Inhibition of proteinase-activated receptor 2 (PAR2) decreased the malignant progression of lung cancer cells and increased the sensitivity to chemotherapy

The Normal human lung epithelial cells BEAS-2B and lung cancer cell lines H460, A549 and NCI-H1299 were purchased from American Type Culture Collection (ATCC, Manassas, VA, USA) and cultured in RPMI 1640 supplemented with 10% fetal bovine serum (FBS). The culture was placed in an incubator at 37 ℃ and 5% CO₂. When the bottom of the culture flask was 70–80% full of cells, digestion and passage were performed. Cells in the logarithmic growth phase were used for subsequent experiments.

Firstly, the siRNA and transfection reagent were prepared. The siRNA used was specifically designed for targeted silencing of PAR2. The sequences for the siRNA non-targeting control were as follows: forward: 5’-GCGACGAUCUGCCUAAGAUdTdT-3’, reverse: 5’-AUCUUAGGCAGAUCGUCGCdTdT-3’. For the siRNA targeting PAR2: si-PAR2#1: the sequence was 5ʹ-AAUGGCAUGGCCCUCUGGAUC (dTdT)-3ʹ. si-PAR2#2: the sequence was 5’-GCUCUGCAAGGUGCUCAUUGGCUUU-3’. For the transfection process, 100 μL of Opti-MEM was used as a medium. To this, the siRNA and transfection reagent were added. The mixture was gently pipetted to ensure a homogeneous distribution of the siRNA and transfection reagent within the Opti-MEM. Once the siRNA and transfection reagent were thoroughly mixed into the Opti-MEM, the mixture was allowed to stand for 10 min. This incubation period is crucial as it allows the formation of siRNA-lipid complexes, which are necessary for efficient transfection. Following the 10-min incubation, the siRNA-transfection reagent mixture was added dropwise to a 6-well plate containing the cells. Care was taken to distribute the drops evenly across the well to ensure uniform transfection. The cells were then cultured in a 10% FBS medium. The culture was placed in an incubator set at 37 ℃ and 5% CO₂. These conditions were maintained to ensure optimal cell growth and siRNA uptake. The cells were monitored regularly to assess the transfection efficiency and to ensure that the cells were not undergoing any adverse effects due to the transfection process. Since the transfection efficiency of the two siRNA was different, and si-PAR2#2 could not completely silence the expression level of PAR2 effectively, we selected si-PAR2#1 with high knockout efficiency for the subsequent experiment (Figure S1).

CancerSEA is a multi-functional website aimed at comprehensively exploring the different functional states of cancer cells at the single-cell level [7, 23]. In this study, CancerSEA was used to investigate the correlation between different functional states of the PAR2 gene and lung cancer. An average association was observed between PAR2 and different functional states of lung cancer, including invasion, metastasis, proliferation, and EMT.

In this study, the Human Protein Atlas [24, 25] was used to analyze the expression level of PAR2 in normal lung tissues and lung cancer tissues. The correlation between different expression levels of PAR2 and prognosis of patients with lung cancer was analyzed.

Total RNA was extracted using the RNA extraction kit in accordance with the manufacturer’s instructions. It was then reverse-transcribed into cDNA using a reverse transcription kit. Fluorescence quantitative PCR was performed using Roche’s SYBR Green Master Mix. The Q-PCR reaction system was as follows (20 μL): 10 μL of SYBR qPCR Mix, 0.8 μL each of qPCR upstream and downstream primers (10 μmol/L), 2 μL of cDNA, 0.4 μL of 50 × Rox reference dye, and de-RNase water until 20 μL. Primers were synthesized by Sangon Biotech Co., Ltd. The sequences are displayed in Table 1. The reaction system on the machine detection was as follows: pre-denaturation at 95 ℃ for 1 min, followed by 95 ℃ for 30 s, 60 ℃ for 40 s, 40 cycles. All samples were tested three times with three parallel holes. Gene transcription level was corrected by GAPDH by using the 2^−ΔΔCT method.

Cells in the logarithmic growth phase were collected. Cells at a density of 3 × 103 cells per well were inoculated into 96-well plates. After culture for 12 h, the supernatant was discarded. Melittin (1, 2, 4 mg/L) and 200 μL of gefitinib medium (1 μmol/L) were added to each well CCCCC [26‐28]. Then, 20 μL of MTT (5 mg/mL) was added to each well after 48 h in the incubator. The cells were cultured at 37 ℃ for 4 h and then added with 150 μL of DMSO. Before detection, the cells were shaken and mixed gently, and the enzyme-linked detector was used to detect the optical density value of each hole at the wavelength of 490 nm (D(450)). The cell proliferation inhibition rate was calculated according to the following formula: Inhibition rate of cell proliferation = ((optical density value of control group-optical density value of drug treatment group)/ optical density value of control group) × 100. The experiment was repeated three times.

Matrigel (serum-free medium) was diluted to the desired concentration by adding 30 μL of each Transwell chamber and allowed to set. Serum-free 1640 medium was used to adjust the cell concentration to 2 × 105 cells/mL. The upper and lower compartments of the Transwell chamber were added with 200 μL of cell suspension and 600 μL of RPMI 1640 containing 10% serum, respectively. The Transwell chambers were incubated for 48 h. Unmigrated cells on the membrane were gently wiped off using a cotton swab. The filter membrane was fixed with methanol for 30 min. The cells were stained with 0.1% crystal violet solution for 20 min. The number of cells crossing the membrane was counted and compared under a microscope. The total number of cells was counted in five fields of vision, namely, upper, lower, left, right, and middle, and averaged.

Cells in the logarithmic growth phase were inoculated into a 6-well plate at a cell density of 2 × 103 cells/well. After 24 h of culture, RPMI 1640 medium containing 1% FBS was replaced. Then, melittin or gefitinib was added in different concentrations. After 3 days of drug intervention, RPMI 1640 medium containing 10% FBS was replaced for further culture for 10 days. At the end of the experiment, the cells were washed once with phosphate-buffered saline. The samples were fixed with 0.5% crystal violet (prepared with 10% methanol) and stained for 15 min. The number of clones formed by the cells was recorded.

Cells in each group were lysed with RIPA lysate (1 mL RIPA + 10μL PMSF + 10μL aprotinin) for 30 min and operated on ice. Protein concentration was measured by BCA method, and loading buffer was added to denatured protein. Prepare 10% SDS-PAGE and add 20 μg protein sample to each well. Use wet transfer to transfer to PVDF membrane. 5% skimmed milk powder was closed for 2 h. Primary antibody of PAR2 (ab180953, Abcam, Cambridge, MA, USA), Oct4 (ab200834), SOX2 (ab171380), Nanog (ab109250), Snail1 (ab31787), Slug (ab51772)), Twist1 (ab50887)), E-cadherin (ab40772), Vimentin (ab92547) was diluted at 1: 1000 TBST at 4 ℃ overnight. The 1: 5000 diluted secondary antibody was added and incubated for 2 h at room temperature. ECL luminescence kit was developed and analyzed after fixing.

Statistical analysis was performed using SPSS 17.0 statistical software. Measurement data were expressed as mean ± standard deviation. Student’s t-test was used for comparison between the two groups. One-way ANOVA followed by Tukey’s post-hoc test was used for multi-component comparison. Statistical significance was considered at P < 0.05.

Single-cell sequencing analysis can solve tumor heterogeneity, improve the accuracy of experimental data analysis, and provide valuable help for the diagnosis, detection, and treatment of diseases. This study first analyzed the correlation between PAR2 and functional properties of lung cancer through the CancerSEA website. Correlation analysis results of PAR2 in multiple functional states of lung cancer showed that PAR2 expression was positively correlated with the metastasis, EMT, invasion, and proliferation of cells (Fig. 1A). The developmental process that PAR2 may participate in was analyzed. The scatter plot of T-SEN functional analysis describes the distribution of cells, with each dot representing a cell and the color of the dot representing the expression of the gene in the cell. T-SEN analysis showed that the low expression of PAR2 in lung cancer cells clumped together. At the same time, the highly PAR2-expressing cell population clumped together (Fig. 1B). Survival analysis showed that PAR2 expression was associated with a poor prognosis of lung cancer. Patients with high PAR2 expression had a short survival time (Fig. 1C). These results suggest that high expression of PAR2 in patients with lung cancer indicates a poor prognosis. Thus, it may be used as a prognostic indicator in patients with lung cancer. Furthermore, the differences in the expression levels of PAR2 in lung tissues and lung cancer tissues were analyzed through The Human Protein Atlas website. Immunohistochemical test results showed that the expression of PAR2 was significantly higher in lung cancer tissue than in normal lung tissue (Figs. 1D, E).

Bioinformatics data analysis revealed that PAR2 plays a role in lung cancer. We further analyzed the co-expression correlation between PAR2 and EMT genes. As shown in Fig. 2A, PAR2 was co-positively correlated with the mesenchymal marker vimentin. Further detection revealed that the expression level of PAR2 was co-positively correlated with transcription factors Twist1 and SNAI2 (Figs. 2B, C).

The expression of PAR2 was higher in A549 and NCI-H1299 cells than in normal lung epithelial cells (Fig. 3A). Therefore, we selected A549 and NCI-H1299 lung cancer cell lines for subsequent studies. To further verify the role of PAR2, we knocked down the expression of PAR2 in A549 and NCI-H1299 cells. Verification results of transfection efficiency showed that siRNA PAR2 could effectively reduce the expression of PAR2. The knockdown efficiency of the siRNA in A549 was 87.2%. The knockdown efficiency of the siRNA in NCI-H1299 was 83.8% (Fig. 3B). We designed two siRNAs (si-PAR2#1, si-PAR2#2). Subsequently, we detected the effects of PAR2 knockdown on the expression levels of stem cell markers OCT4, SOX2, and Nanog. qRT-PCR results showed that PAR2 knockdown decreased the expression levels of OCT4, SOX2, and Nanog (Figs. 3C–E). It also decreased the expression levels of Snail1, Slug, and Twist1 in A549 and NCI-H1299 cells (Figs. 3F–H). Further results showed that PAR2 knockdown upregulated the expression of epithelial marker E-cadherin while decreased the expression of mesenchymal marker vimentin (Figs. 3I, J). The results of western blot were consistent with those of PCR (Fig. 3K). After silencing PAR2, tumor-related proteins expression was inhibited.

The expression of PAR2 was knocked down in lung cancer A549 and NCI-H1299 cells, and the changes in proliferation, invasion, and clone formation were detected. MTT results showed that the proliferation rate of both PAR2 knockdown cells significantly decreased compared with the control group (Figs. 4A, B). Transwell experiment results showed that the invasion of the siPAR2-transfected cells significantly decreased compared with that of the siNC group (Figs. 4C, D). The results of the clone formation experiment showed that the clone formation of the siPAR2-transfected cells significantly decreased compared with that of the SINC group (Figs. 4E, F). These results indicate that the low expression of PAR2 in lung cancer can inhibit the proliferation, invasion, and clone formation of cells. We further supplemented the effect of silencing PAR2 on apoptosis through TUNEL assay. TUNEL results showed that apoptosis rates of A549 and NCI-H1299 cells were significantly up-regulated after PAR2 silenced (P < 0.01). The experimental results are supplemented in Figs. 4G, H.

MTT assay was used to investigate the effect of PAR2 knockdown and gefitinib alone or in combination on the survival rate of lung cancer cells. Results showed that either PAR2 knockdown alone or gefitinib treatment reduced the survival rate of lung cancer cells. PAR2 knockdown increased further gefitinib inhibition (Fig. 5A). Transwell was used to evaluate the invasiveness of cells. Either PAR2 knockdown alone or gefitinib treatment reduced the invasion of lung cancer cells. PAR2 knockdown further increased the inhibitory effect of gefitinib (Fig. 5B). The inhibitory effect of PAR2 knockdown and gefitinib on the colony formation of NSCLC cells was tested by colony formation assay. Results showed that either PAR2 knockdown alone or gefitinib treatment reduced the ability of lung cancer cells to form clones. PAR2 knockdown further increased the inhibitory effect of gefitinib (Fig. 5C). When PAR2 was knocked down and combined with gefitinib, E-cadherin expression was upregulated (Fig. 5D), but vimentin expression was inhibited (Fig. 5E). PAR2 knockdown alone or treatment with gefitinib decreased MMP2 and MMP9 expression in lung cancer cells. However, PAR2 knockdown further increased the inhibitory effect of gefitinib (Figs. 5F–G).

MTT assay, Transwell assay, and colony formation assay were used to detect the effects of melittin on the proliferation, invasion, and colony formation of lung cancer cells. Results showed that melittin inhibited the proliferation, invasion, and colony formation of lung cancer cells in a dose-dependent manner (Figs. 6A–C). Melittin inhibited the expression of PAR2 in a dose-dependent manner (Fig. 6D). EMT marker detection results showed that melittin could dose-dependently upregulate the expression of E-cadherin and inhibit the expression of vimentin (Figs. 6E, F).

MTT assay was used to analyze the effect of melittin and gefitinib on the survival rate of lung cancer cell lines. Results showed that melittin alone or gefitinib treatment reduced the survival rate of lung cancer cells. Melittin increased the inhibitory effect of gefitinib (Fig. 7A). Transwell results showed that melittin alone or gefitinib treatment reduced the invasion of lung cancer cells. Melittin further increased the inhibitory effect of gefitinib (Fig. 7B). Colony formation experiments showed that melittin alone or gefitinib treatment reduced the colony formation of lung cancer cells. Melittin further increased the inhibitory effect of gefitinib (Fig. 7C). When melittin was combined with gefitinib, E-cadherin expression was upregulated (Fig. 7D), but vimentin expression was inhibited (Fig. 7E).