ROS/PI3K/Akt and Wnt/β-catenin signalings activate HIF-1α-induced metabolic reprogramming to impart 5-fluorouracil resistance in colorectal cancer

The following colorectal adenocarcinoma cell lines with STR profiling, were obtained from KeyGEN BioTECH, Jiangsu: HCT8 (male), HCT15 (male), HCT116 (male), LoVo (lymph node metastasis, male), SW480 (male), SW1116 (male), HT29 (female), Caco-2 (male), DLD-1 (male), and T84 (lung metastasis, male). The DiFi cell line was a generous gift of Dr. Li Luo. Cells were cultured in Roswell Park Memorial Institute (RPMI)-1640 medium supplemented with 10% fetal bovine serum (FBS), penicillin (100 mg/ml) and streptomycin (100 mg/ml), and cells were subcultured after dissociation with 0.25% trypsin-EDTA once they had reached 80% confluence. In general, all cultures were maintained in a 37 °C 5% CO₂ incubator, or incubated in a hypoxia chamber at 94% N₂, 5% CO₂, and 1% O₂ for certain experiments.

Male athymic BALB/c nude mice (4 weeks old) and male NOD/scid mice (4 weeks old) were purchased from SPF (Beijing) Biotechnology Co., Ltd. and housed in the animal center of Qianfoshan Hospital Affiliated to Shandong University. All procedures were approved by the Institutional Animal Care and Use Committee of Qianfoshan Hospital Affiliated to Shandong University. All animal studies complied with the relevant ethical regulations for animal testing and research.

Fresh and neutral-buffered formalin-fixed tumor samples from 42 patients with CRC were collected from the Department of Gastrointestinal Surgery, Qianfoshan Hospital Affiliated to Shandong University and the Department of Colorectal Surgery, Qilu Hospital of Shandong University (Table S1). At the time of tumor sample collection, 5 mL peripheral venous blood from the cubital vein and 5 mL blood from the tumor reflux veins were also obtained from these patients. An informed consent form was signed by each patient. The Ethics Committee of Qianfoshan Hospital Affiliated to Shandong University granted approval for this study. Datasets involved (GSE104645, GSE69657) were downloaded from the public Gene Expression Omnibus (GEO) database (https://​www.​ncbi.​nlm.​nih.​gov/​gds/​).

HCT8, HCT15, HCT116, LoVo, T84, and DiFi cell lines were continuously treated with a gradually increasing concentration of 5-FU rising from 10^− 8 M to 10^− 4 M initially. We assessed 5-FU resistance at each dose by calculating the IC₅₀ using CCK8 assays. We defined 5-FU resistance as a resistance index (RI, IC₅₀ of the WT cells/IC₅₀ of the 5-FU-R cells) > 10 after 5-FU treatment of approximately 8 months duration. We succeeded in generating stable cells lines of HCT8 (RI = 396.63), HCT15 (RI = 110.84), and LoVo (RI = 347.60) with acquired 5-FU resistance.

Small interfering RNA (siRNA) duplexes and negative control (NC) targeting HIF1A and CTNNB1 were transfected into cells by overnight incubation using Lipofectamine RNA iMAX reagent according to the manufacturer’s protocol. For lentivirus constructs, the short hairpin RNA (shRNA) for HIF1A was cloned into a hU6-MCS-Ubiquitin-EGFP-IRES-puromycin lentiviral (GV248) vector. After lentiviral-mediated transfection and puromycin selection, transfection efficiency was verified by RT-qPCR and WB. The sequences of siRNA and shRNA targeting HIF1A or CTNNB1 are listed in an additional file.

For cell cytotoxicity assays, 5000 cells per well were seeded into 96-well plates 24 h before treatment. The cells were then treated with the indicated agents for 48-72 h, after which 10% v/v of water-soluble WST-8 dye was added for 0.5-2 h. The absorbance of the formazan was measured at 450 nm using a microplate reader after mixing gently on an orbital shaker for 1 min. All experiments were performed with at least three replicates.

Cells were visualized using the CytoPainter phalloidin-iFluor 488 reagent. Fixed and permeabilized cells were stained with phalloidin-iFluor 488 in 1% BSA in PBS for 1 h to label the F-actin. DAPI was used to stain the nuclei. Slides were covered with mounting medium containing DAPI and photographed using an Axio Scope A1 microscope (Zeiss, Germany) at 400× magnification.

Cells at 5000 per well were plated in 96-well plates for 24 h, and then treated with 10^− 5 M 5-FU for 48 h. After incubation with 10 μM EdU for a further 2 h, the cells were fixed in 4% paraformaldehyde (PFA) and stained with Click-iT reaction solution at 100 μL per well. Hoechst 33342 was used to stain the nuclei. Images were obtained using an ImageXpress Micro High Content Screening System (Molecular Devices, USA) at 200× magnification, and the ratio of EdU/Hoechst 33342-double-positive cells was quantified.

Cells were seeded into 6-well plates and treated with or without 10^− 5 M 5-FU for 48 h, after which they were harvested using trypsin without EDTA. For cell apoptosis analysis, washed cells were immediately stained with PE-conjugated annexin V and 7-AAD and analyzed using a BD FACSAria II instrument (BD Biosciences, USA) and FlowJo software. For cell cycle analysis, cells were fixed in 70% ethanol overnight at − 20 degrees and then resuspended in 1 ml of PBS containing propidium iodide and RNase. Cell cycle stage detection was performed on a FACSAria II machine (BD Biosciences, USA) and data analyzed with ModFit LT software.

Cells were cultured in 6-well plates until 80% confluence was achieved. To analyze mitochondria organization, cells were incubated with 1 mL of the working solution of Mito-Tracker for 1 h at 37 °C and kept on ice protected from light. Texas Red fluorescence was visualized using a BD FACSAria II instrument (BD Biosciences, USA) and flow cytometry data were analyzed using FlowJo software.

Cells were dissociated using trypsin-EDTA solution and collected by centrifugation. They were then fixed in electron microscope fixation liquid for 2 h at room temperature and stored in the dark at 4 °C. Next, fixed samples were sequentially treated with agarose pre-embedding, post-fixation, dehydration, resin penetration, EMBed 821 embedding, polymerization, ultrathin sectioning, and staining. The cuprum grids were observed under an Hitachi HT7800 transmission electron microscope (Hitachi, Japan) and images captured.

1 × 10⁵ cells were plated per well in 6-well plates, incubated for 24 h at 37 °C and then treated with the indicated agents for the appropriate time or transfected with HIF1A siRNA or control siRNA. Cells were incubated with sugar-free RPMI-1640 medium with 100 μM 2-NBDG for 2 h after starving them in glucose in sugar-free RPMI-1640 medium overnight. After 2-NBDG incubation, washed cells were digested and collected in 1 ml of PBS. The mean fluorescence intensity (MFI) of samples was measured by BD FACSAria II (BD Biosciences, USA) flow cytometry using the FITC channel.

To measure lactate levels secreted into the culture supernatants, 2 × 10⁴ cells per well were seeded into 24-well plates. The medium was refreshed with 1 mL complete RPMI-1640 medium per well for 24 h after treating with the indicated agents. The next day, culture supernatants were harvested and the lactate concentration was measured by colorimetric assays according to the manufacturer’s protocol of the Lactate Assay Kit. Additionally, protein quantitation was measured by the BCA method and lactate release counts were normalized to total protein concentrations.

Cultured cells were washed with ice-cold PBS and removed from the plate by gentle scraping. 2 × 10⁷ cells per sample were collected in triplicate. After removal of the supernatant, 1 mL ice-cold methanol was added and cells were fragmented by ultrasound in an ice bath. Finally, the supernatant was collected after centrifugation, dried and resolubilized in 450 μL D₂O containing 30 μM 3-(tetramethysilane) propionic acid-2,2,3,3-d4 (TMSP) for spectral referencing. All ¹H-NMR spectra were recorded at 298 K using a Bruker Avance III 600 MHz spectrometer (Bruker Biospin, Germany), and a standard Bruker noesygppr1d pulse sequence for water suppression was used. The raw ¹H-NMR spectra were imported into MestReNova 9.0.1 software (Mestrelab Research, Spain) for Fourier transformation, phase and baseline correction.

Cells (1 × 10⁷ cells per sample) were suspended in 80% methanol, spiked with 20 μL of internal standard solution (2 μg/mL succinic acid-¹³C₄, 4 μg/mL Fructose-1,6-bisphosphate-¹³C₆, 10 μg/mL glucose-¹³C₆), and processed by 5 cycles of ultra-sonication in an ice-water bath. After 30 min at − 20 °C, the cell mixture was centrifuged at 4 °C and 15,000 g for 15 min. The cell-free supernatant was evaporated to dryness and reconstituted in 40 μL of 50% acetonitrile prior to UHPLC-MS/MS analysis. The quality control (QC) sample was obtained by isometrically pooling all the prepared samples. All glycometabolism standards were prepared separately and mixed to a 25 μg/mL standard solution, including glucose, citric acid, cis-aconitic acid, isocitric acid, α-ketoglutaric acid, succinic acid, fumaric acid, malic acid, lactic acid, pyruvic acid, Glucose-6-phosphate (G6P), fructose-6-phosphate (F6P), fructose-1,6-bisphosphate(FBP), ribulose-5-phosphate (Ru5P), xylulose-5-phosphate (Xu5P), sedoheptulose-7-phosphate (S7P), 3-phosphoglyceric acid (3-PGA), glyceraldehyde-3-phosphate (GAP), phosphoenolpyruvic acid (PEP), ribose-5-phosphate (R5P), erythrose-4-phosphate(E4P), and dihydroxyacetone phosphate (DHAP).

The UHPLC-MS/MS analysis was performed on an Agilent 1290 Infinity II UHPLC system coupled to a 6470A Triple Quadrupole mass spectrometer (Santa Clara, USA). Samples were injected into a Waters BEH Amide column (100 mm × 2.1 mm, 1.7 μm) at a flow rate of 0.25 mL/min. The mobile phase consisted of (A) water in 15 mM ammonium acetate at pH 8.5 and (B) 90% acetonitrile. The chromatographic separation was conducted by a gradient elution program as follows: 0-2 min, 90% B; 14 min, 75% B; 15 min, 65% B; 15.2-16.9 min, 50% B; 17-20 min, 90% B. The eluted analytes were ionized by an electro-spray ionization source in positive mode (ESI⁻). The temperatures of the ESI⁻ source drying gas and sheath gas were 300 °C and 350 °C. The flow rates of ESI⁻ source drying gas and sheath gas were 5 and 11 L/minute, respectively. The pressure of the nebulizer was 40 psi, and capillary voltage was 4000 V. Dynamic multiple reaction monitoring (dMRM) was used to acquire data in optimized MRM transition. MassHunter software (version B.08.00, Agilent) was used to control instruments and acquire data.

5 × 10⁶ cells were harvested and washed in pre-cooled PBS. Cells were incubated with anti-GLUT1 (1:50, Abcam) or anti-MCT4 (1:200, Abcam) primary antibodies for 1 h on ice. After washing 3x with cold PBS, cells were incubated with Alexa-conjugated-488 secondary antibody (1:500) for 30 min on ice. At the end of the incubation, cells were sorted on a BD FACSAria III instrument (BD Biosciences, USA) for high and low expression of GLUT1 or MCT4. Sorted cells were then cultured and CCK8 cytotoxicity assays performed.

1 × 10⁴ cells were seeded into XFe96 cell culture plates in complete RPMI-1640 medium and incubated at 37 °C overnight in 5% CO₂. To equilibrate temperature and pH of the detection system, cells were washed with assay RPMI-1640 medium and incubated at 37 °C for 1 h in a CO₂-free incubator before assessment. OCR and ECAR were detected with an Agilent Seahorse XFe96 extracellular flux analyzer (Agilent Technologies, USA). To examine mitochondrial respiratory activity, cells were treated with oligomycin (1.5 μM), FCCP (1 μM) and rotenone/antimycin A (0.5 μM) using a Seahorse XF Cell Mito Stress Test Kit. For assessment of glycolytic activity, cells were treated with glucose (100 mM), oligomycin (10 μM) and 2-deoxy-D-glucose (2-DG, 500 mM) using a Seahorse XF Glycolytic Rate Assay Kit in sequence. All experiments were done in seven replicas each time and data expressed as means with SEM.

4 × 10⁵ cells per well were seeded into 6-well plates until 70-90% confluence was achieved. Cells were lysed and cell lysates used for detecting ATP and total protein concentrations. ATP concentrations were measured using a luminometer and determined based on the standard curve. The results were normalized to protein content (BCA assay).

When cells in T25 flasks had reached 60% confluence, they were probed using 10 μM 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) incubated at 37 °C for 20 min. Fluorescence signals in the FITC channel were acquired on a BD FACSAria II (BD Biosciences, USA) instrument for measurement of intracellular ROS. Data were analyzed using FlowJo software.

Lactate dehydrogenase (LDH), catalase (CAT), glutathione peroxidase (GPx), and superoxide dismutase (SOD) activities were measured by colorimetry, following the manufacturer’s protocols. Enzyme activities were normalized to total protein levels (BCA assay).

To extract total proteins, cells were lysed in RIPA buffer containing a protease inhibitor and a phosphatase inhibitor. In addition, nuclear, cytosolic, and membrane proteins were extracted using a Nuclear Protein Extraction Kit or a Membrane Protein Extraction Kit according to the manufacturer’s instructions. Protein solutions were boiled in 5 × loading buffer at 98 °C for 10 min and then resolved by SDS-PAGE. All the primary antibodies used in the experiment were: anti-CDK2 (1:1000, Proteintech), anti-Cyclin D1 (1:1000, Proteintech), anti-p21 (1:2000, Proteintech), anti-Bcl-XL (1:1000, Proteintech), anti-Cleaved caspase 3 (1:500, Affinity), anti-Cleaved caspase 9 (1:1000, Affinity), anti-NDUFB8 (1:2000, Abcam), anti-SDHB (1:100000, Abcam), anti-UQCRC1 (1:1000, Proteintech), anti-COX4 (1:2000, Abcam), anti-ATP5F1 (1:500, Proteintech), anti-GLUT1 (1:5000, Abcam), anti-GLUT2 (1:5000, Abcam), anti-GLUT3 (1:1000, Abcam), anti-GLUT4 (1:500, Abcam), anti-MCT1 (1:1000, Abcam), anti-MCT2 (1:500, Proteintech), anti-MCT4 (1:200, Santa), anti-LDHA (1:1000, Proteintech), anti-HK2 (1:1000, Abcam), anti-GAPDH (1:10000, Proteintech), anti-ENO1 (1:1000, Abcam), anti-PKM2 (1:500, CST), anti-G6PD (1:1000, Abcam), anti-HIF-1α (1:500, Abcam), anti-Catalase (1:2000, Proteintech), anti-GPx1 (1:2000, Abcam), anti-SOD1 (1:50000, Abcam), anti-SOD2 (1:1000, Abcam), anti-PI3K (1:1000, Affinity), anti-Phospho-PI3K (1:1000, Affinity), anti-AKT (1:500, Abcam), anti-Phospho-AKT (1:1000, Abcam), anti-β-catenin (1:5000, Proteintech), anti-Axin2 (1:1000, Abcam), anti-Dvl1 (1:1000, Proteintech), anti-TCF1 (1:1000, Proteintech), anti-TCF4 (1:1000, Proteintech), anti-β-Actin (1:5000, Proteintech), anti-Lamin B1 (1:2000, Proteintech). Detailed antibody information was listed in additional file. Primary antibodies were detected by goat anti-rabbit/mouse IgG (H + L), horse radish peroxidase (HRP)-conjugated secondary antibodies, and reacted with a chemiluminescent HRP substrate. Chemiluminescence images were captured using an Amersham Imager 680 (GE Healthcare, USA).

Pierce Co-IP Kits (Thermo Scientific) were used for the isolation of natural protein complexes. Our approach is briefly summarized in the following steps. Primary antibodies against β-catenin (0.5 μg/μL, Proteintech) or HIF-1α (0.165 μg/μL, Abcam) were first covalently immobilized to AminoLink Plus coupling resins for 2 h at room temperature in a tube rotator, with IgG serving as the negative control. Cells were solubilized in lysis buffer (Tris 0.025 M, NaCl 0.15 M, EDTA 0.001 M, NP-40 1%, and glycerin 5%), and 500 μL of the cell lysates incubated with pre-prepared anti-β-catenin or anti-HIF-1α primary antibody-conjugated resins overnight at 4 °C in a tube rotator. After incubation, the natural protein complexes were eluted and analyzed by Western blotting with anti-β-catenin (1:5000, Proteintech), anti-HIF-1α (1:500, Abcam), anti-TCF1 (1:1000, Proteintech), and anti-TCF4 (1:1000, Proteintech) primary antibodies as described previously.

1 × 10⁵ cells were seeded on cell climbing slices coated with poly-D-lysine in 24 well plates. Prepared cells were fixed in 4% PFA for 20 min, permeabilized with 0.5% Triton X-100 for 5 min, and blocked in 10% goat serum for 1 h at room temperature. The following primary antibodies were incubated overnight at 4 °C: anti-LDHA (1:250, Proteintech), anti-β-catenin (1:200, Proteintech), or anti-HIF-1α (1:200, Abcam; 1:100 Proteintech). Next day, cells were incubated with secondary antibodies for 1.5 h at room temperature: CoraLite594-conjugated goat anti-rabbit IgG(H + L) (1:250, Proteintech), CoraLite488-conjugated goat anti-mouse IgG(H + L) (1:250, Proteintech). Cell climbing slices were mounted on slides with mounting medium containing DAPI and photographed by a TCS SP8 confocal laser scanning microscopy (Leica, Italy) or an Axio Scope A1 microscope (Zeiss, Germany) at 400× magnification.

Male athymic BALB/c nude mice were raised under 12 h light/12 h dark cycles in an SPF environment. We subcutaneously implanted 5 × 10⁶ WT or 5-FU-R cells with or without stable knockdown of shHIF1A into the right forelimb underarm of 4 week-old nude mice. One week after subcutaneous injection, the mice were intraperitoneally injected with 5-FU (25 mg/kg, three times a week), or saline as a control. In the experiments on HIF-1α pharmacological inhibition, one week after subcutaneous injection, both WT or 5-FU-R cell-bearing nude mice were then randomly divided into 4 groups: control, 5-FU, IDF-11774, and 5-FU + IDF-11774. 5-FU was intraperitoneally injected at the dose of 25 mg/kg three times a week, IDF-11774 was intraperitoneally injected at the dose of 30 mg/kg twice a week, and saline as a control. Subcutaneous tumor-bearing mice were continuously monitored, and tumor volumes (V = L × W²/2, where L is the length and W is the width) were assessed. Mice were sacrificed under anesthesia when the tumor reached a diameter of about 1.5 cm.

Tumor tissues derived from a rectal cancer patient (male, Dukes’ C) received neoadjuvant chemotherapy containing 5-FU and subsequent surgery. Fresh well-trimmed tumor tissues were cut into pieces about 3 mm in size and immediately placed in RPMI-1640 medium supplemented with 50% FBS and penicillin/streptomycin. We subcutaneously implanted tumor pieces into the right forelimb underarm of 4 week-old NOD/scid mice, and xenografts were harvested when they reached a diameter of about 1.5 cm. They were then cut up and implanted again into fresh NOD/scid mice. When these xenografts had been growing for about 20 days, mice were divided into four groups: control (saline), 5-FU (25 mg/kg, three times per week), IDF-11774 (30 mg/kg, twice per week), and 5-FU with IDF-11774. Mice were sacrificed under anesthesia when the PDXs reached a diameter of about 1.5 cm.

CDX/PDX tumors and CRC tissues of patients were fixed in 4% PFA, embedded in paraffin, and sectioned. Tumor sections were dewaxed with dewaxing agent and dehydrated in graded alcohol concentrations. After antigen retrieval with heated citrate buffer and blocking with 10% goat serum, the following primary antibodies were incubated overnight at 4 °C: anti-Ki-67 (Proteintech, 1:5000), anti-HIF-1α (1:200, Abcam), anti-GLUT1 (1:500, Abcam), anti-HK2 (1:100, Abcam), anti-PKM2 (1:200, CST), anti-LDHA (1:200, Proteintech), anti-MCT4 (1:50, Santa), anti-Phospho-AKT (1:100, Abcam), anti-β-catenin (1:1000, Proteintech), and anti-TCF1 (1:200, Proteintech). Next day, the sections were incubated with HRP-conjugated anti-rabbit/mouse IgG and detected by 3,3′-diaminobenzidine (DAB) staining. The nuclei were stained with hematoxylin. The stained sections were photographed using an Axio Scope A1 microscope (Zeiss, Germany) at 200× magnification.

WT or 5-FU-R cell-bearing nude mice were injected with 10 nmol IRDye 800CW 2-DG Optical Probe (Li-Cor Biosciences) via the tail vein, and then imaged using an IVIS Kinetic (Caliper Life Sciences, USA) small animal imaging system with a cooled Hamamatsu ORCA-R2 camera (Hamamatsu, Japan) 24 h later. Probe signals were displayed as pseudo-colored bioluminescent images and merged with grey-scale white light images of the mice. Circular ROIs were drawn over the areas and quantified, and the results are reported as total radiant efficiency.

Tumor lactate concentrations of WT or 5-FU-R cell-bearing nude mice were quantified with MRS. The data were acquired on a Siemens Skyra 3.0 T MRI scanner (Siemens Skyra, Germany) using an 8-channel small animal special coil (mouse coil) for reception of the signal. T2-weighted anatomical images were acquired using a standard 3D sequence with an isotropic voxel size of 1 mm. Subsequently, the lactate spectrum was acquired from a single voxel snug-fit to the tumor with TR/TE of 1700 ms/135 ms. The acquisition duration was set to 853 ms with a bandwidth of 1200 Hz.

Tumor-reflux venous blood was collected from patients with CRC during surgery, and peripheral venous blood was collected at the same time. Three mL normal saline (0.9%) and 200 μL PFA (8%) were added to 5 mL EDTA-anticoagulated whole blood samples, which were then transferred to a filter with an 8 μm diameter aperture membrane. CTCs were captured on the membrane by a CTCBIOPSY device (YZYBIO Company, China). Given that captured cells on the membrane included CTCs but also normal blood cells, candidate CTCs were distinguished by Wright’s staining. After destaining, detection of HIF-1α expression was performed by immunofluorescence analysis.

All data are shown as means ± standard errors of the mean (SEM). A two-tailed Student’s t-test was used to compare variables of two groups, and one-way or two-way ANOVA were performed for multi-group comparisons. Correlation analysis used Pearson or Spearman correlation analysis. Patient survival data related to HIF-1α expression was evaluated by the Kaplan-Meier method with survival analysis using Log-rank (Mantel-Cox) testing. Significance of differences is marked ns = not significant, * p < 0.05, ** p < 0.01, and *** p < 0.001, and all p values < 0.05 were considered statistically significant. Statistical details are included in the respective figure legends.

To investigate the influence of metabolic reprogramming on 5-FU resistance in CRC, we generated three acquired 5-FU resistance (5-FU-R) CRC cell line models (HCT8, HCT15, and LoVo). We cultured wild-type (WT) cells with increasing 5-FU concentrations (10^− 8 M to 10^− 4 M) over approximately 8 months (Fig. S1a). We calculated the half maximal inhibitory concentration (IC₅₀) and found that 5-FU-R cells had resistance indexes of 100 to 500 at the end of 5-FU induction and measured after 2 weeks of drug withdrawal (Fig. 1a). WT cells usually grow and fuse into pieces, and the intercellular space was less distinct in in vitro culture. Phalloidin staining showed the 5-FU-R cells were more independent and stretched out compared with WT cells (Fig. S1b). EdU assay revealed an increase in 5-FU-R cell proliferation under control and 5-FU treatments compared with control cells with the respective treatments; treatment with 5-FU had no impact on 5-FU-R cells compared with untreated 5-FU-R cells (Fig. 1b and Fig. S1c). We further found that 5-FU treatment induced cell cycle arrest of WT cells in S phase while it had no effect on 5-FU-R cells (Fig. 1c and Fig. S1d). Western blot analysis showed WT and 5-FU-R cells had different regulations on cell cycle governors under control and 5-FU treatment, like CDK2, cyclin D1 and p21 (Fig. 1d). Moreover, WT cells displayed a higher apoptosis rate 5-FU treatment compared with 5-FU-R cells (Fig. 1e and Fig. S1e). Similar results were observed with the apoptosis markers Bcl-XL, cleaved caspase 3 and cleaved caspase 9 (Fig. 1f). Together, these findings indicate that 5-FU-R CRC cells show low response to high-dose 5-FU treatment and confirm successful in vitro cell model establishment.

Mitochondria are the center of cellular energy metabolism [23]. To determine whether 5-FU-R CRC cells showed altered glucose metabolism, we evaluated the status of mitochondria. Mitochondria were labeled using Mito-tracker to determine mitochondrial content. Flow cytometry revealed that 5-FU-R cells displayed markedly decreased mean fluorescence intensities compared with WT cells (Fig. 1g). We next visualized the mitochondria at the ultrastructural level by transmission electron microscopy. The mitochondria of 5-FU-R cells were pyknotic and showed vacuolization, ruptured membrane, cristae disorganization, fusion and low numbers compared with WT cells (Fig. 1h). The abnormal mitochondrial number and distribution in 5-FU-R cells pointed to potential mitochondrial dysfunction. The top biological function of mitochondria is oxidative metabolism, and five enzyme complexes of the mitochondrial respiratory chain are responsible for generating ATP by OXPHOS. The gene and protein expressions of mitochondrial enzymes (NDUFB8, SDHB, UQCRC1, COX4, and ATP5F1) were significantly down-regulated in 5-FU-R cells compared with controls (Fig. 1i, j). To directly assess mitochondrial respiration, we measured OCR. The 5-FU-R cells demonstrated significantly decreased OCR compared with WT cells (Fig. 1k). Basal respiration, maximal respiration, and spare capacity were also significantly reduced in 5-FU-R cells (Fig. S1f). These results show that 5-FU resistance is accompanied by abnormal mitochondrial structure and function. We observed that 5-FU-R cells did not exhibit reduced ATP production compared with WT cells (Fig. 1l). This suggests that 5-FU-R cells probably develop a metabolic shift and activate alternative pathways to increase ATP production to compensate for mitochondrial damage.

Energy metabolism plays an important role in the biological behaviors of tumors [8, 24]. To investigate the metabolic alterations underlying 5-FU resistance of CRC, we assessed the metabolism of two important energy substrates, glucose and lactate.

Although tumor cells are flexible in energy sources, glucose is the primary carbon source [6, 25]. High metabolic activity is often accompanied by high glucose uptake [26]. We evaluated uptake of the fluorescence-labeled glucose analogue 2-NBDG and found that 5-FU-R cells displayed significantly increased 2-NBDG uptake (Fig. 2a). We also observed increased fluorescence of the IRDye 800CW 2-DG optical probe in the subcutaneously implanted 5-FU-R cell model compared with the WT model (Fig. 2b). Glucose uptake changes might be attributed to expression changes of glucose transporters (GLUTs). Among GLUT1-4, GLUT1 was the most up-regulated in 5-FU-R cells (Fig. 2c and Fig. S2a). We then cultured cells with STF-31 [27] (a highly selective GLUT1 inhibitor, 10 μM) for 48 h. The 5-FU-R cells were more sensitive to STF-31 compared with WT cells (Fig. 2d). To assess the relevance between 5-FU resistance and glucose uptake, we isolated 5-FU-R cells with high and low GLUT1 expression by flow cytometry. We found that lower GLUT1 expression tended to indicate a higher 5-FU sensitivity (Fig. 2e).

Enhanced aerobic glycolysis, known as the Warburg effect, is a major metabolic phenotype in tumor cells [28]. Warburg effect is presenting as glucose addiction, and additional lactate flux was also observed. Here we offer a new perspective on lactate using the most recently reported literature: Tumor cells can utilize lactate as an energy substrate, and it is definitely not a waste end product of glycolysis. Therefore, we evaluated lactate metabolism in 5-FU-R cells by conducting intracellular lactate (Fig. S2b) and lactate release assays (Fig. 2f). The 5-FU-R cells displayed significantly increased lactate release in comparison with WT cells, while there were no consistent changes in intracellular lactate. Magnetic resonance spectroscopy demonstrated higher lactate concentration in the subcutaneously implanted tumors formed by 5-FU-R cells (Fig. 2g). To further explore the characteristics and regulation of lactate metabolism in 5-FU-R cells, the expression levels of monocarboxylic acid transporters (MCTs) were examined. We observed significant up-regulation of MCT1 and MCT4 in 5-FU-R cells (Fig. 2h and Fig. S2c). We then treated cells with AZD3965 [29] (a highly selective MCT1 inhibitor) and syrosingopine [30] (a MCT inhibitor, with far higher affinity for MCT4) alone and in combination for 72 h. All CRC WT and resistant cell lines were susceptible to syrosingopine. The 5-FU-R cells displayed higher sensitivity to syrosingopine compared with WT cells, and syrosingopine combined with AZD3965 exhibited higher activity in 5-FU-R cells compared with syrosingopine alone or AZD3965 alone (Fig. 2i). These results indicated that MCTs, in particular MCT4, are important for remodeling of metabolism in 5-FU-R cells. We performed flow sorting as described above, and a significantly increased 5-FU sensitivity was observed in 5-FU-R cells with low MCT4 expression (Fig. 2j).

Lactate dehydrogenase (LDH) is a main metabolic enzyme for glycolysis and lactate production [31]. Notably, 5-FU-R cells showed high LDH expression (Fig. S2d) and intracellular LDH catalytic activity was significantly enhanced (Fig. S2e). Full oxidation of glucose to CO₂ has been thought to provide energy to most cells, and lactate is a by-product of incomplete oxidation. Recent studies showed lactate can serve as an important carbon source under aerobic conditions, and intracellular lactate oxidation occurs in the mitochondria [32, 33]. These findings contradict our observations of mitochondrial damage and increased lactate flux in 5-FU-R cells at the same time. We thus examined the distribution of mitochondria and LDHA in cells. Despite the lower mitochondrial content in 5-FU-R cells, LDHA strongly co-localized with mitochondria (Fig. S2f). This finding suggests that mitochondria remain well lactate oxygenated under mitochondrial injury in 5-FU-R cells. Hence, our results indicate that MCTs and LDH mediated lactate exchange between the inside and outside of cells and maintain relatively constant lactate levels in 5-FU-R cells.

To analyze the dependence of 5-FU responsiveness on glucose and lactate metabolism, we cultured 5-FU-R and WT cell lines under low glucose (0.5 mM glucose) or exogenous lactate supplementation conditions (10 mM lactate) for 48 h. CRC cells were dependent on adequate glucose for viability, and 5-FU-R cells exhibited a more severe glucose addiction. When external glucose supplies are insufficient, lactate is more likely to become the alternative carbon source for cell survival in 5-FU-R cells (Fig. 2k). These results suggest that 5-FU-R cells have an increased dependence on glucose and lactate utilization, and the choice of energy substrates becomes much more flexible. Additionally, this metabolic plasticity is associated with sensitivity or resistance of 5-FU treatment.

The detailed glucose metabolic profiles in 5-FU-R cells were investigated using UHPLC-MS/MS followed by unsupervised hierarchical clustering. UHPLC-MS/MS analysis indicated differential metabolites of central carbon metabolism in 5-FU-R cells compared with WT cells (Fig. S3a). Analysis of intermediate metabolites of glucose metabolite pools revealed increased fluxes of glycolysis and PPP in 5-FU-R cells compared with WT cells (Fig. 3a). Metabolic activities are often determined by the metabolic enzymes. Thus, we examined the mRNA and protein expressions of enzymes involved in glucose metabolism. Both mRNA and protein levels of enzymes involved in glycolysis and PPP including hexokinase 2 (HK2), enolase 1 (ENO1), pyruvate kinase M2 (PKM2), and glucose-6-phosphate dehydrogenase (G6PD) were up-regulated in 5-FU-R cells compared with WT cells (Fig. 3b-d). Hence, we speculated that glycolysis and the PPP are activated as a compensatory mechanism for the impaired mitochondrial respiration to ensure energy supply in 5-FU-R cells. This may also explain the increased fluxes of glucose and lactate in 5-FU-R cells.

We also determined the ECAR to assess glycolytic stress and found that 5-FU-R cells showed a trend toward a higher ECAR (Fig. 3e). Increased basal glycolysis and glycolytic capacity were observed, and the glycolytic reserve was markedly diminished in 5-FU-R cells (Fig. S3b). To determine whether glycolysis and PPP are critical for 5-FU-R cell survival, we cultured cells with 3-bromopyruvatic acid [34] (a selective glycolysis inhibitor) or 6-aminonicotinamide [35] (a competitive inhibitor of G6PD) for 48 h. Despite the abundance of oxygen, 5-FU-R cells relied heavily on glycolysis and PPP pathways for survival (Fig. 3f, g).

These results indicate that a conversion to glycolysis and PPP occurs in the metabolic reprogramming of 5-FU-R CRC cells. Prolonged exposure to 5-FU leads to progressive irreversible mitochondrial damage in CRC cells. Metabolic reprogramming is driven by mitochondrial dysfunction and damage, and the adaptive augmented glycolysis and PPP might be associated with 5-FU resistance.

We next examined whether metabolic reprogramming of glucose is involved in the pathogenesis of 5-FU resistance in CRC in both animal models and human. We detected the expressions of glycolytic enzymes and membrane transporters, including GLUT1, HK2, PKM2, LDHA, and MCT4, in subcutaneous transplantation tumor models from WT and 5-FU-R HCT8 cells by IHC. We also examined three groups of Dukes’ C or D stage CRC patients: the no chemotherapy group (without preoperative chemotherapy), response group (good response to preoperative fluorouracil analog–based chemotherapy), and no response group (poor response to preoperative fluorouracil analog–based chemotherapy) (Table S1). The expressions of glycolytic enzymes and membrane transporters were assessed in primary tumors of the three CRC patient groups using IHC. Consistent with the in vitro 5-FU-R CRC cell lines, the protein levels were elevated in both 5-FU-R HCT8 tumors (Fig. 4a) and the no response CRC patient group (Fig. 4b). 5-FU-R CRC cells displayed high glycolysis even compared with WT CRC cells that already show increased glycolysis.

Increased aerobic glycolysis has been associated with the acquisition of a number of tumor phenotypes, including chemotherapy resistance. We further examined the mechanisms of 5-FU resistance by investigating glycolysis regulation. The HIF-1α transcription factor is a master glycolytic activity regulator that upregulates genes encoding glycolytic enzymes and membrane transporters [13, 14]. We observed significantly higher levels of HIF-1α in 5-FU-R HCT8 transplantation tumors compared with WT models (Fig. 4a). The CRC no response patient group demonstrated a markedly increased HIF-1α protein and mRNA expression compared with the other two groups (Fig. 4b-d).

We further examined CTCs in the blood of peripheral veins and tumor reflux veins (such as the inferior mesenteric vein in rectal cancer) in the three CRC patient groups (Fig. 4e). The detection rate of CTCs did not differ significantly among the three groups, and the no response group had higher proportions of HIF-1α-positive CTCs both in peripheral venous blood and tumor reflux venous blood compared with the other two groups (Fig. 4f, g). These results illustrated that resistance of CRC to fluorouracil analog was associated with increased expression of HIF-1α in tumor cells.

Furthermore, CRC patients subjected to preoperative fluorouracil analog–based chemotherapy with high HIF-1α expression in primary tumors or CTCs demonstrated a poor disease-free survival after surgery (Fig. 4h-j). Recent studies showed that CTCs are a strong independent prognostic factor for progression-free survival and overall survival of CRC patients [36, 37]. We found significant correlations between HIF-1α expression of CTCs and disease-free survival in patients previously treated with fluorouracil analog, especially CTCs in the reflux veins of tumor (Fig. 4j).

We examined whether HIF1A mRNA levels showed predictive value for 5-FU chemotherapeutic efficacy using the public Gene Expression Omnibus databases (GSE69657, GSE104645). The results revealed no differences in HIF1A expression in primary tumors before chemotherapy between patients who responded and those who did not respond to fluorouracil analog–based chemotherapy (Fig. S4a). This observation suggested that high HIF-1α expression is a result from long-term exposure to fluorouracil analog (5-FU or Capecitabine) in CRC patients with acquired resistance and HIF-1α expression in primary tumors before exposure to fluorouracil analog may not have a predictive value for chemotherapy efficacy.

These results indicate that failure of fluorouracil analog-based chemotherapy in CRC is accompanied by increased HIF-1α levels. Thus, HIF-1α may serve as a potential biomarker for assessment and prognosis in CRC patients with fluorouracil analog treatment.

We further evaluated the functional role of HIF-1α in 5-FU-R CRC cells. The 5-FU-R cells express elevated HIF-1α protein and mRNA levels under normoxia (Fig. 5a, b). Immunofluorescence showed that HIF-1α localized in the cytoplasm and nucleus in WT cells, whereas HIF-1α expression was strongly nuclear in 5-FU-R cells (Fig. 5c). Western blot also showed very high expressions of nuclear HIF-1α in 5-FU-R cells (Fig. S4b).

Tumor cells in vitro and in vivo show a notable difference, as tumor cells are exposed to a complex oxygen microenvironment in vivo. We observed that HIF-1α expression in 5-FU-R cells showed increased responses to 1% oxygen (Fig. S4c), suggesting that the high HIF-1α expression in 5-FU-R cells is independent of oxygen concentration. HIF-1α is readily degraded under normoxia conditions [13]. We performed experiments with cycloheximide, a protein synthesis inhibitor, and found that HIF-1α was degraded quickly in WT cells in normoxia, whereas it was much more stable in 5-FU-R cells (Fig. 5d). Taken together, these results show that HIF-1α protein is nuclear and stabilized in 5-FU-R cells.

To further examine the effects of HIF-1α on 5-FU resistance and glucose metabolism in 5-FU-R cells, we stably knocked down endogenous HIF-1α using lentivirally-expressed HIF1A shRNA (shHIF1A) (Fig. S4d). HIF1A knock-down partially reversed 5-FU resistance in the 5-FU-R cell lines (Fig. 5e). We investigated HIF-1α protein levels in 11 CRC cell lines and correlated them with the IC₅₀ of 5-FU (R² = 0.5454, P = 0.0094) (Fig. 5f and Fig. S4e, f); 5-FU resistance showed a direct correlation with HIF-1α expression. Based on this, it is well-documented that HIF-1α expression level can affect 5-FU sensitivity in CRC cells.

We then evaluated the influence of HIF-1α on glucose metabolism in 5-FU-R cells. HIF1A knock-down in 5-FU-R cells resulted in significantly decreased 2-NBDG uptake and lactate release compared with control cells (Fig. 5g, h). HIF1A knock-down decreased glycolysis and glycolytic capacity as detected by OCR and ECAR, but showed no significant effect on mitochondrial respiration (Fig. 5i, j). HIF-1α downstream glycolytic enzymes and transporters including GLUT1, HK2, PKM2, LDHA and MCT4 were down-regulated in shHIF1A 5-FU-R cells (Fig. 5k). These results suggest that HIF-1α mediates 5-FU resistance by glucose metabolic reprogramming.

To evaluate the influence of HIF-1α on 5-FU resistance of CRC cells in vivo environments, we established subcutaneous transplantation tumor models of WT and 5-FU-R HCT8 cells with or without stable HIF1A knock-down in nude mice. Tumor-bearing mice were treated with 5-FU or saline one week after implantation. We observed significant reduction in tumor volume and proliferation in 5-FU-treated WT HCT8-bearing mice, with no change in body weight. However, 5-FU failed to show effective antitumor efficacy in 5-FU-R HCT8-bearing mice. HIF1A knock-down slowed down tumor growth and diminished the proportion of Ki-67-positive cells in both WT and 5-FU-R groups. Tumor volume and proliferation of HIF1A knock-down tumors decreased significantly upon 5-FU treatment in both WT and 5-FU-R groups (Fig. 6a-e and Fig. S5b). knock-down of HIF1A caused a significant decrease in the expression of glycolytic enzymes and membrane transporters, including HIF-1α, GLUT1, HK2, PKM2, LDHA, and MCT4, in IHC (Fig. S5a). There were no significant changes in protein expressions after short-term 5-FU treatment compared with saline treatment (Fig. S5a).

To demonstrate the potential clinical value of HIF-1α as an intervention, we investigated whether pharmacological inhibition of HIF-1α in vivo had the same effect as HIF1A knock-down. We injected 5-FU, the HIF-1α inhibitor IDF-11774 [38] or saline in subcutaneous tumor models in nude mice starting one week after implantation. Tumor volume and proliferation were inhibited by IDF-11774 to the same extent as HIF1A knock-down in both WT and 5-FU-R groups (Fig. 6f-i and Fig. S5c, d). To further establish the value of pharmacological inhibition of HIF-1α in increasing 5-FU sensitivity, we selected a patient with rectal cancer (male, Dukes’ C) who did not respond to 5-FU-based preoperative neoadjuvant chemotherapy. We generated patient-derived xenografts in nude mice to mimic actual clinical presentation. The combination of 5-FU in combination with IDF-11774 markedly inhibited tumor growth and proliferation compared with 5-FU alone (Fig. 6j-m and Fig. S5e, f).

These findings indicate that HIF-1α gene knock-down and pharmacological inhibition are effective treatments for 5-FU-R CRC in vivo.

ROS plays an important role in tumorigenesis and tumor development [39]. ROS is linked with damaged and dysfunctional mitochondria [40], and the release of NADPH from oxidative PPP counteracts the excess ROS and helps maintain intracellular ROS balance [41]. These phenomena are in line with the observed mitochondrial damage and high levels of PPP in 5-FU-R cells, which suggests that 5-FU-R cells are in the high ROS load condition. We measured ROS levels by flow cytometry and found high ROS levels in 5-FU-R cells (Fig. 7a). We next considered whether impairment of ROS clearance was associated with 5-FU resistance. The expressions and activities of mitochondrial ROS-scavenging enzymes catalase (CAT), glutathione peroxidase (GPx), and superoxide dimutase 2 (SOD2) were significantly decreased in 5-FU-R cells (Fig. 7b and Fig. S6a, b), while the changes in cytoplasmic ROS-scavenging enzyme superoxide dimutase 1 (SOD1) were inconsistent among the different cell lines (Fig. 7b). Taken together, these data supported that both the increased generation of ROS and the destruction of mitochondrial ROS-scavenging enzyme system induced the accumulation of ROS in 5-FU-R cells in two different aspects.

The PI3K/Akt pathway plays a central role in the regulation of substance and energy metabolism [42]. Up-regulated HIF-1α expression and increased glycolysis in tumor cells are dependent on the activated PI3K/Akt pathway, regardless of oxygen levels [43]. We hypothesized that the PI3K/Akt pathway may promote HIF-1α-mediated glucose metabolic reprogramming and 5-FU resistance in 5-FU-resistant CRC. Western blot showed that phosphorylated PI3K (p-PI3K) and phosphorylated Akt (p-Akt) were up-regulated in 5-FU-R cells (Fig. 7c). In addition, IHC revealed p-Akt and HIF-1α expression in tumors of 27 CRC patients who received preoperative fluorouracil analog–based chemotherapy (Fig. S6c). Pearson correlation analysis showed that p-Akt/Akt was significantly positively correlated with HIF-1α (R² = 0.5387, P < 0.001) (Fig. 7d). Furthermore, the level of p-Akt dramatically decreased in 5-FU-R cells upon treatment with LY294002 [44] (a broad-spectrum inhibitor of PI3K) for 48 h, and HIF-1α protein and mRNA levels were decreased (Fig. 7e and Fig. S6d). Our results indicated that the activated PI3K/Akt pathway up-regulates HIF-1α in 5-FU-R cells. However, significant changes of phosphorylation levels of PI3K and Akt were not observed in 5-FU-R cells with HIF1A knock-down (Fig. S6e), suggesting that there is no feedback regulation between HIF-1α and the PI3K/Akt pathway.

Previous studies revealed that ROS directly activates PI3K to amplify its downstream signaling through reversible inactivation of the phosphatase and tensin homolog (PTEN) [45, 46]. Other reports established a reciprocal regulation of ROS and HIF-1α by complex interactions [17‐19]. The regulatory circuit between ROS and HIF-1α remains elusive due to the vast heterogeneity of tumors. We hypothesized that ROS-induced HIF-1α high expression in 5-FU-R CRC cells is mediated by the activated PI3K/Akt signaling pathway. To investigate the effects of ROS on the PI3K/Akt pathway and HIF-1α expression in 5-FU resistance, we generated cell models with decreased and increased levels of intracellular ROS. HIF-1α, p-PI3K, and p-Akt gradually increased in response to tert-butylhydroperoxide (t-BHP) from 0 μM to 100 μM in cultured WT HCT8 cells (Fig. 7f). Moreover, we detected decreased expression of HIF-1α, p-PI3K, and p-Akt in 5-FU-R cells treated with N-acetylcysteine (NAC, a ROS scavenger) (Fig. 7g). Thus, both PI3K/Akt pathway activity and HIF-1α expression were influenced by ROS. Collectively, these results suggested that ROS-induced HIF-1α high expression in 5-FU-R CRC cells is, to a certain extent, mediated via PI3K/Akt pathway activation.

We next verified if modulating ROS levels of CRC cells could improve 5-FU resistance and shift the glucose metabolic phenotype. Treatment with 100 μM t-BHP up-regulated ROS in WT cells, while 750 μM NAC diminished ROS in 5-FU-R cells. Thus, scavenging ROS in 5-FU-R cells can increase sensitivity to 5-FU, while accumulation of ROS in WT cells increased resistance to 5-FU (Fig. 7h). Furthermore, ROS elimination in 5-FU-R cells led to significantly decreased 2-NBDG uptake, lactate release, and expressions of glycolysis-related proteins in contrast to controls without ROS scavenger, while an enhanced glycolytic phenotype observed in WT cells cultured with t-BHP (Fig. 7i-k). Together these findings establish that the response of CRC cells to 5-FU can be controlled through modulation of intracellular ROS levels.

Aberrant activation of Wnt/β-catenin signaling is a critical factor for tumorigenesis and development [47]. Previous studies showed that β-catenin, the key molecule of Wnt signaling, interplays with HIF-1α in multiple physiological and pathological processes [48], and activated Wnt signaling pathway plays a role in chemoresistance [49]. Therefore, we hypothesized that β-catenin may affect the chemosensitivity of 5-FU through its interaction with HIF-1α. Western blot confirmed activated Wnt signaling pathway in 5-FU-R cells compared with WT cells (Fig. 8a). We examined β-catenin and found that its half-life was much longer in 5-FU-R cells in cycloheximide experiments (Fig. S7a). Immunofluorescence showed that β-catenin was located in the cell membrane, cytoplasm and nucleus in WT cells, while β-catenin was predominantly localized in the nucleus in 5-FU-R cells (Fig. 8b).

We also detected co-localization of HIF-1α and β-catenin in 5-FU-R cells (Fig. 8b). To further assess the effect of β-catenin on HIF-1α, 5-FU-R cells were transfected with siRNA targeting β-catenin (siCTNNB1). Knock-down of CTNNB1 caused a portion of HIF-1α protein to migrate to the cytoplasm (Fig. 8b). We also observed up-regulated cytosolic distribution and down-regulated nuclear distribution of HIF-1α in 5-FU-R cells with CTNNB1 knock down (Fig. 8c). Moreover, we examined the stability of HIF-1α in 5-FU-R cells following knock-down of β-catenin, and HIF-1α showed a short half-life in cells with β-catenin knock-down (Fig. 8d). These results indicated that β-catenin plays important roles in stabilization and nuclear translocation of HIF-1α in 5-FU-R CRC cells.

In particular, the interaction of β-catenin with specific receptors in the nucleus was dependent on the T cell factor/lymphoid enhancer-binding factor (TCF/LEF, hereafter referred to as TCF) [50]. We next examined the interaction of HIF-1α, β-catenin and TCF. We immunoprecipitated β-catenin and HIF-1α and detected binding in both WT and 5-FU-R cells (Fig. 8e, f and Fig. S7b, c). While HIF-1α/β-catenin complex did not bind TCF1 or TCF4 in WT cells, we found that TCF1, but not TCF4, interacted with the HIF-1α/β-catenin complex in 5-FU-R cells. This may suggest TCF1 contributes to the formation of HIF-1α/β-catenin transcriptional complex in 5-FU-R cells.

We next measured the protein expressions of β-catenin, TCF1, and HIF-1α in tumors of 27 CRC patients who received preoperative fluorouracil analog–based chemotherapy by IHC (Fig. S7d). Spearman rank correlation analysis showed a significant positive correlation between IHC scores of HIF-1α and β-catenin (r = 0.554, p = 0.003) (Fig. 8g) as well as HIF-1α and TCF1 (r = 0.470, p = 0.013) (Fig. 8h). Together, this suggests that activation of the Wnt signaling pathway and β-catenin expression may play a part in HIF-1α stabilization in 5-FU-R cells.

To investigate whether the pharmacological inhibition of β-catenin affects the metabolic phenotype and 5-FU resistance in 5-FU-R cells, we cultured 5-FU-R cells with MSAB [51] (a selective inhibitor of Wnt/β-catenin signaling) to decrease the expression of β-catenin. Suppressed β-catenin resulted in significantly diminished 5-FU resistance in 5-FU-R cells (Fig. 8i). Furthermore, 2-NBDG uptake, lactate release, and expressions of glycolysis-related proteins were significantly decreased in β-catenin-suppressed 5-FU-R cells (Fig. 8j-l). These results indicate that inhibition of β-catenin leads to decreased 5-FU resistance and glycolysis in 5-FU-R cells.