Mouse sarcoma cell lines CCRF S-180 II, and WEHI-164, and human sarcoma cell lines HT-1080 (RRID: CVCL_0317), were obtained from the Korean Cell Line Bank (KCLB, Seoul, Korea), and MES-SA (RRID: CVCL_1400) was obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA). All cell lines were authenticated by short tandem repeat (STR) profiling within the past three years to confirm their identity. The STR profiling was performed by the Genomics Core Facility of National Cancer Center, and results were compared against reference profiles. Prior to experimental use, all cell lines were routinely tested and confirmed to be free of mycoplasma contamination using a PCR-based mycoplasma detection assay.

CCRF S-180 II cells were cultured in DMEM supplemented with 10% fetal bovine serum (FBS). WEHI-164 and HT-1080 cells were cultured in RPMI 1640 medium supplemented with 10% FBS. MES-SA cells were cultured in McCoy’s 5A medium. All culture media were supplemented with penicillin (100 U/ml), and streptomycin (100 mg/ml). Cell lines used in this study were all authenticated by DNA fingerprinting and were routinely tested for Mycoplasma.

Cell viability following doxorubicin treatment was assessed using the CellTiter-Glo^® 2.0 Cell Viability Assay (Promega, Madison, WI, USA) according to the manufacturer’s instructions. Briefly, cells were seeded in 96-well plates (2 × 10³ cells per well) and allowed to adhere overnight. The next day, cells were treated with serial dilutions of doxorubicin for 48 hours. Following treatment, an equal volume of CellTiter-Glo reagent was added to each well, and luminescence was measured using a microplate reader (Infinite 200 Pro, Tecan, Switzerland). Relative cell viability was normalized to untreated controls. IC₅₀ values were calculated by nonlinear regression analysis using a four-parameter logistic model in GraphPad Prism (version 8.3.1). All experiments were performed in six replicates and repeated independently at least three times.

Cells were seeded onto 8-well Lab-Tek II chamber slide (Thermo Fisher Scientific, #154534) and allowed to adhere overnight. Doxorubicin of IC₅₀ doses for each cell line or DMSO (vehicle) was applied for 48 hours. After treatment, cells were washed three times with cold PBS and fixed with cold methanol at -20°C for 10 minutes. Blocking was performed with 1% bovine serum albumin (BSA) in PBS for 1 hour. For γ-H2AX staining, cells were incubated with a primary antibody against γ-H2AX (Ser139) (Cell Signaling #2577, 1:800 dilution) at 4°C overnight. After washing twice with PBS, cells were incubated with a goat anti-rabbit Alexa Fluor 594 secondary antibody (Thermo Fisher Scientific, #A-11012, 1:500) for 1 hour at room temperature in the dark. For PicoGreen staining, Quant-iT PicoGreen dsDNA reagent (Thermo Fisher Scientific, 3μl/mL) was applied at 37°C for 1 hour. Nuclei were counterstained with Hoechst 33342 (1:500 dilution) for 10 minutes at room temperature, and fluorescent images were captured using a confocal microscope. Staining intensities were calculated using ImageJ software.

RNA was isolated from cultured cells using TRIzol (Thermo Fisher Scientific), and complementary DNA was synthesized from 1μg of total RNA with ReverTra Ace^® qPCR RT Master Mix (Toyobo, # FSQ-201) following the manufacturer’s protocols. Real-time quantitative PCR was performed using LightCycler 96 Real-Time PCR system (Roche) and Power SYBR Green PCR Master Mix (Applied Biosystems). Gene expression levels were calculated using the ΔΔCt (Delta–Delta Ct) method, with GAPDH serving as the endogenous control.

The sequences of the primers used in this study are listed below (Table 1).

Sting1-deficient cells were generated using the CRISPR/Cas9 system (18). In brief, the sgRNA sequences were cloned into the LentiCRISPR v2 vector containing the Streptococcus pyogenes Cas9 nuclease gene. The sgRNA sequences were designed using a web-based tool (https://crispr.mit.edu) (Table 2). Lentivirus was prepared in HEK293FT cells by co-transfection of the LentiCRISPR v2 vector and the viral packaging vectors pLP1, pLP2, and pLP/VSVG. Viral supernatant was collected 48 hours after transfection. Target cells were transduced with polybrene (8 μg/ml) and selected with puromycin for 2–3 days, starting 48 hours after transduction. Knockout effect was confirmed by immunoblot analysis of whole cell protein extracts. The guide RNA sequences used in this study are listed below.

Cells were lysed with radio-immunoprecipitation buffer (50 mM Tris-Cl, pH 7.5, 150 mM NaCl, 0.1% SDS, 0.5% sodium deoxycholate and 1 mM EDTA) containing protease and phosphatase inhibitors (1 mM NaF, 1 mM Na3OV4, PMSF, 2 mg/ml leupeptin and pepstatin; all purchased from Sigma) for 30 min at 4°C. The protein concentration was quantified with a Pierce BCA protein assay kit (Thermo Scientific). Blots were incubated with primary antibodies at 4°C overnight. The following antibodies were used for immunoblots: anti-STING (Cell Signaling #13647, 1:1,000) and anti-GAPDH (Cell Signaling #2118, 1:1,000).

All mouse experiments were performed under approval by the Institutional Animal Care and Use Committee (IACUC) of the National Cancer Center. A total of 3 × 10⁶ WEHI-164 cells were subcutaneously inoculated near the thigh of BALB/c mice. Tumor volume (0.5 × length × width²) was monitored regularly using a caliper. When the tumor volume reached 200mm³, mice were received weekly intratumoral injections of doxorubicin (MedChemExpress, HY-15142) at a dose of 5mg/kg body weight and/or twice-weekly intratumoral injections of 25μg of ADU-S100 (InvivoGen, tlrl-nacda2r-01).

Grafted tumors were harvested 7 days after drug treatment and dissociated using the Tumor Dissociation Kit (Miltenyi Biotec, #130-096-730). The dissociated tumor tissue was stained with anti-mouse CD45 microbeads (Mitenyi Biotech, #130-052-301). CD45⁺ cells were positively selected using QuadroMACS separator LS columns (Miltenyi Biotec, #130-091-051, #130-042-401), according to the manufacturer’s protocol. The sorted cells were stained with CD45 (BD, #5562848), and 7-AAD (BD, #344563) antibodies and analyzed by flow cytometry to confirm successful selection.

RNA was isolated using TRIzol (Thermo Fisher Scientific), and total RNA integrity number (RIN) was assessed using TapeStation RNA screentape (Agilent, #5067-5576). Only high-quality RNA samples with a RIN greater than 7.0 were used for library preparation. The cDNA libraries were prepared using the Illumina TruSeq Stranded mRNA Sample Prep Kit (Illumina, Inc., San Diego, CA, USA, #RS-122-2101). Indexed libraries were subsequently sequenced on an Illumina NovaSeq platform (Illumina, Inc., San Diego, CA, USA) using paired-end (2×100 bp) sequencing. After quality filtering with Trimmomatic (v0.38), raw sequencing data were aligned to the reference genome (mm10) using HISAT2 (v2.1.0) (19), and the sequence reads were counted with StringTie (v2.1.3) (20). Differential gene expression was statistically determined using DESeq2 (v1.38.3) (21). Gene ontology analysis was performed using clusterProfiler (v4.14.4) (22). All data analysis and visualization of differentially expressed genes was conducted using R (version 4.4.1). The data have been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE287710 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE287710).

TCGA-SARC dataset was accessed using the TCGAbiolinks package (v2.34.0) (23). Survival analysis was conducted using the survival R package (v3.8-3), and Kaplan-Meier plots were visualized using the survminer R package (v0.5.0).

All in vitro experiments were performed with at least three biological replicates (independent experiments) and at least three technical replicates per condition, unless otherwise specified.

Cytotoxic agents, such as cisplatin and etoposide, induce the production of inflammatory cytokines via a STING-dependent mechanism (24). To investigate whether doxorubicin exerts a similar effect, we assessed its ability to induce type I IFN signature genes in STS cell lines. Mouse (CCRF S-180 II and WEHI-164), and human (HT1080 and MES-SA) STS cell lines were treated with doxorubicin at their respective IC₅₀ concentrations (Supplementary Figure 1). Double-stranded DNA breaks (DSBs) were prominently detected via γH2AX staining (Figure 1A). DSBs can lead to cytoplasmic DNA leakage, which subsequently activates the STING pathway (25). Consistent with this, doxorubicin treatment caused a significant increase in cytoplasmic DNA levels in STS cells (Figure 1B), resulting in the upregulation of STING at the protein level and increased expression of type I IFN signature genes, including Ccl5, Cxcl10, and Ifnb1 in mouse sarcoma cells, and CCL5, CXCL10, IFNB1 in human sarcoma cells (Figure 1C, and Supplementary Figures 1B, C). Collectively, these findings indicated that doxorubicin induces the activation of STING pathway via DSB-mediated DNA leakage into the cytoplasm, leading to the upregulation of type I IFN signature genes.

To confirm whether the doxorubicin-induced expression of type I IFN signature genes is mediated by the activation of STING pathway, we knocked out Sting1 in two mouse STS cell lines using the CRISPR-Cas9 method (Figure 2A). The proliferation rates of Sting1-knockout (Sting1-KO) cell lines were comparable to those of non-target controls, and their responses to doxorubicin were also similar in vitro (Figure 2B and Supplementary Figure 2). However, while the doxorubicin-induced upregulation of Ccl5 and Cxcl10 was observed in both non-target controls and Sting1-KO cells, their relative expression levels remained significantly attenuated in both Sting1-KO cell lines (Figure 2C). These findings corroborate the fact that the activation of STING pathway mediates doxorubicin-induced upregulation of type I IFN signaling. Furthermore, because STING deficiency did not affect the antitumor effect of doxorubicin in vitro where immune cells are absent, we sought to investigate the role of STING pathway in mediating the antitumor effect of doxorubicin in an immunocompetent in vivo model.

Type 1 IFN signaling promotes proinflammatory responses, which is critical for mediating the antitumor effect of doxorubicin in vivo (11). Therefore, we investigated whether activating the STING pathway would potentiate the antitumor effects of doxorubicin using an in vivo syngeneic model, wherein WEHI-164 cells were grafted into BALB/c mice. For inducing the activation of STING pathway, we used ADU-S100, a STING agonist that has been tested in clinical trials. When the grafted tumors reached a size of 200 mm³, doxorubicin was administered either alone or in combination with ADU-S100 (Figure 3A). Intratumoral injection of doxorubicin alone suppressed the growth of the grafted tumor. However, its antitumor effect was significantly enhanced by coadministration of ADU-S100 (Figure 3B). To determine whether this enhancement was primarily due to ADU-S100 itself, we repeated the experiment including an additional group treated with ADU-S100 alone. Tumor volumes in the combination group were smaller than those in either monotherapy group, corroborating that STING pathway activation by ADU-S100 enhances the antitumor efficacy of doxorubicin in vivo (Supplementary Figure 3).

Given that activation of the STING pathway induces proinflammatory responses, we sought to identify which type of immune cell signaling within the tumor microenvironment (TME) contributes to the observed antitumor effects. To address this, we harvested tumors treated with the control vehicle, doxorubicin alone, or the doxorubicin and ADU-S100 combination. The tumors were dissociated, and immune cells within the TME were isolated using CD45-linked microbeads and magnetic-activated cell sorting. RNA sequencing was subsequently performed on the CD45⁺ cell population (Figure 3C). In the analysis of differentially expressed genes (DEGs), doxorubicin treatment alone led to the upregulation of Cd3, Cd8, and Pdcd1 in the immune cells within the TME (Figure 3D, right panel). Gene ontology (GO) analysis of the DEGs further supported this finding, showing enrichment of T-cell signaling pathways (Figure 3E, right panel). When comparing the doxorubicin and ADU-S100 combination with either doxorubicin alone or the control vehicle, significant upregulation of genes associated with monocyte/macrophage lineages (Ly6a, Ly6c1, and Ly6c2), and of cytokines or chemokines (Ccl11, Il10, and Il6) that promote immune cell infiltration into the TME was noted (Figure 3D, left and middle panel). GO analysis further confirmed these findings, showing enrichment of innate immune signatures and activation of proinflammatory responses (Figure 3E, left and middle panel).

Comparisons of the upregulated genes in immune cells from tumors treated with doxorubicin and ADU-S100 with those treated with doxorubicin alone or the control vehicle reflected gene signatures consistent with the activation of STING pathway. We subclassified the DEGs that were exclusively upregulated (fold change >2 and raw p-value <0.05) in the doxorubicin plus ADU-S100 group compared with that in the doxorubicin-alone group as “unique gene set (N = 78).” Additionally, genes upregulated in the doxorubicin plus ADU-S100 group compared with that in the control vehicle group, but not overlapping with the upregulated DEGs in the doxorubicin versus control comparison, were combined with the “unique gene set” and collectively termed the “broad gene set (N = 307)” (Figure 4A, and Supplementary Tables 1, 2). We sought to explore whether the gene sets reflecting the activation of STING pathway in the TME of our experimental model could predict the clinical outcomes in patients with STS. Using transcriptome data of The Cancer Genome Atlas Sarcoma (TCGA-SARC), we performed single-sample gene set enrichment analysis (ssGSEA) with the “unique gene set,” and the “broad gene set.” We then compared the overall survival among groups with high (top 25^th percentile), moderate (25^th–75^th percentile), and low (bottom 25^th percentile) expression levels. Patients with high expression levels of either the “unique gene set” or the “broad gene set” had significantly longer overall survival compared with those with low expression levels (Figures 4B, C). These findings indicated that patients with STS exhibiting higher expression of STING activation markers have improved clinical outcome, supporting our experimental model and highlighting the potential of strategies aimed at activating the STING pathway for STS therapy.