactive Analysis (gepia. cancer-pku.cn/index.html), which is a visualization website for TCGA data that provides differential expression analysis of genes between tumor and normal patients (Fig. 2H). Lung adenocarcinoma patients had high FGL1 expression (Fig. 2H; denoted in red).
Cell proliferation
The present study used four different FGL1-targeting sequences to interfere with FGL1 expression in A549 cells, and their efficiency was evaluated by RT-qPCR (Fig. 3A). The silencing efficiency of the four siRNAs was very high. A549 cells transfected with the FGL1-targeting siRNAs were used in the colony formation assay. Following FGL1 silencing, the cell growth rate was significantly increased (Fig. 3B and C).
EMT
The effect of FGL1 on cell migration was assessed using a wound healing assay. The scratch area of the FGL1-silenced A549 cells was significantly reduced compared with the control A549 cells 48 h post-scratching (Fig. 3D and E), indicating that FGL1 inhibited cell migration. Immunofluorescence staining of the actin filaments with phalloidin was used to observe changes in cell morphology following FGL1 knockdown (Fig. 3F). The cells became long and fusiform-shaped with more angular edges, indicating that the cells had undergone EMT changes. The protein expression levels of FGL1 were further confirmed via western blot analysis in LKB1 mutant lung adenocarcinoma cells (A549 and H157) and LKB1 mutant large cell lung cancer cells (H460); the results demonstrated that transfection with the control siRNA had no effect on FGL1 protein levels, while transfection with the FGL1-targting siRNA (FGL1-3) markedly reduced its protein expression levels (Fig. 3G). The protein expression levels of EMT-associated markers were then evaluated via western blotting in LKB1 mutant lung adenocarcinoma cells (A549 and H157) and LKB1 mutant large cell lung cancer cells (H460; Fig. 3H). CDH1 expression was lower, while CDH2 and VIM expressions were higher following FGL1 silencing in LKB1 mutant lung adenocarcinoma cells (Fig. 3H). However, CDH1 and VIM expression did not noticeably differ following FGL1 silencing in LKB1 mutant large cell lung cancer cells (Fig. 3H). RT-qPCR was also used to detect the mRNA expression levels of EMT-associated markers in the LKB1 mutant lung adenocarcinoma A549 cells and similar results to those of the western blot analysis were observed (Fig. 3I). These results indicated that FGL1 silencing promoted EMT, and that intrinsic FGL1 expression may inhibit EMT occurrence in LKB1 mutant lung adenocarcinoma.
Angiogenesis
RT-qPCR was used to detect expression changes in angiogenesis-related markers in FGL1-silenced A549 cells. The results revealed higher mRNA expression levels following FGL1 silencing for the angiogenesis-associated markers VEGFA, VEGFB, hypoxia-inducible factor (HIF)1α, insulin-like growth factor-1 (IGF-1) and epidermal growth factor receptor (EGFR), compared with A549 control cells (Fig. 3J). These results suggested that FGL1 silencing promoted angiogenesis in LKB1 mutant lung adenocarcinoma cells.
IHC analysis
Lung cancer tissue samples from 30 patients with lung adenocarcinoma were used for IHC analysis for LKB1 expression (Fig. 4A). Then, the patients that exhibited low LKB1 expression in their lung cancer tissues were selected and grouped by FGL1 expression levels (Fig. 4B). IHC was used to stain for the EMT-associated indicator, CDH2, and the angiogenesis-related indicator, VEGFA, separately in the low and high FGL1 expression groups (Fig. 4B). CDH2 and VEGFA were highly expressed in the low FGL1 expression group, indicating that low FGL1 expression promoted EMT and angiogenesis in LKB1-low lung adenocarcinoma tissue samples.
Gene function enrichment analysis
GSEA was used to further explore the gene function of FGL1 (Fig. 5). Using the TCGA database, lung adenocarcinoma information from 592 patients was acquired. These patients were ranked according to the expression level of FGL1, and the 200 patients with the lowest and highest FGL1 expression were selected. Then these 200 patients were divided into two groups according to FGL1 expression for GSEA analysis. Signaling pathways, such as 'regulation of epithelial cell migration', 'cell adhesion molecules' and 'epithelial cell development', that are associated with EMT, were enriched in the low FGL1 expression group based on the analysis results from both GO and the KEGG (Fig. 5A-F); this further suggested that low FGL1 expression promoted EMT in lung adenocarcinoma patients. The angiogenesis-associated GO signaling pathway 'positive regulation of vasculature development' was also enriched in the low FGL1 expression group (Fig. 5G), indicating that low FGL1 expression promoted angiogenesis in lung adenocarcinoma patients. Finally, two cell growth-associated GO signaling pathways were enriched in the low FGL1 expression group (Fig. 5H and I), indicating that low FGL1 expression promoted cell growth.
Discussion
Although many treatment modalities exist for lung adenocarcinoma, such as surgery (22), radiotherapy (23), chemotherapy (24) and targeted treatment (25), the 5-year survival rate is very low due to late diagnoses and recurrence (26). Many studies are associated with targeted gene treatment, and genes are continually being reported as biomarkers for diagnosis, prognosis and treatment of lung cancer patients (27-29). Zer et al (27) analyzed Kras mutations and concluded that Kras mutant subtypes were not homogeneous in their prognostic and predictive effects. Qiu et al (28) reported that microRNA-499 could be a useful biomarker for predicting poor prognosis for patients with lung cancer. Tang et al (29) conducted a large-scale meta-analysis to evaluate published gene expression prognosis signatures for biomarker-based clinical studies on lung cancer. However, few biomarkers are associated with LKB1 mutant adenocarcinoma. The present study focused on LKB1 mutant adenocarcinoma to discover effective diagnostic, prognostic and therapeutic indicators for these patients. Bioinformatics data mining and experimental verification revealed that FGL1 was significantly highly expressed in LKB1 mutant lung adenocarcinoma; thus, the functional role of FGL1 in LKB1 mutant lung adenocarcinoma was explored.
LKB1 encodes a serine/threonine kinase that directly activates AMPK to regulate lipid, cholesterol and glucose metabolism (30). LKB1 has a high mutation rate in lung adenocarcinoma (31,32), and many studies have examined the role of LKB1 mutation in lung adenocarcinoma. Calles et al (33) reported that loss of LKB1 was a biomarker for more aggressive biology in Kras-mutant lung adenocarcinoma. Gao et al (34) examined the occurrence of LKB1 mutation with EGFR and Kras mutation and demonstrated that Kras and LKB1 had very high co-mutation frequencies. Shackelford et al (35) verified an association between LKB1 mutation and the therapeutic response to the metabolic drug phenformin; phenformin may act as a cancer metabolism-based therapeutic drug to selectively target LKB1-deficient tumors. These previous studies indicated that LKB1 may have an important role in lung adenocarcinoma; therefore, the present study focused on exploring differential gene expression associated with the LKB1 mutation in lung adenocarcinoma and FGL1 was identified.
Gene expression information of patients with lung adeno-carcinoma was downloaded from TCGA and GEO, analyzed and validated by experimentation. FGL1 was significantly highly expressed in LKB1 mutant lung adenocarcinoma; thus, it was evaluated whether FGL1 may be closely associated with LKB1. FGL1 is mainly expressed in the liver and is a secreted protein with mitogenic activity on primary hepato-cytes. Demchev et al (36) postulated that FGL1 might have key roles in metabolism and liver regeneration. Zou et al (37) indicated that bone marrow-derived mesenchymal stem cells attenuated acute liver injury by regulating FGL1 expression. Nayeb-Hashemi et al (14) demonstrated that loss of FGL1 accelerated hepatocellular carcinoma development. To the best of our knowledge, the only study focusing on FGL1 in lung cancer was conducted by Wang et al (38), who reported that FGL1 might be a critical EMT effector involved in cellular adhesion and communication. The present results further confirmed that loss of FGL1 was closely associated with EMT in LKB1 mutant adenocarcinoma.
The present study concluded that loss of FGL1 promoted cell growth, the EMT process and angiogenesis in LKB1 mutant lung adenocarcinoma by functional experiments and GSEA analysis. Çeliktas et al (39) indicated that LKB1 mutation was closely associated with cell growth, metabolism and prognosis in lung adenocarcinoma. Okon et al (40) concluded that LKB1 inhibited angiogenesis by promoting RAB7-mediated neuropilin-1 degradation. Roy et al (41) verified that LKB1 inactivation triggered EMT in lung cancer cells by inducing zinc finger E box binding homeobox 1. These studies were consistent with our findings and provided support for our research.
The present study is the first to link LKB1 and FGL1 and to demonstrate that loss of FGL1 induced EMT and angiogenesis in LKB1 mutant lung adenocarcinoma. Two databases, TCGA and GEO, were used for data mining and FGL1 was identified by gene expression analysis. We combined this information with functional experiments in cell lines in vitro to validate our findings. However, the present study had several limitations. First, our verified experiments were not comprehensive and could not fully explain our conclusion. Second, the present only used two lung adenocarcinoma cell lines (A549 and H157) and one large cell lung cancer cell line (H460) to conduct experiments in vitro and no in vivo experiments were conducted. Furthermore, the exact mechanism by which LKB1 overexpression represses FGL1 expression remains unclear. Overexpression of LKB1 can inhibit anabolism through the AMPK signaling pathway, promotes catabolism, and maintains energy homeostasis in high metabolic cells (such as A549) (42). During this process, since anabolism is inhibited, it may result in a decrease in FGL1 synthesis, resulting in a decrease in the FGL1 expression levels. The exact mechanism needs further experimental verification. Studies on FGL1 are rare, especially in lung cancer. Therefore, the detailed functions of FGL1 require further study.
The present study aimed to explore novel biomarkers in LKB1 mutant lung adenocarcinoma. By data mining of TCGA and GEO databases and in vitro functional experiments, the current results demonstrated that loss of FGL1 induced EMT and angiogenesis in LKB1 mutant lung adenocarcinoma. FGL1 may therefore serve as a new biomarker for indicating EMT and angiogenesis in patients with LKB1 mutant lung adenocarcinoma.
Funding
This study was supported by the National Science Foundation of China (grant nos. 81602009 and 81672288) and The Joint Research Funds for Shandong University and Karolinska Institute (grant no. SDU-KI-2019-16).
Availability of data and materials
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Authors' contributions
FB, GW and JD designed the experiments. FB, GW, XQ and YW collected and processed the data. CH and YW wrote and polished article. All of the authors read and approved the final manuscript.
Ethics approval and consent to participate
The Ethics Committee of Shandong Provincial Hospital Affiliated to Shandong University approved all experimental protocols involving the use of human tissues. Informed consent was obtained from all participants included in the study.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Acknowledgments
Not applicable.
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