Apatinib enhances targeted immunotherapy via the IL-6-gp130-PI3K pathway in HER2-positive gastric cancer

Cell culture and reagents

The human GC cell lines NCI-N87, AGS, HGC-27, MKN-45, and NUGC-3 were purchased from Procell Life Science & Technology Co., Ltd (Wuhan, Hubei, China). SNU-216 was purchased from Kinlogix Biotech Co., Ltd (Guangzhou, Guangdong, China). NCI-N87, SNU-216, HGC-27, MKN-45, and NUGC-3 were cultured in RPMI-1640 medium (GibcoTMLife Technologies, NY, USA), whereas AGS was maintained in Ham’s F-12 medium (Procell Life Science & Technology Co., Wuhan, China), both supplemented with 10% fetal bovine serum (FBS) (GibcoTMLife Technologies, NY, USA). The cells were grown in a humidified incubator at 37°C under 5% CO₂. Apatinib mesylate (Sigma-Aldrich, St Louis, MO, USA), 740 Y-P (TargetMol, Shanghai, China), and coumermycin A1 (GlpBio, California, USA) were stored at −80°C, whereas trastuzumab (Roche Pharma, South San Francisco, CA), tislelizumab (BeiGene Co., Beijing, China), and tocilizumab (Roche Pharma, South San Francisco, CA) were stored at 4°C.

Transfection

Short-interfering RNA (siRNA) constructs targeting HER2 (HER2-siRNA1–3) and a non-targeting control were designed and synthesized by Mailgene (Beijing, China). Sequences are provided in Table S1. NCI-N87 or SNU-216 cells (1 × 10⁵ per well in 6-well plates) were transfected with 50 nM HER2-siRNA1–3 or non-targeting control with Lipofectamine 2000 reagent (Invitrogen, San Diego, CA), according to the manufacturer’s instructions. Cells were harvested 48 h after transfection for subsequent analysis.

Cell proliferation, colony formation, and 5-ethynyl-2′-deoxyuridine (EdU) assays

Cell Counting Kit (CCK)-8 assays (Report Biotech, Shijiazhuang, China) were used to measure cell proliferation. In accordance with the manufacturer’s protocol, cells were seeded at a density of 1 × 10⁴ cells/well in 96-well plates with 100 μL medium. Three duplicate wells were used per group. After incubation times of 0, 12, 24, 48, 72, or 96 h, 10 μL CCK-8 medium was added to each well for 2 h. The absorbance of each well was measured at 450 nm with a microplate reader (Bio-Rad, Hercules, CA).

For colony formation assays, HER2-positive GC cells were seeded at a density of 2 × 10³ cells/well in 6-well plates and cultured for 10 days. At day 10, colonies were fixed with 4% paraformaldehyde for 15 min and stained with 0.1% crystal violet solution for 10 min. After staining, images of each well were acquired with a digital camera. Colony numbers were quantified in ImageJ software (NIH, Bethesda, MD, USA).

For EdU incorporation assays, HER2-positive GC cells were seeded in 24-well plates at a density of 2 × 10⁴ cells/well for 24 h, then incubated with 10 μM EdU (Beyotime, Shanghai, China) for 2 h at 37°C. After fixation with 4% paraformaldehyde and permeabilization with 0.5% Triton X-100, EdU detection was performed with BeyoClick™ EdU-555 (Beyotime, Shanghai, China) according to the manufacturer’s instructions. Nuclei were counterstained with 4′,6-diamidino-2-phenylindole (DAPI) for 10 min. Fluorescence images were captured with a fluorescence microscope (Olympus, Tokyo, Japan) at 200× magnification. The proliferation rate was calculated as (EdU⁺ and DAPI⁺ nuclei)/(total DAPI⁺ nuclei) × 100%.

Migration assays

Transwell chambers with 8-μm pore sizes (Corning, New York, NY) were used to determine cell migration. A total of 200 μL cell suspension (diluted in RPMI-1640 without FBS) with a density of 1 × 10⁵ cells/mL was added to the upper chamber, whereas 600 μL RPMI-1640 with 10% FBS was added to the lower chamber. The chamber was incubated at 37°C for 24 h, and a cotton swab was used to remove the non-migratory cells from the upper surface of the chamber membrane. Cells that migrated to the underside were fixed with 4% paraformaldehyde and stained with 1% crystal violet. Stained cells were counted in 3 random fields with an inverted microscope (Nikon, Tokyo, Japan) at 200× magnification.

Cell cycle analysis

HER2-positive GC cells were harvested 48 h after the indicated treatments and washed twice with phosphate-buffered saline (PBS). Subsequently, cells were permeabilized with 70% ethanol overnight at 4°C. After being washed twice in PBS, cells were incubated for 30 min at room temperature (RT) in a staining solution containing propidium iodide (50 μg/mL) and RNase A (200 μg/mL). Finally, cells were harvested, washed, resuspended in PBS to a final concentration of 1 × 10⁶/mL, and analyzed with a BD LSRFortessa flow cytometer (BD Biosciences, Franklin Lakes, USA).

Western blot

Total protein extracted from cells or cancer tissues with radioimmunoprecipitation assay buffer (Zomanbio, Beijing, China) was subjected to sodium dodecyl sulfate–polyacrylamide gel electrophoresis, followed by electrotransfer to a polyvinylidene difluoride membrane. The membrane was blocked in 5% non-fat dry milk for 2 h and incubated at 4°C overnight with primary antibodies (listed in Table S2). The membranes were washed before incubation with secondary antibodies (dilution 1:5,000; S1002; Report Biotech, Shijiazhuang, China) for 2 h. The protein bands were visualized with enhanced chemiluminescence (Zomanbio, Beijing, China). Band intensities were quantified through gray value analysis in ImageJ software.

Bioinformatics analysis

Publicly available RNA-sequencing (RNA-seq) and microarray datasets were retrieved from the NCBI GEO database under accession numbers GSE129221 (apatinib-treated lung adenocarcinoma cells), GSE185783 (apatinib-treated liposarcoma cells), and GSE220917 (patients with HER2-positive GC with differential survival outcomes after trastuzumab maintenance monotherapy). Differentially expressed genes (DEGs) were identified through statistical comparison of gene expression profiles between distinct groups (e.g., apatinib treatment vs. control; long-term responding vs. fast progressing group). The clusterProfiler package, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases, was used for pathway enrichment analysis of the identified DEGs.

RNA-seq data for 44 HER2-positive stomach adenocarcinoma (STAD) samples were retrieved from The Cancer Genome Atlas (TCGA) database. All gene expression data were normalized before analysis. HER2-positive samples were stratified into interleukin-6 (IL-6)-high (n = 22) and IL-6-low (n = 22) groups according to the median IL-6 expression value. Pearson correlation analyses were performed to evaluate the associations of IL-6 expression with angiogenesis-related genes [VEGFA, kinase insert domain receptor (KDR)] and the Angiogenesis Score. The Angiogenesis Score was calculated for each sample via single-sample gene set enrichment analysis based on a gene set comprising VEGFA, VEGFC, Fms-related receptor tyrosine kinase 1 (FLT1), KDR, hypoxia inducible factor 1A (HIF1A), angiopoietin-1 (ANGPT1), and angiopoietin-2 (ANGPT2). The cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to deconvolute the relative abundance of immune cell subsets [CD8⁺ T cells, regulatory T cells (Tregs), and M2-like tumor-associated macrophages (M2-TAMs)] within the tumor microenvironment (TME). An Immune Suppression Index was calculated as the ratio of (Tregs + M2-TAMs) to (CD8⁺ T cells + M1 macrophages). Spearman correlation analysis was used to assess the relationship between IL-6 expression and immune cell subsets.

Co-immunoprecipitation (co-IP)

Protein extracted from cells with IP Lysis Buffer (Boyi Biotech, Changzhou, China) was incubated with anti-gp130 (Table S2) for 30 min and absorbed to Protein A/G MagPoly Beads (Boyi Biotech, Changzhou, China) overnight to form immunocomplexes. These immunocomplexes were released by boiling and analyzed with western blot.

Cellular immunofluorescence (IF)

Cells were seeded at a density of 1 × 10⁵ cells/well in 6-well plates with 1 mL medium and incubated at 37°C for 24 h, after which the medium was removed. After fixation in 4% paraformaldehyde for 10 min, permeabilization with 0.3% Triton X-100, and blocking with 3% bovine serum albumin, the cells were incubated at 37°C for 2 h with the following primary antibodies: anti-phospho-HER2, anti-phospho-PI3K, and anti-gp130 (listed in Table S2). The cells were then incubated with secondary polymer-horseradish peroxidase anti-rabbit/mouse antibody (no dilution; AFIHC001; AiFang biological, Changsha, China) for 20 min at RT. A tyramide signal amplification kit (AiFang biological, Changsha, China) was used to avoid non-specific antibody staining from the same species, in accordance with the manufacturer’s instructions. Cell nuclei were stained with DAPI for 10 min, and images were captured with a fluorescence microscope at 200× magnification. Fluorescence intensity was analyzed in ImageJ software as a semi-quantitative measure of protein expression.

Isolation of human CD34⁺ cells

Human cord blood samples were collected from healthy full-term deliveries. In accordance with previously reported protocols for isolation of human CD34⁺ (hCD34⁺) cells²⁹, mononuclear cells were isolated from cord blood in a 1:1 ratio with lymphocyte separation solution (Miltenyi Biotec, GoldBach, Germany), then centrifuged at 2,000 rpm for 20 min. Subsequently, a MACS human CD34 MicroBead Kit (Miltenyi Biotec, GoldBach, Germany) was used to select hCD34⁺ cells from the isolated mononuclear cells, in accordance with the manufacturer’s instructions.

Animals

Animal experiments were approved by the Ethics Board of the Animal Ethics Committee of the Fourth Hospital of Hebei Medical University (ethics number 2022166). Twelve athymic BALB/c-nu mice 4–6 weeks old were purchased from HFK Bioscience Company [Beijing, China; permission no. SCXK (Jing) 2019-0008], and 36 athymic NOD/ShiLtJGpt-Prkdc^em26Cd52Il2rg^em26Cd22/Gpt (NCG) mice 5–6 weeks old were purchased from GemPharmatech [Beijing, China; permission no. SCXK (Jing) 2023-0008]. All mice were housed and treated in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.

Six- to eight-week-old NCG mice were exposed to 200 cGy radiation. Subsequently, 2 × 10⁵ isolated hCD34⁺ cells in 0.1 mL PBS were intravenously injected into NCG mice. At 12 weeks after transplantation, the NCG mice injected with hCD34⁺ cells were assessed according to the percentage of hCD45⁺ cells in peripheral blood. Humanized NCG mice with more than 20% hCD45⁺ cells were used in subsequent experiments.

Xenograft tumors were established by subcutaneous injection of NCI-N87 cells at a density of 1 × 10⁷ cells/mL in 0.2 mL PBS into the shoulders of BALB/c-nu and humanized NCG mice. After tumor volumes reached 100 mm³, the BALB/c-nu mice were randomly divided into 4 groups (n = 3 per group): control, apatinib treated, trastuzumab treated, and apatinib plus trastuzumab treated. To verify successful human immune reconstitution in the TME, we sacrificed 3 humanized NCG mice bearing 100 mm³ tumors before treatment initiation. Human immune cell infiltration in tumor tissues was assessed with flow cytometry for human CD45, CD3, and CD68. The distribution frequency of these immune cells was similar to that in previous reports^30,31, thus confirming the successful reconstitution of a humanized mouse model with human immune cells. To investigate the synergistic effect of apatinib on trastuzumab-induced inhibition in ICI therapy for HER2-positive GC cells, we randomized humanized hematopoietic stem cell and tumor cell line-derived xenografts (hHSC-CDXs) into 4 groups (n = 3 per group): control, apatinib plus tislelizumab, trastuzumab plus tislelizumab, and triple-drug regimen (apatinib, trastuzumab, and tislelizumab). Furthermore, to assess the effect of tocilizumab on ICI therapy in HER2-positive GC, we divided hHSC-CDXs into 6 groups (n = 3 per group): control; tocilizumab plus tislelizumab treatment; tocilizumab and apatinib plus tislelizumab treatment (TAT); triple-drug regimen of tocilizumab, trastuzumab, and tislelizumab (TTT); triple-drug regimen of apatinib, trastuzumab, and tislelizumab (ATT); and quadruple-drug regimen of tocilizumab, apatinib, trastuzumab, and tislelizumab (TATT). Apatinib was administered intragastrically at a dose of 20 mg/kg daily; trastuzumab was administered via intraperitoneal injection at a dose of 10 mg/kg every 5 days; tocilizumab was administered via intraperitoneal injection at a dose of 10 mg/kg every 5 days; and tislelizumab was administered via intraperitoneal injection at a dose of 5 mg/kg every 5 days. In the combined treatment groups, each drug was administered at 30 min intervals. Tumor volume was calculated with the following formula: length × (width)²/2. Tumor tissues were processed through the following methods: fixation in 4% formaldehyde solution, storage at −80°C without embedding medium, or storage at −80°C after embedding in optimal cutting temperature compound.

Tumor tissue immunohistochemistry, flow cytometry, and IF

Tumor tissues were fixed 24 h in 4% formaldehyde and paraffin-embedded, and 4 μm-thick sections were immunostained with anti-CD31 (1:500 dilution; HA724146; Huabio, Hangzhou, China) overnight at 4°C. After being washed with PBS, the sections were incubated with undiluted secondary antibodies (PV-6001; ZSGB-BIO, Beijing, China) for 20 min, then washed again. Detection was performed with a horseradish peroxidase–conjugated compact polymer system with diaminobenzidine as the chromogen. Finally, the slices were counterstained with hematoxylin, dehydrated, and mounted on resinous mounts. Micro-vessel density (MVD) was quantified according to the Weidner method: any CD31-positive cell or cluster distinctly separate from the adjacent tissue was counted as a single micro-vessel. Individual micro-vessels of the highest neovascularization areas in the tumor tissue were counted at high magnification (200×) after scanning at low magnification (100×)³².

Tumor tissues were excised and homogenized in R10 medium (RPMI 1640 + 10% FBS + 1× penicillin–streptomycin). Single-cell suspensions, generated by passage of homogenized tissue through a 70 μm cell strainer, were centrifuged (300 × g) at 4°C for 5 min, then layered over Ficoll-Paque medium. After centrifugation again (400 × g) at RT for 20 min, cells were collected, washed, and resuspended in FACS staining buffer. For flow cytometric analysis, 1 × 10⁶ cells were stained with antibodies (listed in Table S2) for 15 min at RT, then washed twice with FACS staining buffer. Data were analyzed in FlowJo v10.8.1 software after analysis with a BD LSRFortessa flow cytometer. Immunophenotyping used a hierarchical gating strategy: first, hCD45 was stained to identify human immune cells, and M2-TAMs were identified as CD68⁺CD163⁺, whereas CD8⁺ T cells were identified as CD3⁺CD8⁺ within the hCD45⁺ gate. Within the CD3⁺CD8⁺ subset, granzyme B (GZMB) and T-cell immunoglobulin and mucin-domain containing molecule 3 (TIM-3) were co-stained to distinguish cytotoxic subsets (GZMB⁺TIM-3⁻) from exhausted (GZMB⁻TIM-3⁺) CD8⁺ T cells. Concurrently, Foxp3 and CD4 were co-detected to identify Tregs as CD4⁺Foxp3⁺ cells within the CD3⁺CD8⁻ subset.

Frozen tissue embedded in optimal cutting temperature compound was serially sectioned into 4 μm-thick sections and incubated for 60 min with a mixture of primary antibodies: anti-CD68 paired with anti-CD163; anti-CD4 paired with anti-FOXP3; anti-CD3E paired with anti-CD8; anti-CD8 paired with anti-GZMB; or anti-CD8 paired with anti-TIM3 (listed in Table S2). The sections were subsequently incubated with a mixture of secondary anti-rabbit (1:400 dilution; A24221; Abbkine Scientific, Wuhan, China) and anti-mouse antibodies (1:400 dilution; A24211; Abbkine Scientific, Wuhan, China) for 30 min. All experiments were performed in a dark humidified chamber at RT. The sections were then cover-slipped with Antifade Mounting Medium (Solarbio, Beijing, China) and imaged with a fluorescence microscope at 400× magnification. The number of cells was counted in ImageJ software.

Cytokine detection

Six cytokines, IL-2, IL-4, IL-6, IL-10, tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ), were analyzed with a flow fluorescence immunomicrobead assay (Weimi Bio-Tech, Hunan, China). For tumor tissue, 50 μL lysis buffer (Thermo Fisher Scientific, Waltham, MA) was used to homogenize 10 mg mouse tumor tissue, and the protein content was subsequently diluted to 5 mg/mL. For HER2-positive GC cells, 2 × 10⁵ cells were cultured for 72 h, and the medium was collected. Next, 25 μL prepared lysis buffer or cell culture medium was incubated with 10 μL microbeads and detection antibody for 3 h in the dark. Finally, the samples were analyzed with a BD FACSCanto flow cytometer (Becton, Dickinson and Company, Franklin Lake, New Jersey).

RNA extraction and quantitative reverse transcription polymerase chain reaction (qRT-PCR)

Total RNA was extracted with TRIzol (Invitrogen, USA), and cDNA synthesis was performed with a cDNA Synthesis Kit (Zsgentech, Tianjin, China) according to the manufacturer’s protocol. qRT-PCR was performed with a 2× ZAPA3G SYBR Green qPCR Mix kit (Zsgentech, Tianjin, China) and a qRT-PCR detection system (Bio-Rad Laboratories, USA). The reaction cycling program consisted of 95°C for 5 min, followed by 40 cycles of 10 s at 95°C and 20 s at 60°C. Relative expression levels of IL-6 and miR-520f-3p were calculated with the 2^−ΔΔCt method with GAPDH and U6 normalization. Primer sequences are provided in Table S3.

Patients

Three patients with HER2-positive stage IV GC were admitted to the Fourth Hospital of Hebei Medical University. All procedures were approved by the Ethics Committee of the Fourth Hospital of Hebei Medical University (ethics number 2020KY191), and written informed consent to participate was obtained from the patients.

Statistical analysis

Bioinformatic differential expression analysis was performed with the limma R package to identify genes with differential expression across distinct groups. DEGs were defined under stringent thresholds of P-value ≤ 0.05 and absolute log₂ (fold change) >1. Functional enrichment analysis was applied to the DEGs, and pathways with P ≤ 0.05 were considered statistically significant. Correlation analyses between 2 variables were performed with Pearson or Spearman correlation coefficients, depending on data normality and linearity assumptions. The Wilcoxon rank-sum test was used for comparisons between 2 groups. One-way ANOVA was applied for comparisons among multiple groups, and post hoc pairwise comparisons were performed with the LSD-t test when the overall difference was statistically significant (P ≤ 0.05). The results are presented as mean ± standard deviation, and a P-value ≤ 0.05 was considered to indicate statistical significance. Statistical analyses were performed in IBM SPSS Statistics 28.0 and R software (v. 4.5.0).

Apatinib enhances trastuzumab-induced inhibition of HER2-positive GC cells

We initially investigated the synergistic effect of apatinib in enhancing trastuzumab efficacy in HER2-positive GC cells. The NCI-N87 and SNU-216 cell lines were used, because they were found to exhibit the highest HER2 expression among the 6 investigated GC cell lines (Figure S1A), as supported by previous reports³³. We established isogenic HER2-negative controls through siRNA transfection in HER2-positive GC cells. HER2-siRNA3 showed the most pronounced inhibitory effect on HER2 levels and was therefore selected for subsequent functional experiments (Figure S1B). Dose–response analysis revealed that 5 μM apatinib and 10 μg/mL trastuzumab were the lowest effective concentrations exerting anti-proliferative effects at 48 h in HER2-positive GC cells (Figure S1C, D). These concentrations were therefore used for subsequent experiments. Apatinib inhibited cell proliferation (48–96 h), colony formation, DNA synthesis (EdU incorporation), cell cycle progression (evidenced by increased G0/G1-phase fraction and decreased S-phase fraction), and migration in both cell lines (Figures 1A–C and S1E, F). Trastuzumab treatment and HER2 knockdown mimicked the changes in proliferation, colony formation, DNA synthesis, cell cycle progression, and migration observed under apatinib treatment (Figures 1A–C and S1E, F). In addition, treatment with apatinib plus trastuzumab, in contrast to control, monotreatment (apatinib only or trastuzumab only) or HER2 knockdown, amplified these functional changes (Figures 1A–C and S1E, F). Because the PI3K/AKT, JAK2/STAT3, and MAPK signaling pathways modify trastuzumab resistance, we measured the changes in these signal transduction pathways under apatinib and/or trastuzumab treatment. Both apatinib and trastuzumab decreased the phosphorylation of PI3K p85α (Tyr607), AKT (Ser473), JAK2 (Tyr1007/1008), and STAT3 (Tyr705) (Figure 1D). Combined treatment further amplified the effects of PI3K/AKT and JAK2/STAT3 pathway inhibition beyond those observed in the control, monotreatment, and HER2 knockdown groups (Figure 1D). Therefore, apatinib enhances trastuzumab-induced inhibition by blocking the PI3K/AKT and JAK2/STAT3 pathways in HER2-positive GC cells.

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

Figure 1

Apatinib enhances trastuzumab-related inhibition of HER2-positive GC in vitro. (A) CCK-8 assay showing the effects of HER2-siRNA, apatinib, and/or trastuzumab on proliferation in NCI-N87 and SNU-216 cells. (B) Colony formation assay analyzing the clonogenicity of NCI-N87 and SNU-216 cells after HER2 knockdown, and apatinib and/or trastuzumab treatment. (C) Transwell assay measuring the migratory ability of NCI-N87 and SNU-216 cells after HER2 knockdown, and apatinib and/or trastuzumab treatment. Scale bar: 200 μm. (D) Western blot analysis of key proteins in the MAPK, PI3K/AKT, and JAK2/STAT3 pathways in GC cells after HER2 knockdown, and apatinib and/or trastuzumab treatment. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. NC, negative control; HER2, human epidermal growth factor 2; GC, gastric cancer; CCK-8, Cell Counting Kit 8; PI3K, phosphatidylinositol 3-kinase; AKT, protein kinase B; MAPK, mitogen-activated protein kinase; MEK, mitogen-activated protein kinase kinase; ERK, extracellular regulated protein kinases; JAK2, Janus kinase 2; STAT3, signal transducer and activator of transcription 3.

Apatinib enhances the inhibitory effect of trastuzumab through the PI3K/AKT/STAT3 pathway

We next investigated how apatinib enhanced the inhibitory effect of trastuzumab via the PI3K/AKT and JAK2/STAT3 pathways. The PI3K agonist 740 Y-P and the JAK2 agonist coumermycin A1 were added to HER2-positive GC cells treated with apatinib or trastuzumab. Because 10 μM 740 Y-P markedly increased PI3K p85α phosphorylation at Tyr607 between 24 h and 48 h (Figure S2A), and 10 μM coumermycin A1 enhanced JAK2 phosphorylation at Tyr1007/1008 during the same period in HER2-positive cells (Figure S2B), we selected these concentrations for functional rescue assays. Treatment with 740 Y-P fully abrogate the apatinib or trastuzumab-induced suppression of the phosphorylation of PI3K p85α (Tyr607), AKT (Ser473), and STAT3 (Tyr705) without affecting JAK2 (Tyr1007/1008) phosphorylation (Figure S2C). Coumermycin A1 restored phosphorylation of JAK2 (Tyr1007/1008) and STAT3 (Tyr705) after inhibition by apatinib or trastuzumab, without affecting PI3K/AKT pathway phosphorylation (Figure S2C).

Furthermore, both 740 Y-P and coumermycin A1 significantly attenuated the anti-proliferation, anti-clonogenicity, anti-DNA synthesis, cell cycle arrest (increased G0/G1 and decreased S-phase fractions), and anti-migratory functions under apatinib or trastuzumab treatment (Figures S2D and S3A–D). Of note, 740 Y-P almost completely reversed the cellular functional changes (including proliferation, clonogenicity, DNA synthesis, cell cycle progression, and migration) induced by apatinib or trastuzumab, whereas no significant differences in functional changes with respect to the control group were observed (Figures S2D and S3A–D). In contrast, coumermycin A1 only partially attenuated the effects of apatinib or trastuzumab treatment, but showed significant changes with respect to the control group (Figures S2D and S3A–D). Therefore, the synergistic effects of apatinib and trastuzumab were achieved primarily through inhibition of the PI3K/AKT/STAT3 axis.

Apatinib enhances trastuzumab-induced tumor inhibition in BALB/c-nu xenografts

We next verified the synergistic effects of apatinib and trastuzumab in vitro. Compared with controls, apatinib achieved growth inhibition of BALB/c-nu xenografts at 16 days (Figure 2A), and trastuzumab simultaneously achieved growth inhibition (Figure 2A). Moreover, the tumor volume of xenografts treated with apatinib plus trastuzumab from 16 to 20 days was significantly lower than observed for control xenografts; a growth difference with respect to monotreatment xenografts was also observed from 12 to 20 days (Figure 2A). Therefore, apatinib enhanced trastuzumab-induced inhibition in vivo. CD31 expression was measured to compare the MVD difference after target treatment, and both apatinib and trastuzumab induced significantly lower MVD than observed in the controls (Figure 2B). In agreement with the tumor shrinkage trend, the combination of apatinib with trastuzumab significantly enhanced the decrease in MVD with respect to that observed in with both control xenografts and each monotherapy xenograft (Figure 2B). Therefore, apatinib enhanced trastuzumab-induced inhibition by inhibiting angiogenesis. The trend in phosphorylation changes for PI3K p85α (Tyr607), AKT (Ser473), and STAT3 (Tyr705) after apatinib and/or trastuzumab treatment was similar to that observed in vitro (Figure 2C). In summary, apatinib coordinates with trastuzumab in suppressing HER2-positive GC tumors via inhibiting angiogenesis and the PI3K/AKT/STAT3 signaling pathway.

• Download figure
• Open in new tab
• Download powerpoint

Figure 2

Apatinib enhances trastuzumab-associated inhibition of HER2-positive GC in BALB/c-nu xenografts. (A) Images of NCI-N87 derived tumor tissues and tumor growth curves for BALB/c nu mice treated with vehicle, apatinib, trastuzumab, or both. (B) MVD quantified by CD31 immunohistochemistry. Black scale bar: 100 μm; red scale bar: 30 μm. (C) Western blot analysis of key proteins in the PI3K/AKT/STAT3 pathway in tumor tissues. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. NC, negative control; HER2, human epidermal growth factor 2; GC, gastric cancer; PI3K, phosphatidylinositol 3-kinase; AKT, protein kinase B; STAT3, signal transducer and activator of transcription 3; MVD, micro-vessel density.

Apatinib acts through regulating IL-6

To explore the underlying mechanisms of apatinib in enhancing trastuzumab efficacy, we performed bioinformatics analysis based on GEO data. The DEG profiles after apatinib treatment (GSE129221, lung adenocarcinoma; GSE185783, liposarcoma) implicated cytokine-related pathways and immune-related signaling pathways (Figure 3A, B) in this process, and also highlighted apatinib’s effect on the ErbB signaling pathway (Figure 3A, B). We subsequently analyzed dataset GSE220917, which compares DEGs between patients with long-term responding vs. fast progressing HER2 positive GC during trastuzumab maintenance monotherapy. The PI3K/AKT pathway and cytokine-related pathways appeared to modify trastuzumab sensitivity (Figure 3C). Therefore, we hypothesized that apatinib related trastuzumab enhancement might involve cytokines and the immune response.

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

Figure 3

Functional enrichment and cytokine profiling reveal that apatinib is associated with IL-6. (A) KEGG and GO pathway enrichment analysis in lung adenocarcinoma cells (GSE129221: post- vs. pre-apatinib treatment); (B) KEGG and GO pathway enrichment analysis in liposarcoma cells (GSE185783: post- vs. pre-apatinib treatment); (C) KEGG and GO pathway enrichment analysis in patients with HER2-positive GC (GSE220917: long-term responders vs. fast progressors during trastuzumab maintenance). (D). Flow fluorescence immune-microbead assay quantifying cytokine levels in NCI-N87 and SNU-216 cells after treatment with HER2-siRNA, apatinib, and/or trastuzumab. (E) qRT-PCR analysis of IL-6 mRNA expression in NCI-N87 and SNU-216 cells treated with HER2-siRNA, apatinib, and/or trastuzumab. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, Gene Ontology; HER2, human epidermal growth factor 2; GC, gastric cancer; NC, negative control; IL-2, interleukin-2; IL-4, interleukin-4; IL-6, interleukin-6; IL-10, interleukin-10; TNF-α, tumor necrosis factor-α; IFN-γ, interferon-γ; qRT-PCR, quantitative reverse transcription polymerase chain reaction.

To validate this hypothesis, we measured cytokines (including IL-6, IFN-γ, IL-2, TNF-α, IL-4, and IL-10) in HER2-positive GC cells after apatinib treatment. HER2 knockdown, apatinib monotreatment, and trastuzumab monotreatment decreased IL-6 levels with respect to those in the control group, and the combined treatment resulted in a more pronounced IL-6 decrease (Figure 3D). The suppressive effect of these treatments on IL-6 expression was further confirmed through qRT-PCR (Figure 3E), which indicated that IL-6 counteracted HER2-targeted inhibition by apatinib and trastuzumab.

To further clarify the biological importance of IL-6 in HER2-positive GC, we compared IL-6 expression in 44 HER2-positive GC tumors from the TCGA-STAD cohort. Correlation analysis revealed that IL-6 expression was positively associated with both the Angiogenesis Score (Figure S4A) and expression of KDR (also known as VEGFR2; Figure S4B), a key angiogenic receptor and direct target of apatinib. These bioinformatics analysis results indicating the association between IL-6 and VEGFR2, together with our data, suggested that apatinib inhibits IL-6 by targeting VEGFR2. Additional bioinformatics analyses indicated that IL-6 was associated with an immunosuppressive TME in HER2-positive GC, as evidenced by elevated infiltration of M2-TAMs (Figure S4C); an elevated Immune Suppression Ratio (Figure S4D); and significantly diminished expression of GZMB (Figure S4E), a marker of cytotoxic lymphocyte effector function. Therefore, apatinib might enhance the efficacy of immunotherapy by altering the immunosuppressive TME via inhibition of IL-6 in HER2-positive GC.

Apatinib suppresses HER2-positive GC cells via the IL-6-gp130-PI3K pathway

We next investigated the regulatory mechanism of IL-6 for downstream signals. Dose–response assays identified 20 ng/mL IL-6 and 10 μg/mL tocilizumab as the minimal effective concentrations for proliferation at 48 h in HER2-positive GC cells (Figure S5A, B). Therefore, these concentrations were selected for subsequent experiments. IL-6 promoted cell proliferation (24–96 h), clonogenicity, DNA synthesis, cell cycle progression (elevated S-phase fraction and reduced G0/G1-phase fraction), and migration, all of which were suppressed by apatinib and/or trastuzumab (Figures 4A–D and S5C). In contrast, tocilizumab, an antibody to IL-6R, suppressed these malignant phenotypes [including proliferation, clonogenicity, DNA synthesis, cell cycle progression (decreased S-phase fraction and elevated G0/G1-phase fraction), and migration], and further enhanced the inhibitory effect of apatinib and/or trastuzumab on GC cells (Figures 4A–D and S5C).

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

Figure 4

Apatinib suppresses HER2-positive GC cells via IL-6. (A) CCK-8 assay assessing the proliferation of NCI-N87 and SNU-216 cells after treatment with apatinib, trastuzumab, IL-6, or TCZ. (B) Colony formation assay analyzing the clonogenicity of GC cells after treatment with apatinib, trastuzumab, IL-6, or TCZ. (C) EdU assay quantifying DNA synthesis of GC cells after treatment with apatinib, trastuzumab, IL-6, or TCZ. Scale bar: 200 μm. (D) Transwell migration assay on GC cells after treatment with apatinib, trastuzumab, IL-6, or TCZ. Scale bar: 200 μm. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. NC, control group; TCZ, tocilizumab; IL-6, interleukin-6; HER2, human epidermal growth factor 2; GC, gastric cancer; CCK-8, Cell Counting Kit 8; EdU, 5-ethynyl-2′-deoxyuridine.

The application of IL-6 and tocilizumab demonstrated that IL-6 activates the PI3K/AKT/STAT3 pathway and consequently enhances the growth of HER2-positive GC cells (Figure 5A). Because IL-6 binding to gp130 induces PI3K p85 tyrosine phosphorylation in prostate cancer³⁴, we further examined gp130 status after IL-6 induction. IL-6 upregulated gp130 expression in HER2-positive GC cells, as expected (Figure 5B). Moreover, miR-520f-3p–mediated suppression of gp130 was alleviated by IL-6 in GC (Figure S5D), as previously reported³⁵. Additionally, increased gp130 expression was accompanied by increased recruitment of both PI3K p85α and HER2 to the gp130 complex, thus resulting in elevated phosphorylation of HER2 (Tyr1248) and PI3K p85α (Tyr607) (Figure 5A–C). IF analysis further confirmed that the levels of gp130, phosphorylated-HER2 (Tyr1248), and phosphorylated-PI3K p85α (Tyr607) were co-upregulated under IL-6 stimulation (Figure 5D). Tocilizumab suppressed these IL-6-induced changes by downregulating gp130 expression through upregulating miR-520f-3p, and further inhibited the binding of PI3K p85α and HER2 to the gp130 complex, thus attenuating the phosphorylation of both HER2 (Tyr1248) and PI3K p85α (Tyr607) (Figures S5D and 5A–D). Therefore, IL-6 might induce the activation of PI3K and HER2 through gp130. Treatment with apatinib and trastuzumab decreased gp130 expression via increasing miR-520f-3p levels, and decreased levels of PI3K p85α and HER2 in the gp130 complex (Figures S5D and 5B). Combined treatment with apatinib and trastuzumab amplified these effects through IL-6 induced neutralization, and tocilizumab further enhanced this amplified effects (Figure 5B). Therefore, apatinib suppressed HER2-positive GC cells through the IL-6-gp130-PI3K pathway with HER2 involvement.

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

Figure 5

Apatinib suppresses HER2-positive GC cells via the IL-6-gp130-PI3K pathway. (A) Western blot analysis of key proteins in the PI3K/AKT/STAT3 pathway in GC cells treated with apatinib, trastuzumab, IL-6, and TCZ. (B) Co-immunoprecipitation assay assessing the interaction between gp130 and HER2 or PI3K in GC cells across treatment groups. (C) Western blot analysis of phosphorylated-HER2 (Tyr1248) levels in GC cells. (D) Immunofluorescence staining showing co-expression of gp130, phosphorylated-HER2 (Tyr1248), and phosphorylated-PI3K p85α (Tyr607) in GC cells. Scale bar: 200 μm. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. HER2, human epidermal growth factor 2; GC, gastric cancer; NC, negative control; TCZ, tocilizumab; IL-6, interleukin-6; PI3K, phosphatidylinositol 3-kinase; AKT, protein kinase B; STAT3, signal transducer and activator of transcription 3.

Apatinib enhances targeted immunotherapy for HER2-positive GC xenografts

hHSC-CDXs for HER2-positive GC were successfully established, as verified by the detection of human immune cell populations (human CD45⁺, CD3⁺, and CD68⁺ cells) in the TME in 3 randomly selected mice before treatment initiation (Figure S6A). Growth inhibition of xenografts after treatment with apatinib plus tislelizumab, compared with controls, was achieved at 16 days; moreover, the growth inhibition with trastuzumab plus tislelizumab treatment was achieved at the same time point, whereas the growth inhibition with triple-drug treatment (apatinib, trastuzumab, and tislelizumab) was achieved at 12 days (Figure 6A). The triple-drug treatment achieved more pronounced growth inhibition than both the trastuzumab plus tislelizumab group at the 12-day timepoint and the apatinib plus tislelizumab group at the 16-day timepoint (Figure 6A). Therefore, apatinib promoted the efficiency of targeted immunotherapy in HER2-positive GC xenografts.

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

Figure 6

Apatinib enhances targeted immunotherapy against HER2-positive GC in hHSC-CDXs. (A) Images of NCI-N87-derived tumor tissues and tumor growth curves for hHSC-CDXs treated with tislelizumab, apatinib, and trastuzumab. (B) CD31 immunohistochemistry for MVD quantification. Black scale bar: 100 μm; red scale bar: 30 μm. (C) Flow cytometry analysis of the human CD45⁺ cell proportion in tumor tissues. (D) M2-TAM (CD68⁺CD163⁺) proportion in CD45⁺ pre-gated cells. (E) CD8⁺ T cell (CD3⁺CD8⁺) proportion in pre-gated CD45⁺ cells. (F) CD8⁺ T cell subset (GZMB⁺TIM-3⁻ cytotoxic; GZMB⁻TIM-3⁺ exhausted) proportion in pre-gated CD3⁺CD8⁺ T cells. (G) Treg (CD4⁺Foxp3⁺) proportion in the pre-gated CD3⁺CD8⁻ T population. (H) Flow fluorescence immunomicrobead assay for IL-6 in tumor tissues. (I) Western blot analysis of the PI3K/AKT/STAT3 pathway in tumor tissues. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. NC, negative control; HER2, human epidermal growth factor 2; GC, gastric cancer; hHSC-CDXs, humanized hematopoietic stem cell and tumor cell line-derived xenografts; MVD, microvessel density; TAM, tumor-associated macrophage; Treg, regulatory T cell; GZMB, granzyme B; TIM-3, T-cell immunoglobulin and mucin-domain containing molecule 3; IL-6, interleukin-6; PI3K, phosphatidylinositol 3-kinase; AKT, protein kinase B; STAT3, signal transducer and activator of transcription 3.

The TME of these xenografts underwent changes under targeted immunotherapy. The MVD in xenografts treated with apatinib plus tislelizumab, and trastuzumab plus tislelizumab, was lower than observed in control xenografts (Figure 6B). Beyond the favorable outcomes observed with dual-drug treatment, the triple-drug regimen of apatinib, trastuzumab, and tislelizumab also led to a significantly lower MVD than observed in the control and dual-drug groups (Figure 6B). Although no significant differences were observed in the percentages of human CD45⁺ cells, the percentages of M2-TAM polarization, Tregs, IL-6 levels, and phosphorylated PI3K/AKT/STAT3 levels gradually decreased in the control, dual-drug, and triple-drug groups, while the CD8⁺ T cell percentages gradually increased. Subtype analysis revealed that cytotoxic CD8⁺ T cells initiated this increase, whereas exhausted CD8⁺ T cells decreased correspondingly (Figure 6C–I). Representative flow cytometry dot plots are presented in Figure S6B–F. IF further confirmed that the changing trends in immune cell populations were consistent with those observed by flow cytometry (Figures S7 and S8).

In summary, apatinib enhanced the efficiency of targeted immunotherapy by promoting CD8⁺ T cell activation while decreasing the levels of MVD, M2-TAMs, and Tregs in the TME.

Tocilizumab enhances targeted immunotherapy efficiency in HER2-positive GC xenografts

We further evaluated the effects of tocilizumab on the efficacy of targeted immunotherapy in HER2-positive GC. Three randomly selected hHSC-CDX mice were sacrificed before treatment initiation. Human immune cells (CD45⁺, CD3⁺, and CD68⁺ cells) in tumor tissues were analyzed by flow cytometry to verify the successful establishment of these animal models (Figure S9A). Marked tumor growth suppression was observed after 12 days of dual-drug (tocilizumab plus tislelizumab), triple-drug (TAT, TTT, and ATT), and four-drug (TATT) treatments, in contrast to the control (Figure 7A). Specifically, the triple-drug combination exhibited greater tumor growth inhibition than the dual-drug combination from 12 to 28 days (Figure 7A). Among all treatment groups, the four-drug combination demonstrated the greatest growth inhibition from 12 to 28 days (Figure 7A). These findings suggested that tocilizumab enhanced the efficiency of targeted immunotherapy in HER2-positive GC xenografts, regardless of whether it was used in combination with apatinib or trastuzumab.

• Download figure
• Open in new tab
• Download powerpoint

• Download figure
• Open in new tab
• Download powerpoint

Figure 7

Tocilizumab enhances targeted immunotherapy in HER2-positive GC hHSC-CDXs. (A) Images of NCI-N87-derived tumor tissues and tumor growth curves for hHSC-CDXs treated with tislelizumab, apatinib, trastuzumab, and TCZ. (B) CD31 immunohistochemistry for MVD quantification. Black scale bar: 100 μm; red scale bar: 30 μm. (C) Flow cytometry analysis of the human CD45⁺ cell proportion in tumor tissues. (D) M2-TAM (CD68⁺CD163⁺) proportion in CD45⁺ pre-gated cells. (E) CD8⁺ T cell (CD3⁺CD8⁺) proportion in pre-gated CD45⁺ cells. (F) CD8⁺ T cell subset (GZMB⁺TIM-3⁻ cytotoxic; GZMB⁻TIM-3⁺ exhausted) proportion in pre-gated CD3⁺CD8⁺ T cells. (G) Treg (CD4⁺Foxp3⁺) proportion in the pre-gated CD3⁺CD8⁻ T population. (H) Flow fluorescence immunomicrobead assay for IL-6 in tumor tissues. (I) Western blot analysis of the PI3K/AKT/STAT3 pathway in tumor tissues. Data are presented as mean ± S.D. *P ≤ 0.05, **P ≤ 0.01. NC, negative control; HER2, human epidermal growth factor 2; GC, gastric cancer; hHSC-CDXs, humanized hematopoietic stem cell and tumor cell line-derived xenografts; MVD, microvessel density; TAM, tumor-associated macrophage; Treg, regulatory T cell; GZMB, granzyme B; TIM-3, T cell immunoglobulin and mucin-domain containing molecule 3; PI3K, phosphatidylinositol 3-kinase; TCZ, tocilizumab; AKT, protein kinase B; STAT3, signal transducer and activator of transcription 3.

Regarding TME changes, the MVD gradually decreased in the control, dual-drug, triple-drug, and four-drug groups (Figure 7B). Similarly to the trend of decreased MVD, we observed no significant differences in the percentages of human CD45⁺ cells; however, the percentages of M2-TAMs and Tregs also gradually decreased in these groups, as did the levels of IL-6 and phosphorylated PI3K/AKT/STAT3 in tumor tissue. In contrast, the percentages of CD8⁺ T cells gradually increased in these groups, as did those of cytotoxic CD8⁺ T cells, whereas exhausted CD8⁺ T cells showed an opposite trend (Figure 7C–I). Representative flow cytometry dot plots are presented in Figure S9B–F. IF further confirmed that the changing trends in immune cell populations were consistent with those observed by flow cytometry (Figures S10 and S11). In summary, tocilizumab enhanced the efficiency of targeted immunotherapy by expanding cytotoxic CD8⁺ T cell infiltration, and decreasing the MVD and the levels of M2-TAMs and Tregs.

Clinical validation of enhanced targeted immunotherapy efficacy by apatinib in patients with HER2-positive GC

We next validated the efficacy of the triple-drug regimen of trastuzumab, apatinib, and immunotherapy in patients with HER2-positive GC. Case 1 was HER2-positive (3+) gastric adenocarcinoma (PD-L1 CPS <1) in a 57-year-old man who was diagnosed with stage IVB GC (cT4aN2M1) at the Fourth Hospital of Hebei Medical University (Figure S12A–F). He refused chemotherapy because of concerns regarding adverse effects and declined pembrolizumab for economic reasons. First-line treatment with tislelizumab (200 mg IV q3w) plus apatinib (250 mg qd) led to disease progression after 3 cycles, with new liver lesions and enlarged lymph nodes (Figure S12G, March 2021). Further progression was confirmed after an additional cycle performed at the patient’s request (Figure S12G, June 2021). He received the chemotherapy-free regimen as the second line treatment, comprising tislelizumab (200 mg IV q3w), trastuzumab (loading dose 8 mg/kg, then 6 mg/kg IV q3w), plus apatinib (250 mg PO qd). After 3 cycles, imaging showed a partial response (PR) and decreased liver metastasis size (Figure S12G, September 2021). However, the disease progressed again after 3 additional cycles (Figure S12G, December 2021). The patient achieved a progression-free survival 2 (PFS2) of 6.9 months under second-line treatment with triple drugs, then died after 2 additional ineffective treatments, thus resulting in an overall survival of 19.5 months (Figure S12H).

Case 2 [stage IVB (cT4aN3M1) and HER2 (3+)] was in a 64-year-old man who could not tolerate further chemotherapy, because of concurrent liver cirrhosis and chemotherapy-related myelosuppression after 4 cycles of first-line chemotherapy-containing treatment (Figure S13A–C). We subsequently treated him with the chemotherapy-free triple regimen (the anti-PD-1 immunotherapy serplulimab, trastuzumab, and apatinib), and he achieved a stable disease (SD) state at 11-month follow-up (Figure S13D, E).

Case 3 was GC [stage IVB (cT4aN3M1), HER2 (2+) and fluorescence in situ hybridization (+)] in a 46-year-old man who experienced progressive disease and severe myelosuppression after 15 cycles of chemotherapy-containing therapy (Figure S14A–D). Subsequent application of camrelizumab, trastuzumab, and apatinib achieved SD, and a 7% decrease was observed in the sum of target lesion diameters after 2 cycles. Progression was confirmed after 2 additional cycles, with a PFS2 of 3.9 months (Figure S14E, F). These cases further validated the ability of apatinib to increase the efficacy of targeted immunotherapy in patients with HER2-positive GC in a real-world scenario.