CDK1 bridges NF-κB and β-catenin signaling in response to H. pylori infection in gastric tumorigenesis

SUMMARY

Infection with Helicobacter pylori (H. pylori) is the main risk factor for gastric cancer, a leading cause of cancer-related death worldwide. The oncogenic functions of cyclin-dependent kinase 1 (CDK1) are not fully understood in gastric tumorigenesis. Using public datasets, quantitative real-time PCR, western blot, and immunohistochemical (IHC) analyses, we detect high levels of CDK1 in human and mouse gastric tumors. H. pylori infection induces activation of nuclear factor κB (NF-κB) with a significant increase in CDK1 in in vitro and in vivo models (p < 0.01). We confirm active NF-κB binding sites on the CDK1 promoter sequence. CDK1 phosphorylates and inhibits GSK-3β activity through direct binding with subsequent accumulation and activation of β-catenin. CDK1 silencing or pharmacologic inhibition reverses these effects and impairs tumor organoids and spheroid formation. IHC analysis demonstrates a positive correlation between CDK1 and β-catenin. The results demonstrate a mechanistic link between infection, inflammation, and gastric tumorigenesis where CDK1 plays a critical role.

In brief

Zhu et al. show induction of CDK1 in response to H. pylori infection via NF-κB-dependent transcription regulation. CDK1-mediated activation of β-catenin signaling, promoting expansion of cancer cells. The results demonstrate a mechanistic link between infection, inflammation, and gastric tumorigenesis where CDK1 plays a critical role.

Graphical Abstract

INTRODUCTION

Gastric cancer is a leading cause of cancer-related death worldwide.¹ Most patients with gastric cancer in the United States are diagnosed at a late stage (stages III and IV), with a poor 5-year survival rate.² Therefore, identifying signaling pathways and druggable molecular vulnerabilities relevant to the biology of gastric cancer are important approaches to improve our diagnostic, preventive, and therapeutic strategies in the fight against gastric cancer.

Helicobacter pylori (H. pylori) is a spiral-shaped gram-negative bacteria that colonizes the human stomach. H. pylori infection has a very high prevalence,³ with an estimated presence in more than half of the world’s population.⁴ The World Health Organization has classified infection with H. pylori as a group 1 carcinogen.⁵ H. pylori infection is typically acquired during childhood and persists as a chronic infection for several decades.⁶ Chronic H. pylori infection is the most established etiological factor in the development of human gastric adenocarcinoma.^6,7 We and others have shown that infection with H. pylori promotes gastric tumorigenesis.^8–10 Infection initiates a chronic inflammatory environment with histopathologic progression from chronic gastritis to gastric atrophy, intestinal metaplasia, dysplasia, and finally, gastric cancer.^7,11 H. pylori infection can also activate several oncogenic signaling pathways such as WNT/β-catenin, EGFR, and FAK.^6,12

Inflammation plays an important role in the development and progression of several cancers.¹³ Nuclear factor κB (NF-κB) comprises a family of inducible transcription factors that regulate many genes involved in response to both injury and infection.¹⁴ NF-κB is one of the most important molecules linking chronic inflammation to cancer. NF-κB activation occurs in cancer cells as well as the tumor microenvironment of most solid cancers and hematopoietic malignancies.¹³ When cells are exposed to the appropriate activating stimuli, such as tumor necrosis factor (TNF), this causes the inhibitor of κB kinase to facilitate the phosphorylation-dependent ubiquitination and destruction of the inhibitor of κB (IκB) proteins (IKK).The free NF-κB translocates to the nucleus and induces transcription of a wide-range of target genes that regulate key biological cellular processes.¹⁵ In addition to its role in the survival of cancer cells, NF-κB activation has been described in cancer stem cells, where it can promote a pro-inflammatory environment, inhibit apoptosis, and stimulate cellular expansion.¹⁶

Cyclin-dependent kinases (CDKs) are serine/threonine kinases that control cell-cycle progression and other critical functions.¹⁷ Cell division is closely linked to DNA damage response (DDR) maintaining genetic integrity and cellular homeostasis.¹⁸ CDK1 belongs to the family of CDKs that play a central role in cell-cycle progression, which drives cells through the G2 phase to mitosis.¹⁷ There are increasing lines of evidence supporting the role of CDK1 in the DDR, particularly in DNA repair by homologous recombination and activation of the checkpoint response. Of note, overexpression and accumulation of cytoplasmic CDK1 are associated with cancer growth and poor survival rate in ovarian cancer.¹⁹

The Wnt/β-catenin pathway is essential for embryonic development and adult tissue homeostasis.²⁰ Wnt proteins block the phosphorylation and degradation of β-catenin by binding to the low-density lipoprotein receptor-related protein 5/6 and their co-receptor Frizzled.²¹ Aberrant activation of the Wnt/β-catenin signaling pathway strongly correlates with tumorigenesis and progression.²² The activation of the Wnt/β-catenin pathway is associated with gastric carcinogenesis and clinical aggressiveness.²³ The nuclear translocation and accumulation of β-catenin is necessary for transcription activation of the β-catenin/T cell factor (TCF) complex.

Although mutations in APC or CTNNB1 are a major cause of β-catenin nuclear accumulation in colorectal cancer,²⁴ these mutations generally occur in low frequencies (7% and 4%, respectively).²⁵ However, APC mutations are relatively more prevalent in the MSS/TP53+ subtype of gastric cancer than other molecular subtypes.²⁶

Mechanisms of mutation-independent activation of the β-catenin pathway including upregulation of c-Met and EGFR or inhibition of tumor suppressors RUNX3 or TFF1 were observed.^23,27 Other mechanisms include upregulation of WNT receptors and ligands (FZDs and WNTs) or hypermethylation of repressors of ligand/receptors (DKK, SFRP, and RNF43).²⁸

This study aimed to investigate mechanisms of upstream activation of CDK1 and its downstream functional impact on gastric tumorigenesis in response to H. pylori infection. Our results establish CDK1 as a transcriptional target of NF-κB induced by H. pylori infection. This aberrant overexpression of CDK1 mediated β-catenin accumulation and activation to promote cellular expansion and counteract infection-induced cell death in gastric carcinogenesis.

RESULTS

H. pylori infection increases CDK1 expression

To identify key genes that are abnormally expressed in gastric cancer and exclusively associated with H. pylori infection, we analyzed the TCGA gastric cancer cohort (including 375 tumor tissues and 32 non-tumor tissues) and local cohort 1 (whole-transcriptome sequencing data from 36 human gastric tumor tissues and matched non-tumor tissues).²⁹ In addition, we performed whole-transcriptome sequencing on H. pylori infection (PMSS1, n = 7) and uninfected C57BL/6 mouse gastric tissues (n = 7) and also on a public dataset of a C57BL/6 mouse model with H. pylori infection (GEO: GSE13873). We used the significance levels (|log (fold change)|>0.5 and p < 0.05) to identify 1,602 and 251 significant differentially expressed genes (DEGs) from the human cohort and mouse cohort, respectively. By intersecting the DEGs from the human and mouse cohorts, we finally obtained 60 DEGs containing 25 genes (including CDK1) significantly upregulated in gastric cancer (Figure 1A; Table S1). These upregulated DEGs were considered candidate genes that play an important role in gastric tumorigenesis, stimulated by H. pylori infection. Among these 25 genes, we focused on the CDK1 gene because (1) CDK1 is among the top 5 abnormal overexpression genes in the TCGA cohort; (2) CDK1 is a key member of the CDK family, (3) targeting CDKs has gained significant attention in the past few years,³⁰ and (4) its function in H. pylori infection-induced gastric tumorigenesis has not been explored yet. Herein, we found that Cdk1 expression was significantly induced in mice with H. pylori infection in our local and GEO: GSE13873 cohorts (Figure 1B). Furthermore, we detected a notable increase in CDK1 protein levels by performing immunofluorescence staining in H. pylori strain PMSS1-infected C57BL/6 (Figure 1C). We cultured gastric cancer (GC) cells alone or co-cultured with the wild-type cag+ H. pylori strain 7.13 or J166. The western blot and quantitative real-time PCR results showed that H. pylori infection significantly increased CDK1 mRNA and protein expression (p < 0.01; Figures 1D and 1E).

Figure 1. CDK1 is overexpressed in gastric cancer.

(A) Analyses of two Gene Expression Omnibus (GEO) datasets from tumor versus normal (TN) and H. pylori (HP) cohorts. Hierarchical clustering heatmap and volcano plots of significant differentially expressed genes (DEGs) are shown in DEG analysis. Overlapping TN cohorts and HP cohorts initially identified 60 DEGs.

(B) The mRNA expression levels of CDK1 were examined in the GEO datasets and our local cohort with H. pylori infection.

(C) Immunofluorescence staining for CDK1 (red) was performed in mice orogastrically challenged with Brucella broth or PMSS1, and representative images are shown. H&E staining of representative histological features of gastric mucosa mice.

(D and E) Western blot and quantitative real-time analysis of CDK1 in GES1, AGS, and MKN28 cells following H. pylori infection.

Experiments were performed in triplicates. *p < 0.05 and **p < 0.01.

Using cell-cycle analysis, we have confirmed the classical function of CDK1 by showing a significant G2/M phase delay following the small interfering RNA (siRNA) knock down of CDK1 (Figure S1). Recent studies from our lab and others have demonstrated that overexpression of mitotic kinases in cancer such as Aurora kinases can have several functions in cancer cells.^31–33 Therefore, we became interested in identifying functions for CDK1 in GC.

NF-κB binds to CDK1 promoter and regulates its expression

To accurately predict transcription factors (TFs) that can bind to the CDK1 promoter, we performed bioinformatics analysis with the TRRUST tool³⁴ by inputting DEGs of the CDK1-high expression group versus the CDK1-low expression group in the four indicated cohorts (Figure 2A). We finally identified 13 overlapping TFs, including two NF-κB relative TFs (NFkB1 and RELA) with high JASPAR scores (Figure 2B).³⁵ H. pylori infection activates NF-κB through both the canonical and the non-canonical pathways.³⁶ Therefore, we investigated whether H. pylori infection could upregulate CDK1 expression through activation of NF-κB. Western blot analysis data showed that H. pylori infection upregulated CDK1 and promoted induction of p-P65 (S536), confirming the activation of NF-κB (Figures 2C and 2D). To validate the pro-inflammatory effect of H. pylori, we evaluated the mRNA expression of inflammation-mediating cytokines in AGS cells infected with H. pylori. The quantitative real-time PCR data revealed that H. pylori infection significantly induced interleukin-1β (IL-1β) and TNF-α expression (p < 0.01; Figures S2A and S2B). To further prove that H. pylori infection leads to activation of NF-κB and increases expression of CDK1, we infected mice with mouse adapted H. pylori strain (PMSS1). Western blot analysis data showed an increase in CDK1 and p-P65 (S536) protein levels in the H. pylori-infected group compared with the non-infected controls (Figure 2E). The quantitative real-time PCR analysis of mice gastric tissues showed that infection with H. pylori resulted in significantly increased Cdk1 mRNA expression compared with the uninfected controls (p < 0.01; Figure S2C). We next investigated if NF-κB regulates CDK1 expression. We used transient expression of P65 in AGS and MKN28 cells, which led to a 2.5-fold induction of CDK1 mRNA expression with a notable increase in CDK1 protein level (Figure 2F). We further verified these findings by using a TNF-α or NF-κB inhibitor. We treated GC cells with TNF-α or an NF-κB inhibitor (Bay 11-7082) to activate or inhibit NF-κB, respectively, and evaluated the CDK1 mRNA and protein expression by quantitative real-time PCR and western blot analysis. We noticed that TNF-α significantly upregulated CDK1 mRNA (Figure 2G) and protein (Figure 2H) levels in AGS and MKN28 cells. Collectively, these data suggest that NF-κB plays an important role in the transcriptional regulation of CDK1 expression.

Figure 2. Activation of NF-κB-P65 upregulates CDK1 expression.

(A) The transcription factor binding sites were predicted by the PROMO website using a 2,000-bp conserved segment of the CDK1 promoter.

(B) A list of putative transcriptional factors with higher JASPAR scores in human and mouse CDK1 promoters.

(C and D) Western blot analyses of p-P65 (S536), P65, and CDK1 in GES1, AGS, and MKN28 cells following H. pylori infection (7.13 and J166).

(E) The western blot analyses of p-P65 (S536), P65, and CDK1 were performed in mice orogastrically challenged with Brucella broth or with PMSS1.

(F) The immunoblot analyses and quantitative real-time PCR were performed to determine CDK1 expression in AGS and MKN28 cells transiently transfected with P65 or empty vector.

(G and H) The immunoblot analyses and quantitative real-time PCR of p-P65 (S536), P65, and CDK1 were performed in AGS and MKN28 cells following TNF-α and Bay 11-7082 treatment.

Experiments were performed in triplicates. *p < 0.05.

Our analysis of the CDK1 promoter identified six possible NF-κB binding sites (Figure 3A). To characterize the NF-κB crucial elements for regulation on the CDK1 promoter region, we designed 5 paired primers (P1–P5) containing all the putative binding sites (Figure 3B). To determine whether NF-κB regulates the expression of CDK1 by directly binding to the promoter, we performed a chromatin immunoprecipitation (ChIP) assay by using a specific antibody against P65 to immunoprecipitate formaldehyde-fixed chromatin in AGS cells following transfection with pcDNA-p65 for 48 h or infection with H. pylori (7.13) for 24 h. We observed that P65 directly binds to the P1 region of the CDK1 promoter and not to other regions (p < 0.01 and p < 0.05; Figure 3C). To further confirm the role of H. pylori in CDK1 transcription regulation, AGS cells were transfected with CDK1-Luc luciferase reporter plasmid and co-cultured with H. pylori strain (7.13) alone or in combination with Bay 11-7082 (NF-κB inhibitor). We found a significant induction of the CDK1-Luc reporter activity following H. pylori infection; the luciferase activity was completely blocked following NF-κB inhibition (p < 0.01; Figure 3D). To further validate NF-κB-P65 and CDK1 promoter interaction, cells were transfected with a wild-type (WT)CDK1-Luc and P1 mutant luciferase construct (mutCDK1-Luc) reporter plasmid and then treated with TNF-α alone or in combination with Bay 11-7082 (Figures 3E and 3F). The promoter activity analysis showed that the relative luciferase activity of the WT-CDK1 significantly increased with TNF-α treatment (p < 0.01); treatment with Bay 11-7082 reversed these effects. In contrast, the relative luciferase activity of the mutCDK1 was not increased by TNF-α stimulation (Figures 3E and 3F). Notably, transient overexpression of P65 led to a dose-dependent increase of luciferase activity of the WT-CDK1, but not mutCDK1, reporter in AGS and MKN28 cells (p < 0.01; Figures 3G and 3H).

Figure 3. NF-κB transcriptionally upregulates CDK1 expression.

(A and B) A table and a scheme showing putative NF-κB transcription factor binding sites on the CDK1 promoter and the CHIP primers designed in the CDK1 promoter (P1–P5).

(C) Chromatin immunoprecipitation (ChIP) assay using a specific antibody against P65 to immunoprecipitate formaldehyde-fixed chromatin in AGS cells, followed by quantitative real-time PCR with primers designed for the NF-κB-P65 binding site of the CDK1 promoter region with H. pylori infection or P65 plasmid transfection.

(D) Luciferase reporter assay for CDK1-Luc in AGS cells infected with H. pylori alone or combined with Bay 11-7082 treatment.

(E and F) Luciferase reporter assay for CDK1-Luc or mutCDK1-Luc in AGS and MKN28 cells treated with TNF-α alone or in combination with Bay 11-7082.

(G and H) Luciferase reporter assay for CDK1-Luc or mutCDK1-Luc constructs in AGS and MKN28 cells expressing P65 or empty vector.

Experiments were performed in triplicates. *p < 0.05, **p < 0.01, and ***p < 0.001.

H. pylori infection activates CDK1-β-catenin axis

Recent studies have suggested non-mitotic functions of constitutively overexpressed mitotic proteins in cancer cells.^19,31–33 To explore the downstream signaling pathways regulated by CDK1 in GC in response to H. pylori infection, we performed gene set enrichment analysis (GSEA) using our cohort of mice with and without H. pylori infection. Earlier reports have shown activation of Wnt/β-catenin signaling by H. pylori, promoting cellular proliferation and transformation.^9,29,37 Our analysis demonstrated enrichment of several important oncogenic gene sets, including the Wnt signaling pathway in H. pylori infection samples (Figure 4A). Furthermore, Pearson’s correlation test revealed a strong correlation between CDK1 and CTNNB1 expression levels in the GEO: GSE84433 cohort (Figure 4B). These findings suggested that β-catenin may be a critical downstream pathway in CDK1-high expressing cells in GC. To validate this hypothesis, we performed overexpression of CDK1 by using a CDK1 plasmid or tet-inducible system. We utilized the immortalized non-neoplastic gastric cells (GES1) or GC cells (AGS) that have absent to low endogenous CDK1 expression. We observed an increase in the β-catenin protein level following the overexpression of CDK1. The reverse effects were detected following the knock down of endogenously high levels of CDK1 in MKN45 cells (Figure 4C). Immunofluorescence analysis confirmed these findings where high levels of nuclear β-catenin were detected in AGS-CDK1 cells (Figure 4D). Furthermore, the TOP/FOP luciferase reporter data, as a measure of β-catenin/TCF transcription activity, demonstrated a significant induction of luciferase activity following overexpression of CDK1 (p < 0.01; Figure 4E). Opposite results were observed following the knock down of endogenous CDK1 (p < 0.01; Figure 4F). To confirm activation of β-catenin, the mRNA expression levels of β-catenin/TCF target genes were analyzed. The results demonstrated a significant increase in the mRNA expression levels of AXIN2 (p < 0.05, and p < 0.01), and CCDN1 (p < 0.01) in AGS and MKN28 cells with CDK1 overexpression compared with control (Figures 4G and 4H). In contrast, the knock down of endogenous CDK1 expression in MKN45 cells resulted in opposite effects (p < 0.05, and p < 0.01, respectively; Figures 4G and 4H). We also analyzed additional β-catenin/TCF target genes with ectopic CDK1 expression as well as with CDK1 knockdown with and without H. pylori infection in AGS and MKN28 cells. The results showed that CDK1 overexpression and H. pylori infection increased CCND1, AXIN2, LEF1, and LGR5 mRNA levels (Figures S3A and S3B). Conversely, silencing CDK1 in MKN45 reversed the results (Figure S3C). These findings suggest that CDK1 is required for β-catenin target genes.

Figure 4. CDK1 regulates β-catenin protein levels and enhances β-catenin transcriptional activity.

(A) Gene set enrichment analysis (GSEA) in a mouse model with H. pylori infection was performed by comparing infection cases with non-infection cases. Canonical Wnt signaling pathway was significantly enriched in H. pylori infection samples (p < 0.01).

(B) Pearson’s correlation test revealed strong correlations between CDK1 expression and CTNNB1 level in the GEO: GSE84433 cohort (R = 0.39, p < 0.01).

(C) The immunoblot analyses were performed to determine β-catenin and p-GSK-3β (S9) expression in GES1 and AGS cells with overexpression of CDK1 or its knockdown by CDK1-specific siRNA in MKN45 cells.

(D) Representative immunofluorescent images of β-catenin (green) and CDK1 (red) in AGS cells’ overexpression of CDK1; nuclei were stained with DAPI (blue).

(E and F) β-catenin luciferase reporter assays. TOP-flash contains wild-type TCF binding sites. FOP-flash, containing mutated TCF binding sites, is served as a negative control; *p < 0.05 and **p < 0.01.

(E) The gastric cancer (GC) cells were transfected with indicated amounts (0.5 or 1.0 μg) of CDK1 expression vector or empty vector control (Ctrl).

(F) The MKN45 cells were transfected with CDK1 siRNAs or scrambled siRNA (Ctrl).

(G and H) AGS or MKN28 cells were transfected with CDK1 expression plasmid or empty vector (Ctrl), and MKN45 cells were transfected with CDK1 siRNA or scramble siRNA control (Ctrl). Quantitative real-time PCR analysis of β-catenin targets, including AXIN2 and CCND1.

Experiments were performed in triplicates. *p < 0.05 and **p < 0.01.

It is important to understand cell signaling in a context relevant to the biology of the cancer type to improve our therapeutic strategies. To confirm that infection with H. pylori drives CDK1-β-catenin axis in gastric tumorigenesis, we cultured GES1, AGS, or MKN28 cells alone or co-cultured with H. pylori strain 7.13 or J166. Western blot results showed that H. pylori infection significantly increased CDK1 protein and phosphorylation of GSK-3β (S9) and β-catenin (S552) (Figures 5A and S4). The increase in phospho-GSK-3β (S9) level explains the increase in β-catenin levels as phospho-GSK-3β (S9) is inactive, allowing β-catenin accumulation and nuclear translocation. For in vivo validation, C57BL/6 mice were challenged with Brucella broth, as a negative control, or mouse adapted H. pylori strain PMSS1. Western blot analysis of mice gastric tissues showed that infection with H. pylori significantly increased CDK1 protein and phosphorylation of GSK-3β and β-catenin compared with uninfected controls (Figure 5B). Of note, the induction of phosphorylation of GSK-3β and β-catenin by H. pylori infection was abrogated by CDK1 knockdown (Figures 5C and 5D). Consistent with these results, H. pylori infection increased the TOP/FOP-flash reporter activities (6 h p < 0.05, 24 h p < 0.01) as a measure of β-catenin/TCF activity; this increase was abrogated by CDK1 knockdown (Figures 5E, 5F, and S5A). Similarly, H pylori infection upregulated the mRNA expression of β-catenin targets such as AXIN2 and CCND1 (Figures 5G, 5H, S5B, and S5C). Following these findings, immunofluorescence results demonstrated that H. pylori infection enhanced the nuclear accumulation of β-catenin (Figure 5I). Taken together, our results indicated that H. pylori infection activated the β-catenin signaling axis via induction of CDK1.

Figure 5. H. pylori infection increases β-catenin transcriptional activity through a CDK1-dependent manner.

(A) Western blot analysis of p-β-catenin (S552), β-catenin, p-GSK-3β (S9), GSK-3β, and CDK1 in GES1, AGS, and MKN28 cells with H. pylori infection (7.13) at different time points (3, 6, and 24 h).

(B) The western blot analysis of p-β-catenin (S552), β-catenin, and CDK1 were performed in mice orogastrically challenged with Brucella broth or with PMSS1.

(C and D) Western blot analysis of p-β-catenin (S552), β-catenin, p-GSK-3β (S9), GSK-3β, and CDK1 with H. pylori infection and CDK1 siRNA knockdown in GES1 and AGS cells.

(E and F) Luciferase reporter assay for TOP or FOP in GES1 and AGS cells with H. pylori infection and CDK1 siRNA knockdown.

(G and H) Quantitative real-time PCR analysis of β-catenin targets, including AXIN2 and CCND1, were performed in GES1 or AGS cells with H. pylori infection (7.13).

(I) Representative immunofluorescent images of β-catenin (green) and CDK1 (red) in AGS cells with H. pylori infection; nuclei were stained with DAPI (blue).

Experiments were performed in triplicates. *p < 0.05 and **p < 0.01.

CDK1 regulates the GSK-3β/β-catenin pathway via protein-protein interaction

Next, we investigated if CDK1 can directly interact with GSK-3β and/or β-catenin. Using in situ proximity ligation assay (PLA) for endogenous CDK1 and GSK-3β or CDK1 and β-catenin, we detected a positive ligation, visualized by red signals for CDK1 and GSK-3β and CDK1 and β-catenin, indicative of their close proximity in AGS cells. These signals were not detected in the negative control as well as in PLA control using a single antibody (Figures S6A and S6B). We next utilized dual co-immunoprecipitation (coIP) to confirm the PLA findings and determine protein-protein interactions with the GSK-3β/β-catenin complex. We detected protein-protein interactions between CDK1, GSK-3β, and β-catenin (Figure S6C). Using in vitro kinase assay, we investigated whether CDK1 directly binds and phosphorylates GSK-3β. The results, using purified human recombinant CDK1 and GSK-3β proteins, confirmed that CDK1 can directly phosphorylate GSK-3β (S9) (Figure S6D). Notably, this effect was not seen using TFF1 recombinant protein (negative control). These results suggest that CDK1 regulates β-catenin via direct binding to and phosphorylating GSK3-β, rendering it inactive. This allows β-catenin to escape GSK-3β-mediated degradation, an essential step that promotes accumulation and activation of β-catenin in GC cells.

CDK1 promotes cell survival and expansion

Sustained activation of the β-catenin pathway provides cancer cells with stem-like properties including self-renewal and expansion capacities, associated with therapeutic resistance.^20,38 We therefore investigated the role of the CDK1-β-catenin axis in promoting these properties in GC cells. The GSEA indicated enrichment of several stem cell-relevant signatures^39,40 in GC samples with high-CDK1 expression across the TCGA and GEO datasets (Figure 6A). We also observed a correlation between the single-sample GSEA (ssGSEA) scores with β-catenin and its targets (Figure 6B). Furthermore, we tested the functions of CDK1 on cell expansion utilizing a spheroid culture assay. Spheroids with stable CDK1 shRNA knockdown showed less β-catenin staining than control cells (Figure 6C). CDK1 knockdown significantly decreased the size of spheroids (p < 0.01) compared with control groups (Figures 6D and 6E). Western blot analyses results showed that CDK1 knockdown significantly decreased phosphorylation of GSK-3β and β-catenin in MKN28 cells’ spheroids (Figure 6F), confirming the role of CDK1 on β-catenin.

Figure 6. CDK1 depletion represses GC cell expansion.

(A) GSEA in samples with high-CDK1 expression across the TCGA and GEO datasets.

(B) A weak to moderate correlation of the ssGSEA scores with β-catenin and its targets was observed.

(C) Representative immunofluorescent images of β-catenin (green) and CDK1 (red) in spheroids from MKN28 cells with stable knockdown CDK1; nuclei were stained with DAPI (blue).

(D) Spheroids (scale bars, 100 μm) derived from MKN28 cells with stable knockdown of CDK1 (CDK1 shRNA 01, CDK1 shRNA 02) displayed significantly smaller spheroids compared with the scrambled shRNA cells (Ctrl).

(E) The quantification of sphere size and the number was expressed as the mean ± SD of 3 independent fields: **p < 0.01 and ***p < 0.001.

(F) Western blot analysis of p-β-catenin (S552), β-catenin, p-GSK-3β (S9), GSK-3β, and CDK1 in spheroids derived from MKN28 cells with CDK1 shRNA knockdown.

(G and H) At the age of 8 weeks, K19^creCDK1^fl/fl (control) or K19^creCDK1^fl/fl mice received tamoxifen (50 mg/kg, intraperitoneally [i.p.]) for 10 days. At 10 weeks of age, the mice were infected with H. pylori (PMSS1 strain) for 1 month. The size of gastric organoids established from these mice was measured.

Experiments were performed in triplicate. **p < 0.01 and ***p < 0.001.

Silencing Cdk1 in mouse gastric mucosa abrogated H. Pylori-induced activation of β-catenin

Although in vitro assays are valuable tools to dissect mechanisms, it is critical to recapitulate the findings using in vivo models. To verify the role of CDK1 in β-catenin activation in vivo, we performed successful crossings of the Cdk1^flox/flox mouse model (The Jackson Laboratory, Bar Harbor, ME, USA) with the Krt19^Cre mouse model (the Jackson Laboratory) and obtained the Krt19^Cre/Cdk1^flox/flox conditional CDK1 knockout mouse model. We established 4 groups (n = 5 per group): a control group, Krt19^Cre/Cdk1^floxl/flox, mice only infected with H. pylori (PMSS1), Krt19^Cre/Cdk1^flox/flox receiving tamoxifen (TAM) treatment, and Krt19^CreCdk1^flox/flox mice receiving TAM treatment and H. pylori infection (TAM + PMSS1) (Table S2). We developed organoids from these mice. Consistent with the in vitro observations, H. pylori infection increased the organoids’ size, and CDK1 knockout significantly decreased the size of the organoids (p < 0.01; Figures 6G and 6H). The immunofluorescence staining of antral glandular stomach tissues demonstrated similar results as observed in cell lines: the H. pylori infection mice had higher CDK1 expression and increased numbers of nuclear β-catenin+ cells (Figure 7A). Using organoid tissue cultures from antral stomach regions of the four groups of mice, we determined that organoids from the H. pylori infection mice have higher CDK1 expression and β-catenin nuclear immunostaining than in the control and TAM + PMSS1 mice (Figure 7B). Concordant with these findings, we detected a significant increase in the mRNA expression levels of β-catenin target genes, Ccnd1, Axin2, Lgr5, and Lef1 in the H. pylori (PMSS1)-infected mice, compared with the control and TAM + PMSS1 mice (Figure S7). In addition to in vivo and organoid data, silencing of CDK1 or its pharmacologic inhibition with dinaciclib or RO3306 attenuated sphere size and viability (Figures S8A–S8E). Consistently, pharmacologic CDK1 inhibition with dinaciclib or RO3306 decreased cell viability in multiple GC cell lines as measured by ATPGlo cell viability assay (IC50s are shown in Figures S8F and S8G).

Figure 7. In vivo studies of CDK1/β-catenin axis in gastric tumorigenesis.

(A) At the age of 8 weeks, K19^creCDK1^fl/fl (control) or K19^creCDK1^fl/fl mice received tamoxifen (50 mg/kg, i.p.) for 10 days. At 10 weeks of age, the mice were infected with H. pylori (PMSS1 strain) for 1 month. Immunofluorescence analyses of β-catenin (green) and CDK1 (red) from these mice were performed. H&E staining of representative histological features of gastric mucosa from mice.

(B) Immunofluorescence analyses of β-catenin (green) and CDK1 (red) were performed in gastric organoids established from K19^creCDK1^fl/fl (control) or K19^creCDK1^fl/fl mice receiving tamoxifen treatment and/or H. pylori infection. Nuclei were stained with DAPI (blue). H&E staining of representative histological features of gastric organoids.

(C) Representative immunohistochemistry staining (scale bars, 100 μm) of CDK1 (n = 216) and β-catenin (n = 117) in human gastric tumors and adjacent non-tumor tissues.

(D) Composite expression score of CDK1 (n = 216) and β-catenin (n = 117) in tumor and non-tumor tissues.

(E) Spearman’s correlation between IHC staining scores of CDK1 and β-catenin in tumor slides of 117 patients. TAM, tamoxifen.

(F) Illustration of the study model.

High levels of CDK1 and β-catenin in human GC tissue samples

Immunohistochemistry (IHC) staining of CDK1 and β-catenin on human gastric tissue samples revealed weak immunostaining in the normal gastric mucosa (Figure 7C). Conversely, we observed strong immunostaining of CDK1 and β-catenin in adenocarcinomas (Figure 7C). Using a composite expression score (CES) as described in the STAR Methods, the IHC data indicated a significant increase in the expression of both CDK1 and β-catenin in gastric tumors (p < 0.0; Figure 7D). Moreover, a moderate correlation between CDK1 and β-cate-nin expression was revealed by Spearman’s correlation analysis (coefficient R = 0.41, p < 0.001; Figure 7E). Our results from in vitro, mouse, and human models support the link between H. pylori infection, CDK1 expression, and β-catenin activation in gastric carcinogenesis. A diagram summarizing our findings is shown in Figure 7F.

DISCUSSION

GC ranks fifth for incidence and fourth for mortality worldwide. Despite efforts to eradicate H. pylori, the main risk factor, GC is responsible for over one million new cases in 2020, with an estimated 769,000 deaths.¹ Furthermore, most patients with GC present with advanced disease and have poor clinical out-comes.⁴¹ Therefore, it is important to identify the molecular players in GC, a key step for improving our current diagnostic and therapeutic approaches. The objective of this study was to investigate whether H. pylori infection-induced inflammation could upregulate CDK1 expression, thereby facilitating gastric tumorigenesis.

H. pylori is classified by the World Health Organization as a class 1 carcinogen.⁵ Chronic H. pylori infection and inflammation are the most established etiologic factors in the development of human GC.^6,7 We and others have shown that H. pylori infection of gastric mucosa creates a strong pro-inflammatory tumorigenic environment with activation of NF-κB, STAT3, β-catenin, and AKT.^9,10,42,43 This study reports a mechanism by which H. pylori infection promotes gastric tumorigenesis through activation of CDK1 expression. Our results link infection, inflammation, and activation of CDK1-dependent β-catenin signaling in gastric tumorigenesis.

Chronic inflammation is a key step in gastric tumorigenesis. Numerous pro-inflammatory stimuli activate NF-κB through the canonical or non-canonical pathways.^44,45 In this study, we reported that H. pylori infection mediated activation of pro-inflammatory NF-κB signaling associated with the increase in CDK1 level. Furthermore, we identified and confirmed several critical binding sites of NF-κB on the CDK1 promoter required for transcription regulation of CDK1 expression following H. pylori infection. We have previously shown that the TFF1^−/− mouse model of gastric tumorigenesis and human GCs develop activation of NF-κB signaling in early stages.^10,46 NF-κB activation is a crucial mediator of inflammation-induced tumor growth and progression.⁴⁷ Our results show that H. pylori-mediated NF-κB activation increases CDK1 expression, strongly suggesting that CDK1 oncogenic functions may contribute to H. pylori-mediated gastric tumorigenesis. CDK1 is a cell-cycle regulator that drives cells through the G2 phase and mitosis. Accumulation of CDK1 was associated with cancer growth and a poor survival rate in several cancer types.^19,48 Targeting CDK1 increased the efficacy of sorafenib treatment by targeting cancer stem cells in a preclinical model of hepatocellular carcinoma.⁴⁹ CDK1 inhibition induced caspase activation in pancreatic cell lines of pancreatic cancer.⁵⁰

The equilibrium between cell migration, cell proliferation, and cell-cycle arrest is crucial for maintaining the homeostasis of the gastrointestinal epithelium. The canonical Wnt signaling pathway regulates proliferation, stem cell maintenance, and homeostasis in normal gastric mucosa in addition to its involvement in early embryogenesis.^20,22 β-catenin is a signaling transducer in the Wnt signaling pathway that serves as a transcriptional co-activator of TCF/LEF implicated in several cancer types.²² Sustained activation of the β-catenin pathway provides cancer cells with stem-like properties and self-renewal capacity, regulating numerous aspects of cancers, including initiation, development, and progression. Although mutations in APC or CTNNB1 are a major cause of β-catenin nuclear accumulation in colorectal cancer,²⁴ these mutations generally occur in low frequencies (7% and 4%, respectively).²⁵ APC mutations are relatively more prevalent in the MSS/TP53+ subtype of GC than other molecular subtypes.²⁶ However, GCs demonstrate frequent β-catenin activation in the absence of causal mutations in APC or CTNNB1.^23,51

Non-phosphorylated GSK-3β (S9) is kinase active and phosphorylates β-catenin (Ser33/37/Thr41), targeting it for E3 ligase-dependent ubiquitylation and subsequent proteasomal degradation.⁵² We have demonstrated that activation of CDK1 by H. pylori infection induces binding to GSK-3β with phosphorylation at Ser9, rendering it kinase dead. Inactivation of GSK-3β via phosphorylation at Ser9 leads to accumulation of β-catenin with subsequent nuclear translocation and activation of the β-catenin/TCF transcription complex,⁵³ a critical step in gastric tumorigenesis. Using the Krt19^Cre/Cdk1^flox/flox mouse model, we confirmed that silencing CDK1 abrogates the H. pylori-mediated nuclear accumulation of β-catenin. While earlier studies have shown activation of β-catenin by H. pylori,^6,9,12 our findings demonstrate a previously unknown role of CDK1 in this important process. Consistent with the role of β-catenin in cellular proliferation and expansion, gastric organoids and spheroids were fewer in number and smaller in size following silencing CDK1. Furthermore, we detected decreased cancer cell viability in response to CDK1 pharmacologic inhibition. Collectively, our results highlight an important role of CDK1 in GC and provide an explanation for non-mutational frequent activation of β-catenin under H. pylori infection in gastric tumorigenesis.

Given the importance of β-catenin in regulating numerous aspects of cancers, including the initiation, development, and progression of tumors, there have been several attempts to develop inhibitors along the WNT/β-catenin signaling pathway. However, most of the medications targeting Wnt/β-catenin signaling remain experimental and therapeutically poor and did not achieve satisfactory efficacy, specificity, and safety in clinical trials.²² On the other hand, the use of dinaciclib, a small-molecule inhibitor of CDKs 1/2/5, showed encouraging effectiveness and favorable tolerability in a phase II clinical trial for myeloma⁵⁴ and a phase III clinical trial for chronic lymphocytic leukemia.⁵⁵ In lieu of our results, we suggest that targeting CDK1 and CDK1-dependent β-catenin signaling using CDK1 inhibitors could be an attractive therapeutic strategy whether as a single agent or, more likely, in combination with chemotherapeutics.

In summary, this study underscores a critical role of CDK1 overexpression in response to H. pylori infection during gastric tumorigenesis. CDK1 serves as a signaling bridge that links infection and inflammatory signaling to the activation of β-catenin, a critical transcription network co-activator in GC. This mechanism may explain the observed non-mutational activation of β-catenin in GC. The results suggest CDK1 as a molecular druggable vulnerability for the treatment of GC.

Limitations of the study

There are a number of limitations of the study. The present study did not investigate human tissues infected with H. pylori across the stages of gastric tumorigenesis. While the study showed the role of NF-κB in regulating the transcription of CDK1, it is possible that other TFs, activated by H. pylori, may also have an additive effect. Regulation of β-catenin is complex and heterogeneous. While CDK1 presents one mechanism regulating β-catenin, its precise contribution to the overall activation of β-catenin signaling versus other signaling pathways was not determined. The study did not investigate the efficacy of CDK1 inhibitors as single agents or in combination with standard-of-care chemotherapeutics in eliminating cancer cells.

STAR★METHODS

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Wael El-Rifai (wxe45@miami.edu).

Materials availability

This study did not generate new unique reagents.

Data and code availability

• The original data within the paper will be available from the lead contact upon request.

• This paper does not report original code.

• Any additional information in this paper is available from the lead contact upon requests.

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Animals

The 129S(B6N)-Cdk1^tm1Eddy/J (Cdk1^flox/flox) mice and Krt19^Cre/ERT mice were purchased from The Jackson Laboratory (Bar Harbor, ME).^56,57 The Cdk1^flox/flox and Krt19^Cre/ERT were crossed to obtain the Krt19^Cre/Cdk1^flox/flox mice. All animals were maintained in a pathogen-free state following the animal care committee-approved protocol of the University of Miami. Frozen and formalin-fixed paraffin-embedded stomach tissue samples were collected. All mice were of C57/B6/S129 mixed background. The age of mice was between 8-16 weeks. Male and female mice were included in all experiments. The remaining half of the stomach was snapfrozen and stored at −80°C for further use.

Cell culture and reagents

AGS cells were purchased from American Type Culture Collection (ATCC, Manassas, VA). MKN28 and MKN45 cells were obtained from the Riken Cell Bank (Tsukuba, Japan). AGS cells were cultured in F12 media (GIBCO, Carlsbad, CA). MKN28 and MKN45 cells were maintained in RPMI/1640 medium. All the mediums were supplemented with 10% fetal bovine serum (FBS, Invitrogen Life Technologies, Carlsbad, CA) and 1% penicillin/streptomycin (GIBCO). GES1 cells were a kind gift from Dr. Dawit Kidane-Mulat (The University of Texas-Austin, Austin, TX). GES1 cells were cultured in Dulbecco’s modified Eagle’s (GIBCO) medium. All cell lines were ascertained to conform to the original in vitro morphological characteristics. Cell lines were authenticated using short tandem repeat (STR) profiling (Genetica DNA Laboratories, Burlington, NC). All cell lines reported here have been tested and had shown to be free of mycoplasma (R&D Systems, Minneapolis, MN). Reagents and kits are listed in Table S3. Antibodies used in this study are listed in Table S4.

DNA plasmids, siRNA transfection, and shRNA lentivirus generation

Polyjet and LipoJet reagents were used for DNA and siRNA transfection. Respectively, following the manufacturer’s instructions (Signagen Laboratories, Frederick, MD). Cdc2-HA was a gift from Dr. Sander van den Heuvel (Addgene plasmid # 1888). Control siRNA (universal negative control1) was purchased from Sigma-Aldrich (St. Louis, MO). The CDK1 siRNA (AM51331) was obtained from Thermo Fisher Scientific (Waltham, MA). The control shRNA and shCDK1 lentiviral plasmids were purchased from VectorBuilder (Guangzhou, China. https://en.vectorbuilder.com/). The control shRNA or CDK1shRNA lentiviral plasmids and 2nd Generation lentivirus packaging system (LV003, Abmgood) were co-transfected into HEK293T cells using the polyjet transfection reagent. Gastric cells were infected with the lentivirus (control shRNA or CDK1shRNAs) in the presence of 8 μg/mL of polybrene (TR-1003, Sigma-Aldrich). The transient transfection of pCMV4-p65 plasmid (purchased from Addgene)⁵⁸ or CDK1-Luciferase (VectorBuilder) was performed in 6-well plates. More details of DNA plasmids and shRNAs are listed in the Table S3. The siRNA and shRNA sequences are listed in Table S5.

METHOD DETAILS

Luciferase assay

The luciferase reporter assay was performed according to the manufacturer’s protocol (Promega) as previously described.²⁷ Measurements using a Luminometer (BMG LABTECH) were conducted, following the manufacturer’s protocol. β-galactosidase was used for normalization; each transfection was performed in triplicate.

Quantitative real-time PCR analysis

Total RNA was isolated by using the RNeasy Mini Kit (Qiagen, Valencia, CA)and 1 μg RNA was reverse transcribed by an iScript cDNA synthesis kit (Bio-Rad, Hercules, CA). The quantitative real-time PCR (qRT-PCR) was performed using a Bio-Rad CFX Connect Realtime System (Bio-Rad), with the threshold cycle number determined by Bio-Rad CFX manager software version 3.0. All primers were purchased from Integrated DNA Technologies (Table S5). The results of three independent experiments were subjected to statistical analysis. Fold change was calculated using the _ΔΔC(t) method.⁵⁹ HPRT1 was used as a normalization control.

Immunoprecipitation and western blotting

Cells were lysed with RIPA buffer supplemented with protease and phosphatase inhibitors (Santa Cruz, Dallas, TX). Immunoprecipitations of equivalent total protein amounts were performed overnight at 4°C by using a primary antibody previously bound to 40 μL of Protein A Dynabeads (Invitrogen, Carlsbad, CA) per sample. The beads were washed four times with a wash buffer. Proteins were separated on 12.5% SDS-PAGE and transferred to anImmobilon PVDF membrane (Millipore, Burlington, MA). Western blotting analysis was performed using standard methods. β-actin was used as the loading control. All blots were imaged using Bio-Rad ChemiDoc^™ XRS+ System (Bio-Rad).

In situ proximity ligation assay (PLA) and immunofluorescence

To demonstrate the proximity (<40 nm) between two different proteins in gastric cancer cells, PLA was performed by using Duo-link In Situ-Fluorescence kits according to the manufacturer’s instructions (Sigma-Aldrich, St. Louis, MO). The slides were mounted with the mounting solution with DAPI. Each dot represents the proximity of two interacting proteins. Cell images were acquired using an Inverted laser-scanning LSM880-Airyscan (Zeiss, Thornwood, NY) confocal microscope.

Following cell fixation and permeabilization, immunofluorescence was performed using standard methods.⁶⁰ The cells were washed with cold PBS three times and incubated with both Alexa Fluor goat anti-rabbit IgG and Alexa Fluor goat anti-mouse IgG (1:800) (Invitrogen) at room temperature for 1.5 h. Cell images were acquired using an Inverted laser-scanning LSM880-Airyscan (Zeiss, Thornwood, NY) confocal microscope.

Chromatin immunoprecipitation (ChIP)

The ChIP analysis was performed according to the manufacturer’s instructions using ChIP-IT Express Enzymatic and ChIP-IT High Sensitivity kit (Active Motif Inc, Carlsbad, CA). Quantitative real-time PCR was used to analyze the binding of NF-κB to the promoter of the CDK1 target gene. Primers for ChIP qRT-PCR were provided in Table S5.

Infection of mice with H. pylori

All animals studied were carried out following the recommendations from the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. The Institutional Animal Care and Use Committee (IACUC) at the University of Miami approved all protocols and efforts made to minimize animal suffering. C57BL/6 mice were purchased from Charles River Laboratories and divided into two groups (10 per group) for infection with H. pylori or control (broth). At the age of 8–10 weeks, the Krt19^Cre/Ert/Cdk1^flox/flox mice were divided into four group (4–5 per group) for treatment with or without Tamoxifen (50 mg/kg, IP) for 10 days. For infection with H. pylori, mice were orogastrically challenged with Brucella broth, as an uninfected control, or with the mouse-adapted wild-type H. pylori strain PMSS1 (10⁹ CFU/mouse) at the age of 10–12 weeks.⁶¹ Mice were euthanized after 1–2 months post challenge and gastric tissues were harvested for western blot and real-time PCR analyses.

Tumor spheroid culture

MKN28 control and CDK1 stable knockdown cells were seeded into ultra-low attachment 6-well dishes (Corning, Corning, NY) and cultured in serum-free DMEM/F12 supplemented with 20 ng/mL epidermal growth factor (EGF), 10 ng/mL basic fibroblast growth factor (bFGF), 2% B-27 (Life Technologies, Carlsbad, CA). The culture medium was changed every three days. The diameter and number of tumor spheres in three random 100x magnifications fields were calculated under All-in-one Fluorescence Microscope (BZ-X700, Keyence Corp, Atlanta, GA) using the bright field mode.

H. pylori strains

H. pylori cagA⁺ strains (7.13 and J166) were used for cell lines infection. In addition, Rodent-adapted cag⁺ H. pylori strain PMSS1 was used for in vivo mouse experiments. H. pylori bacteria were cultured on trypticase soy agar with 5% sheep blood agar plates (BD Biosciences, Franklin Lakes, NJ) as previously described.⁶² H. pylori strains were then cultured in Brucella broth (BD Biosciences) supplemented with 10% fetal bovine serum (Atlanta Biologicals, Flowery Branch, GA) for 16 to 18 hours at 37°C with 10% CO₂. For in vitro studies, the bacteria were co-cultured with gastric epithelial cells at a multiplicity of infection (MOI) of 100:1.

Gastric organoids

The mouse stomach was cut into 2–3 mm pieces and then incubated in 5 mM EDTA for 30 minutes, with shaking at 37°C. The cell suspension passed through 40 μm cell strainers 2 times. After centrifuging at 1200 RPM for 5 minutes, the pellet was suspended in 50 μL Matrigel (BD Biosciences) and plated in pre-warmed 24-well plates. The 24-well plate was placed in a CO₂ incubator for 20 minutes to allow a complete polymerization of the Matrigel, 500 μL mouse basal medium (STEMCELL, Cambridge, MA) was overlaid. Organoids were collected after 14 days, fixed in 4% paraformaldehyde for 20 min, washed in 1× PBS, and re-suspended in 30 μL Histo-gel (Richard-Allan, White Plains, NY). The histo-gel was placed into a cassette and fixed in 70% ethanol. Paraffin-embedded organoids were pretreated at 65°C for 90 min, followed by deparaffinization using standard procedures.⁶⁰ Antigen retrieval was performed using Tris EDTA Buffer (Genemed, Torrance, CA). Slides were then incubated for primary antibody overnight at 4°C, and further incubated with both Alexa Fluor goat anti-rabbit IgG and Alexa Fluor goat anti-mouse IgG (1:800) (Invitrogen) at room temperature for 2 h. Images were acquired using an inverted laser-scanning LSM880-Airyscan (Zeiss, Thornwood, NY) confocal microscope.

Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA)

The reference gene sets were obtained based on the literature^39,40 or downloaded from MSigDB (https://www.gsea-msigdb.org/gsea/index.jsp). The “limma” package was performed to identify the differential expression genes (DEGs) of CDK1 high expression samples compared with CDK1 low expression samples. The Normalization Enrichment Score (NES) and the false discovery rate (FDR) of each gene set were calculated using the “cluster Profiler”(v3.12.0) package.⁶³ Each gene set was considered significant when the FDR was less than 25%. The Single-Sample Gene Set Enrichment Analysis (ssGSEA) program⁶⁴ was used to quantify the enrichment scores of each stem cell’s relative signature.

Public gene expression data analysis

The TCGA gastric cancer cohort was downloaded from NCI (https://portal.gdc.cancer.gov/) to identify the significant genes and analyze their expression in gastric cancer. In addition, a series of human gastric cancer datasets (GSE122401, GSE84433, GSE54129) and mouse datasets (GSE13873) were obtained from GEO DataSets (https://www.ncbi.nlm.nih.gov/gds/). The mean value of probes was utilized as the gene expression when a gene has multiple probes. All data were analyzed using R software (R 3.6.1; https://www.r-project.org/).

Immunohistochemistry and RNA analysis

Human de-identified gastric tissue samples were obtained from Fujian Medical University Union Hospital (FJMUUH, Fuzhou, China). 216 assessable cases of tumor tissue microarrays (TMA) and their adjacent non-tumor tissues were used for immunohistochemistry. Immunohistochemistry (IHC) staining was performed as described previously,⁶⁵ using the rabbit anti-human CDK1 antibody (ab133327, Abcam, Waltham, MA) and β-catenin antibody (37447, Cell signaling, Danvers, MA). All tissue samples were collected, coded, and de-identified following Institutional Review Board-approved protocols. Images were taken by Olympus FSX100 microscope (Olympus, Japan) at 4× and 40× magnification. The scoring criteria were described as previously.⁶⁵ Five fields were randomly selected to assess the intensity and percentage of positive cells in each slide. The final score for each slide was calculated as the formula: the proportion score × the intensity score (range from 0 to 9 totally).

36 cases of fresh tumor tissues and their adjacent non-tumor tissues were collected for whole-transcriptome sequencing. Trizol (Invitrogen) was utilized to lyse all tissues, and RNA sequencing was performed using gene expression arrays following MIAME guidelines (Shanghai, China). RNA was extracted from 14 mice’s stomachs as described,⁶⁶ the RNA samples were analyzed using the Illumina HiSeq 2500 platform, and the Illumina (San Diego, CA)Tru-seq RNA sample prep kit was used for library preparation. Informed consent was obtained from all the subjects and all experimental protocols using human specimens have been approved by the institutional review committee of FJMUUH.

QUANTIFICATION AND STATISTICAL ANALYSIS

All experiments were repeated in three independent experiments, and a means ± SD was used. The SPSS statistical package for Windows Version 16 (SPSS, Chicago, IL, USA) was used for the Pearson Chi-square test and the multi-variant Cox regression analysis. Statistical significance of the in vitro and in vivo studies was analyzed by the one-way ANOVA, 2-tailed Student’s t-test, and Pearson’s Correlation Coefficient analysis using the GraphPad Prism 8 software (GraphPad Software, Inc, San Diego, CA, USA). Significant differences are described in the figure legends as p < 0.05 or p < 0.01.

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Rabbit CDK1	Cell Signaling	Cat# 28439; RRID: AB_2798959
Mouse CDK1	Cell Signaling	Cat# 9116; RRID: AB_2074795
Rabbit CDK1	AbCam	Cat# ab133327; RRID: AB_11155333
p-GSK3β(S9)	Cell Signaling	Cat# 9323; RRID: AB_2115201
GSK3β	Cell Signaling	Cat# 5676; RRID: AB_10547140
GSK-3 α/β Antibody	R&D Systems	MAB26063
p-β-catenin(S552)	Cell Signaling	Cat# 5651; RRID: AB_10831053
p-β-catenin(S33/37/T41)	Cell Signaling	Cat# 9561; RRID: AB_331729
β-catenin	Cell Signaling	Cat# 8480; RRID: AB_11127855
p-NFKB(S536)	Cell Signaling	Cat# 3033; RRID: AB_331284
NFKB	Cell Signaling	Cat# 8242; RRID: AB_10859369
CagA	Austral Biologicals	HPP-5003-9
β-actin	Sigma-Aldrich	Cat# A1978; RRID: AB_476692
HRP-coupled anti-mouse, anti-rabbit	Promega	Cat# W4021; RRID:AB_430834Cat# W4011; RRID: AB_430833
CDC2/CDK1 Antibody	Novus	Cat# NBP1-85729; RRID: AB_11008973
MIST1/bHLHa15 (D7N4B) XP	Cell Signaling	Cat# 14896; RRID: AB_2798639
Normal IgG	EMD Millipore corp.	3281600
GSK3B Protein	Sino Biological	10044-H07B
CDK1 protein	RayBiotech Life	230-00782-50
Beta-catenin Protein	ABclonal	RP01241
Bacterial and virus strains
J166, 7.13 and PMSS1 H. pylori strains, CagA + types	Gift from Dr. Peek (Vanderbilt University).	N/A
Biological samples
Human gastric tissue samples	Fujian Medical University Union Hospital (FJMUUH, Fuzhou, China)	N/A
Chemicals, peptides, and recombinant proteins
BAY 11-7082	Selleckchem	S2913
Human TNF-alpha	Peprotech	#300-01A-10ug
InSolution™ Cdk1 Inhibitor IV, RO-3306	Millipore Sigma	#217721-2MG
Dinaciclib	Cayman Chemical	# 14707
Tamoxifen	Millipore Sigma	T5648-1G
2nd Generation packaging	Abmgood	LV003
Polybrene	Sigma-aldrich	TR-1003
PolyJet Reagent	Signagen	#SL100688
B-27™ Supplement	Thermo fisher	#17504044
FGF-Basic (AA 1-155) Recombinant Human Protein	Thermofisher	PHG0264
EGF Recombinant Human Protein	Thermofisher	PHG0311
LipoJet Reagent	Signagen	#SL100468
Histo-gel	Richard-Allan, White Plains, NY	HG-4000-012
Critical commercial assays
Duolink In Situ PLA Probe Anti-Rabbit PLUS	Sigma-aldrich	DUO92002
ChIP-IT Express Enzymatic	Active motif	#53039
ChIP-IT High Sensitivity	Active motif	#53040
Tru-seq RNA sample prep kit	illumina	RS-122-2001
Deposited data
Raw and analyzed data	This paper	GEO DataSets: human gastric cancer datasets (GSE122401, GSE84433, GSE54129) and mouse datasets (GSE13873)
Gene Set Enrichment Analysis (GSEA) and Single-sample Gene Set Enrichment Analysis (ssGSEA) data	This paper	MSigDB (https://www.gsea-msigdb.org/gsea/index.jsp)
Experimental models: Cell lines
MKN28	Riken Cell Bank (Tsukuba, Japan	N/A
MKN45	Riken Cell Bank (Tsukuba, Japan	N/A
AGS	American Type Culture Collection (ATCC, Manassas, VA)	N/A
GES1	Gift from Dr. Dawit Kidane-Mulat (The University of Texas-Austin, Austin, TX)	N/A
Experimental models: Organisms/strains
129S(B6N)-Cdk1tm1Eddy/J (Cdk1flox/flox) mice and Krt19Cre/ERT mice	Jackson Laboratory (Bar Harbor, ME)	Strain #:028028 RRID: IMSR_JAX:028028
C57BL/6 mice	Charles River Laboratories (Wilmington, MA)	Strain Code: 027
pTetOne Vector	Takarbio	# 634303
Oligonucleotides
CDK1 siRNA (NM_001786): GGUUAUAUCUCAUCUUUGATT	Thermo fisher	AM51331
pLV[shRNA]-Puro-U6>hCDK1[shRNA#1]: CAGGTTATATCTCATCTTTGA	vectorbuilder	VB201117-1178spk
pLV[shRNA]-Puro-U6>hCDK1[shRNA#2]: CCAGTTGACATTTGGAGTATA	vectorbuilder	VB201117-1180uan
pLV[shRNA]-Puro-U6>hCDK1[shRNA#4]: GCTGTACTTCGTCTTCTAATT	vectorbuilder	VB201228-1074bjm
pLV[shRNA]-Puro-U6>hCDK1[shRNA#3]: GATTTGGACAATCAGATTAAG	vectorbuilder	VB201228-1075auu
Primers for PCR and CHIP, see Table S5	This paper	N/A
Recombinant DNA
Pcmv4 p65 Plasmid	Addgene	#21966
TOP flash (WT TCF Reporter Plasmid)	upstate biotechnology	#21-170
FOP flash (mutant TCF Reporter Plasmid)	upstate biotechnology	#21-169
pRP[Pro]-[CDK1]>Luciferase	vectorbuilder	VB201208-1092sem
Software and algorithms
SPSS statistical package	SPSS, Chicago, IL, USA	NA
GraphPad Prism 8 software	GraphPad Software, Inc, San Diego, CA, USA	NA
JASPAR	https://jaspar.genereg.net/	NA

Highlights.

• Infection with H. pylori is the main risk factor for gastric tumorigenesis

• H. pylori infection induces CDK1 expression via an NF-κB-dependent transcription

• CDK1 promotes activation of β-catenin signaling and cellular expansion