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Cancer-specific type-I interferon receptor signaling promotes cancer stemness and effector CD8+ T-cell exhaustion

ABSTRACT Type-I interferon (IFN-I) signaling is critical to maintaining antigen-presenting cell function for anti-tumor immunity. However, recent studies have suggested that IFN-I signaling may also contribute to more aggressive phenotypes, raising the possibility that IFN-I downstream signaling in cancer and myeloid cells may exert dichotomous functions.We analyzed the clinicopathologic correlation of cancer-specific IFN-I activation in 195 head and neck squamous cell carcinoma patients. We also characterized the immune impact of IFN-I receptor (IFNAR1)-deficiency in syngeneic tumor models using biochemistry, flow cytometry, and single-cell RNA-Seq. We stained HNSCC tissue microarrays with a sensitive IFN-I downstream signaling activation marker, MX1, and quantitated cancer cell-specific MX1 staining. Kaplan-Meier analysis revealed that MX1-high tumors exhibited worse survival, a phenotype that depends on the number of CD8+ intratumoral T-cells. We found that cancer-specific IFNAR1 engagement promotes cancer stemness and higher expression levels of suppressive immune checkpoint receptor ligands in cancer-derived exosomes. Notably, mice bearing Ifnar1-deficient tumors exhibited lower tumor burden, increased T-cell infiltration, reduced exhausted CD4+PD1high T-cells, and increased effector population CD8+IFN-γ+ T-cells. Then, we performed single-cell RNA-sequencing and discovered that cancer-specific IFN-I signaling not only restricts effector cells expansion but also dampens their functional fitness.The beneficial role of IFN-I activation is largely dependent on the myeloid compartment. Cancer-specific IFN-I receptor engagement promotes cancer stemness and the release of cancer-derived exosomes with high expression levels of immune checkpoint receptor ligands. Cancer-specific IFN-I activation is associated with poor immunogenicity and worse clinical outcomes in HNSCC.


Introduction:
As immune checkpoint blockade (ICB) is being moved into the first-line setting for cancer treatment, co-targeting resistance mechanisms have become central to the outcomes of immunotherapies. Conceptually, there are two broad resistance mechanisms. The first mechanism is that tumor and myeloid cells upregulate the expression of the inhibitory immune checkpoint receptor ligands, such as programmed cell death ligand 1 (PD-L1), to dampen the activation of effector T-cells. The second class of resistance mechanisms involves the lack of immune priming signals with minimal inflammatory infiltration in the tumor stroma. The first class of mechanisms can be efficiently targeted by leveraging combinatorial ICBs. However, most tumors show features that fall into the second category. The induction of type-I interferon (IFN-I) signaling has been shown as a powerful priming approach to enhance antigenpresenting cells maturation and effector expansion, which sensitizes hypoimmunogenic cold tumors to ICB in several preclinical cancer models. [1][2][3] According to data from the Centers for Disease Control and Prevention, human papillomavirus (HPV) + Head and Neck Squamous Cell Carcinoma (HNSCC) was one of the only five cancer types that increased from 1975 to 2009; and the increase is predicted to continue until at least the year 2060. 4,5 Notably, in contrast to the generally more favorable response profiles to chemotherapy among patients with HPV + tumors, the Hazard Ratios for nivolumab were almost identical between the HPV + and HPV − groups despite the presence of viral epitopes. 6,7 Similarly, ICB showed little efficacy over standard-of-care in patients with p16 + tumors. 8 Our recent study found that HPV potently suppresses IFN-I production from HNSCC cells and encourages cancer immune escape. 9 In preclinical models, we and others engineered IFN-I-inducing vaccines targeting the HPV16 E6/E7 epitopes and showed that IFN-I is essential to condition the tumor microenvironment for a better response of ICB-induced tumor antigen-specific cytotoxic T-cell immunity. 1,10,11 Not surprisingly, IFN-I-inducing agents have entered clinical trials, including agonists for a central adaptor molecule stimulator of interferon response cGAMP interactor 1 (STING1), which was pivotal for radiotherapy-mediated priming benefits. 3 There are three known human STING1 alleles, which showed different sensitivities to its physiological ligand cGAMP. Novel cyclic di-nucleotides have been engineered to activate all known STING1 alleles. However, a substantial subset of patients remains resistant to even these broadly activating cyclic di-nucleotides. 12 In addition, discrepancies are present in studies assessing the role of IFN-I in cancer outcomes. For example, genome instability creates micronuclei whose rupture activates the STING1-IFN-I pathway. This encourages cancer metastasis and genetic suppression of chromosomal instability delays metastasis even in highly aneuploid tumor mouse models. 13 Higher expression levels of the Bloom Syndrome RecQ-like Helicase (BLM) and exonuclease 1 (EXO1), which facilitate the generation of STING1inducing DNA fragments, are also associated with poor prognosis in response to radiotherapy. 14 Although the activation of the IFN-I pathway is essential for myeloid M1-like polarization and cross-priming of T-cells, it is equally important to understand the mechanisms underpinning the discrepancies in these different studies. Unlike the type II and type III interferons, whose production is restricted to a small collection of cell types, IFN-I is highly evolutionarily conserved, and almost all normal cell types express IFN-I induction machinery and its receptor IFNAR1. The activation of a spectrum of pattern recognition receptors, including the Toll-like receptors (TLRs), RNA sensors such as DExD/H-Box Helicase 58 (DDX58, aka Retinoic Acid-inducible Gene I or RIG-I), Interferon Induced with Helicase C Domain 1 (IFIH1, aka Melanoma Differentiation-Associated Protein 5 or MDA5), or DNA sensor cyclic GMP-AMP Synthase (cGAS), leads to the phosphorylation of IRF3 and NF-κB. Nuclear phospho-IRF3 and phospho-p65 form an enhanceosome to drive the generation of IFN-I, which includes 13 subtypes of IFN-α, IFN-β, IFN-ω, IFN-ϵ, and IFN-κ. IFN-I functions in an autocrine or paracrine fashion to engage its receptor constituted by IFNAR1 and IFNAR2 on the plasma membrane. Upon activation, tyrosine kinases Tyrosine Kinase 2 (TYK2) and Janus Kinase 1 (JAK1) are phosphorylated, which leads to the phosphorylation of the Signal Transducers and Activators of Transcription (STAT)1 and STAT2. Within the IFNAR1 transcriptional program, MX Dynamin Like GTPase 1 (MX1) is a transgene that is specifically induced by IFN-I and used as a sensitive surrogate marker for IFNAR1 signaling.
Thus, the generation of IFN-I and its downstream signaling upon binding to IFNAR1 are two separate events for cancer cells. The secreted IFN-I may function in a paracrine fashion to stimulate the myeloid compartment, which drives most of the observed benefits. Notably, we and others have shown that multiple solid tumors including HPV − and HPV + HNSCC show deficiencies in the IFN-I induction pathway to evade innate immune detection. However, their IFN-I downstream signaling pathways are often intact, which can be also activated through the Epidermal Growth Factor Receptor (EGFR) pathway. 15 Although IFNAR1 downstream signaling activation in myeloid cells enhances its antigen processing efficiency and cross-priming of CD8 + T-cells, the role of cancer cellspecific IFNAR1 downstream signaling in regulating the tumor immune microenvironment remains unclear. MX1 staining on formalin fixed paraffin-embedded tissues has been well established as a sensitive marker for IFNAR1 signaling activation. 16,17 In this study, MX1 is used as a surrogate marker for IFNAR1 signaling activation. MX1 expression is stimulated specifically by type-I interferon signaling and does not respond to other cytokines such as IL-1 or TNF-α. 18,19 The mechanism by which IFN-I signaling leads to MX1 induction is also well characterized, involving transcriptional regulation through the JAK/ STAT pathway, as with other interferon-stimulated genes. 20 In this study, we performed a cohort analysis of 195 HNSCC patients to assess the prognostic significance of IFNAR1 signaling activation in cancer cells. We also characterized the impact of the suppression of the IFNAR1 pathway in cancer cells upon cancer stemness and intra-tumoral immune infiltration using IFNAR1-deficient murine HNSCC models.

Clinical samples and tissue microarray
Patients with previously untreated HNSCC were recruited by the University of Michigan Head and Neck Cancer Specialized Program of Research Excellence (SPORE) between 2008 to 2012 for a longitudinal study. The patient demographic information and clinical characteristics are summarized in Table 1. The tumor tissues from 218 patients, with a median follow-up of 60 months, were included in tissue microarrays (TMAs). For each tumor, 3 representative 5-μm cores, identified by a head and neck pathologist, were included, each of which contained tumor tissue and surrounding stroma. TMAs were stained with anti-MX1 antibody (1:600; Cell Signaling Technology, catalog #37849S). The secondary antibody was biotinylated goat antirabbit antibody (1:400, Vectastain ABC HRP Kit, PK-4001, Vector Laboratories). Immunohistochemical (IHC) staining intensity was quantitated in tumor tissue for each core by selecting a region of interest using Aperio ImageScope, followed by quantification. IHC scores were averaged from the 3 cores, and those that were missing or had insufficient tumor parenchyma were excluded from subsequent analysis. In total, MX1 IHC scores were available for 195 patients. The investigators who scored the TMAs were blinded from the clinical information. In experiments involving multivariate Cox regression modeling to control for CD4 + and CD8 + T-cells, immunohistochemistry was performed for CD4 and CD8 followed by an enumeration of intratumoral CD4 + and CD8 + cell numbers for each TMA, in triplicate, by trained observers blinded to the clinical information. The CD4 and CD8 staining of the TMA has been reported. 21

Statistics
Univariate Cox linear regression modeling was used to explore the association between cancer-specific MX1 expression in TMAs and patient clinical variables. The association between MX1 IHC scores and patient survival was conducted using both univariate and multivariate Cox regression models as indicated in Table 2. To dichotomize  tumors into MX1-low and MX1-high groups, a threshold  score was estimated by the change point in a Cox regression model, generating a change point cutoff score of 41. Statistical significance in survival probability between MX1low and MX1-high TMAs was evaluated by Kaplan-Meier survival curves and a log-rank test. As a secondary method, we compared overall survival (OS) and recurrence-free time (RFT) in patients exhibiting MX1 scores in the highest quartile (MX1 score ≥ 31.79) vs. patients with lower scores. Statistical analysis between two independent groups was made using unpaired, two-tailed Student's t-tests. Tumor burden between groups was compared using the generalized estimating equation model. Statistical significance is indicated in all figures according to the following scale: *p < .05; **p < .01; ***p < .001; and ****p < .0001. All graphs are presented as the mean ± SEM. To test the correlation between gene expression levels measured by RNA-seq among 520 TCGA HNSCC patients, we calculated their Spearman correlations and computed corresponding p values using the R package stats.

Animals
Eight-week-old C57BL/6 J (strain 000664) mice were purchased from The Jackson Laboratory and housed in specific pathogen-free conditions in a temperature-and lightcontrolled facility. To enhance scientific rigor, and because sex is not a known prognostic variable for HNSCC, both sexes were used. One million empty vector (EV-MOC2-E6 /E7) control or shIfnar1-MOC2-E6/E7 cells were implanted subcutaneously in the flank. Seven days after tumor implantation, tumors were measured every 2-3 days and tumor volume calculated according to the formula 1/2 (length × width 2 ). Tumor weight was measured after animals were sacrificed. Mice were euthanized at the time points indicated in the figure legends, followed by tumor, spleen, and TIL processing for the subsequent analyses.

Gene expression qPCR
Total RNA was extracted using QIAshredder and an RNeasy Plus Mini Kit (catalog 79654 and 74134, respectively; Qiagen). A Nanodrop Spectrophotometer (Thermo Fisher Scientific) was used to determine RNA concentrations. RNA was reversetranscribed into cDNA using High-Capacity cDNA Reverse Transcription Kit and RNase inhibitor (4368814 and N8080119, Applied Biosystems). Primers were obtained from Integrated DNA Technologies and included: Isg54 forward 5′-

Cancer-derived exosome isolation
Cancer-derived exosomes were isolated by using the Total Exosome Isolation Kit (catalog 4478359, invitrogen). The MOC2-E6/E7-EV, MOC2-E6/E7-shIfnar1, NOOC1-EV and NOOC1-shIfnar1 cells were seeded into 10 cm plate with 10 ml culture media. After 48 hours culture, the supernatant was collected and cetrifuged at 2000 × g for 30 minutes to remove the cells and debris. The culture media was mixed with reagent and incubated at 4°C overnight prior to centrifugation at 10,000 × g for 1 hour at 4°C. The pellets at the bottom were resuspended in 120 µl RIPA buffer containing proteinase and phosphatase inhibitors. Equal amounts of exosomes were mixed with 4× NuPAGE LDS Sample Buffer (catalog NP0007, invitrogen) and boiled for 5 minutes at 95°C. The samples were analyzed by SDS-PAGE.

AlamarBlue assay
Empty vector control or shIfnar1 MOC2-E6/E7 cells were seeded at a density of 500 cells/well in flat black bottom 96well microplates (3904, Corning). Every 24 hours from day 1 to day 4, wells were supplemented with 10% alamarBlue (DAL1025, Invitrogen), and the plate was subsequently incubated at 37°C for 4 hours. The fluorescence intensity (excitation 560 nm, emission 590 nm) of these wells was measured using a Biotek plate reader and Gen5 program (version 2.09), and five replicates per group were simultaneously analyzed.

ALDH assay
This assay was performed using the ALDEFLUOR™ Kit (01700, STEMCELL Technologies). In part, empty vector control or shIFNAR1 MOC2-E6/E7 tumor cells and in vitro lines were resuspended into ALDEFLUOR™ Assay Buffer (01701, STEMCELL Technologies) at a working concentration of 1 × 10 5 . Following ALDEFLUOR staining, cells were stained with anti-CD44, and analyzed on a Beckman Coulter CytoFLEX flow cytometer.

Single-cell immune profiling
Whole tumor lysate was treated with ACK Lysing Buffer (A1049201, ThermoFisher), then processed through an EasySep Dead Cell Removal (Annexin V) Kit (17899, STEMCELL Technologies). Cell suspension was submitted in 1× PBS + 0.04% BSA for 10× Genomics 3ʹ-single cell processing and RNA-Seq at a depth of at least 30,000 reads per cell. Libraries were prepared on 10× Chromium and sequencing conducted on Illumina NovaSeq 6000. We utilized the following criteria to select high-quality transcriptomes: (i) the qualified cells must have a unique feature counts between 200 and 7,500; (ii) the mitochondrial reads must be fewer than 10%; (iii) the transcriptomes must have unique molecular identifiers counts over 500. We integrated 12,907 high-quality transcriptomes for downstream analyses. We utilized the sctransform tool to remove the library size effect and the mutual nearest neighbors algorithm to remove the batch effect for final integration. We selected the top 3,000 genes with the highest cell-to -cell variation as well as features to stabilize the immune population structure. We obtained the top 50 principal components from the integrated data set. To characterize the differential gene expression for CD8 + T-cells between conditions, we fitted a generalized linear mixed models on counts using the R package Muscat. 22

High MX1 protein expression levels in cancer cells were associated with poor prognosis in HNSCC patients
Separate from the pathways that induce the production of IFN-I, IFN-I downstream signaling is mediated by its binding with the receptor IFNAR1. Although the expression levels of IFNAR1 do not directly correlate with IFN-I signaling activation (Supplementary Figure 1), IFNAR1 engagement launches a large transcriptional program characterized by the induction of MX1 metagene and other interferon-stimulated genes (Figure 1a). To validate MX1 as an IFN-I-induced metagene in HNSCC, we first performed Spearman correlation analysis using 520 specimens available at the TCGA database. We found that the expression levels of MX1 were significantly positively correlated with those of ISG15 (Spearman ρ = 0.76; p < .0001), IFIT2 (Spearman ρ = 0.76; p < .0001), CXCL9 (Spearman ρ = 0.48; p < .0001), CXCL10 (Spearman ρ = 0.64; p < .0001), and OASL (Spearman ρ = 0.71; p < .0001) (Figure 1b-f). Thus, we then stained an internal HNSCC cohort with anti-MX1 antibody. Based on our recent data and assuming the same effect size, we performed a power analysis using the R-package LogRankPower, we found that the power for 200 patients was 83.2% at α = 0.05. Thus, tissue microarrays (TMAs) were generated utilizing specimens from 195 patients with HNSCC. The majority of specimens were collected from patients with advanced-stage disease (15% stage 3; 65% stage 4) and were relatively representative of the natural distribution across disease sites, including the larynx (17%), oral cavity (46%), oropharynx (30%), and hypopharynx/other (7%). Other parameters evaluated in this patient cohort, summarized in Table 1, included age, gender, adult comorbidity evaluation (ACE) score, HPV status, and history or present use of tobacco products and alcohol consumption. To assess the prognostic value of cancer cellspecific IFNAR1 downstream signaling, we analyzed MX1 protein levels by IHC staining of the TMAs. MX1 exhibited a diffuse cytoplasmic staining pattern that was highly variable in density among different tumors. MX1 was also stained in the infiltrating immune cells, as expected. To specifically examine the role of cancer-specific IFNAR1 activation, we manually selected tumor parenchyma for 585 cores, with three cores representing one tumor, prior to quantitation (Figure 1g). Cancer-specific MX1 staining scores were quantitated using Aperio ImageScope, as we previously reported. 9 These results supported the heterogeneous nature of MX1 distribution, with descriptive statistics summarized in Supplementary Table 1.
To analyze the association with relevant clinical variables, MX1 scores were assessed in both continuous form and a dichotomized form wherein tumors were divided into MX1-high and MX1-low groups using the change point threshold in Cox regression modeling, which generated a cutoff score of 41. No significant association was observed between MX1 scores and disease site or nodal metastasis, although a trend existed between the MX1 scores and advanced cancer stage (p = .09) (Supplementary Figure 2ac). We next examined the impact of cancer cell-specific MX1 protein expression on HNSCC patient overall survival (OS). The Kaplan-Meier survival curves were compared between MX1-high and MX1-low groups using a log-rank test, which revealed that MX1-high staining was significantly correlated with worse overall survival (*p = .02; Figure 1h). Utilizing a univariable Cox regression model where MX1 is the single predictor of outcome, we found that the MX1-high group was correlated with significantly worse OS (*p = .02; Table 2. We also built a multivariate Cox regression model controlling for age, clinical stage, disease site, ACE scores, HPV status, smoking, and CD4 + T-cells among tumor-infiltrating leukocytes (TILs). We found that MX1-high staining remained correlated with significantly worse OS (*p = .04; Table 2). Notably, using a multivariate Cox regression model that controlled for the same aforementioned clinical and social factors but also controlled for CD8 + T-cells instead of CD4 + T-cells among TILs in this cohort of HNSCC specimens, MX1-high tumors were no longer associated with worse prognosis (p = .42; Table 2), suggesting an interaction between high cancer-specific MX1 expression levels and CD8 + T-cells which impacted patient outcomes.
To substantiate the prognostic importance of tumorspecific MX1 expression, we also performed clinical analyses using MX1 scores in the highest quartile (MX1 score ≥ 31.79) vs. patients with lower scores. The Kaplan-Meier survival curves were compared between patients in the MX1-highest 25% and MX1-lowest 75% groups using a log-rank test, which revealed that patients in the highest quartile tended to exhibit worse overall survival and had   Figure 3a-b). Then, we controlled patient age, clinical stage, disease site, comorbidities, and T-cell infiltration in a multivariate model and compared the Kaplan-Meier survival curves. We found a similar trend where MX1-highest 25% group showed a worse prognosis ( Supplementary Figure 4a-b). To summarize our findings, we first utilized a univariate model and found that patients with MX1 scores in the highest quartile tended to exhibit worse overall survival (p = .07) and decreased recurrencefree survival (p = .056; Table 3). Then, we built a multivariate Cox model controlling for age, clinical stage, disease site, ACE scores, HPV status, smoking, and CD4 + T-cells. We found that high protein levels of MX1 in cancer cells were associated with significantly worse survival. Notably, the prognostic value of tumor-specific MX1 expression was completely lost when we controlled for CD8 + T-cells (Table 3, Supplementary Figure 5a), in agreement with the results from the dichotomous MX1 expression levels grading model. These results suggest that the clinical impact of tumor-specific MX1 expression depends on CD8 + T-cells.

Loss of IFN-I signaling in HNSCC cells inhibits cancerderived exosomal checkpoint receptor ligands expression and reduces tumor burden
To model the impact of the loss of tumor-specific IFN-I downstream signaling upon the CD8 + T-cells and the tumor immune microenvironment, we first utilized an established MOC2-E6/E7 syngeneic HNSCC model. 10 This model does not produce IFN-I upon transfection with STING1 agonists, 9 which allows us to assess tumor response to IFN-I only from the tumor microenvironment.
We engineered a derivative model in which the IFN-I receptor Ifnar1 is defective (MOC2-E6/E7-shIfnar1) (Figure 2a). A deficiency of Ifnar1 resulted in abolished Mx1 gene expression in response to recombinant Ifn-β treatment (Figure 2b). In agreement, Ifnar1-deficient MOC2-E6/E7 cells also exhibited significantly reduced expression levels of two representative ISGs, Isg54 and Isg15 (Figure 2c-d). Recently, we generated a new HNSCC murine model that bears over 90% similarity to human tobacco-associated cancers, NOOC1. 23 To validate our findings, we generated Ifnar1-deficient NOOC1 cells (Figure 2e). We found that a defect in Ifnar1 expression resulted in compromised expression of Mx1, Isg54, and Isg15 in response to Ifn-β (Figure 2f-h).
Previous evidence showed that IFN-I promotes the expression of PD-L1 on cancer cell membrane and promotes resistance to anti-PD-1 ICB. 24 Exosomal checkpoint ligand-mediated inhibition of effector T-cells correlates with HNSCC progression. 25,26 However, it is unclear whether Ifnar1 signaling in cancer cells modulates the content of cancer-derived exosomes. We purified CD63 + cancer-derived exosomes from empty vector control as well as Ifnar1-deficient MOC2-E6/E7 and NOOC1 cells. We found that the loss of Ifnar1 signaling abrogated exosomal expression of immune checkpoint receptor ligands PD-L1 and Galectin-9 in MOC2-E6/E7 cells (Figure 2i). Loss of Ifnar1 signaling did not affect exosomal PD-L1 expression but substantially reduced the exosomal Galectin-9 levels in NOOC1 cells (Figure 2j). Checkpoint ligands represent a critical mechanism driving cancer resistance to immune killing. 27 To assess the functional impact of specific disruption of Ifnar1 signaling engagement in cancer cells, we next sought to characterize the immune microenvironment in Ifnar1-deficient tumors. As a control, we showed that impaired downstream IFN-I signaling did not affect cell proliferation in vitro (Figure 2k). Interestingly, when we implanted empty vector control and Ifnar1-deficient MOC2-E6/E7 cells into C57BL/6 mice, we observed a significant reduction in tumor growth and improved survival (**p = .0019) in the Ifnar1-deficient tumor group (Figure 2l-n).

Cancer-specific IFNAR1 engagement promotes cancer stemness and effector exhaustion
HNSCC stem cells have been demonstrated to express higher levels of PD-L1 and promote resistance to immune killing. 28 Based on our findings that Ifnar1 signaling maintains exosomal  immune checkpoint ligands expression and growth advantage in vivo (Figure 2), we next specifically assessed the impact of Ifnar1 signaling on cancer stemness. We observed that Ifnar1 deficiency reduced the fraction of CD44 high ALDH high cells showing features of stemness (Figure 3a-b). To comprehensively profile cancer stemness-associated markers, we employed two high-fidelity models, including MOC2-E6/E7 and NOOC1. In agreement with our flow cytometry findings, loss of Ifnar1 resulted in a substantial reduction of CD44 expression in both models (Figure 3c-d). In addition, we found that Ifnar1 signaling in cancer cells maintained high levels of phosphorylated Akt, which is essential to maintain cancer stemness (Figure 3c-d). 29,30 Indeed, we examined a recently established cancer stemness marker for HNSCC, BMI-1. 31 We found that Ifnar1 signaling deficiency resulted in a decrease in the levels of BMI-1 in MOC2-E6/E7 and NOOC1 cells (Figure 3c-d). The signaling competency required for the generation of IFN-Is is independent of the Ifnar1 signaling downstream of IFN-Is binding to their receptor. Indeed, the Ifnar1 deficiency only affected the downstream cancer stemness pathway and did not impact the phosphorylation of p65 and IRF3 (Figure 3c-d), which are enhanceosome components for IFN-I genes transcription. To validate these findings in vivo, we homogenized established empty vector control and Ifnar1-deficient MOC2-E6/E7 tumors and immunoblotted CD44. We found that Ifnar1 signaling deficiency resulted in substantial suppression of CD44 (Figure 3e). Then, we examined the immunohistochemical staining of CD44 in the HNSCC TMAs. We identified a significant positive correlation between the scores of CD44 and those of MX1 in oropharyngeal squamous cell carcinomas (Spearman ρ = 0.4, p = .003) (Supplementary Figure 5b).

Cancer-specific IFN-I downstream signaling impacts the global immune landscape
To directly assess the impact of cancer-specific Ifnar1 signaling activation upon the tumor immune microenvironment, we separated the TILs through Ficoll-Paque gradient centrifugation and identified an enhancement in CD4 + and CD8 + T-cell infiltration in Ifnar1-deficient tumors (Figure 4a-d). Then, we compared the functional status of intratumoral T-cells from empty vector control and Ifnar1-deficient tumors. Notably, we found that a defect in cancer cell-specific IFN-I downstream signaling significantly reduced the terminally exhausted effector T-cell subsets, including CD4 + PD1 high T-cells (Figure 4ef). 32 To characterize the functional impact of such changes, we next stimulated TILs with PMA/Ionomycin and quantitated intracellular IFN-γ. We found that CD8 + T-cells isolated from Ifnar1-deficient tumors expressed higher levels of IFN-γ (Figure 4g-h), consistent with its reduced tumor burden. Such changes were specific to the tumor microenvironment as no apparent changes were observed from the lymphocytes separated from spleens ( Supplementary Fig. 6).
Thus, using parallel flow cytometry and single-cell analysis, we found that the activation of downstream IFN-I signaling in cancer cells not only led to lymphoid contraction within the tumors but caused dysfunction of CD8 + T-cells. To delineate the impact of cancer-intrinsic IFN-I activation upon the differentiation of CD8 + T-cells, we separated the CD8 + subsets (clusters 6 and 18) and performed Potential of Heat-diffusion for Affinity-based Transition Embedding (PHATE) analysis, which revealed the functional development pathways of CD8 + T-cells. We found that the CD8 + T-cells in empty vector control and Ifnar1-deficient tumors assumed divergent functional commitments. MOC2 has been established as a hypoimmunogenic HNSCC model that is refractory to ICBs. 33,34 In agreement, we found that the CD8 + T-cells in control tumors largely committed to a terminal exhaustion phenotype with high expression levels of Pd-1 and Tim-3. These cells were low on activation markers such as Cd28 and Cd69 as well as stemness markers Tcf7 and Slamf6. In contrast, increased frequency of CD8 + T-cells in Ifnar1-deficient tumors expressed high levels of Cxcr3, which is rapidly induced upon activation of Th1 effectors. 35 Notably, most of these CD8 + T-cells in Ifnar1-deficient tumors preserved stemness features, which are critical in maintaining cancer immunogenicity. 36,37 Then, we utilized the R-package muscat to identify novel differentially expressed genes between the CD8 + T-cells separated from the two groups (Supplementary Table 3). In agreement with the enhanced effector function in the CD8 + T-cells from Ifnar1-deficient tumors, we observed higher expression levels of Cxcr3, which is expressed by activated Th1 T-cells. 35 In addition, the CD8 + T-cells from Ifnar1-deficient tumors also expressed significantly higher levels of Stat5b, which is essential for effector maintenance and proliferation 38,39 (Supplementary  Table 3). Glutaminolysis has been shown to be activated in Th1 cells to support their effector function. [40][41][42] Interestingly, we found that the terminally exhausted CD8 + T-cells in control tumors largely lost the expression of a glutamine transporter Slc38a2. However, Slc38a2 was highly expressed in CD8 + T-cells that also expressed a stemness marker Tcf7 (Figure 5d).

Discussion
Progress has been made toward understanding cancer resistance to ICB. An optimal response to immunotherapy requires the existance of a pool of tumor-specific T-cells prior to e1997385-10 treatment. STING-mediated IFN-I activation underpins the success of multiple innate immune priming strategies that aim to enrich the tumor-specific T-cell pool. Irradiation, inhibition of DNA damage repair, and direct stimulation with cyclic dinucleotides are utilized to trigger DNA-induced STING1 activation. However, the efficacy of this broad class of innate immune priming treatments is challenged by unknown mechanisms that dampen tumor sensitivity to STING1 stimulation. The main focus on the immune remodeling effect of STING1 agonists had been on the M1-like repolarization of myeloid cells. This study aims to understand whether cancer-specific IFN-I downstream signaling contributes to immunosuppression. We first assessed whether cancer intrinsic IFNAR1 signaling is clinically significant for patients with HNSCC. Utilizing univariate and multivariate Cox regression models, we found that high MX1 protein levels in cancer cells were associated with worse overall survival. MX1 is a sensitive surrogate marker for IFNAR1 downstream signaling activation, suggesting that sustained IFNAR1 engagement was an unfavorable prognosticator in HNSCC. Notably, the association between cancer-specific MX1 expression and worse outcomes is dependent on the number of intra-tumoral CD8 + T-cells. A caveat in assessing TILs in TMAs is that the small cores may not represent tumor stromal heterogeneity. To address this potential problem, we sampled three cores for each tumor and also validated the link between cancerspecific IFN-I signaling and intra-tumoral CD8 + T-cells using well-defined preclinical models. Future validation using an   independent cohort with other ISGs would also be helpful to characterize further the role of cancer-specific IFN-I activation in patient outcomes.
The current IFN-I agonists were administered to globally activate IFNAR1 signaling in both immune cells and other cell types, including cancer cells. The beneficial effect of STING1-IFN-I activation is dependent on myeloid reprogramming. 3,43 Activation of IFNAR1 signaling in immune cells not only enhances antigen processing, antigen presentation, MHC molecule upregulation but also improves trafficking and recruitment of innate and adaptive immune cells to the otherwise T-celldeficient tumor stroma. However, IFNAR1 activation in cancer cells promotes cancer stemness and potentiates a T-cell exclusion niche. IFN-I stimulation not only makes cancer cells assume stemness features to develop resistance to the immune killing but reprograms the global tumor immune microenvironment. We performed parallel flow cytometry and single-cell RNA-Seq to reveal the divergent myeloid and lymphoid remodeling imposed by cancer-specific IFN-I signaling disruption. We found that Ifnar1-deficient tumors harbor reduced MDSCs and expanded effectors, including CD8 + T-cells, non-Treg CD4 + T-cells, and γδ T-cells. Notably, blocking cancer-specific IFN-I signaling not only expands CD8 + T-cell pool but remodels its differentiation trajectory. We utilized a well-established cold cancer model and indeed found that the majority of the intratumoral CD8 + T-cells have committed to terminal exhaustion with the double expression of Pd-1 and Tim-3. However, Ifnar1-deficient tumors expand Tcf7 + stem-like effector T-cells, which preserve high proliferation potential and responsiveness to ICB. Mechanistically, cancer stem cells in HNSCC are a small yet highly tumorigenic population that selectively express PD-L1 and dampen autologous CD8 + T-cell activation. 28 Thus, cancerintrinsic IFNAR1 signaling activation likely initiates a transcriptional program that is overlapping with the cancer stemness program to dampen the anti-tumor effect of STING1 stimulation.
A strong positive link between chronic inflammation and increased cancer risk had been discovered long before the advent of ICB therapy. In fact, a pathologist Rudolf Virchow speculated that chronic inflammation caused cancer in the year 1863. 44 NF-κB activation is a key event for IFN-I induction. It is frequently activated in HNSCC, 45 and its activation in tumor cells enhances HNSCC invasion and resistance to therapy. [46][47][48] Thus, the duration of immune activation therapy is also likely shaping the evolution of tumor resistance. Most preclinical models for STING1 agonists testing were based on relatively acute administration into implantable subcutaneous tumor models. Chronic STING1 stimulation likely results in sustained NF-κB activation in tumor cells. This pathway encourages transcriptional programs associated with stemness that is associated with a more tolerogenic local immune niche.
To enhance the therapeutic effectiveness and avoid chronic STING1 stimulation, several robust delivery vehicles have been engineered for STING1 agonists. Controlled release of STING1 agonists using a peptide hydrogel significantly extends the survival of tumor-bearing mice compared to treatment with free STING1 agonists treatment alone. 11 When STING1 agonists are delivered using nanoparticles in combination with ICB, tumor-specific CD8 + T-cells are significantly expanded. 10 Similarly, two other delivery systems, including endosomolytic polymersomes nanoparticles and biodegradable polymer acetylated dextran microparticles also enhance the efficacy of STING1. 49,50 Nanoparticles and microparticles are preferably taken up by myeloid cells and protect cargo from rapid degradation. Due to the unfavorable pharmacokinetics property of free cGAMP, the integration of these delivery systems is a highly promising strategy to enhance myeloid response and avoid chronic stimulation of the IFNAR1 signaling in cancer cells.

Conclusions
Overall, to better characterize the mechanisms driving cancer resistance to STING1-inducing immune priming therapies, we separated IFNAR1 signaling in cancer cells from the IFN-I signaling in immune cells. Downstream IFNAR1 signaling activation in cancer cells is associated with poor clinical outcomes. Blocking IFNAR1 signaling in the tumor cells expands stem-like effector T-cells, restricts MDSCs, and reduces tumor burden. Future development of robust IFN-I-inducing formulations is important to rapidly control tumors through myeloid reprograming while avoiding prolonged stimulation of HNSCC cells, which triggers an adaptive mechanism promoting resistance to innate immune priming strategies. was approved by the University of Michigan Institutional Review Board (HUM00113038 and HUM00042189). Informed consent was obtained from all patients enrolled in the study.