Rapamycin suppresses small bowel adenocarcinoma HUTU 80 cells proliferation by inhibiting hypoxia-inducible factor-1α mediated metabolic reprogramming

Abstract

BACKGROUND

Small bowel adenocarcinoma (SBA) is a rare malignant tumor of gastrointestinal tract. Currently, there is no standard treatment approach for late-stage SBA, which lead to poor outcome and prognosis. Rapamycin is an immunosuppressive agent that has been reported to inhibit the proliferation of tumor cells. However, whether rapamycin inhibit the growth of SBA remains to be investigated.

AIM

To observe the inhibitory effect of rapamycin on small intestinal adenocarcinoma cells.

METHODS

Methylthiazolyldiphenyl-tetrazolium bromide assay, colony formation assay, cell cycle analysis, and glycolysis assay were used to observe the phenotypic changes of rapamycin-treated HUTU 80 cells. RNA sequencing and untargeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) metabolomics were also used to find the potential targets of action of rapamycin in inhibiting HUTU 80 cells proliferation, and validate potential targets by quantitative polymerase chain reaction and western blotting. The construction of a subcutaneous HUTU 80 xenograft in BALB/c nude mice was used to explore the tumor suppression effect of rapamycin.

RESULTS

Rapamycin inhibited HUTU 80 cell proliferation in vitro and in vivo. Rapamycin inhibited the migration, invasion, and glycolysis of HUTU 80 cells, and induced cell cycle arrest. RNA sequencing and untargeted UHPLC-MS/MS metabolomic analysis indicated that the mechanism of rapamycin action was linked to the hypoxia-inducible factor (HIF)-1α signaling pathway and the related gluconeogenesis/glycolysis pathways. Subsequent experiments found that rapamycin downregulated the messenger RNA expression of HIF-1α and its downstream target genes, LDHA, PDK1 and VEGF. Additionally, rapamycin inhibited expression of phosphorylated mammalian target of rapamycin (mTOR), phosphorylated-70 kDa ribosomal protein S6 kinase (p70S6k), phosphorylated eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and HIF-1α proteins in vitro and in vivo.

CONCLUSION

Downregulation of mTOR/p70S6k/4E-BP1/HIF-1α signaling pathway activation, leading to decreased glycolysis and cell cycle arrest, may be the pivotal mechanism by which rapamycin inhibits SBA.

Key Words: Rapamycin; Small bowel adenocarcinoma; Mammalian target of rapamycin/hypoxia-inducible facto-1α; Metabolic reprogramming; Warburg effect; Cell cycle arrest; Xenograft

Core Tip: Rapamycin is an immunosuppressive agent that inhibits the proliferation of tumor cells. HUTU 80 cells were used as a representative model for small bowel adenocarcinoma (SBA). Rapamycin inhibited the proliferation, migration, and invasion of HUTU 80 cells and downregulated glycolysis levels and cell cycle arrest. Transcriptomic and metabolomic analyses were used to find the potential targets of action of rapamycin in inhibiting HUTU 80 cell proliferation. The key mechanism of rapamycin against SBA is related to the mammalian target of rapamycin/70 kDa ribosomal protein S6 kinase/4E-binding protein 1/hypoxia-inducible factor-1α signaling pathway.

INTRODUCTION

Small bowel adenocarcinoma (SBA) is a rare malignant tumor with a poor prognosis[1]. Tumors occur less frequently in the jejunum and ileum, and > 50% of SBA cases occur in the duodenum, accounting for 30%-40% of small intestinal tumors[2]. At present, surgery is the first choice of treatment for patients with SBA. However, since the symptoms of SBA are atypical, there is still no effective clinical screening strategy. Therefore, most patients with SBA are diagnosed at stages III or IV, by when they have missed the optimal time for surgical intervention. In addition, there is no standardized chemotherapy regimen for SBA, due to a lack of prospective studies. Adjuvant therapy (chemotherapy or chemoradiotherapy) does not significantly improve overall survival of patients with advanced-stage SBA[3,4]. At present, the 5-year survival rate for patients with advanced-stage SBA is < 50%[5]. PIK3CA and KRAS mutations in SBA lead to persistent mammalian target of rapamycin (mTOR) pathway activation, which may contribute to both tumor development and advancement[6]. The incidence of SBA has been rapidly increasing in recent years[7]. Therefore, identifying drugs that can effectively inhibit SBA development and prolong patient survival is a unique challenge.

Metabolic reprogramming is a common microenvironmental event in tumor development, which is crucial for cancer cells to maintain uncontrolled proliferation and survival under stressful conditions. Unlike normal cells that derive energy from oxidative phosphorylation, cancer cells preferentially switch from oxidative phosphorylation to aerobic glycolysis even under normoxic conditions. This is a distinctive metabolic feature known as the Warburg effect, which results from the interplay between pathways such as hypoxia-inducible factor (HIF)-1, phosphoinositide 3-kinase/protein kinase B/mTOR, and other epigenetic mechanisms[8,9]. The Warburg effect is the main driving factor in cancer progression and is an important reason for the poor prognosis caused by the development of drug resistance to traditional therapies[10-12]. Identifying drugs targeting pathways related to metabolic reprogramming appears to be a promising approach for anticancer treatment.

Rapamycin, also known as sirolimus, is a highly specific mTOR inhibitor originally discovered from fungi in soil samples from Easter Island in the 1970s. It has been commonly used as an immunosuppressant for transplant rejection treatment for decades[13]. Rapamycin has antitumor activity and was approved to treat lymphangioleiomyoma by the United States Food and Drug Administration in 2015[14]. In addition, rapamycin has shown a therapeutic effect against osteosarcoma and infantile kaposiform hemangioendothelioma in clinical trials[15,16]. Our previous study also showed that rapamycin can inhibit B16 melanoma cell proliferation in vitro and in vivo[17]. It is unclear whether rapamycin can be used for the treatment of SBA. The multifaceted effects of rapamycin on tumor cells encompass the inhibition of proliferation, invasion, and migration, induction of cell cycle arrest, and suppression of angiogenesis[18,19]. Rapamycin also affects metabolic reprogramming by reducing glycolysis[20]. Rapamycin causes metabolic changes that inhibit tumor progression in certain glioma models and IDH1-mutant human fibrosarcoma models[21,22]. HIF-1α is an important regulator of glycolysis[23]. Everolimus, a derivative of rapamycin, blocks HIF-1α expression in renal cell carcinoma when combined with temsirolimus[24]. Rapamycin analogs reduce HIF-1α expression but not HIF-2α in renal cell carcinoma[25]. We speculate that rapamycin may affect the metabolic reprogramming of tumor cells by regulating HIF-1α expression. The identification and characterization of the potential antitumor targets of rapamycin warrant further investigation.

In the present study, a representative HUTU 80 cell line was used to construct a humanized SBA model, and the inhibitory effect of rapamycin on HUTU 80 cell activity was investigated in vitro and in vivo. The mechanism of rapamycin action was also explored using bioinformatics technology as well as molecular biology. The results indicated that rapamycin inhibited HUTU 80 cell proliferation, invasion migration, and glycolysis, which may be related to downregulation of the mTOR/HIF-1α pathway.

MATERIALS AND METHODS

Cell culture

The human duodenal adenocarcinoma HUTU 80 cells were purchased from China Meisen CTCC (cat. No. CTCC-400-0024). HUTU 80 cells were cultured in Dulbecco’s modified Eagle’s medium (cat. No. C1995500BT; Gibco; Thermo Fisher Scientific) supplemented with 1% penicillin-streptomycin and 10% fetal bovine serum (cat. No. 164210-50; Procell Life Science and Technology Co. Ltd.), and incubated in a carbon dioxide (CO₂) incubator at 37 °C. The medium was changed every 1-2 days to maintain optimal cell proliferation. When the cell confluence reached 80%-90%, cells were passaged using 0.25% trypsin (cat. No. C25200-056; Gibco; Thermo Fisher Scientific) for digestion and subculture. The mycoplasma contamination test carried out for all cells yielded negative results.

Drugs

Rapamycin (cat. No. HY-10219; MedChemExpress) was prepared using dimethylsulfoxide (DMSO) to create a 100 mmol/L concentrated stock solution and stored at -20 °C. The solution was further diluted in culture medium to a concentration range of 10^-3-10⁵ nM for in vitro experiments. For in vivo studies, drug solutions were prepared in anhydrous ethanol and phosphate-buffered saline (PBS) at 1 mg/mL and 3 mg/kg, respectively. These solutions were stored at -20 °C until required.

In vitro cell viability assay

Cells in the logarithmic growth phase were seeded in a 96-well plate at 10000 cells/well in 200 μL overnight, and treated with different doses of rapamycin (10^-3-10⁵ nM) for 48 hours. Then, 20 μL 5 mg/mL methylthiazolyldiphenyl-tetrazolium bromide (MTT) working solution (cat. No. HY-15924; MedChemExpress) was added to each well and incubated for 4 hours. Subsequently, 150 μL DMSO was added to dissolve the purple formazan crystals in each well, and the cells were incubated in the dark for 15 minutes. The absorbance was measured at 492 nm using a microplate reader (Multiskan FC; Thermo Fisher Scientific).

Colony formation

Cells were seeded in a 12-well plate, incubated overnight until cell adherence, treated with 0, 1, 10 and 100 nM rapamycin, and incubated at 37 °C, 5% CO₂ for 14 days until visible clones were observed with the naked eye. Cells were fixed with 4% paraformaldehyde (cat. No. BL539A; Biosharp Life Sciences) and stained with 0.1% crystal violet (cat. No. BL802A; Biosharp Life Sciences). Finally, the number of clones was calculated and analyzed.

Cell cycle analysis

Cells were pretreated with 0, 1, 10 and 100 nM rapamycin in a six-well plate for 48 hours. Cells were digested and collected, transferred to Eppendorf tubes, and centrifuged at 1000 g at 4 °C for 5 minutes. The supernatant was discarded, cells were washed with cold PBS, centrifuged at 1000 g at 4 °C for 5 minutes, repeated twice. Subsequently, 1 mL ice-cold 70% ethanol was gently added and mixed, and cells were fixed overnight at 4 °C. Cells were centrifuged at 1000 g at 4 °C for 5 minutes. The supernatant was discarded and cells were washed with PBS. Staining buffer (500 μL) (cat. No. C1052; Beyotime Institute of Biotechnology) was added to each sample, along with 25 μL propidium iodide staining solution (20) and 10 μL RNase A (50). The samples were incubated at 37 °C in the dark for 30 minutes, and analyzed using flow cytometry (NovoCyte 2040R with FlowJo version 10.9; ACEA Bioscience).

Cellular scarring

Cells in the logarithmic growth phase were seeded in a six-well plate and allowed to adhere overnight. Scratches were made with a 200-μL pipette tip along a ruler. Cells were washed three times with PBS, then incubated in serum-free medium with rapamycin at 0, 1, 10, or 100 nM for 48 hours. Image analysis was conducted under a light microscope at 0 and 48 hours. Cell migration rate = (initial scratch area - area at time x)/initial scratch area, with each group having three replicates.

Transwell invasion assay

Cells in the logarithmic growth phase were selected. A cell suspension was made in serum-free medium containing 0, 1, 10, or 100 nM rapamycin. Cells were added to the upper chambers of a 24-well plate (precoated with Matrigel), and 500 μL complete medium (containing 10% FBS) was added to the lower chambers. The cells were incubated at 37 °C for 48 hours, fixed with 4% paraformaldehyde, stained with 0.1% crystal violet, and dried for 10 minutes. Finally, cells were counted in five randomly selected fields under a light microscope.

Reverse transcription-quantitative polymerase chain reaction

Total RNA was extracted from HUTU 80 cells treated with 0, 1, 10, and 100 nM rapamycin using TRIzol reagent (Invitrogen; Thermo Fisher Scientific) and the A260/A280 ratios of each group of total RNA were measured. A PrimeScript RT reagent kit (cat. No. RR047A; Takara Bio) was used to reverse transcribe RNA into complementary DNA. Quantitative polymerase chain reaction (qPCR) was performed on a real-time PCR detection system (Light Cycler 480II; Roche Diagnostics GmbH) using the TB Green Premix Ex Taq^™ II (cTli RNaseH Plus; cat. No. RR820A; Takara Bio). Messenger RNA (mRNA) expression was analyzed using the 2^-ΔΔCq method with β-actin serving as the internal control for mRNA expression[26]. The primer sequences are listed in Table 1.

Table 1 Primer sequences used in this study.

Gene	Primer sequence (5’-3’)	Accession
β-actin	F: CGGGAAATCGTGCGTGAC	NM_001101.5_
	R: CAGGAAGGAAGGCTGGAAG
HIF-1α	F: GAACGTCGAAAAGAAAAGTCTCG	NM_181054
	R: CCTTATCAAGATGCGAACTCACA
LDHA	F: ATGGCAACTCTAAAGGATCAGC	NM_001165415
	R: CCAACCCCAACAACTGTAATCT
MMP2	F: CCCACTGCGGTTTTCTCGAAT	NM_001302510.2
	R: CAAAGGGGTATCCATCGCCAT
VEGF	F: ACGAACGTACTTGCAGATGTGA	NM_001025366.3
	R: GCAGCGTGGTTTCTGTATCG
PDK1	F: GGATTGCCCATATCACGTCTTT	XM_047444739.1
	R: TCCCGTAACCCTCTAGGGAATA

HIF-1α: Hypoxia-inducible factor-1α; F: Forward; R: Reverse.

Western blotting

Total protein was extracted from cells or mouse tumor tissue using protein lysis buffer containing protease inhibitor (cat. No. BL507A; Biosharp Life Sciences) and phosphatase inhibitor (cat. No. BL615A; Biosharp Life Sciences). The concentration of total protein was determined using a bicinchoninic acid protein quantification kit (cat. No. BL521A; Biosharp Life Sciences), and 40 μg protein samples were prepared for sodium dodecyl sulfate-polyacrylamide gel electrophoresis using a gel preparation kit (cat. No. P0012A; Beyotime Institute of Biotechnology). The samples were transferred to a polyvinylidene difluoride membrane, blocked with rapid blocking buffer (cat. No. P0252; Beyotime Institute of Biotechnology) for 15 minutes at 4 °C, incubated overnight with antibodies including cyclin-dependent kinases 2 (CDK2) (cat. No. 60312-1-Ig; ProteinTech Group, diluted 1:1500), mTOR (cat. No. AF6308; Affinity Biosciences, diluted 1:1500), phosphorylated (p)-mTOR (cat. No. AF3308; Affinity Biosciences, diluted 1:1500), 70 kDa ribosomal protein S6 kinase (p70S6k) (cat. No. AF6226; Affinity Biosciences, diluted 1:1500), p-p70S6k (cat. No. AF3228; Affinity Biosciences, diluted for 1:1500), eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) (cat. No. AF6432; Affinity Biosciences, diluted 1:1500), p-4E-BP1 (cat. No. AF3830; Affinity Biosciences, diluted 1:1500), HIF-1α (cat. No. BF8002; ProteinTech Group, diluted 1:10000), and β-actin (cat. No. 66009-1-lg; ProteinTech Group, diluted 1:1500). The membranes were washed three times with PBS-0.05% Tween 20, followed by incubation at room temperature for 2 hours with horseradish-peroxidase-conjugated anti-rabbit (cat. No. SA00001-2; ProteinTech Group, diluted 1:10000) or anti-mouse secondary antibodies (cat. No. SA00001-1; ProteinTech Group, diluted 1:10000). After washing with PBS three times, the membrane was subjected to imprint detection using an enhanced chemiluminescence kit (cat. No. BL520A; Biosharp Life Sciences). ImageJ software (National Institutes of Health) was used for semi-quantitative analysis of protein bands[27].

RNA sequencing and bioinformatics analysis

Total RNA was extracted from cells treated with and without 100 nM rapamycin using TRIzol reagent and subjected to high-throughput sequencing at Jikai Genetics in Shanghai, as previously described[28]. RNA sequencing (RNA-Seq) was performed on the Illumina NovaSeq platform (150 bp paired-end reads), with an average sequencing depth of 50 million reads per sample. Raw reads were subjected to quality control using FastQC (v0.11.9), and high-quality paired-end reads were aligned to the reference genome using HISAT2 (v2.0.5). The original RNA-Seq data were processed using a standard RNA-Seq analysis workflow. Identification of differentially expressed genes (DEGs) was based on a |log2 (fold change) | ≥ 0 and P ≤ 0.05. DEGs between the samples were annotated and subjected to enrichment analysis using databases such as Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). To visualize the data, heatmaps, Venn diagrams and volcano plots were created using R package[29].

Metabolite extraction and untargeted metabolomics analysis

The cell samples were placed in liquid nitrogen for rapid freezing. Following thawing, the samples were centrifuged at 7500 g at 4 °C for 10 minutes and the supernatant was freeze-dried to obtain a powder. The samples were dissolved in 10% methanol according to the sample volume, and subjected to liquid chromatography-tandem mass spectrometry analysis, as previously described[30]. Hypersil Goldcolumn (100 mm, 2.1 mm, 1.9 mm) using a 12-minute linear gradient at a flow. Q ExactiveTMHF mass spectrometer was operated in positive/negative polarity mode with spray voltage 3.5 kV, capillary temperature 320 °C, sheath gas flow rate 35 psi, and aux gas flow rate 10 L/minute, S-lens RF level 60, and aux gas heater temperature 350 °C. The raw data files were imported into CD 3.3 database software for procession[31], resulting in identification and relative quantification of metabolites. Identified metabolites were annotated using the KEGG (https://www.genome.jp/kegg/pathway.html), Human Metabolome Database (https://hmdb.ca/metabolites) and LIPID MAPS (https://www.lipidmaps.org) databases, and heatmaps, Venn diagrams and volcano plots were generated using R package.

Detection of glycolytic metabolism

Glucose consumption in HUTU 80 cells treated with 0, 1, 10, and 100 nM rapamycin was measured using a glucose assay kit (cat. No. S0201S; Beyotime Institute of Biotechnology). The cell culture medium was collected to assess the decrease in glucose concentration. Lactate production in the cell culture medium was measured using a lactate assay kit (cat. No. BY-JZF0419; Nanjing Byabscience Biotechnology Co. Ltd.). Adenosine triphosphate (ATP) levels were measured using an ATP assay kit (cat. No. S0026B; Beyotime Institute of Biotechnology).

Heterogeneous model transplantation analysis

A total of 18 male BALB/c SPF nude mice (age, 4-5 weeks; weight, 16 g) were purchased from SPF Biotechnology Co. Ltd., and subjected to a 12-hour light/dark cycle at room temperature under sterile conditions with adequate food and water. The study was conducted in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health, eighth edition, 2010, and complied with the ARRIVE guidelines and the AVMA euthanasia guidelines 2020. The animal experiments were approved by the Ethics Committee of Hainan Medical University (2024 Animal Ethics Preliminary Examination No. 568). All protocols were in accordance with the approved guidelines and regulations. HUTU 80 cells in the logarithmic growth phase were subcutaneously inoculated into nude mice (2 × 10⁶ cells/mouse), and when the tumor volume grew to approximately 50 mm³, the nude mice were randomly divided into three groups (control, low-dose rapamycin, and high-dose rapamycin) with six mice/group. The low- and high-dose rapamycin groups were intraperitoneally injected with 1 and 3 mg/kg rapamycin, respectively, for 12 consecutive days, while the control group was given PBS alone for 12 days. The weight and diameter of the transplanted tumor were recorded daily to calculate the tumor size. Tumor volume was calculated as follows: Tumor volume (mm³) = [length (mm) × width (mm) × width (mm)]/2. All mice were humanely killed by an overdose of an intravenous injectable anesthetic (sodium pentobarbital, 150 mg/kg) on day 13 after treatment, when the tumor diameter of control mice reached the execution criteria (15 mm), and the tumors were removed, photographed, and weighed. All animals were alive until this time.

Hematoxylin and eosin staining

The mouse heart, liver, spleen, lungs, and kidneys were removed from the mice after death, and the organs were washed with PBS. These organs were subsequently fixed in 10% formalin, dehydrated with different concentrations of ethanol and xylene, and embedded in paraffin. Tissue sections were prepared and stained with hematoxylin and eosin (HE). The microscopic field of view images of HE-stained samples was analyzed under a light microscope.

Statistical analysis

All experiments were conducted at least three times, and data are presented as mean ± SD. Statistical analysis was performed using GraphPad Prism (version 9.5; Dotmatics). Analysis of variance followed by Tukey’s post hoc test was used for multiple comparisons. P < 0.05 was considered to indicate a statistically significant difference.

RESULTS

Rapamycin inhibited HUTU 80 cell proliferation

MTT assay was conducted to determine the effect of rapamycin on HUTU 80 cell viability. Rapamycin had a dose-dependent inhibitory effect on HUTU 80 cell proliferation (Figure 1A). The IC₅₀ was 112.73 nM (Figure 1B). The colony formation assay revealed that treatment with 1, 10 and 100 nM rapamycin led to a significant decrease in colony numbers of HUTU 80 cells compared with the control group (Figure 1C and D). These results suggested that rapamycin inhibited the proliferation of HUTU 80 cells.

Figure 1 Effects of rapamycin on HUTU 80 cells proliferation. A: Methylthiazolyldiphenyl-tetrazolium bromide assay was used to assess the effect of rapamycin (RAPA) on the proliferation of HUTU 80 cells at 48 hours; B: Calculation of the IC₅₀ of RAPA on cells after 48 hours; C: Colony formation assay was used to assess the effect of RAPA on cell proliferation; D: Colony statistical chart. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. ^cP < 0.001. RAPA: Rapamycin; NS: No significance.

Rapamycin inhibited HUTU 80 cell migration and invasion

The wound healing and Transwell assays were performed to evaluate the effect of rapamycin on HUTU 80 cell migration and invasion. Compared with the untreated group, 1, 10, and 100 nM rapamycin inhibited the migration and invasion of HUTU 80 cells after 48 hours (Figure 2A-D). qPCR revealed there was a significant decrease in MMP2 mRNA levels following rapamycin treatment (Figure 2E). MMP2 is expressed at high levels in intestinal tumors and is particularly important during tumor invasion, progression, and metastasis[32]. These results indicated that rapamycin inhibited the migration and invasion of HUTU 80 cells.

Figure 2 Effects of rapamycin on migration and invasion of HUTU 80 cells. A: Detection of the effect of rapamycin (RAPA) on cell migration ability through a wound healing assay; B: Assessment of the influence of RAPA on cell invasion capabilities using Transwell assay; C: Statistical chart of the cell migration ratio; D: Statistical chart of cell invasion ability; E: Quantitative polymerase chain reaction was used to evaluate the messenger RNA expression level of MMP2. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. ^cP < 0.001. MMP: Matrix metalloproteinase; RAPA: Rapamycin.

Rapamycin induced cell cycle arrest in HUTU 80 cells in vitro

Cell cycle analysis was performed to observe the effect of rapamycin on HUTU 80 cell cycle. Flow cytometry indicated that rapamycin increased the percentage of HUTU 80 cells in the G₁ phase, but decreased the percentage of cells in S phase (Figure 3A and B). Rapamycin induced G₁ phase arrest of HUTU 80 cells in a dose-dependent manner. Simultaneously, western blotting was used to assess cell cycle protein expression. There was downregulation of the cell cycle protein CDK2 expression after rapamycin treatment (Figure 3C and D). These results suggested that rapamycin induced G₁ phase arrest in HUTU 80 cells.

Figure 3 Effects of rapamycin on cell cycle of HUTU 80 cells. A: Flow cytometry was used to assess cell cycle changes; B: Statistical map of cell cycle distribution; C: Detection of protein expression of cell cycle proteins by western blotting; D: Statistical graph of protein expression. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. ^cP < 0.001. PI-A: Propidium iodide-area; RAPA: Rapamycin; NS: No significance; CDK2: Cyclin-dependent kinases 2.

Hypoxia-related pathway in rapamycin inhibition of HUTU 80 cell proliferation

To explore the potential mechanism of rapamycin inhibition of HUTU 80 cell proliferation, high-throughput sequencing was used for RNA-Seq analysis to examine the transcriptome of HUTU 80 cells after treatment with 100 nM rapamycin. There were 875 DEGs identified in the rapamycin treatment group; among which, 282 were upregulated and 593 downregulated (Figure 4A). According to GO and KEGG enrichment analysis, 15 significantly enriched items were related to antitumor effects (P < 0.05; false discovery rate < 0.05), including five biological processes, response to hypoxia, cellular amino acid metabolic process, angiogenesis, cellular amino acid biosynthetic process, and monosaccharide metabolism; five cellular components, transmembrane transporter complex, neuron cell body, exosome, endoplasmic reticulum lumen, and extracellular matrix; and five molecular functions, protein kinase regulator activity, transcription activator activity, oxidoreductase activity, kinase inhibitor activity, and cytokine receptor binding (Figure 4B). HUTU 80 cells treated with rapamycin exhibited enrichment of the HIF-1α signaling pathway and the glycolysis/gluconeogenesis pathway (Figure 4C). Similarly, 12 genes related to regulating HIF-1α and glycolysis/gluconeogenesis were identified in rapamycin-treated HUTU 80 cells; among which, there were 10 downregulated and two upregulated genes (Figure 4D). qPCR was performed to evaluate the mRNA expression of key genes related to HIF-1α and glycolysis/gluconeogenesis, including HIF-1α, PDK1, LDHA, and VEGF. Expression of HIF-1α, PDK1, LDHA, and VEGF was significantly downregulated in the rapamycin-treated HUTU 80 cells (Figure 4E). Therefore, it was hypothesized that the hypoxia-related pathway may be a potential critical target by which rapamycin acts on HUTU80 cells.

Figure 4 RNA sequencing results of rapamycin treatment with HUTU 80 cells. A: Volcano plot showed the number of differentially expressed genes (DEGs) in the rapamycin (RAPA) group and the control group; B: Gene Ontology enrichment analysis related to antitumor functions; C: Selection of the top 10 Kyoto Encyclopedia of Genes and Genomes pathways related to antitumor effects; D: Heatmap displayed DEGs involved in the hypoxia-inducible factor (HIF)-1α and glycolysis/gluconeogenesis pathways; E: Quantitative polymerase chain reaction was used to detect the messenger RNA expression levels of HIF-1α, PDK1, LDHA and VEGF in RAPA-treated HUTU 80 cells. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. ^cP < 0.001. RAPA: Rapamycin; MF: Molecular function; CC: Cellular component; BP: Biological process; ECM: Extracellular matrix; MAPK: Mitogen-activated protein kinase; PI3K/Akt: Phosphatidylinositol 3-kinase/protein kinase B; JAK/STAT: Janus tyrosine kinase/signal transducer and activator of transcription; mTOR: Mammalian target of rapamycin; AMPK: Adenosine 5’-monophosphate-activated protein kinase; HIF-1α: Hypoxia-inducible factor-1α; mRNA: Messenger RNA.

Rapamycin regulated HUTU 80 cell metabolism through the HIF-1α and glycolysis/gluconeogenesis pathway

To explore the metabolic changes of rapamycin-treated HUTU 80 cells, a nontargeted metabolomic analysis was conducted through ultra-high performance liquid chromatography-tandem mass spectrometry. A total of 193 differential metabolites were identified: 91 upregulated and 102 downregulated (Figure 5A). KEGG enrichment analysis revealed a significant association of rapamycin treatment and metabolic pathway changes in HUTU 80 cells, highlighting the impact of rapamycin on the HIF-1α metabolic pathway (Figure 5B). A heatmap was used to display significantly altered metabolites; among which, the level of ATP was significantly downregulated (Figure 5C). Combined analysis of the transcriptome and metabolome demonstrated 105 KEGG pathways connotated by different molecules from the transcriptome and metabolome (Figure 5D). The bar graph shows the top 10 KEGG pathways most associated with antitumor effects, containing the largest number of different molecules, differential genes and differential metabolites, from the intersecting pathways of the two experiments, including the HIF-1α signaling pathway and the central carbon metabolism in cancer (Figure 5E). The results suggested that rapamycin affected HUTU 80 cell metabolism through the HIF-1α signaling pathway and the central carbon metabolism in cancer, which inhibited HUTU 80 cell proliferation.

Figure 5 Metabolome results of rapamycin treatment with HUTU 80 cells and combined omics analysis. A: Volcano plot demonstrated the quantity of different metabolites; B: Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed the top 10 metabolomic pathways related to antitumor effects; C: Heatmap displayed differential metabolites; D: Venn diagram revealed the number of KEGG pathways commonly annotated by different molecules in the transcriptome and metabolome; E: Bar graph displaying the top 10 KEGG pathways with the total number of differential molecules related to anti-cancer properties selected from two groups (number of different genes and number of different metabolites). VIP: Variable importance in projection; HIF-1α: Hypoxia-inducible factor-1α.

Rapamycin inhibited glycolysis in HUTU 80 cells

Glucose consumption, lactate production, and ATP levels were measured to assess glycolysis of rapamycin-treated HUTU 80 cells (Supplementary Table 1). Glucose consumption, lactate production, and ATP levels were decreased after rapamycin treatment (Figure 6A). These results indicated that rapamycin inhibited glycolysis in HUTU 80 cells.

Figure 6 Rapamycin inhibited glycolysis in HUTU 80 cells via inhibition of the mammalian target of rapamycin/hypoxia-inducible facto-1α pathway. A: Measurement of glucose consumption, lactate production and adenosine triphosphate generation to reflect the glycolytic metabolism of HUTU 80 cells; B: Protein levels were assayed after treatment of HUTU 80 cells with rapamycin, including mammalian target of rapamycin (mTOR), eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and 70 kDa ribosomal protein S6 kinase (p70S6k), phosphorylated (p)-mTOR, p-4E-BP1 and p-p70S6k and hypoxia-inducible facto-1α; C: Quantification of protein expression using ImageJ. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. ^cP < 0.001. HIF-1α: Hypoxia-inducible factor-1α; ns: No significance; RAPA: Rapamycin; ATP: Adenosine triphosphate; mTOR: Mammalian target of rapamycin; p-mTOR: Phosphorylated-mammalian target of rapamycin; 4E-BP1: Eukaryotic translation initiation factor 4E-binding protein 1; p-4E-BP1: Phosphorylated-eukaryotic translation initiation factor 4E-binding protein 1; p70S6k: 70 kDa ribosomal protein S6 kinase; p-p70S6k: Phosphorylated-70 kDa ribosomal protein S6 kinase.

Rapamycin inhibited the mTOR/HIF-1α pathway in HUTU 80 cells

HIF-1α represents downstream components of the mTOR/p70S6k/4E-BP1 signaling pathway, and can be negatively affected by agents that suppress activation of mTOR[33]. Therefore, we investigated expression of key proteins of the mTOR/HIF-1α signaling pathway, including mTOR, p70S6k, 4E-BP1, and HIF-1α in HUTU 80 cells. Western blotting revealed that rapamycin significantly inhibited phosphorylation of mTOR, but had no impact on overall expression of mTOR (Figure 6B and C). Rapamycin also inhibited phosphorylation of key downstream targets of the mTOR signaling pathway, p70S6k and 4E-BP1 (Figure 6B and C). Rapamycin significantly reduced expression of HIF-1α protein in HUTU 80 cells (Figure 6B and C). Since the phosphorylation of p70S6k and 4E-BP can regulate cell proliferation and protein synthesis by HIF-1α expression, it was hypothesized that rapamycin suppressed cell proliferation in HUTU 80 cells via the mTOR/p70S6k/4E-BP1/HIF-1α pathway.

Rapamycin inhibited HUTU 80 cell proliferation in vivo

To assess the in vivo antitumor effects of rapamycin, a mouse xenograft model was induced with HUTU 80 cells, followed by daily intraperitoneal injections of 1 mg/kg rapamycin, 3 mg/kg rapamycin, or PBS alone. The increase in tumor size was significantly attenuated after treatment with rapamycin (Figure 7A-C). Comparisons of tumor volume and weight among treatment groups did not reach statistical significance. Although the body weight of the mice changed in the xenograft model (Figure 7D), HE staining of the heart, liver, spleen, kidneys, and lungs was normal, indicating that there was no acute toxicity associated with the treatment (Figure 7E).

Figure 7 Effects of rapamycin on HUTU 80 cells proliferation in vivo. A: Tumor anatomies showing the subcutaneous xenograft model with different treatments of HUTU 80 cells as well as the tumor anatomy of the euthanized mice (n = 6 mice per group); B: Weight of mouse tumors; C: Tumor volume change curves of mice; the tumor volume was calculated as [length (mm) × width (mm) × width (mm)]/2; D: Tumor weight change curves of mice. Data are presented as the mean ± SD (n = 6); E: Hematoxylin-eosin staining of the internal organs of nude mice after different treatments. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. ^cP < 0.001. RAPA: Rapamycin.

Rapamycin inhibited the mTOR/HIF-1α signaling pathway in a mouse xenograft model

To explore whether rapamycin affected the mTOR/HIF-1α signaling pathway in vivo, western blotting was carried out to evaluate the expression of related proteins in tumor tissue. Western blotting showed that rapamycin inhibited expression of p-mTOR, p-4E-BP1, p-p70S6k, and HIF-1α proteins. The results also showed no effect on changes in total protein levels, including mTOR, 4E-BP1, and p70S6k (Figure 8). These findings suggest that rapamycin can downregulate the mTOR/HIF-1α signaling pathway in SBA tissue.

Figure 8 Rapamycin reduces the protein expression of phosphorylated-mammalian target of rapamycin, phosphorylated-eukaryotic translation initiation factor 4E-binding protein 1, phosphorylated-70 kDa ribosomal protein S6 kinase and hypoxia-inducible factor-1α in tumors in vivo. A: Protein levels were assayed after treatment of tumors with rapamycin, including mammalian target of rapamycin (mTOR), eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1) and 70 kDa ribosomal protein S6 kinase (p70S6k), phosphorylated (p)-mTOR, p-4E-BP1 and p-p70S6k and hypoxia-inducible facto-1α; B: Quantification of protein expression using ImageJ. Data are presented as the mean ± SD (n = 3). ^aP < 0.05. ^bP < 0.01. RAPA: Rapamycin; mTOR: Mammalian target of rapamycin; p-mTOR: Phosphorylated-mammalian target of rapamycin; 4E-BP1: Eukaryotic translation initiation factor 4E-binding protein 1; p-4E-BP1: Phosphorylated-eukaryotic translation initiation factor 4E-binding protein 1; p70S6k: 70 kDa ribosomal protein S6 kinase; p-p70S6k: Phosphorylated-70 kDa ribosomal protein S6 kinase.

DISCUSSION

The present study demonstrated that rapamycin inhibited the proliferation of small duodenal adenocarcinoma HUTU 80 cells both in vitro and in vivo. Rapamycin also weakened the invasion and migration of HUTU 80 cells. Through the application of omics methodologies and molecular biology, the important role of the HIF signaling pathway and the related glycolysis/gluconeogenesis metabolism was screened and verified in rapamycin-treated HUTU 80 cells. Based on these results, it is hypothesized that the downregulatory role of rapamycin on the mTOR/HIF-1α pathway is a key mechanism for HUTU 80 cell proliferation suppression and inhibition of SBA progression.

Rapamycin is a highly specific mTOR inhibitor commonly used as an immunosuppressant in clinical practice, whose drug safety and efficacy have been reliably validated[34]. Unlike calcineurin inhibitors such as cyclosporine A and tacrolimus, rapamycin may not increase the incidence of cancer while preventing post-transplantation rejection[35-37]. Rapamycin has good efficacy in treating some diseases including cancer, diabetes, obesity, neurological diseases, and genetic diseases[38,39]. Rapamycin is currently approved for clinical treatment of conditions such as lymphangioleiomyomatosis, tuberous sclerosis complex-associated renal vascular leiomyolipoma, and subependymal giant cell astrocytoma[40,41]. Additionally, its potential for treating head and neck cancer, and muscle-invasive bladder cancer is being explored in ongoing clinical trials[42,43]. Despite these advances, the mechanism of action of rapamycin in cancer therapy is not fully understood. Previous studies have found that rapamycin can inhibit the growth of gastric and colorectal cancer cells in vitro and in vivo[44,45]. However, its potential antitumor effects on small intestinal adenocarcinoma have not yet been established. In the current study, the inhibitory effect of rapamycin was investigated on human duodenal adenocarcinoma HUTU 80 cells, and the potential targets for rapamycin action were explored though high throughput sequencing.

Rapamycin exhibits a powerful inhibitory effect on cancer cell activity. The antitumor effect of rapamycin has been demonstrated in tumor models of lung, colorectal, and gastric cancer[46-48]. Our previous study also indicated that rapamycin can inhibit melanoma B16 cell proliferation in vitro and in vivo[17]. The current study also showed that rapamycin inhibited the proliferative activity of HUTU 80 cells in a dose-dependent manner.

Distant metastasis is one of the main causes of cancer-related death. Similar to other malignant tumors, SBA cells can metastasize from the primary site to distant tissue and organs[49,50]. Therefore, inhibiting tumor metastasis is an important way to delay disease progression. Previous studies have found that rapamycin can markedly reduce the migration and invasion of pancreatic cancer and glioma cells[51,52]. The current study also revealed that rapamycin attenuated the migration and invasiveness of HUTU 80 cells, highlighting its antimetastatic potential. The expression of matric metalloproteinases (MMPs) is associated with the migration and invasion of tumor cells. Among the MMP family, MMP2 is a key participant in the development of metastasis, which promotes the degradation of extracellular matrix[53,54]. In a model of human nasopharyngeal carcinoma cells and sarcomatoid cholangiocarcinoma, rapamycin was able to inhibit the expression of MMP2[55,56]. Similarly, it was shown that rapamycin decreased expression of MMP2 mRNA in HUTU 80 cells. It was hypothesized that rapamycin may reduce tumor migration and invasion by affecting MMP2.

Abnormal cell cycle progression is a significant indicator of tumor occurrence; therefore, cell cycle regulation is considered a key target of cancer therapy. One aspect of cell cycle regulation that is crucial for tumor development is the activation of specific cell cycle protein/CDK complexes at different intervals. The complex of CDK2 and cyclin E is necessary for the transition from G₁ phase to S phase[57,58]. Rapamycin has been found to induce G₀/G₁ cell cycle arrest in various tumor cell lines, such as human germ cell tumor, thyroid cancer, and breast cancer[59-61]. The current study also demonstrated that rapamycin treatment led to a significant increase in the number of G₁ phase HUTU 80 cells and a decrease in the number of S phase cells. Meanwhile, there was a decrease in the expression levels of CDK2 protein in the cell cycle. Therefore, it was hypothesized that the inhibitory effect of rapamycin on the cell cycle is an important mechanism by which it reduces HUTU 80 cell proliferation and migration.

Metabolic reprogramming is another important characteristic of tumor development. It is not clear how metabolic reprogramming coordinates with abnormal cell cycle to promote the proliferation of tumor cells. HIF-1α is a well-known oxygen-responsive transcription factor. Its overexpression in various human malignancies is associated with poor prognosis[24,62-66]. HIF-1α has been reported to regulate numerous key pathways in the metabolic reprogramming of cancer cells[23,67]. The elevation of HIF-1α in cancer cells increases glycolysis, which promotes metabolic reprogramming and cancer progression[68]. Downregulation of the HIF-1α pathway suppresses tumor progression by inducing cell cycle arrest and accelerating cell senescence[69]. Targeting therapy to reduce HIF-1α expression can inhibit glycolysis, reduce angiogenesis within the tumor, and inhibit tumor invasion and metastasis[70]. Therefore, HIF-1α may be a key molecule that coordinates metabolic reprogramming and cell cycle regulation, and promotes rapid proliferation of tumor cells. In the current study, it was concluded that genes related to HIF-1α and glycolysis/gluconeogenesis were reduced in rapamycin-treated HUTU 80 cells. Rapamycin inhibited glycolysis in HUTU 80 cells, and downregulated expression of the downstream genes VEGF, PDK1, and LDHA in the HIF-1α pathway. Consequently, it was hypothesized that the HIF-1α pathway may be the key target for rapamycin to induce cell cycle arrest and inhibit glycolysis, by which it suppresses HUTU 80 cell proliferation and invasion.

The mTOR pathway, which is closely associated with tumor development and progression, is involved in regulating the transcription and translation of HIF-1α[71,72]. The critical downstream targets of the mTOR signaling pathway, S6K and 4E-BP, have been identified as key regulators of the protein synthesis of HIF-1α[73,74]. Activation of the mTOR/HIF-1α signaling pathway promotes the Warburg effect and cell proliferation in non-small cell lung cancer[75]. In the present study, it was also revealed that rapamycin inhibited the phosphorylation of mTOR, p70S6k, and 4E-BP1 of HUTU 80 cells, and decreased expression of HIF-1α in a dose-dependent manner. It was hypothesized that rapamycin may prevent the cell cycle progression and metabolic reprogramming by inhibiting the mTOR/p70S6k/4E-BP1/HIF-1α signaling pathway, which suppresses HUTU 80 cell proliferation and migration.

The present study also found that rapamycin inhibited the proliferative activity of HUTU 80 cells in a dose-dependent manner in vivo. Rapamycin significantly reduced tumor size and weight compared with controls. Adverse effects of rapamycin are frequently seen in clinical radiotherapy[76], and in the present study, we observed that mice began to lose weight after day 7 of treatment. Since no significant differences were observed in cell morphology, size, arrangement, nuclear morphology, or cytoplasmic staining intensity across different groups, it can be concluded that rapamycin does not exert significant toxic effects on mouse organs during treatment. This evidence suggests that rapamycin demonstrates relative safety in terms of organ toxicity within the scope of this study. However, potential long-term effects still require validation.

There were several limitations to the present study. First, although the study clearly demonstrated the therapeutic efficacy of rapamycin in the xenograft SBA model, clinical efficacy in SBA patients still needs further investigation. Studies have shown that rapamycin and its derivatives have achieved good therapeutic effects in combination therapy with other anticancer drugs, and have overcome drug resistance in tumors[77,78]. These manifestations highlight the potential of rapamycin and its derivatives in combination therapy for cancer. Due to the limited duration of treatment with rapamycin in this study, it is unclear whether there was a resistance problem with this regimen. Due to the lack of mTOR/HIF-1α pathway-specific inhibitors, we were unable to validate the targeted regulation of glycolysis by rapamycin directly. In the future, we plan to observe the therapeutic effects of glycolysis inhibitors such as 2-deoxyglucose, 3-bromopyruvate, and 6-aminonicotinamide on HUTU 80 cells and further explore the potential mechanisms of targeted metabolic reprogramming for the treatment of SBA.

CONCLUSION

Rapamycin may inhibit HUTU 80 cell proliferation, migration, and invasion by inducing cell cycle arrest and preventing metabolic reprogramming via the mTOR/HIF-1α pathway. It provides a potential treatment strategy for SBA, and lays the foundation for further targeted therapy in clinical research.

ACKNOWLEDGEMENTS

The authors are grateful to the support and assistance in terms of instruments and facilities provided by Public Research Center of Hainan Medical University, Haikou, Hainan, China.