Inhibition of STAT6 with Antisense Oligonucleotides Enhances the Systemic Antitumor Effects of Radiotherapy and Anti–PD-1 in Metastatic Non–Small Cell Lung Cancer

Lung cancer remains the leading cause of cancer-related death worldwide (1). Current therapeutic approaches fail to achieve satisfactory response rates in patients with aggressive tumors and late-stage cancers (1). Recently, immunotherapy based on immune checkpoint inhibitors (ICI) has attracted substantial attention and has become a standard of care for the most common category of lung cancer, non–small cell lung cancer (NSCLC; ref. 2); however, overall survival (OS) rates remain low (3). Therefore, approaches that focus on disrupting immune resistance are actively being evaluated as potential therapeutic approaches to improve antitumor efficacy.

Radiotherapy (RT) remains an important treatment for NSCLC. Although RT was classically thought to mediate its tumoricidal effects through direct destruction of rapidly dividing cancer cells, it has come to be appreciated that much of RT's benefit owes to its activation of the immune system (4). This radiation-induced activation of the immune system can lead to recession of tumors at remote, unirradiated locations; a phenomenon known as the abscopal effect (5). The immunogenic effects of RT can be further augmented with immunotherapy. Even so, the coveted abscopal effect remains rare (4). Several factors hamper immunogenic eradication of any given resistant cancer. One contributor is the fact that, just as radiation induces cell damage and inflammation, it also stimulates the activation and recruitment of suppressive immune cell populations that resolve inflammation and turn the site of damage (i.e., the tumor) into a state of quiescence (6). Among these immunosuppressive cells are M2 tumor-associated macrophages (TAM), which facilitate angiogenesis, tumor growth, and metastasis and directly inhibit responding immune cells via inhibitory cytokines such as IL10 and TGFβ1 (7). Consequently, inhibition of M2 macrophages is an area of continued focus for cancer immunotherapy (7, 8).

A novel potential treatment that targets TAMs is the inhibition of STAT6. STAT6 signaling downstream of ILs, IL4/IL13, contributes to M2-macrophage polarization (9). STAT6 is highly activated in many tumor types and associates with metastases, immunosuppression, and radio-resistance (9–12). In patients with lung cancer, about 54% of NSCLCs have high STAT6 expression, specifically in infiltrating immune cells located in the lung interstitium (13). Conversely, mice lacking STAT6 show resilience to a variety of cancers (14–17). STAT6 deficiency in CD11b⁺ cells, but not in tumor cells, is shown to decrease both IL4 secretion and the differentiation of CD11b⁺ cells into M2 macrophages (11). In inflammatory breast cancer, the administration of a STAT6 inhibitor (PM37) improves radiosensitivity and decreased M2 polarization (12). However, STAT6 is notoriously difficult to target with traditional small-molecule strategies. Here, we used an antisense oligonucleotide (ASO)–based inhibitory platform to knockdown STAT6. We hypothesized that NSCLC antitumor responses can be improved through inhibition of M2 polarization by use of a STAT6 ASO in combination with RT.

Lewis lung carcinoma (LLC), CT26, and 4T1 cells were purchased from the ATCC. The ID8-VEGF cell line was a gift from Ionis Pharmaceuticals. The metastatic mouse lung cancer cell line 344SQ-P was a gift from Dr. Jonathan Kurie at MD Anderson Cancer Center (MDACC). We also used a 344SQ anti–PD-1–resistant cell line (344SQ-R) that had previously been established from 344SQ-P cells in our laboratory (18). LLC, CT26, 4T1, 344SQ-P, and 344SQ-R cells were cultured in RPMI-1640 medium (Gibco) with 10% heat-inactivated FBS (Gibco) and supplemented with 100 U/mL penicillin (Invitrogen) and 100 mg/mL streptomycin (Invitrogen) in a humidified incubator with 5% CO₂ at 37°C. ID8-VEGF cells were cultured in DMEM medium (Gibco) with 4% FBS (Gibco), 100 U/mL penicillin (Invitrogen), 100 μg/mL streptomycin (invitrogen), 5 μg/mL insulin–transferrin–selenium-X supplement (Invitrogen) in a 5% CO₂ atmosphere at 37°C. All cell lines were authenticated by the STR test and were routinely tested to confirm the absence of Mycoplasma contamination. The cells used to establish the tumor models were within 3 to 6 passages from the source cells.

Eight- to 12-week-old female B6.Cg-Foxp3^tm2(EGFP)Tch/J (i.e., B6.Foxp3^EGFP) mice and C57BL/6 mice were purchased from The Jackson Laboratory. BALB/c and 129Sv/Ev mice were purchased from the Charles River Laboratories and Taconic Biosciences, respectively. All mice were bred at a mouse colony maintained by the Department of Experimental Radiation Oncology at MDACC. All mice were maintained under specific pathogen-free conditions with a maximum of five mice per cage. All animal procedures were conducted under the approval of the Institutional Animal Care and Use Committee of The University of Texas MDACC.

Subcutaneous two-tumor models were established as follows: B6.Foxp3^EGFP (or 129Sv/Ev) mice were subcutaneously injected with LLC (or 344SQ-R) cell lines in both hind legs. Primary tumors were established by injecting 1×10⁵ cells in 100 μL PBS into the right legs on day 0, and secondary tumors were established by injecting 5×10⁴ cells in 100 μL PBS into the left legs on day 3. The 344SQ-P model was created by injecting 129Sv/Ev mice with 4×10⁵ 344SQ-P cells in the right leg and 1×10⁵ in the left leg. Subcutaneous one-tumor models were established as follows: B6.Foxp3^EGFP (or C57BL/6) mice were subcutaneously injected with 1×10⁵ LLC (or ID8-VEGF) cells in 100 μL PBS in the right hind legs. BALB/c mice were subcutaneously injected with 4×10⁵ CT26 cells or 4T1 cells in the right hind legs.

Mice were euthanized with CO₂ when the primary or secondary tumors reached 1,500 mm³ or at day 50, whichever came first. At that time, the lungs were harvested, and metastases were counted after staining with Bouin's fixative solution (Polysciences Inc.). Tumor length and width were measured using digital calipers, and tumor volume was calculated as length×width²/2.

Hypofractionated RT (hRT) was delivered in the Department of Experimental Radiation Oncology at MDACC. When primary tumors of the two-tumor models of LLC, 344SQ-P and 344SQ-R reached 150 to 200 mm³, they were irradiated locally with 3 fractions of 12 Gy each from a Cesium source, as previously described (19). The choice of radiation dose was based on relevance to clinically used stereotactic doses and our prior experience (20, 21). Secondary tumors were unirradiated.

For immune-checkpoint blockade therapy to the two-tumor models of LLC, 344SQ-P and 344SQ-R, a 200 μg/dose of anti–mouse-PD-1 (Bio X Cell, clone RMP1–14) in 250 μL sterile PBS was given intraperitoneally twice a week, beginning on the first day of radiation and continuing until death or experimental endpoint. Macrophage depletion to the two-tumor model of LLC was accomplished by alternating intraperitoneal/intratumor injections of 100 μg/dose of anti-mouse F4/80 (Bio X Cell, clone CI: A3–1) starting on day 5, for up to 10 days, and then twice a week thereafter (19). CD8⁺ and CD4⁺ T cells to the LLC two-tumor model were depleted by intraperitoneally injected anti-CD8 (10 mg/kg, CI:A3–1, BioXCell) and anti-CD4 (10 mg/kg, clone GK 1.5, BioXCell) on day 5 and twice a week thereafter. Cellular depletion of macrophages, CD8⁺ T cells, and CD4⁺ T cells was confirmed by flow cytometry.

All ASOs used in this study were 16 nucleotides in length, connected sequentially by phosphorothioate internucleoside linkages. The 3 nucleotides at both the 5′ and 3′ ends were composed of 2′-4′ constrained ethyl (cEt)-modified ribonucleotides, which conferred an increased affinity to the target mRNA and increased resistance to exo- and endonucleases within the cell. The central portion was composed of 10 deoxynucleotides, enabling RNase H1 to recognize and cleave the target mRNA in the ASO:RNA duplex. We used two distinct non-targeting control ASOs (792156 and 549148, Ionis Pharmaceuticals) and two distinct ASOs targeting mouse Stat6 RNA (867782 and 867776, Ionis Pharmaceuticals).

Normal BALB/c mice (Charles River Laboratories) were subcutaneously administered with unformulated STAT6 ASO (867776) and control ASO (549148) at 50 mg/kg twice a week for 8 weeks. At the end of the study, tissues (liver and spleen) and peritoneal macrophages were collected for RNA extraction and RT-qPCR analysis of Stat6 mRNA expression, as described below. Briefly, peritoneal macrophages were collected through peritoneal lavage with growth media (RPMI-1640 supplemented with 2% FBS, Thermo Fisher Scientific) followed by plastic adherence for 6 hours at 37°C. The nonadherent cells were removed by three PBS washes. Adherent peritoneal macrophages were either left untouched or polarized to M1-type [20ng/mL LPS (Sigma) and 20 ng/mL IFNγ (BioLegend)] or M2-type [20 ng/mL IL4 (BioLegend) and 20 ng/mL IL13 (BioLegend)] for 24 hours. For STAT6 inhibition in murine tumor models, 40 mg/kg of mouse STAT6 ASO (867776) or control ASO (549148) was delivered by subcutaneous injection daily, starting 3 days before RT and continuing until death or experimental endpoint.

Bone marrow cells were collected from the femora and tibiae of 6 weeks BALB/c mice (Charles River Laboratories) and cultured in the IMDM medium (Gibco) containing macrophage colony–stimulating factor (M-CSF, 10 ng/mL, BioLegend). After 7 days in culture, contaminating nonadherent cells were removed by washing with PBS and adherent bone marrow–derived macrophages (BMDM) were harvested and cultured at desired density on 96-well plates. BMDMs were treated with different concentrations of unformulated STAT6 and control ASOs for 72 hours. After that, IL4 (20 ng/mL, BioLegend) and IL13 (20 ng/mL, BioLegend) were added for M2 macrophage polarization. Twenty-four hours later, cells were collected for determining tyrosine phosphorylation of STAT6 (p-STAT6) and total STAT6 by flow cytometry and mRNA expression of Stat6 and macrophage polarization markers Arg1 and Mrc1 by RT-qPCR (described below).

Freshly isolated tumor tissues (5 mice/group) from the two-tumor model of LLC were digested with 250 μg/mL of Liberase TR and 20 μg/mL DNase I (both from Roche) and further dissociated with a gentleMACS Octo Dissociator with Heaters (MiltenyiBiotec), according to the manufacturer's protocol. Briefly, run the program (37_m_TDK_1) and filtered MACS SmartStrainers (70-μm, MiltenyiBiotec) afterwards. Harvested spleens were pressed through 70-μm filters, washed with RPMI-1640 medium, incubated for 1 minute with 2-mL ACK lysing buffer (Lonza) to remove RBCs, and then washed again.

Macrophages were isolated from tumor-cell suspensions and splenocytes using anti-F4/80 microbeads according to the manufacturer's protocol, in a buffer prepared by diluting MACS BSA stock solution (#130–091–376) 1:20 with autoMACS Rinsing Solution (#130–091–222). First, F4/80⁺ cells were magnetically labeled with anti-F4/80 MicroBeads UltraPure (MiltenyiBiotec, #130–110–443). Cell suspensions were then loaded onto a MS Column (MiltenyiBiotec) and placed in a MACS Separator (MiltenyiBiotec). The magnetically labeled F4/80⁺ cells were retained within the column, and the unlabeled cells contained in the run-through were collected and considered depleted of F4/80⁺ cells. The magnetically retained F4/80⁺ cells were eluted as the positively selected cell fraction. To increase the purity, the cell fraction containing the F4/80⁺ cells was separated over a second column. The purity of isolated cells was 99% determined by flow cytometry using anti–CD45-Pacific blue [Clone: 30-F11; Isotype: Rat IgG2b, κ (clone: RTK4530), BioLegend], anti–CD11b-APC [Clone: M1/70; Isotype: Rat IgG2b, κ (clone: RTK4530), BioLegend), and anti-F4/80-FITC (Clone: BM8; Isotype: Rat IgG2a, κ; clone: RTK2758), BioLegend], and samples were analyzed by flow cytometry using Gallios Flow Cytometer (BD Biosciences). Cell debris and dead cells were excluded from the analysis based on scatter signals and 7-AAD (MiltenyiBiotec, # 130–111–568) fluorescence. The isolated macrophages were used for RT-qPCR.

Total RNA was isolated from tissues (liver and spleen) or macrophages isolated from the two-tumor model of LLC with the RNeasy Kit (Qiagen) according to the manufacturer's protocol. mRNA was retrotranscribed with an iScript gDNA Clear cDNA Synthesis Kit (Bio-Rad). The setup for cDNA synthesis is 4-μL iScript Reverse Transcription Supermix and 16-μL DNase-treated RNA template per reaction. And then mRNA was analyzed by qPCR by using SYBR Green Supermix (Bio-Rad) with specific primers (Supplementary Table S1). Samples were run on the Bio-Rad real-time PCR instrument (Bio-Rad CFX96 Touch). We did a triplicate biological replicate. For each biological replicate, two technical replicates were run for each PCR reaction. The relative abundance of mRNAs versus CD45 expression in immune cells was calculated with the comparative ∆∆C_t method.

TGFβ1 cytokine levels were measured in serum samples from the two-tumor model of LLC with an R&D Systems Mouse/Rat/Porcine/Canine TGFβ1 Quantize ELISA Kit. Briefly, blood samples were collected from the cheek of 5 mice/group on day 16 and centrifuged for 20 minutes at 2,000 × g. The serum was then acid-activated (40 μL of serum with 10 μL of 1N HCL; samples incubated 10 minutes at room temperature; 10 μL of 1.2N NaOH/0.5 mol/L HEPES was then added) and diluted (60-fold dilution in Calibrator Diluent RD5–53) before incubation with assay diluent RD1–73 and TGFβ1 conjugate. The TGFβ1 control (within the kit) was reconstituted with 1-mL distilled water and was used as the standard stock solution to produce a dilution series (2,000, 1,000, 500, 250, 125, 62.5, 31.3, and 0 pg/mL). The undiluted TGFβ1 standard served as the high standard (2,000 pg/mL), and the Calibrator Diluent RD5–53 (diluted 1:4) served as the zero standard (0 pg/mL). Optical density was read in a microplate reader (BioTek) at 450 and 570 nm. For wavelength correction, the values at 570 nm were subtracted from the readings at 450 nm and plotted accordingly. The average of duplicate readings for each standard, control, and sample were determined and the averaged zero standard optical density was subtracted. Concentrations were determined using the standard curve, and measured concentrations were multiplied by the final dilution factor.

Tumor tissues from the two-tumor model of LLC were fixed in 10% neutral buffered formalin, processed, embedded in paraffin, and sectioned (4-μm). For multiplex staining, a board-certified veterinary pathologist reviewed the hematoxylin and eosin–stained slides and marked areas of immune cell infiltration, after which 6-mm tissue cores, including peripheral and central areas of the tumor section, were manually incorporated into a tissue microarray. A Leica Bond Rx Auto Stainer with antibodies (STAT6 and IBA-1) listed in Supplementary Table S2 and a Vector TrueVIEW Autofluorescence Quenching Kit were used for multiplex staining per the manufacturer's instructions. Microarrays were imaged at ×20 magnifications with a Leica Versa 8 fluorescent digital scanning microscope system, with Leica digital image analysis software used for quantification. For image preprocessing, tissue cores were each annotated separately, and the exclusion tool was used to exclude histologic artifacts. Four 500×500 μm areas were placed at the periphery and central areas of the tumor. A cellular immunofluorescence algorithm from Leica Imagescope software version 12.4.6 was trained for quantification of markers in each channel.

Splenocytes and tumor-infiltrating lymphocytes (TIL) enriched from the two-tumor model of LLC tumors by Histopaque separation (Sigma) were washed with PBS containing 2% FBS and stained for cell surface and intracellular markers as follows: anti-CD45 Pacific blue [Clone: 30-F11; Isotype: Rat IgG2b, κ (clone: RTK4530; BioLegend), anti-CD4 APC-Fire 750 (Clone: GK1.5; Isotype: Rat IgG2b, κ (clone: RTK4530), BioLegend], anti-CD8 PerCP-Cy5.5 [Clone: 53–6.7; Isotype: Rat IgG2a, κ (clone: RTK2758), BioLegend], anti-CD11b Alexa Fluor 700 [Clone: M1/70; Isotype: Rat IgG2b, κ(clone: RTK4530), BioLegend], anti-F4/80 BV510 [Clone: BM8; Isotype: Rat IgG2a, κ (clone: RTK2758), BioLegend], anti-CD38 PE-Cy7 [Clone: 90; Isotype: Rat IgG2a, κ (clone: RTK2758), BioLegend], anti-CD206 PE [Clone: C068C2; Isotype: Rat IgG2a, κ (clone: RTK2758), BioLegend], anti-NK1.1 PE-Cy7 [Clone: PK136; Isotype: Rat IgG2a, κ (clone: MOPC-173), BioLegend], anti-Gr1 PE [Clone: RB6–8C5; Isotype: Rat IgG2b, κ (clone: RTK4530), BioLegend], anti-STAT6 APC [Clone: YE361; Isotype: IgG (clone: EPR25A), Abcam], anti-STAT6 phosphate (Tyr641) PE [Clone: A15137E; Isotype: Mouse IgG1, κ (MOPC-21), BioLegend], and IFNγ BV711 [Clone: XMG1.2; Isotype: Rat IgG1, κ (R3–34), BD Biosciences]. Foxp3 was identified by GFP in the B6.Foxp3^EGFP mice. For cell surface protein staining, all samples were stained at room temperature for 30 minutes; for intracellular staining, cells were fixed (BD Biosciences, RRID:SCR_013311), permeabilized (Invitrogen eBioscience Permeabilization Buffer, 00–8333–56), and stained according to the manufacturer's instructions; for IFNγ stimulation, cells were restimulated with PMA (10 ng/mL, Sigma) and ionomycin (1 μg/mL, Sigma). Ten hours later, brefeldin A (GolgiPlug, BD Biosciences) was added for 2 hours to destroy the Golgi and allow intracellular accumulation, and then cells were fixed, permeabilized, and stained according to the manufacturer's instructions. All samples were run on the Gallios (BD Biosciences) and Aurora (Cytek Biosciences) Flow Cytometer and analyzed with FlowJo V10 (RRID:SCR_008520) software. Gating strategies are provided in Supplementary Table S3.

NanoString analysis was done as previously described (19, 22). Briefly, RNA samples were extracted from Histopaque-enriched TILs (3 mice/group, two-tumor model of LLC) by an RNeasy Mini Kit (Qiagen) according to the manufacturer's protocol. The RNA samples were submitted to the Advanced Technology Genomics Core at MDACC for NanoString analysis. Expression profiling was performed on the nCounter FLEX Instrument using nCounter Mouse PanCancer Immune Profiling panel (NanoString Technologies). Briefly, purified RNA was quantitated using the Qubit system (Life Technologies) and quality checked using NanoDrop One (Thermo Fisher Scientific) and TapeStation 4200 (Agilent). 100–150 ng, depending on the amount of degradation, of RNA were hybridized to gene-specific fluorescent-labeled probes. The hybridized products were then purified on the nCounter Prep Station. The fluorescent-labeled products were then scanned on the nCounter Digital Analyzer, and the nCounter Mouse PanCancer Immune Profiling panel was used and included 770 genes (https://www.nanostring.com/products/gene-expressionpanels/gene-expression-panels-overview/hallmarks-cancer-geneexpression-panel-collection/ pancancer-immune-profiling-panel?jumpto¼SUPPORT).

RNA was extracted from whole tumors and additionally used to run the NanoString Technology's nCounter Mouse PanCancer Pathways panel for 770 genes from 13 cancer-associated canonical pathways using the same method as above. No custom probes were added for either panel. Data from the NanoString nCounter System were normalized to the internal positive controls and housekeeping genes using the recommended settings in the nSolver Software Normalization Module (NanoString Technologies). Normalized data were exported, and differential expression analysis was performed using a linear model method with the limma package for the R programming language. Cell typing and pathway analysis, and genes differentially expressed in each treatment were identified from the expression data of 770 genes by nSolver. Analysis and normalization of the raw NanoString data were done with nSolver Software v4.0 and nCounter Advanced Analysis (NanoString Technologies).

Terminal blood samples were obtained through cardiac puncture from BALB/c mice treated with PBS or control ASO (549148) or STAT6 ASO (867776) and were collected in blood collection vials containing K2 EDTA (SAI Infusion Technologies). Each sample was then divided into two tubes. One tube was sent to IDEXX Bioanalytics for complete blood count analysis. The plasma from the second set was separated by centrifugation and ALT, AST, total bilirubin, blood urea nitrogen and albumin were measured using Beckman Coulter chemistry analyzer AU480 according to the manufacturer's protocols at Ionis Pharmaceuticals.

Statistical analyses were done with GraphPad Prism (RRID:SCR_002798). A P value of ≤0.05 was indicative of statistical significance. Tumor growth curves were compared by two-way ANOVA with multiple comparisons and error bars representing the standard deviation (SD). Unpaired t tests were used to compare differences between different treatment groups. Survival rates were analyzed with the Kaplan–Meier method and the curves were compared with log-rank tests. The lack of a significance marks denotes a true lack of statistically significant difference.

The data generated in this study are available upon request from the corresponding author.

We first evaluated the effects of STAT6 ASOs in macrophages in vitro. We isolated mouse bone marrow and generated BMDMs. We then cultured these BMDMs with either two distinct control (792156 and 549148) or STAT6 (867782 and 867776) ASOs. To establish baseline gene signatures, we differentiated our BMDMs toward either the M1 or M2 phenotype using IFNγ + LPS or IL4 + IL13, respectively. To control for any potential off-target effects of the ASO itself, this differentiation was done in the presence of the control ASO. We then analyzed the transcriptomic expression of M1-related genes (Nos2 and Tnfα) and M2-related genes (Arg1, Mrc1) via RT-qPCR (Supplementary Fig. S1A). Having established this baseline, BMDMs were then treated with unformulated STAT6 and control ASOs for 72 hours, after which we polarized them to the M2 phenotype with IL4 + IL13 for 24 hours. Both STAT6 ASOs induced a potent dose-dependent reduction of Stat6 mRNA in M2 macrophages (Fig. 1A; Supplementary Fig. S1). Both STAT6 ASOs prevented mRNA expression of M2 macrophage markers Arg1 and Mrc1 (Fig. 1B) and Cd163 (Supplementary Fig. S1B), consistent with the role of STAT6 in IL4/IL13-driven M2 macrophage polarization. Reduction of both total and phosphorylated (p-)STAT6 protein was observed in the STAT6 ASO group compared with control ASO using flow cytometry (Supplementary Fig. S1C and S1D).

Having demonstrated that STAT6 ASOs could impair STAT6 expression and also reduce M2-related gene expression in vitro, we next assessed the effect of the most potent STAT6 ASO (867776) in vivo. Mice were subcutaneously administered STAT6 ASO at 50 mg/kg twice a week for 8 weeks. As with the cultured BMDMs, this induced robust Stat6 mRNA reduction in the spleen and liver (Fig. 1C), as well as in isolated peritoneal macrophages (Fig. 1D). This STAT6 ASOt effect was unaffected when peritoneal macrophages from treated mice were polarized to either the M1 or M2 phenotype (Fig. 1D). To evaluate the potential off-target effects of the STAT6 ASO on other STATs, we analyzed the fold changes in the mRNA transcript expression of other STATs (Stat1, Stat3, Stat4, Stat5a, Stat5b, and Stat6) in LLC tumors isolated from mice treated with STAT6 ASO versus control ASO on day 16 by NanoString (Supplementary Fig. S1E). Only Stat6 expression was significantly perturbed (P = 0.0245). Long-term systemic inhibition of STAT6 by ASO was well-tolerated and lacked the overt phenotypes seen in Stat6-knockdown mice (Supplementary Table S4). Overall, STAT6 ASOs potently reduced STAT6 mRNA, inhibited M2 polarization, and were well-tolerated.

To identify the antitumor effect of STAT6 ASO in vivo, we established multiple tumor models (CT26, ID8-VEGF, 4T1, and LLC) and treated them with PBS, control ASO, or STAT6 ASO. Tumor growth was stunted by the STAT6 ASO (867776) in the CT26, ID8-VEGF, and 4T1 models, but not in the LLC model (Supplementary Fig. S2). Given our initial focus studying immunoresistant lung cancers, we used the LLC line as our model for the remainder of this study. To determine whether the STAT6 ASO in combination with hRT exerted systemic antitumor effects, we used a bilateral tumor model in which LLC cells were implanted in B6.Foxp3^EGFP mice randomized into the following four treatment groups: (i) control ASO; (ii) STAT6 ASO; (iii) hRT + control ASO; and (iv) hRT + STAT6 ASO (Fig. 2A). Tumor size and survival was monitored, and the experimental endpoint was when primary or secondary tumors reached 1,500 mm³. The median OS in each group was 20 (control ASO), 24 (STAT6 ASO), 28 (hRT + control ASO), and 38 days (hRT + STAT6 ASO, P < 0.0001). The combination of hRT and STAT6 ASO resulted in all five (100%) mice surviving until day 30; no other treatment group exhibited this rate of survival (Fig. 2B). The STAT6 ASO alone and the ASO control did not significantly differ in reducing primary (Fig. 2C) or secondary tumor growth (Fig. 2D). The combination of hRT + control ASO significantly reduced growth of primary tumors (P < 0.0001), but not secondary tumors. In contrast, the combination of STAT6 ASO and hRT significantly suppressed primary (P = 0.0017, on day 25) and secondary (P = 0.0001, on day 22) tumor growth relative to hRT + control ASO-treated animals. Tumor growth curves for individual mice in each group are shown in Fig. 2E and F. Body weights of mice in the indicated treatment groups revealed no evidence of dose-limiting toxicity during treatment (Fig. 2G).

To confirm that the ASO knocked down STAT6 in our LLC model, we measured Stat6 expression in magnetically isolated macrophages 7 days after hRT using RT-qPCR. The STAT6 ASO significantly reduced Stat6 expression in macrophages isolated from primary tumors (P = 0.031), secondary tumors (P = 0.019), and spleens (P = 0.006) relative to control ASO (Fig. 3A). Conversely, hRT + control ASO led to increased Stat6 expression in irradiated primary tumors (vs. control ASO, P = 0.0164), but not in unirradiated secondary tumors or spleens (Fig. 3A). The combination of hRT + STAT6 ASO reduced Stat6 expression in primary tumors, secondary tumors, and spleens relative to STAT6 ASO alone or the hRT + control ASO group (Fig. 3A). We then used immunofluorescent staining of IBA1, a pan macrophage marker [33], to confirm that STAT6 suppression was occurring within TAMs (Fig. 3B and C). Concordant with our mRNA data, we found fewer STAT6⁺ macrophages in both primary and secondary tumors (Fig. 3B–D) after treatment with the STAT6 ASO. We again observed that hRT + control ASO increased STAT6⁺ macrophages in primary tumors (vs. control ASO, P = 0.014), but not in secondary tumors (vs. control ASO, P = 0.944, Fig. 3D). However, combining hRT with the STAT6 ASO significantly reduced the number of STAT6⁺ macrophages in primary tumors (vs. hRT + control ASO, P = 0.0013, Fig. 3D), but a significant decrease was not observed in secondary tumors (vs. hRT + control ASO, P = 0.0914, Fig. 3D). In a separate experiment, tumors and spleens were harvested 10 days post irradiation, and STAT6⁺ macrophages were quantified by flow cytometry. Consistent with the mRNA expression and immunofluorescence results, flow cytometry showed an increase in STAT6⁺ macrophages in primary tumors of the hRT + control ASO group (vs. control ASO, P = 0.038, Fig. 3E and F) and a significant decrease after hRT + STAT6 ASO in primary tumors (vs. hRT + control ASO, P = 0.005) and spleens (P < 0.0001, Fig. 3E and F). The total number of macrophages was not significantly changed with STAT6 ASO treatment alone (vs. control ASO, P > 0.05), but was significantly increased in both primary and secondary tumors after treatment with hRT + control ASO or hRT + STAT6 ASO (vs. control ASO, all P < 0.05, Supplementary Fig. S3A). Collectively, our findings show that the STAT6 ASO reduces STAT6 systemically and that hRT + STAT6 ASO ablate the radiation-induced increase in STAT6⁺ macrophages.

Having demonstrated that the STAT6 ASO effectively reduced STAT6 expression in macrophages and improved the effects of hRT on tumor control and OS, we next sought to determine the mechanism behind this. We therefore tested whether the STAT6 ASO inhibited M2 polarization, thereby improving the systemic antitumor effects of hRT. To assess this, we analyzed the transcriptional expression of M1- and M2-related genes in macrophages isolated from tumors and spleens 7 days after the last fraction of hRT. In macrophages isolated from primary tumors from mice treated with hRT + STAT6 ASO, we detected heightened expression of three M1-related genes—Il1r, iNos, and Cd80 (Fig. 4A)—and decreased expression of the M2-related genes Arg1, Fizz1, Cd163, and Cd206 relative to hRT + control ASO (Fig. 4B) and observed the same trend in secondary tumors (Fig. 4C and D). No increase in M2-related genes was observed in the macrophages isolated from secondary tumors of mice treated with hRT + control ASO (Fig. 4B and D). Similar trends were noted in spleens (Supplementary Fig. S3B and S3C). Our findings suggest that STAT6 knockdown reverses hRT-induced promotion of M2 macrophage polarization and, instead, inhibits the expression of M2-associated genes in macrophages.

To confirm that macrophages from mice treated with the STAT6 ASO were, as our transcriptomic data suggested, being polarized toward the M1 phenotype, we used flow cytometry to identify M1 (CD11b⁺F4/80⁺CD38⁺) and M2 (CD11b⁺F4/80⁺CD206⁺) populations in primary tumors (Fig. 4E; Supplementary Fig. S3D), secondary tumors (Fig. 4F; Supplementary Fig. S3E), and spleens (Supplementary Fig. S3F) on day 21, following the design in Fig. 2A. In line with the mRNA data, we found that M2 macrophage infiltration was elevated in primary tumors after hRT + control ASO treatment, whereas M1 macrophage prevalence was unchanged. In contrast, we observed increased M1 macrophage prevalence in the primary tumors and reduced M2 macrophage percentages in primary tumors, secondary tumors, and spleens of mice treated with hRT + STAT6 ASO.

We next sought to test whether this favoring of the M1 over the M2 phenotype observed in TAMs from STAT6 ASO-treated mice contributed to the systemic antitumor effect. We therefore depleted macrophages in mice treated with hRT plus the STAT6 ASO using anti-F4/80, and depletion of macrophages was confirmed by flow cytometry (Supplementary Fig. S4A). When we did this, the antitumor effect of hRT + STAT6 ASO previously observed in both primary (P = 0.021) and secondary tumors (P = 0.01, Fig. 4G) was significantly compromised, as was the survival benefit thereof (Fig. 4H). Primary and secondary tumor growth curves for individual mice are shown in Supplementary Fig. S4B and S4C. To determine whether polarization of M1 macrophages was sufficient to induce the antitumor effect or whether T cells were required, we depleted CD8⁺ and CD4⁺ T cells by using anti-CD8 and anti-CD4, respectively, and depletion was confirmed by flow cytometry (Supplementary Fig. S4D). The antitumor effects in both primary and secondary tumors, and the survival benefit of hRT + STAT6 ASO, were compromised with the depletion of CD8⁺ and CD4⁺ T cells (Supplementary Fig. S4E and S4F). Simultaneous depletion of CD8⁺ T cells, CD4⁺ T cells, and macrophages completely eliminated any effect of the STAT6 ASO.

To gain a deeper understanding of the mechanism(s) by which STAT6 ASO might be affecting the tumor microenvironment (TME), we next examined molecular signaling pathways in primary tumors on day 19 using the NanoString nCounter Mouse PanCancer Pathways platform. In primary tumors, hRT upregulated tumor-promoting factors, including cell-cycle activation and proliferation pathways, such as JAK-STAT, PI3K, MAPK, and TGFβ signaling. In contrast, the addition of the STAT6 ASO attenuated these pathways (Fig. 4I). Altogether, our results demonstrate that hRT promotes the accumulation of STAT6⁺ M2 macrophages in primary tumors, but this accumulation is attenuated by inhibition of STAT6, leading instead to elevated M1 macrophages, improved tumor control, and prolonged survival.

LLC tumors are relatively “cold,” with minimal T-cell infiltration, downregulated PD-L1 expression, and resistance to anti–PD-1/PD-L1 (23). We therefore explored whether hRT + STAT6 ASO therapy could reverse this, making the tumors labile to anti–PD-1 (Fig. 5A). Predictably, anti–PD-1 alone did not suppress the growth of either primary (Fig. 5B) or secondary tumors (Fig. 5C), and the addition of the STAT6 ASO to anti–PD-1 did not suppress tumor growth relative to anti–PD-1 alone. Although hRT + anti–PD-1 did reduce tumor growth relative to single-agent therapy, no significant difference was found between hRT + anti–PD-1 and hRT + control ASO groups in primary (P = 0.765, Fig. 5B) or secondary tumors (P = 0.822, Fig. 5C), indicating no additional benefit of anti–PD-1 to the hRT. However, the triple combination of hRT + STAT6 ASO + anti–PD-1 effectively reduced both primary (Fig. 5B) and secondary (Fig. 5C) tumor volume to a greater extent than all other treatments. The triple therapy also increased OS rates in treated mice at day 40 from 0% (hRT + anti–PD-1) and 40% (hRT + STAT6 ASO) to 80% (Fig. 5D). Tumor growth curves for individual mice for each group are shown in Supplementary Fig. S5A and S5B.

To validate these findings, we also explored the antitumor effects of hRT + STAT6 ASO ± anti–PD-1 in two additional bilateral murine lung cancer models: 344SQ-P and anti–PD-1–resistant 344SQ-R. In the 344SQ-P model, the combination of hRT + STAT6 ASO suppressed tumor growth relative to hRT + control ASO in both primary (P < 0.0001, Fig. 5E) and secondary tumors (P < 0.0001, Fig. 5F). The addition of anti–PD-1 to this further enhanced systemic tumor control achieved with hRT + STAT6 ASO (all P < 0.0001 in both primary and secondary tumors, Fig. 5E and F). A similar effect was observed for primary tumors in the 344SQ-R model, with significant reductions in tumor volume after treatment with either hRT + STAT6 ASO or hRT + STAT6 ASO + anti–PD-1 (both P < 0.001) compared with hRT + control ASO (Fig. 5G). However, in secondary tumors, only the triple therapy reduced tumor growth (P = 0.019, vs. hRT + control ASO; Supplementary Fig. S5C). Assuming that these effects result from the aggressive nature of 344SQ-R model, which may have obscured effects on secondary tumors, we counted lung metastases on day 24 and found that, relative to hRT + control ASO, all three experimental interventions (STAT6 ASO alone, hRT + STAT6ASO, and the triple therapy) significantly decreased lung metastasis (Fig. 5H).

STAT6 is a common component in numerous immune cell populations and transcriptional programs (24). Ergo, its inhibition via the ASO was likely to have broader effects than just those involving macrophage polarization. To further explore these potential effects, we harvested both primary and secondary tumors 7 days after hRT for RNA isolation and NanoString analysis of 770 immune-related genes. Results of this indicated that hRT + STAT6 ASO, with or without anti–PD-1, led to the upregulation of genes related to T_H1 T-cell identity and function and the downregulation of genes associated with CD8⁺ T-cell exhaustion in both primary and secondary tumors (all P < 0.05, vs. hRT + control ASO, Fig. 6A and B). However, no significant difference in total macrophage signature genes (such as Cd84 or Cd68) was noted between hRT + STAT6 ASO ± anti–PD-1 versus hRT + control ASO in primary tumors. To further explore the effects of different treatments on macrophages and other immune cell populations, we harvested primary and secondary tumors on day 20 post primary tumor inoculation and assessed lymphoid and myeloid populations by flow cytometry. The M1/M2 ratio was significantly higher in the STAT6 ASO group compared with control ASO in both primary (P = 0.0065) and secondary tumors (P = 0.0108). In the primary tumors, the ratio of M1/M2 increased in the hRT + STAT6 ASO and triple-therapy groups (both groups P < 0.0001, vs. hRT + control ASO, Fig. 6C), with similar results detected for secondary tumors (both groups P < 0.01, vs. hRT + control ASO, Fig. 6C). However, there was no significant difference in the M1/M2 ratio between hRT + STAT6 ASO and triple therapy, indicating no additional benefit on macrophage polarization from PD-1 blockade (Fig. 6C; Supplementary Fig. S6A and S6B).

We also examined T-cell subpopulations and discovered that treatment with STAT6 ASO alone did not change the proportion of CD4⁺ T cells, CD8⁺ T cells, or regulatory T cells (Tregs) in either primary and secondary tumors (all P > 0.05, Fig. 6D). However, when the STAT6 ASO was paired with hRT, it led to upregulation of total and cytotoxic IFNγ⁺CD8⁺ T cells in primary and secondary tumors (all P < 0.05, vs. hRT + control ASO, in Fig. 6D and E, respectively, Supplementary Fig. S6C and S6D). The addition of anti–PD-1 further increased total and cytotoxic T cells in both primary and secondary tumors (all P < 0.05, vs. hRT + STAT6 ASO, in Fig. 6D and E, respectively, Supplementary Fig. S6E and S6F). No change in CD4⁺ T cells was seen in either primary or secondary tumors following treatment with hRT + STAT6 ASO (both P > 0.05, vs. hRT + control ASO, Supplementary Fig. S6G and S6H). Tregs were downregulated by both hRT + STAT6 ASO and the triple therapy in primary tumors (P = 0.0009 and P = 0.0007, respectively, vs. hRT + control ASO, Fig. 6D) and secondary tumors (P = 0.033 and P = 0.005, respectively, vs. hRT + control ASO, Fig. 6E). To explore the influence of different treatments on STAT6 expression in different cells in the TME, we phenotyped STAT6 expression in macrophages, natural killer cells, T cells, myeloid-derived suppressor cells, and tumor cells from primary and secondary tumors on day 21 via flow cytometry. We observed that macrophages were among the TME cell subsets that most expressed STAT6, concordant with the efficient STAT6 knockdown observed in these cells (Supplementary Fig. S6I).

TGFβ produced by immunosuppressive cell populations, such as M2 TAMs and Tregs, within the TME is one of the primary tumor defenses against immune clearance (25, 26). Given that both M2 TAMs and Tregs were reduced in primary and secondary tumors of mice treated with the STAT6 ASO, we sought to assess whether STAT6 inhibition affected TGFβ1 levels. To this end, we collected serum samples from treated mice on day 16 and assessed TGFβ1 by ELISA. Both STAT6 ASO alone and hRT + STAT6 ASO treatment led to significant downregulation in TGFβ1 relative to hRT + control ASO (P = 0.0049 and P < 0.0001, respectively, Fig. 6F), and the triple therapy further reduced serum TGFβ1 (P = 0.01, vs. hRT + STAT6 ASO, Fig. 6F).

Finally, we explored the effects of the various treatments on immune function pathways by advanced NanoString analysis in both primary (Fig. 6G) and secondary tumors (Supplementary Fig. S6J). In line with our previous experiment, NanoString analysis revealed that the triple therapy enhanced macrophage and T-cell function, as evidenced by the upregulation of several signature genes of each. We further observed enhanced function in other immune pathways, including innate immunity, cytokines and cytokine receptors, and transporter functions. The only genes that were expressed at reduced levels in primary tumors were those associated with cancer progression (Fig. 6G). Collectively, these findings suggest that triple therapy enhanced the systemic antitumor effect by increasing CD8⁺ T cells, decreasing Tregs, reducing TGF-β1 levels, favoring M1 macrophage polarization and stimulating innate and adaptive immune pathways.

STAT6 has been widely reported to promote tumor progression in a wide variety of cancer types, including colorectal (27–29), breast (12, 28), lung (9, 30), and other cancers (31, 32). STAT6 is most commonly activated by IL4 and IL13 (33), the former of which is reported to be upregulated following irradiation in human carcinoma (34). These cytokines bind to their receptors and activate the JAK/STAT pathway, inducing phosphorylation of STAT6, which results in the translocation of p-STAT6 to the nucleus, followed by the transcription of target genes that are specific for M2 macrophages, such as Mrc1 and Fizz1 (35, 36). The mechanisms governing how macrophage polarization is fine-tuned by STAT6 have been extensively explored (37, 38). An example of this is how KLF4, upon activation by STAT6, inhibits the HIF1α/NF-κB pathway, which plays an important role in the activation of M1 macrophages (39). Another is how acetylation of Stat6, mediated by TRIM24, can compromise the transcriptional activity of M2 genes and thus restrains macrophage M2 polarization and potentiates antitumor immunity (40). STAT6 acts as a key transcription factor in shifting the immune system toward a more humoral T_H2 state, in contrast with the more cytotoxic T_H1 response, and, as such, broadly favors tumor progression (33, 41). Conversely, genetic absence of Stat6 in mice has been reported to confer robust resilience to a variety of cancers, including mammary adenocarcinoma (15, 17), prostate cancer (16), and colorectal adenocarcinoma (14). This resistance does not appear to come with any serious drawbacks. Stat6^−/− mice are largely indistinguishable from their wild-type littermates and appear to possess normal levels of each lymphocyte subset (42). The only phenotype of note for Stat6^−/− mice is a shift toward neutrophilia and away from eosinophilia (43), a predisposition to type I inflammation (44) and difficulty resolving it (45). Given the impressive protective effects of STAT6 deficiency and apparent lack of drawbacks, numerous efforts have aimed at inhibiting the STAT6 pathway to inhibit cancer (12, 27, 28, 30–32).

Our study builds upon these findings by showing that STAT6 blockade with an ASO could reduce the protumoral “rebound” that often occurs in the wake of RT (46). We confirmed previous findings that hRT, absent further intervention, induced STAT6 expression and led to higher percentages of M2 macrophages and reduced M1/M2 ratios. This could be circumvented through inhibition of STAT6. Our results indicate that STAT6 inhibition, in association with hRT, improves control of both local and distant tumors. On the basis of our experimental data, our working model (Fig. 7) is that blocking STAT6 inhibits M2 macrophage polarization, thereby favoring M1 polarization and activity. This is evidenced by our transcriptional profiling, which showed an elevation of M1-associated genes and a concordant decrease in M2-associated genes, and flow cytometric profiling of macrophages isolated from the tumors and spleens of mice treated with STAT6 ASO. M2 macrophages are well-documented as being broadly protumor, with M1 macrophages being antitumor, and their induction has been repeatedly implicated as the culprit underlying STAT6’s pro-tumoral effects (9, 12, 30). Thus, this M2-to-M1 population shift deals a double-blow to cancer: it eliminates the tumor-promoting aid of M2 TAMs and reprograms macrophages to a pro-inflammatory, antigen-presenting M1 phenotype that activates cytotoxic T cells. When paired with RT, this creates a one-two hit scenario in which radiation induces tumor destruction and inflammation, and antitumor responses, tilted toward inflammation and away from quiescent homeostasis by the STAT6 ASO, becomes awakened. The effects of this robust antitumor response extend beyond the initial site of radiation, with the tissue damage from the irradiation acting as an in situ vaccine that releases tumor neoantigens and danger signals that, amplified by the M1 macrophages, engage the immune system to seek out and systemically eradicate the tumor (i.e., the abscopal effect; ref. 5). In agreement with this model, we observed that STAT6 ASO + hRT increased the total number of CD8⁺ T cells and IFNγ⁺CD8⁺ T cells in both primary and secondary tumors. NanoString pathway analysis showed that transcriptional pathways, indicative of increased T-cell function, T_H1 activity, and decreased exhaustion, were upregulated in the secondary tumor. The addition of PD-1 blockade further enhanced these systemic antitumor effects, suggesting that the triple combination of hRT + anti–PD-1 + STAT6 ASO may represent an alternative approach for patients with metastatic NSCLC.

Other factors, including the abundance of Tregs and levels of the suppressive cytokine TGFβ, have also been shown to dictate the fate of TAMs (47). We found increased Foxp3⁺ Tregs after hRT, which were decreased after treatment with hRT + STAT6 ASO, and significantly lower serum TGFβ1 in the hRT + STAT6 ASO ± anti–PD-1 treatment groups. These findings, in tandem with the heightened T_H1 signature we detected via NanoString, concur with other reports showing that elevated TGFβ blocks the differentiation of naïve T cells into T_H1 effector cells, while promoting their maturation into Tregs (48). M2 macrophages also drive tumor cell invasion and metastases by expressing matrix metalloproteinases, cathepsin, urokinase plasminogen activator, and matrix-remodeling enzymes, which facilitate tumor cell escape (47). In the current study, we found that the STAT6 ASO, with or without hRT or anti–PD-1, led to significant decreases in lung metastases in the aggressively growing 344SQ-R model, suggesting that STAT6 inhibition also limits tumor metastasis.

To conclude, our study provides robust evidence that inhibition of STAT6 and hRT combines to promote an effective antitumor immune response that controls tumor growth and extends survival in a murine lung cancer model. This response is most likely driven by the preferential reprogramming of macrophages away from the M2 phenotype, thereby selectively favoring M1 polarization and activity. Using an ASO has the advantage over a small-molecular inhibitor because of better target specificity. This is a notable advantage, given the potential and controversy of blanket targeting of STAT family members in cancer (24). Considering the role STAT6 plays in multiple cancers, future studies will seek to extend this mechanism to other solid tumor types, such as breast, liver, pancreatic, and colorectal cancers. Also worth consideration is the potential of the STAT6 ASO to be combined with other ICIs, such as anti–CTLA-4, anti-TIM3, and anti-TIGIT therapies, the latter two of which are currently under investigation with RT (49, 50).

H.B. Barsoumian reports nonfinancial support from Ionis Pharmaceuticals during the conduct of the study. H. Maazi reports employment with IONIS Pharmaceuticals. A.S. Revenko reports personal fees from IONIS Pharmaceuticals outside the submitted work. M.A. Cortez reports nonfinancial support from IONIS during the conduct of the study. J.W. Welsh reports nonfinancial support from Ionis Pharmaceuticals and grants from NIH during the conduct of the study; and other support from GlaxoSmithKline, Bristol Meyers Squibb, Merck, Nanobiotix, RefleXion, Alkermes, Artidis, Mavu Pharma, Takeda, Varian, Checkmate Pharmaceuticals, Legion Healthcare Partners, RefleXion Medical, MolecularMatch, Merck, AstraZeneca, Aileron Therapeutics, OncoResponse, Checkmate Pharmaceuticals, Mavu Pharma, Alpine Immune Sciences, Ventana Medical Systems, Nanobiotix, China Medical Tribune, GI Innovation, Genentech, and Nanorobotics outside the submitted work. No disclosures were reported by the other authors.

K. He: Data curation, software, formal analysis, investigation, visualization, writing–original draft. H.B. Barsoumian: Supervision, validation, investigation, writing–review and editing. N. Puebla-Osorio: Supervision, validation, investigation, methodology, writing–review and editing. Y. Hu: Validation, investigation, writing–review and editing. D. Sezen: Investigation, visualization, writing–review and editing. M.D. Wasley: Investigation, methodology. G. Bertolet: Writing–review and editing. J. Zhang: Visualization, methodology. C. Leuschner: Writing–review and editing. L. Yang: Writing–review and editing. C.S.K. Leyton: Investigation, writing–review and editing. N.W. Fowlkes: Validation, investigation, methodology. M.M. Green: Investigation, methodology. L. Hettrick: Investigation, writing–review and editing. D. Chen: Writing–review and editing. F. Masropour: Writing–review and editing. M. Gu: Supervision. H. Maazi: Supervision, writing–review and editing. A.S. Revenko: Supervision, writing–review and editing. M.A. Cortez: Supervision, writing–review and editing. J.W. Welsh: Conceptualization, resources, supervision, writing–review and editing.

This study received financial support from Cancer Center Support (Core) grant P30 CA016672 from the National Cancer Institute, NIH, to the University of Texas MD Anderson Cancer Center. The authors thank Ionis Pharmaceuticals for providing control ASO and STAT6 ASO drugs. The authors also thank the substantial support from Yi Sun and Jinming Yu.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.