FGFR4 Inhibitor BLU9931 Attenuates Pancreatic Cancer Cell Proliferation and Invasion While Inducing Senescence: Evidence for Senolytic Therapy Potential in Pancreatic Cancer

2.1. Expression of FGFR4 in Human PDAC Tissues and PDAC Cell Lines

To examine the expression of FGFR4 in human PDAC tissues, we performed immunohistochemical analysis of FGFR4 using pancreas tissue microarrays. In normal human pancreatic tissues, FGFR4 was weakly localized in normal exocrine and endocrine pancreatic tissues (Figure 1(A-I)). FGFR4 was observed in the cytoplasm and cell membrane of human PDAC cells (Figure 1(A-II) and Figure S1). Strong FGFR4 immunoreactivity was seen in the cancer cells in 67 of 136 (49%) PDAC samples and high FGFR4 expression correlated with larger primary tumor size and more advanced stages of the cancer (p < 0.001, Table 1).

FGFR4 mRNA was expressed in all eight PDAC cell lines examined (Figure 1B). FGFR4 mRNA was highest in T3M-4 and MIA PaCa-2 cells and lowest in PK-45P cells. By contrast, FGFR4 protein levels were highest in PK-1 and T3M-4 cells and lowest in MIA PaCa-2 and PK-45P cells (Figure 1C). Fluorescence-activated cell sorting revealed that cell surface FGFR4 levels were highest in PK-1 and T3M-4 cells (Figure 1D,E). Given that SNP Arg388 of the FGFR4 gene may be associated with decreased survival in certain cancers, we next examined this SNP in the above cell lines, which genotyped as follows: MIA PaCa-2 and PK-8 cells as Gly/Gly; PK-1, PANC-1, and PK-45P cells as Gly/Arg; and PK-59, T3M-4, and KP4 cells as Arg/Arg (Figure S2 and Table 2). Inasmuch as FGF19 is the specific and sole ligand for FGFR4, we next performed real-time quantitative PCR (qPCR) for this ligand. FGF19 mRNA levels were relatively elevated in PK-1, PK-45P, and T3M-4 cells, and lowest in other cell lines (Figure 1F).

The FGF19 gene is occasionally amplified in hepatocellular carcinomas and breast cancer as a consequence of the presence of an amplicon on chromosome 11q13.3 [37,38]. PDAC also exhibits regions of genomic amplification, including the 11q13.3 region in chromosome 11 [39]. To determine whether such an amplicon harbors an FGF19 amplification, we examined gene expression data in The Cancer Genome Atlas (TCGA), a publicly available data base [40,41]. We used the University of Texas Southwestern (UTSW) data set since it was based on high-quality cancer cell-enriched samples [42], which revealed the presence of an amplified FGF19 gene in 11 of the 109 samples in this cohort (Figure 2A). In addition, other genes within this amplicon were also amplified, including FGF4, FGF3, CCND1, RAD9A, RPS6KB2, GAB2, and PAK1 (Figure 2A). In some cases, there was also co-amplification of FGF19 with FGFR4 (Figure 2B), even though the FGFR4 gene is located on chromosome 5q25. Only 7 of the 109 samples exhibited concomitant upregulation of the KLB gene (encoding β-Klotho) and FGFR4 gene (Figure 2B). Only three and two cases exhibited FGFR1 and FGFR2 gene amplification, respectively, whereas seven cases exhibited FGFR3 amplification, including one case that did not have a KRAS mutation. In three patients, there was concomitant overexpression of FGFR3 and FGFR4. Intriguingly, among the eight PDAC cases that did not harbor a KRAS mutation, four cases had either amplification or increased expression of the FGF19, FGF4, FGF3, and CCND1 genes, and six cases had RAD9A and RPS6KB2 gene overexpression, two of which were due to amplification (Figure 2A), raising the possibility that a portion of the 11q13.3 amplicon helps drive PDAC development in the absence of mutated KRAS. Additional real-time qPCR analysis of RNA from the above cell lines for FGF4, FGF3, CCND1, RAD9A, RPS6KB2, GAB2, PAK1, and KLB revealed variable increases in these mRNA moieties in these cells, most notably with respect to RPS6KB2, GAB2, PAK1, and KLB (Figure 2C). Taken together, these results suggest that autocrine/paracrine FGF19/FGFR4 signaling may be functional in PK-1 and T3M-4 cells. Therefore, most subsequent experiments with cell lines were performed using PK-1 and T3M-4 cell lines.

2.2. Effects of BLU9931 on Growth and Cell Cycle of PDAC Cells

To determine whether there was a functional FGF19/FGFR4 signaling axis in human PDAC cells, we cultured PDAC cells with or without the highly specific FGFR4 inhibitor, BLU9931. PK-1 cells exhibited a dose-dependent decrease in proliferation in the presence of BLU9931 (Figure 3A). An inhibitory effect on proliferation was also observed in T3M-4 cells (Figure S3A). By contrast, BLU9931 did no inhibit proliferation in PK-45P cells (Figure 3A), which expressed very low FGFR4 levels (Figure 1). Next, we examined whether BLU9931 exerts toxic effects in PDAC cells. Incubation of PK-1 cells with 2 μM BLU9931 followed by fluorescence activated cell sorter (FACS) analysis using annexin V and propidium iodide (PI) showed that ~2% of the cells underwent apoptosis, necrosis, or cell injury (Figure 3B). Higher concentration (>10 μM) of BLU9931 revealed dead and floating cells suggestive of a toxic effect at these very high concentrations of the drug.

We next examined the effects of BLU9931 on the cell cycle by FACS analysis. There was a higher percentage of BLU9931-treated PK-1 or T3M-4 cells in the G0/G1 phase (70.1% vs. 60.7% and 66.4% vs. 58.0%, respectively) and lower percentage in the S phase (13.5% vs. 20.7% and 27.3% vs. 29.9%, respectively) and G2/M phase (16.4% vs. 18.6% and 6.3% vs. 12.1%, respectively) relative to control cells (Figure 3C and Figure S3B). These results point to a G1 to S phase cell cycle slowdown in BLU9931-treated cells.

Next, we examined the expression of cell cycle related-genes. Real-time qPCR analysis showed that the expression of p21, P27, and E2F1 was upregulated whereas CDK1 expression was downregulated in BLU9931-treated cells (Figure 3D and Figure S3C). We also examined autocrine/paracrine FGF19/FGFR4 signaling by immunoblotting for downstream targets (ERK, AKT, and STAT3). As shown in Figure 3E, reduced phosphorylation of ERK, AKT, and STAT3 was observed in BLU9931-treated PK-1 cells. Similar reductions in phosphorylation in these downstream signaling molecules were observed in T3M-4 cells (Figure S3D). By contrast, phosphorylation of these proteins was not altered by the same concentration of BLU9931 (2 μM) in PK-45P cells. These results indicate that autocrine/paracrine FGF19/FGFR4 signaling is functional in PK-1 and T3M-4 cells but not in PK-45P cells, and that FGFR4 downstream signaling can be inhibited by BLU9931 in certain PDAC cells. Furthermore, BLU9931 reduced FGF19 mRNA levels but not FGFR4 and KLB mRNA levels (Figure 3F and Figure S3E), suggesting that autocrine/paracrine FGF19/FGFR4 signaling upregulates FGF19 expression through the FGF19/FGFR4 signaling feedback loop. Taken together, these results indicate that the inhibitory effect of 2 μM BLU9931 on PDAC cell proliferation is caused by inhibition of autocrine/paracrine FGF19/FGFR4 signaling and not through induction of apoptosis.

2.3. Effects of BLU9931 on Stemness Features of PDAC Cells

To clarify the correlation between autocrine/paracrine FGF19/FGFR4 signaling and stemness in PDAC cells, we examined stemness features, including stemness marker expression, anticancer drug resistance, and sphere-forming ability. Real-time qPCR showed that two of seven examined stemness markers (Sox2 and Nestin) were expressed at lower levels in 2 μM BLU9931-treated PK-1 cells (Figure 4A), whereas one of the seven markers (CD24) was expressed at a higher level in BLU9931-treated PK-1 than in control cells (Figure 4A). These results suggest that autocrine/paracrine FGF19/FGFR4 signaling is not definitively involved in stemness marker expression in PDAC cells. To assess anticancer drug resistance, we used three anti-pancreatic cancer drugs, gemcitabine, 5-FU, and abraxane. Cell survival rates following addition of gemcitabine, 5-FU, and abraxane (all at 100 μM) were approximately 60%, 50%, and 30%, respectively (Figure 4B). However, survival rates were not significantly different in 2 μM BLU9931-treated PK-1 cells following incubation with the above anticancer drugs at either 10 or 100 μM (Figure 4B). Furthermore, we examined the expression levels of four potential anticancer drug transporters. Real-time qPCR analysis revealed that the expression of ABCG2, ABCB1, ABCC1, and ABCC2 was not significantly different between control and 2 μM BLU9931-treated PK-1 cells (Figure 4C). Thus, autocrine/paracrine FGF19/FGFR4 signaling is not involved in regulating the expression of anticancer drug transporters and the resistance toward anticancer drugs in PDAC cells. Next, we examined sphere-forming ability, which is viewed as an indicator of self-renewal and stemness [43,44,45]. Sphere-forming assays showed that the number of spheres was not different between control and 2 μM BLU9931-treated PK-1 cells (Figure 4D). Furthermore, in sphere cells, the expression levels of FGFR4 and FGF19 were markedly lower than those in adherent cells (Figure 4E). Thus, autocrine/paracrine FGF19/FGFR4 signaling is not involved in sphere formation of PDAC cells.

2.4. Effects of BLU9931 on Migration and Invasion of PDAC Cells

We next examined the inhibitory effects of FGF19/FGFR4 signaling on migration and invasion of PDAC cells. In wound healing assays, there were no significant differences in the migration rates between control and BLU9931-treated PK-1 cells (Figure 5A). Furthermore, boyden chamber assays showed that BLU9931 did not alter the migration of PK-1 cells (Figure 5B). Thus, these results indicate that FGF19/FGFR4 signaling does not regulate PDAC cell migration. By contrast, invasion assays showed that numbers of invaded cells were significantly reduced in 2 μM BLU9931-treated PK-1 cells compared with control cells (Figure 5C), indicating that autocrine/paracrine FGF19/FGFR4 signaling promotes invasion. One of key features of invasion is increased production of matrix metalloproteinases (MMPs) [46,47] and MMP2, MMP9, and MT1-MMP are known to be expressed in PDAC cells [48]. Therefore, we hypothesized that FGF19/FGFR4 signaling might promote MMP expression and activity. Real-time qPCR revealed that MT1-MMP mRNA levels were significantly reduced in BLU9931-treated PK-1 cells, while MMP2 mRNA levels were upregulated (Figure 5D). Furthermore, Western blot analysis showed that protein levels of MT1-MMP were significantly reduced in BLU9931-treated PK-1 cells (Figure 5E). MT1-MMP is well known to induce activated MMP2 by proteolytic cleavage of prodomain of proMMP2 [46,47]. Therefore, we next examined the activity of MMP2 released from BLU9931-treated PK-1 cells using gelatin zymography. As shown in Figure 5F, collagenase activity of MMP2 was reduced in BLU9931-treated PK-1 cells. A BLU9931-induced reduction in invasion, MT1-MMP expression, and MMP2 activity was also observed in T3M-4 cells (Figure S4). Thus, autocrine/paracrine FGF19/FGFR4 signaling regulates expression of MT1-MMP and contributes to the activation of MMP2 in PDAC cells.

2.5. Induction of Senescence in PDAC Cells by Long-Term Treatment with BLU9931

During long-term culture (one week) with BLU9931, some populations of cells exhibited an enlarged and flattened morphology (Figure 6A). Such changes may occur in senescent cells [49]. Therefore, we next examined the effects of BLU9931 on senescence in PK-1 cells by assaying for senescence-associated β-galactosidase (SA-β-Gal) activity, which is a well-known marker for senescent cells. BLU9931 increased the number of SA-β-Gal-positive cells compared with the control group (Figure 6A,B). By contrast, a 3-day incubation with BLU9931 did not alter SA-β-Gal staining in PK-1 cells (Figure S5A,B). Furthermore, phosphorylation of H2A.X (γH2A.X), which is an early sign of DNA damage as well as a senescence marker [50,51], was increased in PK-1 cells that had been incubated for 3 days with BLU9931 and further increased in long-term culture with BLU9931 (Figure 6C). There were no differences in telomere length between control and long-term BLU9931-treated PK-1 cells (Figure 6D). Taken together, these results suggest BLU9931 induces premature senescence through DNA damage, possibly through the ATM pathway.

Senescent cells may exhibit a senescence-associated secretory phenotype (SASP) [52], a process whereby high levels of SASP factors, including inflammatory cytokines, are secreted. In the present study, prolonged incubation of PK-1 cells with BLU9931 resulted in a significant increase in the levels of SASP-associated cytokines (IL-1α, IL-1β, IL-6, TNFα, and GM-CSF) when compared with the corresponding levels in control cells (Figure 6E). In T3M-4 cells, the number of SA-β-Gal-positive cells accompanying enlarged and flattened morphology was also increased following prolonged incubation with BLU9931, but the percentage of SA-β-Gal-positive cells was lower than in PK-1 cells (Figure S5C,D). Moreover, among the above SASP cytokines, only GM-CSF was significantly upregulated in these T3M-4 cells (Figure S5E).

It is known that reduction of sirtuin1 (SIRT1) and SIRT6 leads to induction of premature senescence caused from attenuation of DNA damage repair [53]. We therefore examined the expression of SIRT1 and SIRT6 in relation to the induction of premature senescence by BLU9931. BLU9931 reduced the expression of SIRT1 and SIRT6 (Figure 6F and Figure S5F), suggesting that long-term BLU9931 treatment induces premature senescence in PDAC cells, in part, through downregulation of SIRT1 and SIRT6.

2.6. Effects of Senolytic Drugs on BLU9931-Induced Senescent PDAC Cells

Quercetin and dasatinib are senolytic drugs [54] that can selectively eliminate senescent cells. Therefore, the dose-dependent effects of quercetin or dasatinib on the viability of PDAC cell lines (PK-1, PK-45P, T3M-4) were examined next. We added increasing concentrations of quercetin (1.56–50 μM) or dasatinib (7.8–500 nM) to PK-1, PK-45P, and T3M-4 cells. As shown in Figure S6, we identified the maximal concentration without cytotoxic effects as follows: quercetin (25 μM) and dasatinib (62.5 nM) for PK-1 cells, quercetin (25 μM) and dasatinib (7.8 nM) for PK-45P cells, and quercetin (12.5 μM) and dasatinib (7.8 nM) for T3M-4 cells. We then assessed the cytotoxic effects of senolytic drugs on BLU9931-induced senescent PDAC cells. Quercetin significantly decreased the viability of long-term BLU9931-treated PK-1 and T3M-4 cells (Figure 7A and Figure S6) but not PK-45P cells (Figure 7A), whereas dasatinib was not effective in any of the BLU9931-treated cells (Figure 7A and Figure S7). Thus, the senolytic drug, quercetin, was effective in those PDAC cells in which BLU9931 induced senescent changes. As shown in Figure S8A, the poly ADP ribose polymerase (PARP) inhibitor olaparib inhibited the growth of PK-1 cells dose dependently, with an IC50 of 8 μM. At this concentration, olaparib did not significantly alter the number of apoptotic and necrotic/injured cells that had been incubated with BLU9931 (Figure S8B). Next, we examined senescence and cytotoxic effects of BLU9931+quercetin+olaparib. BLU9931+olaparib enhanced the proportion of senescent cells compared with BLU9931 alone (Figure S9A,B). This was associated with a profound decrease in the total number of cells, indicating that in addition to inducing senescence, olaparib inhibited proliferation and exerted a senolytic effect in these cells. However, there was no additive effect on PK-1 cell viability with quercetin addition in BLU9931+olaparib-treated cells (Figure S9C). We speculate that senescent cells induced by olaparib treatment are not sensitive to quercetin.

4.1. Immunohistochemistry

Paraffin-embedded sections from pancreas tissue microarrays (PA1002, PA2072; US Biomax, Inc. Rockville, MD, USA) were immunostained using Histofine Simple Stain MAX PO (R) kit. After deparaffinization, antigen retrieval was performed at 121 °C for 15 min in a sodium citrate buffer solution (pH 6.0). Then, endogenous peroxidase activity was blocked by incubating sections for 30 min with 0.3% hydrogen peroxide in methanol. The tissue sections were incubated overnight with the rabbit polyclonal anti-FGFR4 antibody (1:100 in dilution; Sigma-Aldrich, St. Louis, MO, USA). Bound antibodies were detected with Simple Stain MAX PO (R) reagent, using diaminobenzidine-tetrahydrochloride chromogen (DAB) as the substrate. Negative control studies were performed by omitting the primary antibodies. For the evaluation of the intensity of FGFR4 immunostaining in the tissue microarray, the following scale was employed: 0, no staining; 1+, mild staining; 2+, moderate staining; and 3+, intense staining. Two pathologists (H. Y. and Y. M.) independently evaluated the staining results. Scales 0 and 1 were low, and 2 and 3 were divided into FGFR4 highly localized groups. Correlation between FGFR4 expression and tumor grades were analyzed in 129 cases, and the other factors were analyzed in 136 cases, because of the provided clinical data from the tissue arrays. Microscopic images were taken using Mantra, multi-spectral microscopy (PerkinElmer, Waltham, MA, USA), and then images were loaded into inform software ver. 2.4 (PerkinElmer) to separate specific chromogens, DAB, and hematoxylin, by using the spectral compensation library built in the software according to the manufacturer’s instruction.

4.2. Cell Culture

The human PDAC cell lines PK-1, PANC-1, PK-59, and MIA PaCa-2 were obtained from the Cell Resource Center for Biomedical Research, Institute of Development, Aging and Cancer, Tohoku University (Sendai, Japan). PK-45P, PK-8, T3M-4, and KP4 human PDAC cells were provided by the RIKEN BRC through the National Bio-Resource Project of the MEXT, Japan. Cells were grown in growth medium (RPMI 1640 medium containing 10% fetal bovine serum) at 37 °C under a humidified 5% CO₂ atmosphere. For 3-D culture, cells in growth medium were plated at 1.0 × 10⁴ cells/well or 3.0 × 10³ cells/well in 24-well ultra-low attachment plates (Corning Inc., Kennebunk, ME, USA) or 96-well ultra-low attachment plates (Thermo Fisher Scientific, Waltham, MA, USA), respectively. The spheres were aspirated after 7 days using micropipettes and placed in microcentrifuge tubes for use in further experiments. Cells were treated with BLU9931 (EMD Millipore Corp., Burlington, MA, USA) or 0.005% dimethyl sulfoxide as vehicle control for 3 days, and after further experiments were performed.

4.3. Genotyping

Genomic DNA was extracted from PDAC cell lines using DNeasy Blood & Tissue Kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. Genotypes were determined according to the previous report [91]. Briefly, FGFR4 exon 9 was amplified using primers (Forward: 5′-GAC CGC AGC AGC GCC CGA GGC CAG-3′; Reverse: 5′-AGA GGG AAG AGG GAG AGC TTC TG-3′) and analyzed for Gly388Arg polymorphism. PCR products were digested with BstNI (New England Biolabs Inc., Ipswich, MA, USA). SNP Arg388 in FGFR4 gene was characterized by two distinctive fragments of 82 and 27 bp. On the other hand, the FGFR4 Gly388 wild-type allele was identified by a single fragment of 109bp.

4.4. FACS Analysis

Cells were harvested and dissociated cells were incubated on ice for 30 min with rabbit polyclonal anti-FGFR4 antibody (antibodies-online GmbH, Aachen, Germany) diluted in FACS buffer (0.5% [w/v] bovine serum albumin and 0.1% [w/v] sodium azide in phosphate buffered saline [PBS]). After washing, the cell suspension was incubated on ice for 30 min with Alexa Fluor^® 488-conjugated secondary antibodies (Molecular Probes, Eugene, OR, USA) diluted in FACS buffer. Cell analysis was performed using a FACSAria™ Cell Sorter (Becton Dickinson, Franklin Lakes, NJ, USA). Mean fluorescence intensities (MFIs) were calculated after subtracting the intensities of the controls.

4.5. Real-Time qPCR

Total RNA was isolated from cells using the RNeasy plus mini kit (QIAGEN) and subsequently reverse-transcribed using the ReverTra Ace^® qPCR RT Kit (Toyobo, Osaka, Japan) according to the manufacturer’s instructions. Real-time qPCR was performed using the Power Sybr^® Green kit (Applied Biosystems, Foster City, CA, USA) and a StepOnePlus^™ real-time PCR system (Applied Biosystems). β-actin was amplified as an internal control. Primer sets for real-time qPCR are listed in Table S1. Real-time qPCR analysis for FGFR4 was performed using TaqMan Fast Universal PCR Master Mix (Life Technologies Corporation, Carlsbad, CA, USA) and TaqMan Gene Expression Assays (Life Technologies), with 18S rRNA serving as an internal control.

4.6. Cell Proliferation Assay

Cells were cultured in growth medium at a density of 3 × 10³ cells/well in 96-well plates followed by incubation for 72 h. ATP assays were used to examine proliferation using the CellTiter-Glo^® 2.0 Assay (Promega, Madison, WI, USA) according to the manufacturer’s protocol.

4.7. Apoptosis Assay

Measurement of the percent of apoptotic cells was performed using an Annexin V-Biotin Apoptosis Detection kit (BioVision Inc., Milpitas, CA, USA) per the manufacturer’s instructions. Cells were analyzed using a FACSAria™ Cell Sorter.

4.8. Cell Cycle Assay

Cells were washed in PBS, resuspended in PBS, and stained with cell cycle assay solution (deep red; Dojindo Molecular Technologies, Inc., Rockville, MD, USA) at 37 °C for 15 min. The cell cycle profiles were obtained using a FACSAria™ Cell Sorter at 640 nm. Data were analyzed using FlowJo software (Becton Dickinson).

4.9. Immunoblotting

Cells were lysed with lysis buffer (50 mM Tris-HCl pH 7.4, 150 mM NaCl, 1.5 mM MgCl₂, 5 mM EDTA, and 1% Triton^™ X-100) containing protease and phosphatase inhibitor cocktails. Samples prepared as described above were separated by SDS-PAGE and then transferred onto Polyvinylidene difluoride membranes (Merck Millipore, Billerica, MA, USA). After blocking, the membranes were incubated with the following primary antibodies: polyclonal rabbit anti-FGFR4 (ab41948; Abcam, Cambridge, UK), monoclonal rabbit anti-ERK1/2 (#4695; Cell Signaling Technology, Danvers, MA, USA), monoclonal rabbit anti-pERK1/2 (#4370; Cell Signaling Technology), monoclonal rabbit anti-AKT (#4691; Cell Signaling Technology), monoclonal rabbit anti-pAKT (#4060; Cell Signaling Technology), monoclonal mouse anti-STAT3 (#9139; Cell Signaling Technology), polyclonal rabbit anti-pSTAT3 (#9131; Cell Signaling Technology), monoclonal rabbit anti-MT1-MMP (ab51074; Abcam), and monoclonal mouse anti-β-actin (A5316; Sigma-Aldrich). Membranes were then incubated with the appropriate peroxidase-conjugated secondary antibodies (Cell Signaling Technology), washed, and developed with ECL^™ Prime reagents (GE Healthcare, Piscataway, NJ, USA). Image densitometry was performed with ImageJ software (National Institutes of Health, Bethesda, MD, USA). Full blot images with molecular weight markers are shown in Figure S10.

4.10. Sphere-Forming Assay

To form spheres, cells (5.0 × 10³ cells/well) were plated in 24-well ultra-low attachment plates with RPMI 1640 medium containing FGF-2 (10 ng/mL, ReproCELL, Tokyo, Japan) and EGF (20 ng/mL, AUSTRAL Biologicals, San Ramon, CA, USA). After 7 days, the spheres that formed were counted by using a phase-contrast microscope (Eclipse TS-100, Nikon, Tokyo, Japan).

4.11. Anti-Drug Resistance Assay

Cells (3.0 × 10³ cells/well) were plated in 96-well culture plates with growth medium with or without BLU9931. Each anticancer drug was administered at the indicated concentration after 3 days culture and cell growth rates were measured by ATP assays 4 days after treatment of anticancer drug. Cell viability was calculated as the percentage of luminescence in drug-treated cells relative to non-treated control cells.

4.12. Wound Healing/Cell Scratch Assay

Cells were seeded at a density of 7 × 10³ cells on each side of an Ibidi culture insert (Ibidi GmbH, Martinsried, Germany), with a 500-μm separation between each side of the well, and allowed to grow for 24 h in growth medium. After removal of the insert, cells were incubated in the same medium. Cells were photographed using phase contrast microscopy at insert removal (0 h) and following 6 and 24 h of incubation. Accurate measurements of the wounds were taken during the time course to calculate the migration rate according to the equation: Percentage of wound healing = [(wound area at 0 h) − (wound area at 6 or 24 h)]/(wound length at 0 h) × 100.

4.13. Boyden Chamber Assay

Cell culture inserts (8-μm pore size and 6 mm in diameter) were used according to the manufacturer’s instructions. Cells were plated at a density of 1 × 10⁵ cells/500 μL on the upper chamber of the inserts with serum-free medium, and medium containing 10% serum was used in the lower chamber. Six hour later, cells that had migrated through the membrane pores were fixed and stained with a Diff-Quick staining kit (Polysciences, Inc., Warrington, PA, USA), and counted under a light microscopy.

4.14. Invasion Assay

Invasion assays were performed using Corning Matrigel invasion chambers (pore size: 8 μm, Discovery Labware Inc., Bedford, MA, USA). Cells were plated at a density of 1 × 10⁵ cells/500 μL on the upper surface of the inserts, and, 16 or 24 h later, cells that had migrated through the membrane to the lower surface of the filter were fixed and stained with a Diff-Quick staining kit (Polysciences, Inc.) and counted under a light microscope.

4.15. MMP Gelatin Zymography

Media samples collected from cells cultured in serum-free medium for 24 h at 37 °C were concentrated using Amicon^® Ultra Centrifugal Filters (Merck Millipore), and protein assays were performed. The same amounts of samples were resolved on 8% SDS-PAGE gels containing 4.0 mg/mL gelatin. The gels were rinsed with wash buffer (50 mM Tris-HCl, pH 7.5, 5 mM CaCl₂, 1 μM ZnCl₂, 2.5% Triton X-100) and soaked in incubation buffer (50 mM Tris-HCl, pH 7.5, 5 mM CaCl₂, 1 μM ZnCl₂, 1% Triton X-100) at 37 °C for 24 h. After incubation, the gels were fixed and stained with Coomassie R-250, washed, and scanned.

4.16. SA-β-Gal Assay

SA-β-Gal activity was assayed using a senescence detection kit (BioVision Inc., Milpitas, CA, USA) as described in our previous reports [92]. Briefly, cells were washed twice with PBS, exposed to fixation solution for 10 min, and then incubated overnight in freshly prepared staining solution. After staining, cells were counterstained with DAPI and then four fields of view were examined microscopically. By counting the number of SA-β-Gal-positive cells based on their blue color and the total number of cells stained with DAPI using ImageJ software, the percentage of SA-β-Gal-positive cells was calculated to estimate the percentage of senescent cells.

4.17. Telomere Length Assay

Telomere length was quantified by real-time PCR using a Telomere Length Quantification qPCR Assay Kit (ScienCell Laboratory, Carlsbad, CA, USA) according to the manufacturer’s protocol. Genomic DNA samples were extracted as described in Section 4.3.

4.18. Immunostaining

Cells were fixed with 4% (w/v) paraformaldehyde and washed. Subsequently, cells were permeabilized with 0.1% [v/v] Triton^™ X-100 and blocked with PBS containing 1% (w/v) BSA and 5% (v/v) normal goat serum. After washing, cells were incubated with monoclonal mouse anti-γH2A.X (sc-517348; Santa Cruz Biotechnology, Dallas, TX, USA) at 4 °C overnight. After washing, cells were stained with Alexa Fluor^® 488-conjugated secondary antibodies (Molecular Probes), and then counterstained with DAPI. Immunofluorescence images were acquired using a confocal laser scanning microscope (Leica Microsystems, Wetzlar, Germany). For the quantification of γH2A.X-positive cells, the numbers of γH2A.X-positive cells with green color and the total numbers of cells stained with DAPI from four fields were counted and then the percentage of γH2A.X-positive cells was calculated.

4.19. Senolytic Drug Sensitivity Assay

Cells (3.0 × 10³ cells/well) that were incubated in the presence or absence of BLU9931 for 7 days were plated in 96-well culture plates containing the respective media. Thus, only cells previously incubated with BLU9931 contained the FGFR4 inhibitor. Each senolytic drug, Quercetin (Cayman Chemical, Ann Arbor, MI, USA) or Dasanitib (Cayman Chemical), was then added as indicated and cell growth rates were determined by the ATP assay 4 days later. Cell viability was calculated as the percentage of luminescence in drug-treated cells relative to non-treated control cells.

4.20. Statistical Analysis

Results were shown as means ± SD, and differences between two groups were compared using Student’s t test or Welch’s t test. One-way ANOVA was performed when comparing multiple groups. Chi-square and Fisher’s exact tests were used to analyze correlations between FGFR4 expression and clinicopathological features.

Statistical analysis was performed with EZR (Saitama Medical Centre, Jichi Medical University) [93].