HSP47 inhibition-induced CD155 expression through TRAF2 deubiquitination promotes tumor immune evasion

Abstract

Background

Heat shock protein 47 (HSP47) is crucial for protein quality control and tumor progression. While its role in cancer biology is well established, its impact on cancer immunity remains poorly understood. In this study, we aim to elucidate how HSP47 inhibition modulates immune evasion, with a specific focus on the CD155/T-cell immunoreceptor with Ig and ITIM domains (TIGIT) axis in osteosarcoma (OS).

Methods

We used OS cell lines and mouse models to examine the effects of HSP47 inhibition on tumor growth and immune response. Expression levels of CD155, TIGIT, and other immune checkpoint molecules were analyzed throughflow cytometry, immunofluorescence, and western blotting. We also assessed the therapeutic effects of combining HSP47 inhibition with CD155 blockade or nuclear factor-kappa B (NF-κB) inhibitors in preclinical models.

Results

Inhibition of HSP47 resulted in increased expression of the immune checkpoint molecule CD155, which impaired the antitumor activity of CD8⁺ T cells through the TIGIT receptor. Mechanistically, HSP47 inhibition reduced TRAF2 ubiquitination, leading to enhanced NF-κB signaling and upregulation of CD155 in OS cells. Combining HSP47 inhibition with anti-TIGIT antibodies or the NF-κB inhibitor bortezomib significantly suppressed OS progression and improved survival in mouse models.

Conclusions

HSP47 inhibition promotes immune evasion by upregulating CD155 via the TRAF2-NF-κB pathway, which impairs CD8⁺ T cell-mediated antitumor immunity. The combination of HSP47 inhibition with CD155/TIGIT blockade enhances therapeutic efficacy, suggesting a promising strategy for combination cancer therapies.

WHAT IS ALREADY KNOWN ON THIS TOPIC.

WHAT THIS STUDY ADDS

• This study demonstrates that HSP47 inhibition upregulates the immune checkpoint ligand CD155, impairing CD8⁺ T cell-mediated antitumor immunity via TIGIT interaction. The mechanism involves HSP47-induced TRAF2 deubiquitination, which enhances nuclear factor-kappa B activation and increases CD155 expression. Notably, combining HSP47 inhibition with CD155/TIGIT blockade substantially improves antitumor immunity and suppresses osteosarcoma progression in preclinical models, highlighting a promising combinatorial therapeutic strategy.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• These findings support targeting the CD155/TIGIT axis in combination with HSP47 inhibition as a promising therapeutic approach, particularly for osteosarcoma. This novel strategy combines immune checkpoint blockade with the inhibition of tumor progression pathways, offering potential applications in other cancers where HSP47 and CD155/TIGIT are relevant. Clinical trials are essential to evaluate the safety, efficacy, and translational potential of this combined approach.

Introduction

Osteosarcoma (OS) is a highly aggressive malignant mesenchymal tumor marked by significant heterogeneity, rapid progression, early metastasis, and a poor prognosis.^{1 2} Despite aggressive chemotherapy and surgical interventions as the mainstay of treatment, patient survival has improved minimally over the years. The 5-year survival rate for individuals with metastatic or recurrent OS remains as low as 20%.^{3 4}

Heat shock proteins (HSPs) are essential for various cellular processes, including protein folding and stress responses, and their misregulation is implicated in cancer development.5,7 Among these, HSP47, a collagen-specific member of the HSP family, is essential for the proper folding of collagen and other extracellular matrix (ECM) proteins.⁸ HSP47 functions as a molecular chaperone that retains misfolded proteins within the endoplasmic reticulum (ER) while facilitating the trafficking of correctly folded proteins to the Golgi apparatus.^{8 9} HSP47 is commonly overexpressed in a variety of cancers and significantly contributes to cancer progression. It enhances cancer stemness, facilitates angiogenesis, drives tumor growth, induces epithelial-mesenchymal transition, and boosts metastatic potential.^{10 11} HSP47 inhibition has demonstrated potential in reducing tumor growth and metastasis by disrupting these processes.10,14 Additionally, HSP47 modulates the effectiveness of various cancer treatments, including chemotherapy and radiation therapy.^{15 16} However, the role of HSP47 in modulating the immune response within the tumor microenvironment remains largely unexplored. Understanding its role in modulating immune activity is crucial for optimizing therapeutic strategies that target HSP47.

Tumor cells express a variety of specific proteins on their surface, which interact with immune cells to suppress their attack functions, thereby evading surveillance and elimination by the immune system. CD155 is highly expressed in various types of tumors and plays a crucial role in tumor immune evasion.17,22 For instance, IL-22 produced by T helper cells upregulates CD155 expression in cancer cells, impairing NK cell function and thereby facilitating metastasis.²¹ CD155 interacts with immune inhibitory receptors, such as T-cell immunoreceptor with Ig and ITIM domains (TIGIT), and CD96, and immune activating receptor CD226.23,28 The binding affinity between TIGIT and CD155 is particularly strong, and activation of this pathway prevents CD155 from interacting with other receptors like CD96 and CD226, positioning TIGIT as the primary mediator of immune regulation in this signaling axis.23,2729

TIGIT is an immune checkpoint that can be targeted for cancer therapy.²⁶ In cancer, TIGIT is highly expressed on tumor-infiltrating CD8⁺ T cells and natural killer (NK) cells.^{29 30} CD155 binds to TIGIT, triggering direct inhibitory signals in these immune cells.2629,35 Preclinical studies have shown that CD155/TIGIT blockade can inhibit the progression of various solid and hematologic cancers.3036,42 Recent studies have also shown that CD49f promotes immune evasion of tumor-initiating cells by stabilizing CD155 expression, and that combining anti-CD155 with anti-PD-1 antibodies yields promising results in a mouse model of hepatocellular carcinoma.⁴³ Current strategies to block the CD155 signal mainly focus on antibodies that target CD155 or its receptors like TIGIT. Understanding the regulation of CD155 could uncover new therapeutic strategies to more effectively disrupt this pathway, potentially enhancing the efficacy of cancer immunotherapy.

Tumor necrosis factor receptor-associated factor 2 (TRAF2) is an adaptor protein that interacts with TNF receptor 2 (TNFR2) and is involved in activating the classical nuclear factor-kappa B (NF-κB) signaling pathway.44,46 NF-κB signaling is known to regulate various immune checkpoints.⁴⁷ In this study, we provide evidence that although HSP47 inhibition suppresses tumor growth, in the meantime, it impedes CD8⁺ T cell-mediated immune surveillance through TRAF2 deubiquitination and subsequent NF-κB/CD155 activation in OS. Furthermore, we demonstrated the satisfying therapeutic potential of combining HSP47-targeted therapy with CD155 blockade. Our findings provide new insights into the mechanisms governing immune evasion in OS surviving HSP47 inhibition and highlight a promising combination strategy for enhancing cancer therapy.

Methods

Patients, fresh OS tissue collection and peripheral blood extraction

Patient cohort

This study included 30 OS patients diagnosed between 2022 and 2023 at the Musculoskeletal Tumor Center, the Second Affiliated Hospital of Zhejiang University (SAHZU). Among them, 20 patients were selected for HSP47 immunohistochemical (IHC) staining and 30 patients for TIGIT IHC staining. Additionally, fresh tumor tissues from 13 patients were used for flow cytometry analysis (see online supplemental table 1) for detailed demographic and clinical data.

Tissue collection

Tumor samples were obtained during surgical resections. For IHC analysis, tissues were fixed in 10% neutral buffered formalin and subsequently paraffin-embedded. Fresh tissue samples for flow cytometry were immediately preserved in Tissue Preservation Solution (Solarbio, SR0020) to maintain cell viability and processed within 4 hours postsurgery.

Peripheral blood collection

Blood samples were collected from OS patients before surgery. Processing was conducted within 4 hours to preserve sample integrity for downstream analyses, including flow cytometry.

Sample handling and processing

Formalin fixation and paraffin embedding: Tumor tissues designated for IHC analysis were fixed in 10% neutral buffered formalin according to standard protocols and subsequently paraffin-embedded for sectioning and staining.

Flow cytometry sample preparation: Fresh tumor samples were preserved in Tissue Preservation Solution (Solarbio, SR0020) to maintain cellular integrity. Samples were processed within 4 hours to generate single-cell suspensions for analysis.

Peripheral blood processing: Blood samples were collected in EDTA-coated tubes to prevent coagulation. They were processed within 4 hours for flow cytometry and other assays.

Cancer Cell Line Encyclopedia, The Cancer Genome Atlas, Therapeutically Applicable Research to Generate Effective Treatments and Gene Expression Omnibus data analysis

Data sources

This study’s findings were based on analyses of publicly available datasets, including the Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Gene Expression Omnibus (GEO) dataset (accession number GSE39055).48,52 Transcriptomic and clinical data for a total of 85 OS patients were obtained from the TARGET program database (https://ocg.cancer.gov/programs/target). In addition, the GSE39055 dataset, comprising gene expression profiles and clinical annotations for 37 OS samples,⁵³ was retrieved from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). An overview of the clinical characteristics of patients from both cohorts is provided in table 1.

Table 1. Clinical information of TARGET-OS and GSE39055 datasets.

	TARGET-OS	GSE39055
Samples	85	37
Age (year)	14.5	13.5
Female (%)	43.0	44.8
Survival time (year)	4.11	4.41

OS, osteosarcoma; TARGET, Therapeutically Applicable Research to Generate Effective Treatments.

CCLE analysis

HSP47 mRNA expression levels in OS cell lines were retrieved from the CCLE database, available at https://sites.broadinstitute.org/ccle.⁴⁸

Survival analysis and mRNA expression profiling

Survival curves: The association between HSP47 expression and survival outcomes in sarcoma patients was analyzed using the GEPIA tool (http://gepia.cancer-pku.cn), which provides survival analysis based on TCGA and GTEx data.

Pan-cancer mRNA expression: HSP47 mRNA expression across different cancer types was evaluated using the GEPIA tool, providing a comprehensive pan-cancer expression profile.^{54 55}

Analytical methods

Data extraction: Relevant data were systematically extracted from the above databases using their respective platforms and online tools.

Statistical analysis: Statistical analyses were performed to evaluate the significance of HSP47 expression levels and their correlation with patient survival and the abundance of immune cells. Detailed descriptions of the statistical methods and parameters used are provided in the supplementary materials.

Reagents, cell lines, and cell culture

This study used four human OS cell lines: MNNG/HOS (HOS), U2OS, MG63, and 143B. Additionally, the BALB/c mouse OS cell line K7M2, the human lung cancer cell line A549, the human breast cancer cell line BT-474, and human normal osteoblast cells (hFOB1.19) were included. All cell lines were obtained from the Cell Collection of the Chinese Academy of Sciences.

Mycoplasma contamination was assessed using a detection kit (Catalog #4460626, Thermo Fisher) to ensure cell line integrity, and all lines were confirmed to be free of contamination. OS cell lines were authenticated via DNA short tandem repeat (STR) genotyping.

Cell culture conditions: The OS cell lines (HOS, MG63, 143B, K7M2), A549, BT-474, and hFOB1.19 were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% Fetal Bovine Serum (FBS) at 37°C in a 5% CO2 atmosphere. U2OS cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium under identical conditions.

Reagents used:

• HSP47 Inhibitor (Col003): Purchased from MCE (Catalog #HY-124817).

• p65-Specific Inhibitor (BAY11-7082): Purchased from MCE (Catalog #HY-W067427).

• Exogenous TNF-α: Purchased from MCE (Catalog #HY-P70426A).

• TNF-α Specific Inhibitor (Etanercept): Purchased from MCE (Catalog #HY-P72025).

• Bortezomib (BTZ): Purchased from MCE (Catalog #HY-10227).

• Anti-TIGIT Antibody: Purchased from BioXCell (Catalog #BE0274).

• Cycloheximide (CHX): Purchased from MCE (Catalog #HY-12320).

• MG132: Purchased from MCE (Catalog #HY-12359).

• Chloroquine: Purchased from MCE (Catalog #HY-17589A).

• Bafilomycin A1: Purchased from MCE (Catalog #HY-100558).

• 3-Methyladenine: Purchased from MCE (Catalog #HY-19312).

Transfection of stable cell lines using lentivirus

Short hairpin RNA (shRNA) constructs targeting both human and mouse HSP47 and human TRAF2 were obtained from OBiO Technology (Shanghai, China). An overexpression plasmid for human HSP47 was also used.

The specific sequences used are as follows:

• HSP47 (human): 5’-TGCTAGTCAACGCCATGTTCT-3’

• HSP47 (mouse): 5’-TCCCTGGGTCTTGTGTCACT-3’

• TRAF2 (human): 5’-CCTTCCCAGATAATGCTGCCC-3’

• TRAF2 (mouse): 5’-GCGATCTTCATCAAAGCTATT-3’

Control lentiviruses containing non-targeting shRNA (pHBLV-shCtrl, pGMLV-shCtrl, pGV248-shCtrl) were also provided by the manufacturer; the control shRNA sequence is 5’-TTCTCCGAACGTGTCACGT-3’.

To establish stable gene silencing or overexpression, target cells were seeded into six-well plates at a density of 2×10⁵ cells per well. After 24 hours of incubation, cells were transduced with lentiviral particles containing the specific shRNA constructs or overexpression plasmids. Following transduction, the culture medium was replaced with fresh medium free of lentiviral particles or plasmids, and cells were allowed to grow for an additional 2 days.

Stable transfectants were selected using puromycin at a concentration determined through preliminary dose-response experiments, ensuring effective selection of successfully transduced cells.

Quantitative real-time PCR

Total RNA was extracted from cells using TRIzol reagent (Catalog #15596018; Thermo Fisher Scientific). Complementary DNA (cDNA) was synthesized using a cDNA Synthesis Kit (Catalog #6610; Takara Bio). Quantitative real-time PCR (qPCR) was performed using gene-specific primers and SYBR Premix Ex Taq (Catalog #RR420; Takara Bio) on an ABI StepOnePlus System (Applied Biosystems).

Data acquisition and analysis were carried out using Real-Time PCR software (V.2.4). Relative gene expression levels were calculated using the ΔΔCt method, with normalization against the housekeeping gene GAPDH.

The primer sequences used for the analysis are as follows:

HSP47 (human):

Forward: 5’-TCAGTGAGCTTCGCTGATGAC-3’

Reverse: 5’-CATGGCGTTGACTAGCAGGG-3’

CD155 (human):

Forward: 5’-GGACGGCAAGAATGTGACCT-3’

Reverse: 5’-GGTCGTGCTCCAATTATAGCCT-3’

GAPDH (human):

Forward: 5’-GGAGCGAGATCCCTCCAAAAT-3’

Reverse: 5’-GGCTGTTGTCATACTTCTCATGG-3’

These primer sequences were obtained from PrimerBank (available at: https://pga.mgh.harvard.edu/primerbank/).

Coimmunoprecipitation and Western blot

Protein extraction and analysis

OS tissues or cells were lysed in prechilled RIPA lysis buffer (Catalog #89901; Thermo Fisher Scientific) supplemented with phosphatase inhibitors (Catalog #78420; Thermo Fisher Scientific) and protease inhibitors (Catalog #78428; Thermo Fisher Scientific). The lysates were centrifuged at 15,000×g for 15 min at 4°C to remove insoluble debris. The protein concentration was quantified using a BCA Protein Assay Kit (Catalog #23227; Thermo Fisher Scientific).

Co-immunoprecipitation

For co-immunoprecipitation (Co-IP), cell supernatants were incubated with magnetic A/G beads (Beyotime, catalog #P2179M) at 4°C for 12 hours. After incubation, the beads were washed with immunoprecipitation (IP) buffer to remove unbound proteins. Bound proteins were eluted by boiling the beads in SDS sample buffer, and the eluates were subsequently subjected to immunoblotting to detect co-immunoprecipitates.

Western blotting

Protein samples were separated by SDS-PAGE and transferred to methanol-pretreated PVDF membranes (Catalog #LC2002; Thermo Fisher Scientific). Membranes were blocked with 5% nonfat milk for 1 hour at room temperature. Primary antibodies were incubated with the membranes at 4°C for 10–15 hours. Membranes were washed with Tris-buffered saline containing 0.1% Tween-20 (TBST; Catalog #P9416; Sigma). Following primary antibody incubation, membranes were probed with HRP-conjugated secondary antibodies for 1 hour at room temperature. Protein bands were visualized using ECL detection reagents and an Amersham ImageQuant 800 Western blot imaging system (ImageQuant 800 Control Software V2.0.0).

Flow cytometry and fluorescence-activated cell sorting

Adherent cell CD155 level measurement

Adherent cells grown in culture plates were either enzymatically detached with trypsin or harvested using a cell scraper, depending on the specific cell line and experimental conditions.

Tumor-infiltrating T-cell and organ analysis

Tumor, lung, spleen, and liver tissues were finely minced with sterile blades and dissociated in RPMI 1640 medium supplemented with collagenase type IV (2 mg/mL; Sigma), hyaluronidase (0.1 mg/mL; Sigma), DNase (0.1 mg/mL; Sigma), and BSA (2 mg/mL; Sigma). The resulting tissue suspensions were filtered through 100 µm filters to obtain single-cell suspensions.

Peripheral blood mononuclear cells

Peripheral blood was collected in anticoagulation tubes and diluted 1:1 with phosphate-buffered saline (PBS). The diluted blood was carefully layered onto a lymphocyte separation medium. Following gradient centrifugation, the lymphocyte layer was collected.

Cell surface and intracellular protein staining

For cell surface staining, cells were incubated with appropriate antibodies for 20–30 min at room temperature in a light-protected environment. To assess CD107a expression, cells were stimulated with phorbol 12-myristate 13-acetate (5 µg/mL; Catalog #HY-18739; MCE) and monensin (Catalog #343257; NSC) for 5 hours at 37°C.

For intracellular staining, cells were first stained for surface markers and then fixed with a fix/perm solution (BD Biosciences) for 15 min. Following fixation, cells were permeabilized with a Perm/Wash buffer (BD Biosciences) for 20 min. Intracellular staining was performed by incubating cells with specific antibodies for 20–30 min at room temperature in a light-protected environment.

Flow cytometry and fluorescence-activated cell sorting

Flow cytometry data acquisition and analysis were performed using a Beckman Coulter CytoFLEX LX flow cytometer, equipped with CytExpert V.2.4 software. Data analysis was conducted using FlowJo V.10 software. For fluorescence-activated cell sorting, a Beckman MoFlo Astrios EQ flow cytometer with Summit software V.6.3.1 was used. The gating strategy for flow cytometry analysis is provided as supplementary material (Supplementary Figure 10).

Histology, H&E, immunofluorescence, and IHC staining

Tissue preparation and H&E staining

Human or mouse OS tissues were fixed in 4% paraformaldehyde, dehydrated through a graded ethanol series, and embedded in paraffin. Sections were cut at 5 µm thickness using a microtome and stained with H&E using a Leica Autostainer XL following a standard protocol. Stained sections were analyzed under a light microscope for histopathological evaluation.

Immunofluorescence

For immunofluorescence staining, OS cells were cultured in 24-well plates and fixed with 4% paraformaldehyde for 15 min at room temperature. Tissue sections were deparaffinized with xylene, rehydrated through graded alcohol solutions, and underwent antigen retrieval in a citric acid buffer (pH 6.0). Cells and tissue sections were permeabilized with 0.03% Triton X-100 (Catalog #X100; Sigma) in PBS for 10 min at room temperature, followed by blocking with 5% BSA (Catalog #A4503; Sigma) for 20 min.

Primary antibodies were applied to cells or tissue sections and incubated at 4°C for 10–15 hours. Following primary antibody incubation, samples were brought to room temperature and incubated with fluorophore-conjugated secondary antibodies for 1 hour. Nuclei were counterstained with DAPI-containing mounting medium (Catalog #P36971, Thermo Fisher). PBS washes were applied between each staining step. High-resolution fluorescence images were obtained using a Leica DMi8 inverted microscope.

Immunohistochemistry

IHC staining was conducted using the same antigen retrieval, permeabilization, and blocking procedures as described for immunofluorescence. Tissue sections were incubated with HRP-conjugated secondary antibodies at 37°C for 20 min. Color development was performed using 3,3′-diaminobenzidine substrate, followed by hematoxylin counterstaining. Slides were mounted, and high-definition images were acquired using a Leica microscope. Staining intensity was quantified using the histoscore method, which evaluates both the intensity and percentage of positively stained cells, and image analysis was performed using Leica Application Suite X V.3.7.4 software.^{56 57}

Colony formation assay

For the colony formation assay, cells were seeded in six-well plates at a density of 1×10³ cells per well in complete growth medium (DMEM with 10% FBS and 1% penicillin-streptomycin). The cells were maintained in fresh medium and incubated for 10–14 days to allow colony formation. The medium was refreshed every 3 days to ensure optimal growth conditions. After the incubation period, cells were fixed with 4% paraformaldehyde for 15 min and stained with 0.5% crystal violet for 30 min at room temperature.

Cell Counting Kit-8 Assay

Cell viability was assessed using the Cell Counting Kit-8 (CCK-8; Dojindo Laboratories, Japan), following the manufacturer’s instructions. Cells were seeded into 96-well plates at a density of 5×10⁴ cells per well in 100 µL of complete growth medium and incubated at 37°C in a humidified atmosphere containing 5% CO₂ for 24 hours to allow cell attachment and achieve 70%–80% confluency.

Subsequently, 10 µL of CCK-8 reagent was added to each well, and the plates were incubated for an additional 2 hours under identical conditions. The CCK-8 reagent contains WST-8, a water-soluble tetrazolium salt that is reduced by mitochondrial dehydrogenases in metabolically active cells to form a yellow-colored formazan dye. The intensity of the formazan signal correlates directly with the number of viable cells.

Absorbance was measured at 450 nm using a microplate reader (eg, BioTek or equivalent). Background signal was subtracted using wells containing only medium and CCK-8 reagent (without cells).

Cell viability was calculated using the formula:

Cell viability (%)=(Control OD450−Blank OD450)/(Experimental OD450−Blank OD450)×100.

Data were expressed as the percentage of viable cells relative to the untreated control group. For drug treatment experiments, a dose–response curve was generated by plotting drug concentrations (x-axis) against relative cell viability (y-axis).

Transwell migration and invasion assay

Cell migration and invasion were evaluated using Transwell chambers (pore size: 8.0 µm; Corning, USA). For migration assays, 5×10⁴ cells were suspended in 200 µL of serum-free medium and seeded into the upper chamber. For invasion assays, the upper surface of the membrane was precoated with 50 µL of Matrigel (diluted 1:4 in serum-free medium) and incubated at 37°C for 1 hour to allow gel polymerization prior to cell seeding.

The lower chamber was filled with 600 µL of complete medium containing 10% FBS, serving as a chemoattractant. The cells were then incubated at 37°C in a humidified 5% CO₂ atmosphere for 24 hours (migration) or 48 hours (invasion) to allow directional movement through the membrane.

At the end of the incubation period, non-migrated or non-invaded cells on the upper surface of the membrane were gently removed using a cotton swab. The inserts were then fixed with 4% paraformaldehyde for 10–15 min at room temperature, followed by staining with 0.1% crystal violet in 20% methanol for 15–20 min. Excess stain was removed by rinsing the inserts thoroughly with PBS.

Cells that had migrated or invaded to the lower surface of the membrane were visualized and counted under an inverted phase-contrast microscope at 200×magnification. For quantification, five randomly selected fields per insert were imaged, and the number of stained cells was averaged and compared across experimental conditions.

Wound healing assay

Cell migration was assessed using a wound healing assay. Cells were seeded into 6-well plates (or 12-well plates for higher throughput) at a density of 5×10⁴ to 1×10⁵ cells per well in 2 mL of complete medium (RPMI-1640 or DMEM supplemented with 10% FBS). Following incubation at 37°C in a humidified atmosphere with 5% CO₂ for 24 hours, cells reached near-confluent or confluent monolayers.

A uniform linear wound was introduced by gently scraping the cell monolayer with a sterile 200 µL pipette tip. Care was taken to apply consistent pressure across all samples to ensure comparable wound widths. Detached cells were removed by rinsing twice with PBS.

Fresh complete medium (with or without experimental treatments) was then added. For drug treatment groups, the compounds were added immediately following the scratch at the indicated concentrations. The cells were subsequently incubated at 37°C with 5% CO₂ for the desired time period (24hours) to allow migration into the wound area.

Images of the wound were captured at 0 and 24 hours using an inverted phase-contrast microscope.

Gene Set Enrichment Analysis

Gene Set Enrichment Analysis (GSEA) was performed using OS transcriptomic data from the GEO database (accession number GSE39055). Patients were divided into high and low HSP47 expression groups using the median expression values as the cut-off. A panel of immune regulatory genes, including CD226, PVR, TIGIT, CD96, STAT3, FOXP3, IL10, TGFB1, NFATC2, STAT5A, PTPN11, SH2D1A, GRB2, FYN, LCK, ITGB1, CTLA4, PDCD1, CD3E, ZAP70, LAT, CD274, SOCS1, SOCS3, and IRF4, was selected for their roles in immune checkpoint regulation, T-cell activation, and intracellular signaling.

Pathway enrichment analysis was conducted using curated gene sets from the Molecular Signatures Database, focusing on immune-related pathways potentially affected by varying HSP47 expression. Enrichment was evaluated using normalized enrichment scores, with statistical significance determined by false discovery rate (FDR) q-values. Pathways with an FDR q-value below 0.05 were deemed significantly enriched.

Statistical analysis

All statistical analyses were conducted using GraphPad Prism V.9. Two-group comparisons were evaluated using a two-tailed Student’s t-test. For comparisons of more than two groups, one-way or two-way analysis of variance (ANOVA) was applied according to the experimental design. Post hoc analyses following ANOVA were performed using Tukey’s or Sidak’s tests to adjust for multiple comparisons.

Survival analyses were performed using Kaplan-Meier curves, with significance assessed by the log-rank (Mantel-Cox) test, as detailed in the figure legends. Statistical significance was set at p<0.05, with p values reported as:

*p<0.05, **p<0.01, ***p<0.001, and ****p<0.0001.

Mice, animal orthotopic OS model, and in vivo drug treatment

Mice

Four-to-six-week-old female BALB/c mice and BALB/c nude mice were purchased from Hangzhou Medical College. Mice were housed under specific-pathogen-free conditions, and all procedures followed the Institutional Animal Care and Use Committee guidelines of SAHZU.

Subcutaneous Graft Tumor Model

A subcutaneous graft tumor model was established by injecting 4-week-old BALB/c nude mice subcutaneously with 2×10⁶ K7M2 cells in 100 µL PBS at the scapular region. Tumor growth was measured periodically, and mice were euthanized 21 days after injection. Tumor sizes were monitored to ensure adherence to ethical guidelines, with a maximum limit of 2500 mm³.

Orthotopic OS Model

In the orthotopic tibia OS model, K7M2 cells were injected into the tibial plateau of BALB/c mice. Even days postinjection, mice received intraperitoneal injections of TIGIT monoclonal antibody (mAb) at 200 µg/kg, Col003 at 20 mg/kg, or BTZ at 1 mg/kg, administered every 3 days for 15 days. Mice were euthanized 5 days post-treatment. All procedures complied with ethical standards, and tumor sizes remained within approved limits.

RNA-seq analysis

RNA sequencing (RNA-seq) was performed on U2OS cells and treated cells with HSP47-targeting shRNA. Cells were seeded in 6-well plates at 2×10⁵ cells per well and cultured under standard conditions. Total RNA was extracted using RNAiso Plus reagent (Thermo Fisher, catalog #15596018) per the manufacturer’s instructions. To remove residual platelets, cells were washed three times with PBS before lysis with TRIzol, and lysates were stored at −80°C for later use.

For library preparation, total RNA underwent ribosomal RNA (rRNA) depletion to enrich mRNA. The mRNA was fragmented using a fragmentation buffer and reverse-transcribed into cDNA with random hexamer primers. The cDNA was then purified, end-repaired, polyadenylated, and ligated with Illumina adapters following standard protocols. The quality and quantity of the cDNA library were evaluated using an Agilent 2100 Bioanalyzer.

Sequencing was conducted on an Illumina NovaSeq 6000 platform at Gene Denovo Biotech Co. (Guangzhou, China), producing paired-end reads of 150 bp. Raw sequencing reads were processed with FastQC for quality control and trimmed using Trimmomatic to remove low-quality bases and adapters. The cleaned reads were aligned to the human reference genome (GRCh38) using HISAT2. Gene expression was quantified with featureCounts, and differential expression analysis was performed using DESeq2 to compare control and HSP47 shRNA-treated cells. Genes with an absolute log2 fold change ≥1 and a FDR<0.05 were considered significantly differentially expressed. A full list of differentially expressed genes can be access here: https://zenodo.org/records/17611059.

Antibodies

Details of all antibodies used in this study, including vendor information, catalog numbers, and dilution conditions, are summarized in online supplemental table 2.

Results

The high expression of HSP47 is associated with poor prognosis of OS patients

First, we examined the expression of HSP47 in OS tissues. Western blot analysis of 7 matched OS and adjacent non-tumor (ANT) tissue samples demonstrated increased HSP47 protein levels in tumor tissues (figure 1A,B). These findings were confirmed by IHC analysis of 20 patient-matched samples, showing consistent overexpression of HSP47 in OS tissues (figure 1C,D). Analysis of the GEO (accession number GSE39055) data revealed that HSP47 expression was significantly higher in OS samples compared with healthy bone marrow controls (online supplemental figure 1A), with further increases in relapse samples compared with primary tumors from SAHZU (online supplemental figure 1B). Consistent with OS, HSP47 mRNA levels were significantly elevated across various cancers, including sarcomas, bladder urothelial carcinoma, adrenocortical carcinoma, and lung adenocarcinoma, etc, as shown by TCGA data (online supplemental figure 1C).

Figure 1. High HSP47 expression in OS is associated with poor prognosis. (A, B) Western blot analysis (A) and statistical graphs (B) showing HSP47 protein levels in OS specimens compared with adjacent non-tumor (ANT) tissues (mean±SD, n=7). GAPDH serves as a loading control. (C, D) IHC detection (C) and quantification (D) of HSP47 levels in human OS and ANT tissues (mean±SD, n=20). Scale bars: 120 µm. (E) qPCR analysis of HSP47 mRNA expression in human osteoblast cells (hFOB1.19) and OS cell lines (mean±SD, n=3). (F) Western blot analysis of HSP47 protein levels in human osteoblast cells (hFOB1.19) and OS cell lines. GAPDH serves as a loading control. (G, H) Overall survival rates in low/high SERPINH1 (HSP47) expression groups from TARGET (G) and GEO database (H, accession number GSE39055) projects. **p<0.01, ***p<0.001, ****p<0.0001, ns: not significant. IHC, immunohistochemical; OS, osteosarcoma; TARGET, Therapeutically Applicable Research to Generate Effective Treatments.

Next, we assessed HSP47 expression in different OS cell lines. qPCR results showed elevated HSP47 transcription levels in these OS cell lines (except for HOS cells) compared with human normal osteoblast cells (hFOB1.19) controls (figure 1E). Similarly, HSP47 protein levels were elevated in OS cell lines (except for HOS cells), consistent with the observed mRNA expression patterns (figure 1F).

Finally, we performed survival analyses using the TARGET-OS and GEO (accession number GSE39055) datasets. Univariate Cox regression and Kaplan-Meier analysis revealed a strong association between elevated HSP47 levels and poorer survival (figure 1G,H). Additionally, analysis of TCGA data showed that HSP47 overexpression was associated with shorter disease-free survival (log-rank p=0.019) and overall survival (log-rank p=0.016) in patients with various cancers, including sarcomas, bladder urothelial carcinoma, adrenocortical carcinoma, and lung adenocarcinoma (online supplemental figure 1D).

HSP47 inhibition leads to CD155 upregulation in OS

Given the high expression of HSP47 in OS, we aimed to determine whether inhibiting HSP47 could be a potential cancer treatment. Colony formation (online supplemental figure 2A) and CCK-8 (online supplemental figure 2B) assays showed a significant reduction in cell proliferation in shHSP47-transfected U2OS cells, while HSP47 overexpression in HOS cells significantly increased proliferation. Tumor weight measurements showed that HSP47 knockdown significantly inhibited tumor growth in nude mice (online supplemental figure 2C), which was consistent with IHC analysis results showing decreased Ki67 expression in shHSP47-treated K7M2 tumors (online supplemental figure 2D). Transwell invasion (onlinesupplemental figure 2EF) and wound healing (onlinesupplemental figure 2GH) assays further revealed increased invasiveness and migration in HSP47-overexpressing HOS cells versus controls, while these capacities were significantly reduced in shHSP47-transfected U2OS cells. Western blotting (online supplemental figure 2I) and IHC (online supplemental figure 2J) analyses further revealed a downregulation of EMT markers (Claudin, Vimentin, N-cadherin, E-cadherin) and key components of the Wnt/β-catenin signaling pathway in shHSP47-transfected U2OS cells compared with controls, whereas these markers were upregulated in HSP47-overexpressing HOS cells. These findings show that HSP47 knockdown significantly inhibits OS growth in vivo and cell proliferation in vitro, whereas HSP47 overexpression has the opposite effects.

HSP47 facilitates tumor growth through various mechanisms. First, as a molecular chaperone, HSP47 supports cancer cell survival and proliferation by maintaining the stability and proper folding of tumor-associated proteins. Second, HSP47 strengthens interactions between tumor cells and the ECM, increasing their invasiveness and metastatic potential. However, whether HSP47 inhibition has immunological effect on tumor growth remains largely unclear despite these findings.

To explore this, we performed GSEA using OS patient data from the GEO database (accession number GSE39055). The dataset was divided into high and low HSP47 expression groups based on the optimal cut-off value of HSP47 expression levels. GSEA identified enriched pathways in each group, with a focus on immune-related signaling networks. The analysis revealed significant enrichment of the CD155/TIGIT signaling axis in the low HSP47 expression group (p value=0.03032, p-adjust=0.06822) (figure 2A), suggesting its pivotal role in the tumor immune suppressive effects of HSP47 inhibition.

Figure 2. HSP47 downregulates CD155 expression in OS in vitro and in vivo. (A) Gene set enrichment analysis (GSEA) was conducted on patient data from the GEO database (accession number GSE39055), comparing high-HSP47 and low-HSP47 expression groups. The analysis revealed enriched pathways, emphasizing the immune-related CD155/TIGIT axis in the low-HSP47 group (p=0.03032, p-adjust=0.06822). Results are displayed as enrichment plots with pathway scores. (B) Heatmap depicting significantly different gene expression in U2OS cells and HSP47-knockdown U2OS cells (n=3 per group). CD155, a TIGIT ligand, is upregulated in HSP47-knockdown cells. (C) Western blot analysis of CD155 expression in HOS, HSP47 overexpressing HOS, U2OS, and shHSP47 U2OS cells. GAPDH serves as a loading control. (D) Immunofluorescence images of CD155 (red) and DAPI (blue) in shCtrl or shHSP47 U2OS cells (left) and HOS cells with or without HSP47 overexpression (right). Scale bars: 45 µm. (E) Flow cytometry analysis and quantification of CD155 levels in HSP47-knockdown U2OS cells (left), HSP-knockdown K7M2 cells (middle) or HSP47-overexpressing HOS cells (right, mean±SD.d., n=5). (F) Immunohistochemical staining of CD155 in wild-type (WT) and shHSP47 K7M2 cells in BALB/c mice, with quantification of staining intensity. Scale bars: 270 µm. (G) Flow cytometry analysis and quantification of CD155 levels in U2OS and K7M2 cells after 24-hour Col003 (50 µM) stimulation vs controls (mean±SD, n=5). (H, I) Western blot analysis of CD155 expression in U2OS, K7M2 (H), and HOS (I) cells after Col003 treatment (0, 25, 50 µM for 24 hours). GAPDH serves as a loading control. ***p<0.001, ****p<0.0001, ns: not significant. GEO, Gene Expression Omnibus; MFI, mean fluorescence intensity; OS, osteosarcoma; TIGIT, T-cell immunoreceptor with Ig and ITIM domains.

Additionally, RNA-seq analysis showed a significant increase in CD155 expression in shHSP47 U2OS cells (figure 2B). HSP47 knockdown increased CD155 expression in U2OS and K7M2 cells (figure 2C–E). In vivo studies corroborated these findings, showing increased CD155 expression in K7M2 OS mouse models with HSP47 knockdown compared with wild-type controls (figure 2F). Additionally, CD155 levels significantly increased in U2OS and K7M2 cells treated with Col003 (0, 25, 50 µM for 24 hours) (figure 2G,H), a small-molecule inhibitor of HSP47.²⁷ However, HOS cells, which naturally express lower levels of HSP47, showed no significant increase in CD155 expression under Col003 treatment (figure 2I). We generated HOS cells overexpressing HSP47, which resulted in a reduction in CD155 levels (figure 2C–E). HSP47 inhibition increased CD155 expression in OS cell lines as well as lung cancer A549 and breast cancer BT-474 cells (online supplemental figure 3A). Crucially, Col003 did not alter CD155 expression in non-tumorigenic hFOB1.19 cells (online supplemental figure 3B), highlighting its specificity in cancer cells. Overall, these findings demonstrate the regulatory role of HSP47 in modulating CD155 expression in tumor cells.

CD155/TIGIT blockade enhances the therapeutic effects of HSP47 inhibition by facilitating CD8⁺ T cell responses

Our data indicated that inhibition of HSP47 markedly enhances CD155 expression. Notably, flow cytometry and immunofluorescence analyses showed that TIGIT, the receptor for CD155, had significantly elevated expression in T cells within tumors of patients compared with human peripheral blood mononuclear cells (PBMCs) (figure 3A, onlinesupplemental figure 4AE). We established an orthotopic tibia K7M2 OS model and observed significantly elevated TIGIT expression in OS tissues compared with matched adjacent normal tissues by IHC and immunofluorescence (onlinesupplemental figure 4FH). Importantly, the proportion of TIGIT⁺ CD8⁺ T cells within the tumor microenvironment increased progressively over time (online supplemental figure 4I). In addition, CD8⁺ T cell TIGIT expression was higher in PBMCs of OS patients than healthy volunteers (online supplemental figure 4J). Functional characterization demonstrated that TIGIT⁺ CD8⁺T cells exhibited a marked reduction in coexpression with key activation and degranulation markers, including CD69, CD107a, and the cytotoxic effector perforin, compared with TIGIT^- T cells (onlinesupplemental figure 4KN),³⁴ indicating impaired T cell activation and cytolytic function. These results are consistent with established literature identifying TIGIT as a hallmark of exhausted CD8⁺ T cells in the tumor milieu. Collectively, these findings suggest that the CD155/TIGIT axis contributes to the immunosuppressive environment in tumors when HSP47-targeted therapies are applied.

Figure 3. Combination of HSP47 blockade and anti-TIGIT therapy demonstrates strong antitumor activity in Balb/c mice. (A) Multiplex immunofluorescence imaging of human primary OS tissue showing TIGIT (red) distribution in tumor regions and CD8a (green)-marked tumor-infiltrating lymphocytes. The merged image indicates TIGIT and CD8a colocalization, with nuclei stained by DAPI (blue). Scale bars: 300 µm. (B) Schematic representation of the experimental design evaluating the combined efficacy of HSP47 knockdown and anti-TIGIT therapy in a Balb/c mouse model. The diagram outlines group allocations and treatment protocols following K7M2 cell implantation in the tibia. (C) Kaplan-Meier survival curves depicting survival rates of mice across treatment groups, with improved survival in the combination therapy group. (D) Tibial weight of OS-bearing mice across various treatment groups (mean±SD, n=5). (E) Tibial volumes of OS-bearing mice across various treatment groups (mean±SD, n=5). (F–H) Flow cytometry analysis and corresponding statistical graphs depicting the proportions of CD226⁺ CD8⁺ T cells (F), CD107a⁺ CD8⁺ T cells (G), and PFP⁺ CD8⁺ T cells (H) in CD8⁺ T cells of tumor samples (mean±SD, n=5). (I, J) Flow cytometry analysis and statistical graphs showing the mean fluorescence intensity (MFI) of IFN-γ (I) and TNF-α (J) in CD8⁺ T cells from tumor samples (mean±SD, n=5). *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001, ns: not significant. mAb, monoclonal antibodies; OS, osteosarcoma; TIGIT, T-cell immunoreceptor with Ig and ITIM domains.

Therefore, we investigated whether CD155/TIGIT blockade could enhance the therapeutic efficacy of HSP47 inhibition. We established immune-competent, tumor-bearing mouse models (figure 3B). Both anti-TIGIT antibodies and HSP47 knockdown inhibited tumor growth. Notably, combination therapy demonstrated the greatest therapeutic effect, as shown by reduced tumor volume/weight and increased survival time (figure 3C–E). Consistently, combination therapy enhanced anti-tumor immune responses of CD8⁺ T cells (figure 3F–J). These results suggest that CD155/TIGIT blockade can enhance the therapeutic effect of HSP47 inhibition.

HSP47 modulates CD155 expression via the TRAF2-NF-κB pathway in OS

We aimed to explore the molecular mechanisms underlying HSP47-mediated CD155 expression. RNA-seq analysis of U2OS cells with and without HSP47 knockdown revealed that the TNF signaling pathway was the most significant among the various KEGG pathways (figure 4A,B). Therefore, we hypothesized that HSP47 regulates CD155 expression through the TNF-related pathway. To test this hypothesis, we stimulated OS cells with exogenous TNF-α and observed an increase of CD155 protein levels in a concentration-dependent and time-dependent manner (figure 4C, onlinesupplemental figure 5AC). Furthermore, TNF-α-induced CD155 expression was blocked by the TNF-α-specific inhibitor etanercept (0.25 ng/mL for 24 hours) in both K7M2 and U2OS cells (online supplemental figure 5D). TRAF2-NF-κB is a classic TNF-α-mediated pathway,⁵⁸ and we hypothesized that HSP47 regulates CD155 through TRAF2-NF-κB.

Figure 4. HSP47 modulates CD155 expression via TRAF2- NF-κB Pathway in OS. RNA-seq analysis of U2OS cells with and without HSP47 knockdown identified the TNF signaling pathway as the most significantly enriched. (B) KEGG pathway enrichment analysis reveals the top pathways influenced by HSP47 knockdown in U2OS cells, with TNF signaling ranking highest, suggesting a role for HSP47 in regulating TNF-related mechanisms. (C) Western blot analysis of CD155 expression in OS cells treated with exogenous TNF-α, showing concentration- and time-dependent upregulation. TNF-α at increasing concentrations (0, 10, 20, 30 ng/mL for 24 hours) and varying time points (0, 6, 12, 24 hours at 10 ng/mL) upregulates CD155 in U2OS and K7M2 cells. GAPDH serves as a loading control. (D) Western blot analysis of CD155, TRAF2, p65, and p-p65 expression in HOS cells overexpressing HSP47. HSP47 overexpression reduces TRAF2 and NF-κB activation, resulting in decreased CD155 levels. GAPDH serves as a loading control. (E) Western blot analysis of CD155, TRAF2, p65, and p-p65 in U2OS cells with HSP47 knockdown. HSP47 inhibition significantly enhances TRAF2 and NF-κB activity, which is associated with increased CD155 expression. GAPDH serves as a loading control. (F, G) Western blot analysis of CD155, p65, and p-p65 expression in HOS cells (F) treated with the p65 inhibitor BAY 11–7082 (12 µg/mL, 24 hours). NF-κB inhibition reverses CD155 upregulation caused by HSP47 knockdown in U2OS cells (G). GAPDH serves as a loading control. (H) Western blot analysis showing that TRAF2 silencing significantly reduces CD155, p65, and p-p65 expression in HOS cells, confirming the role of the TRAF2- NF-κB pathway in CD155 regulation. GAPDH serves as a loading control. (I) qPCR analysis of CD155 mRNA expression in HOS and HOS following TRAF2 knockdown (mean±SD, n=4). (J) Western blot analysis of CD155, p65, and p-p65 expression in shTRAF2 U2OS and K7M2 cells. TRAF2 inhibition reduces CD155, p65, and p-p65 expression, even with HSP47 inhibition. GAPDH serves as a loading control. (K) qPCR analysis of CD155 mRNA expression in U2OS cells following HSP47 knockdown and TRAF2 silencing (mean±SD, n=4). NF-κB, nuclear factor-kappa B; OS, osteosarcoma. ***p<0.001, ****p<0.0001, ns: not significant.

Our data demonstrated that TRAF2, the NF-κB subunit p65, and phosphorylated p65 (p-p65) were downregulated in HOS cells overexpressing HSP47 (figure 4D) and upregulated in U2OS and K7M2 cells with HSP47 knockdown (figure 4E, online supplemental figure 5E). HOS cells treated with BAY 11–7082 (12 µg/mL for 24 hours), the inhibitor of p65, showed downregulation of CD155 and p-p65 (figure 4F). BAY 11–7082 (12 µg/mL for 24 hours) reversed the upregulation of CD155 and p-p65 expression in shHSP47 U2OS and K7M2 cells (figure 4G, online supplemental figure 5F). These results suggest that HSP47 inhibition upregulates CD155 expression through NF-κB activation.

TRAF2 silencing significantly downregulated CD155, p65, and p-p65 protein expression (figure 4H, onlinesupplemental figure 5GH) and CD155 mRNA expression (figure 4I) in HOS cells. Inhibition of HSP47 upregulated the expression of TRAF2, p65, phosphorylated p65 (p-p65), and CD155 in both U2OS and K7M2 cell lines. Notably, TRAF2 knockdown effectively attenuated the HSP47 inhibition-mediated upregulation of p65, p-p65, and CD155 expression (figure 4J). CD155 mRNA expression was significantly upregulated in U2OS cells following HSP47 knockdown. Interestingly, in cells with combined HSP47 knockdown and TRAF2 silencing, CD155 mRNA levels were notably reduced compared with HSP47 knockdown alone, suggesting that TRAF2 silencing partially mitigates the upregulation of CD155 induced by HSP47 inhibition (figure 4K). These findings indicate that HSP47 inhibition promotes CD155 expression via the TRAF2-NF-κB axis in OS cells.

HSP47 negatively regulates TRAF2 via the ubiquitin-proteasome pathway

Next, we aimed to elucidate the role of HSP47 in regulating TRAF2. Although qPCR results indicated a modest increase in TRAF2 mRNA levels following HSP47 knockdown (figure 5A), Western blot, IHC, and immunofluorescence analyses consistently demonstrated a marked increase in TRAF2 protein levels in OS cell lines and tumor tissues (figure 4E, onlinesupplemental figure 6AC). Given that TRAF2 is an adapter protein crucial for scaffold function and signaling complex formation,^{59 60} both of which rely on its stability and interaction dynamics, and considering that HSP47 plays a key role in protein folding and stabilization,⁵ we hypothesized that HSP47 might influence TRAF2 stability and its protein interactors.

Figure 5. HSP47 negatively regulates TRAF2 through the ubiquitin-proteasome pathway. (A) RNA-seq analysis of TRAF2 mRNA expression in shCtrl U2OS cells and shHSP47-treated U2OS cells. (B, C) Western blot analysis of TRAF2 levels in HOS (B) and U2OS (C) cells under different treatments: Chloroquine (50 µM, 12 hours), Bafilomycin A1 (50 nM, 12 hours), 3-Methyladenine (10 mM, 12 hours), and MG132 (10 µM, 12 hours). GAPDH serves as a loading control. (D–F) IP assays showing endogenous TRAF2 ubiquitination in shHSP47 U2OS cells (D), U2OS cells treated with Col003 (50 µM for 24 hours) (E), or HOS cells with HSP47 overexpression (F). (G, H) Immunofluorescence showing co-localization of TRAF2 (green) and ubiquitin (red) in HOS (G) and U2OS (H) cells with HSP47 overexpression or knockdown, respectively, treated with MG132. DAPI (blue) stains the nuclei. Insets show magnified views of the dotted regions. Scale bars: 20 µm. (I, J) Western blot analysis of TRAF2 degradation over time in HSP47 overexpressing HOS cells (I) or shHSP47 U2OS cells (J), treated with cycloheximide (CHX), a protein synthesis inhibitor. GAPDH serves as a loading control. Quantification of TRAF2 degradation rates is provided on the right. **p<0.01, ns: not significant. IP, immunoprecipitation.

To explore this process, we first examined whether posttranslational mechanisms contribute to TRAF2 upregulation. We examined common protein degradation pathways using the proteasome inhibitor MG132 and various autophagy inhibitors. Our results showed that only MG132 significantly increased TRAF2 levels in OS cells (figure 5B,C, online supplemental figure 7A), and this effect was reversed by cycloheximide (CHX) (online supplemental figure 7B). These suggest that TRAF2 regulation likely results from ubiquitin-mediated proteasomal degradation. Next, we performed ubiquitination analysis on TRAF2 immunoprecipitated from OS cells. Although TRAF2 showed notable basal ubiquitination, HSP47 interference abolished TRAF2 ubiquitination in U2OS and K7M2 cells (figure 5D, online supplemental figure 7C). Consistently, treatment with the HSP47 inhibitor Col003 (50 µM for 24 hours) significantly reduced TRAF2 ubiquitination (figure 5E, online supplemental figure 7D). Conversely, HSP47 overexpression increased TRAF2 ubiquitination in HOS cells (figure 5F). Immunofluorescence co-staining of TRAF2 and ubiquitin further demonstrated that HSP47 overexpression promoted increased colocalization of TRAF2 with ubiquitin (figure 5G), whereas HSP47 knockdown reduced TRAF2-ubiquitin co-localization (figure 5H). These results support the notion that HSP47 facilitates TRAF2 ubiquitination in OS cells. Pulse-chase analysis using CHX showed that HSP47 deletion significantly prolonged TRAF2 protein half-life in U2OS and K7M2 cells, while HSP47 overexpression significantly shortened it (figure 5I,J, online supplemental figure 7E). Taken together, these findings indicate that HSP47 regulates TRAF2 degradation through a ubiquitination-mediated, proteasome-dependent mechanism in OS cells.

In addition to the function of HSPs in protein folding and misfolded protein degradation in ER, HSPs can actively promote the degradation of proteins via the ubiquitin-proteasome system.^{61 62} We hypothesize that HSP47 not only aids protein folding but also interacts with proteins, facilitating their ubiquitination and subsequent degradation through the proteasome. To investigate this, we assessed whether HSP47 interacts with and ubiquitinates TRAF2. Confocal immunofluorescence analysis confirmed the co-localization of HSP47 and TRAF2 in OS cells (onlinesupplemental figure 8AC). CO-IP experiments further demonstrated an interaction between HSP47 and TRAF2 (onlinesupplemental figure 8D E), suggesting that HSP47 may interact with TRAF2 and promote its ubiquitination and degradation.

Collectively, our findings reveal that HSP47 inhibition upregulates TRAF2 by blocking its ubiquitin-mediated degradation, thereby promoting NF-κB-mediated CD155 expression in OS cells.

HSP47 inhibitor exhibited synergistic effects with the TRAF2/NF-κB blockade in cancer by enhancing the CD8⁺ T cell response

Our study identified CD155 as a target regulated by TRAF2, suggesting that modulating this axis could be pivotal in overcoming immune escape mechanisms in cancer treatment. To investigate the synergistic potential of HSP47 inhibition and TRAF2 blockade, we used an orthotopic tibia OS model with TRAF2-depleted cancer cells in immunocompetent mice (figure 6A). Compared with HSP47 inhibitor Col003 treatment or TRAF2 depletion, the Col003 combined with TRAF2 knockdown significantly reduced tumor growth (figure 6A), with increased infiltration of activated CD8⁺ T cells (figure 6C–E). Consistent with our observations from in vitro experiments, TRAF2 depletion greatly reduced the basal and Col003-induced HSP47 expression in tumor tissues (figure 6C).

Figure 6. HSP47 blockade synergizes with TRAF2 inhibition to enhance CD8⁺ T cell responses in Balb/c mice. Schematic of the experimental design to evaluate the combined efficacy of TRAF2 knockdown and Col003 (20 mg/kg) in a Balb/c mouse model implanted with K7M2 OS cells in the tibia. (B) Tibial weight and tibial volume measurements from OS tumor-bearing mice in the groups described in (A) (mean±SD, n=5). (C) IHC images showing CD8a, Granzyme B, and CD155 expression in K7M2 OS-bearing mice from the treatment groups described in (A). Scale bars: 270 µm. (D) Quantification of IHC staining in (C), showing statistical analysis of CD8a, Granzyme B, and CD155 levels in tumor tissues from each group (mean±SD, n=5). (E) Flow cytometry analysis of activated CD8⁺ T cells in tumors from each group in (A) (mean±SD, n=4). Markers include CD69⁺, PFP⁺ CD8⁺ T cells, and TNF-α MFI of CD8⁺ T cells. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001, ns: not significant. IHC, immunohistochemical; MFI, mean fluorescence intensity; OS, osteosarcoma.

Similarly, administering the HSP47 inhibitor Col003 and NF-κB inhibitor BTZ in tumor-bearing mice significantly reduced tumor mass and volumes compared with either treatment alone (figure 7A,B). This combination therapy also decreased CD155 expression and increased activated CD8⁺ T cell infiltration and function within the tumor tissue (figure 7C–E).

Figure 7. HSP47 blockade synergizes with TRAF2 inhibitor BTZ to enhance CD8⁺ T cell responses in Balb/c mice. (A) Schematic of the experimental design to evaluate the combined efficacy of BTZ (1 mg/kg) and Col003 (20 mg/kg) in a separate Balb/c mouse model with tibial K7M2 OS cells. (B) Tibial weight and tibial volume measurements from tumor-bearing mice in the groups described in (A) (mean±SD, n=5). (C) IHC images of K7M2 OS-bearing mice from different treatment groups (A), showing CD8, Granzyme B, and CD155 expression. Scale bars: 270 µm. (D) Quantification of IHC staining in (C), showing statistical analysis of CD8a, Granzyme B, and CD155 expression levels in tumors from each group (mean±SD, n=5). (E) Flow cytometry analysis of activated CD8⁺ T cells in tumors from each group in (A) (mean±SD, n=4). Markers include CD69⁺, PFP⁺ CD8⁺ T cells, and TNF-α MFI of CD8⁺ T cells. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001, ns: not significant. BTZ, bortezomib; IHC, immunohistochemical; MFI, mean fluorescence intensity; OS, osteosarcoma.

Collectively, these observations suggest that TRAF2/NF-κB blockade enhances the antitumor efficacy of HSP47 inhibition, primarily by strengthening CD8⁺ T cell responses and disrupting immune evasion mechanisms through intervention of the CD155/TIGIT axis.

Discussion

Dysfunction in immune surveillance plays a crucial role in the occurrence and development of cancer.^{63 64} This study identifies HSP47 as playing a significant role in cancer and immunology. Our findings reveal that inhibiting HSP47 increases CD155 expression, a ligand for the immune checkpoint receptor TIGIT, which weakens the tumor’s sensitivity to CD8⁺ T cell-mediated cytotoxicity, and CD155/TIGIT blockade enhances the efficacy of HSP47 inhibitor by reactivating CD8⁺ T cells. We further demonstrate that TRAF2 deubiquitination, triggered by HSP47 inhibition, is pivotal in CD155 expression, revealing the mechanisms of CD155 regulation in OS.

As a crucial component for proper protein folding, HSP47 plays a key role in tumorigenesis and tumor progression, under hypoxia, low glucose, and pH. HSP47 is overexpressed in various tumors, which is associated with poor prognosis.1265,69 Recent studies have shown that overexpression of HSP47 in cancer suppresses tumor immune responses, promoting tumor brain metastasis.⁷⁰ However, our study suggests that HSP47 inhibition suppresses T cell immunity by upregulating CD155 in OS. Notably, CD155/TIGIT blockade by the TIGIT mAb could enhance the efficacy of HSP47-targeted therapies, highlighting the potential of this combination approach for cancer treatment. Furthermore, Col003 has demonstrated minimal in vivo toxicity in previous preclinical studies,70,72 as evidenced by blood routine tests and histological analysis of organ sections through HE staining (onlinesupplemental figure 9AB). These findings support the safety profile of Col003, making it a promising candidate for clinical translation. Col003 works by competitively inhibiting the interaction between HSP47 and collagen, positioning it as a potential therapeutic agent for fibrotic diseases.^{73 74} Recent studies have also shown that the combination of Col003 with PD-L1 blockade can restore CD8⁺ T cell-mediated antitumor immunity.⁷⁰ These findings suggest that Col003 may hold significant therapeutic potential, not only in fibrosis but also in cancer treatment.

Currently, HSP47 inhibitors have shown encouraging results in trials for fibrotic diseases, with ongoing clinical studies in pulmonary fibrosis (ClinicalTrials.gov ID: NCT02227459) and scar inhibition (ClinicalTrials.gov ID: NCT05838833), further validating the safety and therapeutic promise of HSP47-targeted strategies. However, further clinical evaluation is required to fully ascertain the therapeutic potential of this combined approach in cancer patients, particularly in OS. The increasing clinical interest in the CD155/TIGIT axis, especially in conjunction with PD-1/PD-L1 blockade, presents exciting opportunities for the development of synergistic immunotherapies in cancer.

Although CD155 is increasingly recognized as a novel immune checkpoint, the precise mechanisms governing its regulation remain complex and incompletely understood. Previous studies have shown that CD155 expression is modulated by multiple signaling pathways, including oncogenic RAS signaling, sonic hedgehog signaling,⁷⁵ and cytokine-driven IL-8-NF-κB signaling.⁷⁶ Additionally, CD155 expression has been implicated in response to DNA damage and the activation of various signaling networks.⁷⁷ TRAF2, a crucial adaptor protein in various signaling cascades, particularly the NF-κB pathway, has been extensively linked to cancer progression.78,81 Our study identifies a novel regulatory pathway involving HSP47, TRAF2, and the NF-κB signaling axis, governing CD155 expression. HSP47 promotes the ubiquitination and degradation of TRAF2, thereby inhibiting NF-κB activation and downregulating CD155 transcription. In contrast, HSP47 inhibition stabilizes TRAF2, leading to increased NF-κB activity and upregulation of CD155 expression.

The CD155/TIGIT axis has emerged as a significant therapeutic target due to its high expression in various tumors and its critical role in immune evasion. Current therapeutic strategies under clinical investigation include recombinant poliovirus-mediated oncolytic therapies, with ongoing phase I and II trials in glioblastoma multiforme.82,84 There is also growing interest in developing anti-CD155/TIGIT antibodies.^{23 85 86} Several ongoing clinical trials are investigating the use of mAbs targeting the CD155/TIGIT axis, but the results have not met expectations thus far, likely due to several factors. TIGIT often coexpresses with other immune checkpoints like PD-1 and CTLA-4, limiting the effectiveness of monotherapies.87,89 Additionally, low CD155 expression in some tumors may prevent the activation of the CD155-CD226 pathway, reducing the therapeutic impact of TIGIT blockade.⁹⁰ At the same time, clinical trials exploring the combination of CD155/TIGIT inhibition with PD-1/PD-L1 blockade are still underway, with results yet to be published.⁹¹ However, a growing body of preclinical evidence supports the potential of these combination therapies in enhancing immune responses and improving tumor control across multiple cancer types.90,95 While no clinical trials focusing specifically on OS and the CD155/TIGIT axis have been initiated, preclinical data have demonstrated encouraging therapeutic potential for this axis in OS treatment.^{96 97} Our study suggests that NF-κB inhibitor BTZ could serve as a small-molecule inhibitor of CD155, offering an alternative strategy to disrupt the CD155/TIGIT axis. Our research suggests that BTZ can enhance the effects of HSP47 inhibition and the combination of BTZ and HSP47 inhibitors Col003 synergistically boosts immune responses by increasing CD8⁺ T cell infiltration and suppressing tumor growth. Furthermore, BTZ, a well-established clinical proteasome inhibitor, has demonstrated a favorable safety profile in the clinical treatment of multiple myeloma and certain solid tumors.98,100 This combination strategy holds significant potential for improving the effectiveness of immune checkpoint therapies, warranting further clinical evaluation.

In summary, our findings reveal a novel HSP47/TRAF2/NF-κB axis regulating CD155 expression, highlighting CD155/TIGIT blockade as a potential therapeutic target in HSP47 inhibitor-mediated tumor therapy (figure 8). This study provides critical insights into the molecular mechanisms underlying CD155 regulation and offers new combination therapy for cancer therapy, particularly in OS. Further clinical evaluation is necessary to determine the full therapeutic potential of this combined strategy in cancer patients.

Figure 8. Schematic showing HSP47-TRAF2-CD155 axis in HSP47-activated OS cancer and the specific mechanism of combined anti-TIGIT treatment of OS. OS, osteosarcoma; TIGIT, T-cell immunoreceptor with Ig and ITIM domains.

The funders were involved in the study design, data collection, data analysis, interpretation of the results, report writing, and the decision to submit the manuscript for publication.

Data availability statement

Data are available in a public, open access repository. Data are available on reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.