Purpose: Antiproliferative, antiviral, and immunomodulatory activities of endogenous type I IFNs (IFN1) prompt the design of recombinant IFN1 for therapeutic purposes. However, most of the designed IFNs exhibited suboptimal therapeutic efficacies against solid tumors. Here, we report evaluation of the in vitro and in vivo antitumorigenic activities of a novel recombinant IFN termed sIFN-I.

Experimental Design: We compared primary and tertiary structures of sIFN-I with its parental human IFNα-2b, as well as affinities of these ligands for IFN1 receptor chains and pharmacokinetics. These IFN1 species were also compared for their ability to induce JAK–STAT signaling and expression of the IFN1-stimulated genes and to elicit antitumorigenic effects. Effects of sIFN-I on tumor angiogenesis and immune infiltration were also tested in transplanted and genetically engineered immunocompetent mouse models.

Results: sIFN-I displayed greater affinity for IFNAR1 (over IFNAR2) chain of the IFN1 receptor and elicited a greater extent of IFN1 signaling and expression of IFN-inducible genes in human cells. Unlike IFNα-2b, sIFN-I induced JAK–STAT signaling in mouse cells and exhibited an extended half-life in mice. Treatment with sIFN-I inhibited intratumoral angiogenesis, increased CD8+ T-cell infiltration, and robustly suppressed growth of transplantable and genetically engineered tumors in immunodeficient and immunocompetent mice.

Conclusions: These findings define sIFN-I as a novel recombinant IFN1 with potent preclinical antitumorigenic effects against solid tumor, thereby prompting the assessment of sIFN-I clinical efficacy in humans. Clin Cancer Res; 23(8); 2038–49. ©2016 AACR.

Translational Relevance

Despite potent antitumorigenic properties of natural and pharmacologic type I IFNs (IFN1), these agents achieved only a limited success in cancer therapy. This article describes the molecular and biological characterization of de novo engineered and highly potent recombinant IFN (sIFN-I), which has evoked massive clinical interest and is currently undergoing clinical trials in patients with solid tumors in Singapore (CTC1300056) and the United States (NCT02464007), as well as patients with HBV in China (2009L04155). Here, we present data obtained in both in vitro and in vivo settings; these data demonstrate that sIFN-I exhibits superior pharmacodynamic and pharmacokinetic characteristics compared with its parental human IFNα-2b species. Furthermore, studies conducted in cells and in animals harboring transplantable and genetically engineered tumor models reveal that sIFN-I evokes potent antitumorigenic effects at least in part by inhibiting stromal angiogenesis and by stimulating antitumor immunity.

Type I IFN (IFN1) family of antiviral cytokines comprises 13 different subtypes of IFNα, as well as IFNβ, IFNϵ, IFNκ, IFNω, etc (1–3). Potent antiproliferative, proapoptotic, antiangiogenic, and immunomodulatory effects of IFN1 prompted their use for anticancer treatment (reviewed in refs. 4, 5). However, after more than 40 years of trials, the use of IFN1 against tumors is limited by the suboptimal ratio between clinical efficacy and the severity of its side effects (6), as well as limited response rate, which is often attributed to the downregulation of IFN1 receptor (7). This heterodimeric receptor complex encompassing the IFNAR1 and IFNAR2 chains mediates all effects of IFN1 on cells (8–10). Levels of IFN1 receptor were indeed shown to correlate with IFN1-induced growth arrest (11) and apoptosis in the tumor samples (12, 13).

The levels of IFN1 receptor on cell surface are largely regulated by the ubiquitin-mediated internalization and degradation of IFNAR1 (10, 14–18). Downregulation of IFNAR1 can be accelerated in some cancers (19–22), thereby limiting the antitumorigenic effects of IFN1. Remarkably, although activation of the JAK–STAT pathway is required for both antiviral and antitumor effects of IFN1, lower receptor density still allows efficient antiviral responses while impeding ability of IFN1 to suppress cell proliferation (23). Schreiber and colleagues have proposed that responses to IFN1 could be classified as “robust” (such as antiviral effects) or “tunable” (such as antiproliferative or proinflammatory), the latter being much more sensitive to receptor density (24). Indeed, high cell-surface receptor density and maximal receptor occupancy by relatively high doses of ligands are required to mount an efficient antiproliferative effect (24, 25).

Furthermore, the affinity of IFN1 subtypes for the extracellular domain of IFNAR1 correlates with the ability of these subtypes to elicit specific antiproliferative effect (26–29). Thus, antitumorigenic efficacy of IFN1 may be optimized by increasing cell-surface receptor density and/or by designing novel recombinant IFN1 species that display a greater affinity for IFNAR1. A number of IFN1 variants were generated and shown to be effective against tumor cells. For example, a mutant derivative of IFNα-2, IFNα-YNS exhibited tight binding to IFNAR1 and elicited potent proapoptotic activity and antiproliferative/antiangiogenesis effects in vivo; this mutant surpassed IFNα-2 in antitumorigenic activity in a breast cancer xenograft (28, 30).

Yet, another approach to increase efficacy of IFN1 treatment is to improve its pharmacokinetics and biological activities. Various efforts in this direction include the use of IFNα-2b-albumin fusion protein (31), antibody armed with IFN1 (32), and pegylation of IFN1 (33). Furthermore, given that many of antitumorigenic effects of IFN1 are mediated by the stromal cells, generation of an elegant transgenic mouse model that expresses human IFNAR1 and IFNAR2 subunits, and can be used for transplantation of human tumors, resulted in improved ability to test the antitumorigenic effects of IFN1 (34).

Here, we characterized antitumorigenic properties of a novel recombinant IFN1 derived from human IFNα-2b and other IFN1 subtypes by mutagenesis and termed “super-compound interferon-I” (sIFN-I). Compared with IFNα-2b, sIFN-I exhibited higher anti-HIV activity in SCID mice reconstituted with human peripheral blood leukocytes (35). Current studies revealed that sIFN-I exhibits increased affinity for IFNAR1 and has greatly improved pharmacokinetics and signaling in human and mouse cells. sIFN-I robustly inhibits intratumoral angiogenesis and suppresses growth of transplantable and genetically engineered tumors in immunodeficient and immunocompetent mice. We discuss the direct and indirect mechanisms of potent antitumorigenic effects of sIFN-I and potential perspectives of its use in human cancer treatment.

Cytokines

The novel recombinant super-compound IFN (sIFN-I) and interferon IFNα-2b were provided by Sichuan Huiyang Life Science & Technology Corporation and Shanghai Huaxin Biotechnology, respectively. Human IFNβ (#: 10704-HNAS) and murine IFNβ (#: 50708-M02H), M-CSF (#: 11792-H08H), recombinant type I IFN receptor subunit extracellular domain IFNAR1-EC (#: 13222-H08H) and IFNAR2-EC (#: 10359-H08H) were purchased from Sino Biological Inc. Recombinant B18R protein (vaccinia virus-encoded neutralizing type I interferon receptor) was purchased from eBioscience (#: 14-8185).

Protein crystallization, data collection, and structure determination

Crystals of super interferon (sIFN-I) were grown by the hanging-drop vapor diffusion method (3 mg/mL protein concentration) at 20°C with, in the buffer of 1.2 mol/L Li2SO4, 0.1 mol/L 3-(cyclohexylamino)-1-propanesulfonic acid, pH 11.1, 0.02 mol/L MgCL2. Before data collection, the crystals were equilibrated in a solution containing paraffin oil for a few seconds, and then flash cooled in a liquid nitrogen stream at −173°C. Original data collection to 2.6 Å resolutions was conducted by using the synchrotron radiation from beamline BL5A at a photon factory in Tsukuba, Japan. Primary structural determination was achieved by a combination of molecular replacement method. The position of the sIFN-I was found by molecular replacement using PHASER with the crystal structure of IFNα (Protein Data Bank name: IB5L) used as the search model. The final sIFN-I structure was refined by using molecular modeling techniques and a computerized optimization program, CNS1.1.

Surface plasmon resonance assay

On the basis of surface plasmon resonance technology, binding affinities of both IFNα-2b and sIFN-I toward recombinant extracellular (EC) domain of type I interferon receptor subunit IFNAR1-EC or IFNAR2-EC were measured using the Biacore T100 Protein Interaction Array system (General Electric HealthCare Co.). For immobilization of the receptor subunit via binding the carboxylated dextran surface of the chip via amino groups in protein, a CM5 sensor chip was incubated with the IFNAR1-EC subunit and IFNAR2-EC subunit, at 20 and 50 μg/mL, respectively. The two tested IFNs were then injected perpendicularly to ligands at different concentrations within the range of 100 to 3,000 nmol/L for IFNα-2b/IFNAR1 binding, 50 to 1,000 nmol/L for sIFN-I/IFNAR1 binding, and 3.125 to 80 nmol/L for both of them on IFNAR2 binding. During IFNs/IFNAR2 binding, a 5-second regeneration procedure with 2 mol/L NaCl was added between each step of concentration. Data were analyzed by using Biacore T100 software. Dissociation constants KD were determined from the rate constants according to the Equation KD = kd/ka (d, dissociation; a, association).

Cells, cell culture, and reagents

Human amnion epithelium WISH cells, all human (A549, HeLa, HT-29, and SMMC-7721) and murine (MC38, LLC, and B16F10) cancer cell lines were cultured in their complete conditional medium; primary murine melanoma cell line YUMM was cultured as reported previously (36). Lentiviral shRNA targeting sequences were used for knocking down expression of IFNAR1 in WISH cells. For the construction of A549-IFNAR1-KO cells, the IFNAR1 gRNA targeting sequences were inserted into the Cas9/gRNA target vector LentiCRISPR (37). Lentivirus was packaged and used to infect parental A549 cells. The IFNAR1-negative cell clones were selected with 0.2 μg/mL puromycin and then confirmed by FACS assay and immunoblot. Detailed information about the cell lines and cell culture, shRNA, and sgRNA sequences are provided in Supplementary Materials and Methods and Supplementary Table S1.

Preparation of cell suspensions from murine spleen, lymph node, liver, and small intestinal epithelial tissues

Spleen, lymph nodes (including inguinal, brachial, axillary, bilateral superficial cervical, and mesenteric lymph nodes), liver, and small intestinal epithelial tissue were isolated from C57BL/6 mice. Briefly after organs were mechanically disaggregated, primary splenocytes and liver cells were obtained and resuspended in PBS after depletion of red blood cells. For isolation of small intestinal epithelial tissue cells, the intestinal tube of 3-cm length distant from the connection with stomach was cut out, and the interior side was washed from one end by using syringe and sterile PBS. Cells were scraped off with the edge of a cover glass, counted, and collected for further cell culture or mRNA extraction by TRIzol.

Preparation of murine bone marrow–derived macrophages

Bone marrow cells were flushed from the femurs and tibias of sacrificed C57BL/6 mice and then depleted for red blood cells using red cell lysing solution. The cells (1 × 107 cells/well) were cultured in 6-well plates in medium supplemented with 20 ng/mL macrophage colony–stimulating factor (M-CSF). Nonadherent cells were carefully removed, and fresh conditional medium was added every 2 days. On day 5, the adherent murine bone marrow–derived macrophage cells were collected for further treatment.

Mice

Female nude mice (6–8 weeks old) and female C57BL/6 mice (8 weeks old) were purchased from Shanghai SLAC Company. C57BL/6 Ifnar1+/+ or Ifnar1−/− mouse (strain: B6.129S2-Ifnar1tm1Agt/Mmjax) was purchased from The Jackson Laboratory. More detailed information for nude mice models and syngenic transplantable model is provided in Supplementary Materials and Methods. The experiments and animal procedures conducted at Shanghai Institute of Biochemistry and Cell Biology (Shanghai, China) were approved by the Institution Animal Care and Use Committee (IACUC, protocol recording code: IBCB0029REV1). Experiments and all animal procedures conducted at the University of Pennsylvania (Philadelphia, PA) were approved by the IACUC (protocols # 803995). Female C57BL/6 mice harboring Tyr::CreERT2; Braf CA/+; Ptenf/f alleles (which, upon tamoxifen treatment, were converted into BrafV600E/+, PtenΔ/Δ specifically in melanocytes) were kindly provided by Drs. McMahon (University of California, San Francisco, San Francisco, CA) and Bosenberg (Yale University, New Haven, CT). Induction of malignant melanoma by tamoxifen treatment was carried out as described previously (22, 38).

Pharmacokinetic animal experiments

For pharmacokinetics studies, female C57BL/6 mice (8 weeks old; Shanghai SLAC Co.) were injected intraperitoneally with sIFN-I or IFNα-2b. All mice in each IFN-treated group (n = 9, further divided into three subgroups) simultaneously received a dose of 50 μg/kg in PBS. Blood samples from each group were collected after 5, 15, 30 minutes, 1, 1.5, 2, 4, 6, 12, and 24 hours from the retro-orbital sinus (subgroup I: 5 minutes, 1, 4, and 24 hours; subgroup II: 15 minutes, 1.5 and 6 hours; subgroup III: 30 minutes, 2 and 12 hours). Serum was obtained by centrifugation at 10,000 rpm for 10 minutes at 4°C and was stored at −80°C. Untreated mice (n = 3) served as negative control. To determine half-life of the two IFNs in serum, the concentration values, determined from ELISA measurements (VeriKine Human IFN Alpha ELISA Kit, #: 41100, PBL Assay Science Inc.), were plotted against time postinjection and numerically fitted using WinNonlin version 6.2 software (Pharsight) as described elsewhere (39). Noncompartmental models were assumed. Data (including SDs) and curve fits were finally plotted with GraphPad Prism 5.

FACS assays

A549 IFNAR1−/− cells (3 × 105) were seeded into 6-well plates. After 24 hours, the cells were dissociated with cell dissociation buffer (#: 13151-014, Life Technologies), centrifuged at 1,500 rpm for 5 minutes in FACS tube, and washed with 1× PBS once. Then, cells were stained with the self-made mouse anti-human IFNAR1 antibody (1:1,000 diluted in 1% BSA-PBS) for 30 minutes at room temperature. After washing with PBS, cells were stained with AF488-conjugated goat anti-mouse IgG (1:1,000 diluted in 1% BSA-PBS) for 30 minutes. Cells stained with IgG isotype and secondary Ab only were used as negative control and were then analyzed.

For detection of cell populations in spleen from tumor-bearing mice (BrafV600E/+, PtenΔ/Δ), splenocytes were suspended after red cell lysis. Then, cells were incubated with Fc blocker antibody for 15 minutes at room temperature. Subsequently, specific antibodies (listed in Supplementary Table S2) were added and staining was continued for 20 minutes on ice. After a washing step, cells were stained with 0.5 μg/mL DAPI and were then analyzed immediately. Flow cytometry data acquisition was performed by LSRFortessa machine (BD Biosciences), and analysis was performed using FlowJo software.

Immunologic and other techniques

Immunoblots, immunofluorescent analysis, and other immunologic techniques using antibodies are listed in the Supplementary Information and have been described in our previous publications (15–17). For details on the methods for RNA extraction, cDNA synthesis, quantitative PCR, the information of the synthesized primers, H&E staining, cellular senescence detection of paraffin sections, immunofluorescent analysis of frozen sections, for cell viability assay on human and mouse cells and illustrator image processing, data analyzing, and statistics are described in Supplementary Materials and Methods and our previous publications (22).

Statistical analysis

Comparisons between experimental groups were performed using the Student t test and GraphPad Prism 5 software (GraphPad Prism software Inc.). All data were shown as Mean ± SEM. Statistically siginificant differences are indicated in figures by single (P < 0.05), double (P < 0.01) or triple (P < 0.001) symbols (such as * or #).

sIFN-I differs from IFNα-2b in spatial structure and receptor-binding affinity

Primary structural analysis showed that sIFN-I has 89% amino acid sequence homology with IFNα-2b (Fig. 1A). The crystal structure of sIFN-I was solved at 2.6 Å resolution; the resulting structure showed that sIFN-I is mainly composed of six helixes (A–F as shown in Fig. 1A) and two distinct loops (AB and BC). This structure was generally comparable with the one previously reported for IFNα-2b (40). Nevertheless, a difference between these proteins was noted in the structure of AB loop (residues 25–33: SPFSCLKDR) and BC loop (residues 44–52: DGNQFQKAQ; Fig. 1A and Supplementary Fig. S1A). Given previously published data regarding putative role of these loops in the interaction with the ligands (30), we next sought to determine relative affinities of sIFN-I for the receptor chains IFNAR1 and IFNAR2.

Figure 1.

sIFN-I exibits altered binding affinities toward the receptor subunits compared with IFNα-2b. A, Protein sequence and structure comparison between sIFN-I (red) and IFNα-2b (green). Top, amino acid sequence alignment between IFNα-2b and sIFN-I; bottom, the secondary structures on monomer including side view (left) and vertical view (right). Each monomer consists of 6 main segments of the helices (A–F) and the connecting peptide segments. Broken ellipses represent the AB or BC loop. B, Comparison of the dissociation constants for sIFN-I (black) and IFNα-2b (blue) to immobilized IFNAR1-EC. The constants were determined by steady-analysis model. C, Binding curves of IFNα-2b or sIFN-I to immobilized IFNAR2-EC. The constants were determined by dynamic-analysis model. D, Quantification of the binding affinities toward the two receptor subunits between sIFN-I and IFNα-2b.

Figure 1.

sIFN-I exibits altered binding affinities toward the receptor subunits compared with IFNα-2b. A, Protein sequence and structure comparison between sIFN-I (red) and IFNα-2b (green). Top, amino acid sequence alignment between IFNα-2b and sIFN-I; bottom, the secondary structures on monomer including side view (left) and vertical view (right). Each monomer consists of 6 main segments of the helices (A–F) and the connecting peptide segments. Broken ellipses represent the AB or BC loop. B, Comparison of the dissociation constants for sIFN-I (black) and IFNα-2b (blue) to immobilized IFNAR1-EC. The constants were determined by steady-analysis model. C, Binding curves of IFNα-2b or sIFN-I to immobilized IFNAR2-EC. The constants were determined by dynamic-analysis model. D, Quantification of the binding affinities toward the two receptor subunits between sIFN-I and IFNα-2b.

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Surface plasmon resonance assay indeed demonstrated different receptor-binding affinities for sIFN-I and IFNα-2b. Under the condition of steady-analysis model used in this experiment, sIFN-I exhibited greater affinity for the extracellular domain of IFNAR1 [KD 6.003 × 10−7 mol/L (0.6 μmol/L)] than IFNα-2b [KD 2.835 × 10−6 mol/L (2.8 μmol/L); Fig. 1B and D]. Affinity constant of the extracellular domain of IFNAR2 chain analyzed by the dynamic-analysis model exhibited KD for sIFN-I of 2.192 × 10−8 mol/L (21.9 nmol/L) and KD for IFNα-2b of 1.843 × 10−9 mol/L (1.84 nmol/L). Compared with IFNα-2b, sIFN-I displayed a higher affinity to IFNAR1 (4.72-fold) but lower affinity for IFNAR2 (11.9-fold; Fig. 1C and D). These properties distinguish sIFN-I from other IFN1 variants, such as IFN-YNS and IFN-YNS-α8tail, which exhibit increased affinities to both IFNAR1 and IFNAR2 (24). In fact, with weaker binding toward IFNAR2 but stronger binding to IFNAR1, sIFN-I is mostly reminiscent of properties reported for IFNα-21 (29) that shared 95 % homology with sIFN-I (Supplementary Fig. S1B).

sIFN-I requires IFNAR1/IFNAR2 for activating the JAK–STAT pathway

We next compared signaling elicited by sIFN-I and IFNα-2b in human A549 or HeLa cells. A similar extent of STAT1, STAT2, and STAT3 tyrosine phosphorylation was detected after administering both IFN1 types. However, IFNα-2b–induced signaling was more sensitive to inhibition by the vaccinia virus–derived B18R protein mimicking soluble IFN1 receptor and known to inhibit IFN1 pathway via ligand squelching (41) in both cell lines (Fig. 2A and B). This result suggests that sIFN-I may exhibit an enhanced signaling capacity under signaling limiting conditions.

Figure 2.

sIFN-I is capable of an increased signaling under limiting conditions. A, IFN signaling in A549 cells: 10-fold serial dilutions of recombinant B18R protein (1 to 100 ng/mL, final assay concentration) were prepared in media and combined with a constant amount (1 ng/mL, final assay concentration) of each IFN protein (sIFN-I or IFNα-2b) for 1 hour at room temperature. The B18R/IFN complexes were transferred to cells and then incubated for 30 minutes. The phosphorylation and total signal of STAT1, STAT2, and STAT3 were detected by immunoblot, and the p-STAT levels were quantified compared with their corresponding total STAT proteins. +, treatment with 100 ng/mL B18R protein. B, IFN signaling in HeLa cells was analyzed as in A.

Figure 2.

sIFN-I is capable of an increased signaling under limiting conditions. A, IFN signaling in A549 cells: 10-fold serial dilutions of recombinant B18R protein (1 to 100 ng/mL, final assay concentration) were prepared in media and combined with a constant amount (1 ng/mL, final assay concentration) of each IFN protein (sIFN-I or IFNα-2b) for 1 hour at room temperature. The B18R/IFN complexes were transferred to cells and then incubated for 30 minutes. The phosphorylation and total signal of STAT1, STAT2, and STAT3 were detected by immunoblot, and the p-STAT levels were quantified compared with their corresponding total STAT proteins. +, treatment with 100 ng/mL B18R protein. B, IFN signaling in HeLa cells was analyzed as in A.

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Recombinant IFN1 proteins were shown to opportunistically bind other receptors besides IFNAR1/2, such as the opioid receptors (42–44). Thus, we sought to determine whether signaling by sIFN-I depends on canonical IFNAR1/2-JAK-STAT pathway. Experiments in human fibrosarcoma 2fTGH cells (sensitive to IFN1) and derivative clones lacking IFNAR2 (U5A) or JAK1 (U4A) revealed that both IFNAR2 and JAK1 are required for sIFN-I–induced phosphorylation of STAT1 and STAT3 (Fig. 3A).

Figure 3.

sIFN-I elicits its signaling in an IFNAR1/2-dependent manner. A, Human fibrosarcoma 2fTGH cells (sensitive to IFN1) and derivative clones deficient in either JAK1 (U4A) or IFNAR2 (U5A) were treated with human IFNβ, IFNα-2b, or sIFN-I (10 ng/mL). The phosphorylation and total signal of STATs were detected by Western blot analysis after 15-minute treatment. B, The induction of indicated IFN-stimulated genes in cells described in A was detected by qPCR after 24-hour treatment. n.s., not significant. C, WISH cells with stable IFNAR1 knockdown expression were treated with human IFNα-2b or sIFN-I (10 ng/mL) or mouse IFNβ (negative control) for 15 minutes. The phosphorylation of STAT proteins was detected by immunoblot. D, Cells described in C were treated with indicated IFN for 24 hours, and the induction of TRAIL mRNA was detected by qPCR. E, A549 cells harboring various IFNAR1 status expression were treated with indicated IFNs (10 ng/mL) for 30 minutes. The phosphorylation of STAT1 and ERK was detected by immunoblot. F, Lymphocytes (lym), splenocytes (spl), and bone marrow–derived macrophages (BMM) were obtained from Ifnar1 knockout (Ifnar1−/−) or wild-type (Ifnar1+/+) mice. Similar numbers (6–10 × 106) of these primary cells were cultured and treated with murine IFNβ (10 ng/mL), hIFNα-2b (1 μg/mL), or sIFN-I (1 μg/mL) for 24 hours, and then the induction of Irf7 and Isg15 wasquantified by qPCR. *, P < 0.05; **, P < 0.01; ***, P < 0.001, versus mock group; #, P < 0.05; ##, P < 0.01; ###, P < 0.001, versus IFNα-2b group.

Figure 3.

sIFN-I elicits its signaling in an IFNAR1/2-dependent manner. A, Human fibrosarcoma 2fTGH cells (sensitive to IFN1) and derivative clones deficient in either JAK1 (U4A) or IFNAR2 (U5A) were treated with human IFNβ, IFNα-2b, or sIFN-I (10 ng/mL). The phosphorylation and total signal of STATs were detected by Western blot analysis after 15-minute treatment. B, The induction of indicated IFN-stimulated genes in cells described in A was detected by qPCR after 24-hour treatment. n.s., not significant. C, WISH cells with stable IFNAR1 knockdown expression were treated with human IFNα-2b or sIFN-I (10 ng/mL) or mouse IFNβ (negative control) for 15 minutes. The phosphorylation of STAT proteins was detected by immunoblot. D, Cells described in C were treated with indicated IFN for 24 hours, and the induction of TRAIL mRNA was detected by qPCR. E, A549 cells harboring various IFNAR1 status expression were treated with indicated IFNs (10 ng/mL) for 30 minutes. The phosphorylation of STAT1 and ERK was detected by immunoblot. F, Lymphocytes (lym), splenocytes (spl), and bone marrow–derived macrophages (BMM) were obtained from Ifnar1 knockout (Ifnar1−/−) or wild-type (Ifnar1+/+) mice. Similar numbers (6–10 × 106) of these primary cells were cultured and treated with murine IFNβ (10 ng/mL), hIFNα-2b (1 μg/mL), or sIFN-I (1 μg/mL) for 24 hours, and then the induction of Irf7 and Isg15 wasquantified by qPCR. *, P < 0.05; **, P < 0.01; ***, P < 0.001, versus mock group; #, P < 0.05; ##, P < 0.01; ###, P < 0.001, versus IFNα-2b group.

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Consistent with these results, sIFN-I did not induce the expression of IFN-stimulated genes (ISG), such as ISG15 or CCL5 in either U4A or U5A cells (Fig. 3B). Furthermore, RNAi-mediated knockdown of IFNAR1 attenuated sIFN-I–induced phosphorylation of STAT1/STAT3 and expression of TRAIL in WISH cells (Fig. 3C and D and Supplementary Fig. S2), suggesting an important role of IFNAR1 in sIFN-I signaling. To corroborate these data, we used CRISPR/Cas9 approach to knock out IFNAR1 in human A549 cells (Supplementary Fig. S3). A robust phosphorylation of STAT1 observed in response to IFNγ (which utilizes type II IFN receptor; ref. 45) in selected IFNAR1+/− or IFNAR1−/− clones demonstrated that these cells do not harbor defects in JAK signaling. Importantly, STAT1 phosphorylation in IFNAR1-deficient clones was not induced by sIFN-I (Fig. 3E). These data suggest that sIFN-I signals through the IFNAR1/IFNAR2–JAK pathway in human cells.

sIFN-I can act on mouse cells and exhibits distinct pharmacokinetics and tissue responses in vivo

Poor sensitivity of mouse IFN1 receptor to human IFN1 species and suboptimal pharmacokinetics of IFN1-based agents pose a challenge for efficient testing of biological effects of human IFN1 (34). Notably, treatment of primary mouse cells with sIFN-I revealed that activity of this ligand in induction of ISGs (Irf7 and Isg15) is superior to that of human IFNα-2b. All these effects were dependent on IFN1 receptor status as evident from the lack of sIFN-I–induced gene expression increase in Ifnar1 knockout mice (Fig. 3F).

We further compared pharmacokinetics of sIFN-I and IFNα-2b in mice after intraperitoneal injection of these agents. To this end, blood samples were taken at fixed time points after IFN administration, and IFN concentrations in serum were assessed by ELISA, followed by numerical analysis using WinNonlin6.2 software (Fig. 4A and B). The pharmacokinetic parameters of sIFN-I and IFNα-2b after administration at the same dose are summarized in Supplementary Table S3. At 15 minutes after injection, the mean serum peak concentration (Cmax) for IFNα-2b was 16,730 pg/mL. However, the Cmax of sIFN-I with 9,915 pg/mL was delayed to 1 hour after administration. Despite the Cmax differences between sIFN-I and IFNα-2b, the area under concentration versus time curve [AUC (0−ι)] for sIFN-I and IFNα-2b exhibited comparable value (27,425 and 24,648 pg per hour/mL, respectively) at the same dosage. Such pharmacokinetics data suggested volume distribution (Vz-F) of sIFN-I (4,384 mL/kg) is more extensive than that of IFNα-2b (2,055 mL/kg) at steady state. In other words, the tissue concentrations of sIFN-I were higher than that of IFNα-2b. Consistent with these data, the induction of expression of IFN-induced genes Irf7 and Isg15 in mouse lymph nodes, spleen, liver, and intestinal epithelial cells was notably greater after treatment of mice with sIFN-I compared with IFNα-2b (Fig. 4C–F) treatment. In all, these data suggest that compared with IFNα-2b, sIFN-I exhibits a greater distribution in mouse tissues and accordingly elicits a greater IFN-stimulated genes induction in these tissues.

Figure 4.

sIFN-I displays different pharmacokinetics and distinct tissue responsiveness in vivo. A, Calibration curve of human IFNα ELISA used for pharmacokinetic assay. B, C57BL/6 wild-type mice were subjected to intraperitoneal injection in each group (n = 3) with hIFNα-2b or sIFN-I. Serum was obtained at the indicated time point, and the concentrations of serum IFNs were detected by ELISA assay. Comparison of the pharmacokinetic curves of hIFNα-2b or sIFN-I administered as in A. Additional information is provided in Supplementary Table S3. C, C57BL/6 wild-type mice were intraperitoneally injected with murine IFNβ (1 μg/mL), human IFNα-2b (1 μg/mL), or sIFN-I (1 μg/mL), respectively. n.s., not significant. Primary tissues were collected for gene expression detection after 6-hour treatment. The induction of Irf7 and Isg15 mRNA in lymph nodes was quantified by qPCR. D, Analysis of Irf7 and Isg15 mRNA was quantified by qPCR in spleen tissues of mice described in C. E, Analysis of Irf7 and Isg15 mRNA was quantified by qPCR in intestinal epithelial tissues of mice described in C. F, Analysis of Irf7 and Isg15 mRNA was quantified by qPCR in liver tissues of mice described in C. *, P < 0.05; **, P < 0.01; ***, P < 0.001, versus mock group; #, P < 0.05; ##, P < 0.01; ###, P < 0.001, versus IFNα-2b group.

Figure 4.

sIFN-I displays different pharmacokinetics and distinct tissue responsiveness in vivo. A, Calibration curve of human IFNα ELISA used for pharmacokinetic assay. B, C57BL/6 wild-type mice were subjected to intraperitoneal injection in each group (n = 3) with hIFNα-2b or sIFN-I. Serum was obtained at the indicated time point, and the concentrations of serum IFNs were detected by ELISA assay. Comparison of the pharmacokinetic curves of hIFNα-2b or sIFN-I administered as in A. Additional information is provided in Supplementary Table S3. C, C57BL/6 wild-type mice were intraperitoneally injected with murine IFNβ (1 μg/mL), human IFNα-2b (1 μg/mL), or sIFN-I (1 μg/mL), respectively. n.s., not significant. Primary tissues were collected for gene expression detection after 6-hour treatment. The induction of Irf7 and Isg15 mRNA in lymph nodes was quantified by qPCR. D, Analysis of Irf7 and Isg15 mRNA was quantified by qPCR in spleen tissues of mice described in C. E, Analysis of Irf7 and Isg15 mRNA was quantified by qPCR in intestinal epithelial tissues of mice described in C. F, Analysis of Irf7 and Isg15 mRNA was quantified by qPCR in liver tissues of mice described in C. *, P < 0.05; **, P < 0.01; ***, P < 0.001, versus mock group; #, P < 0.05; ##, P < 0.01; ###, P < 0.001, versus IFNα-2b group.

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sIFN-I inhibits growth of solid tumors

We next compared the antitumorigenic properties of sIFN-I and of IFNα-2b. These agents administered at the doses of 50 to 150 μg per mice were reasonably well tolerated by the A549 or HT-29 tumor-bearing immunocompromised mice; these mice did not exhibit body weight loss during the course of treatment (Supplementary Fig. S4). Whereas a modest inhibition of tumor growth was elicited by IFNα-2b, administration of sIFN-I robustly suppressed this growth and led to a stable disease (Fig. 5A and Supplementary Fig. S4). Analysis of tumor tissues revealed that sIFN-I treatment increased cell senescence markers (senescence-associated β-galactosidase) and dramatically decreased the rate of cell proliferation (assessed by Ki67 staining). Accordingly, an increased expression of p53 tumor suppressor protein as well as cyclin-dependent kinase inhibitors p21 and p27 was found in tumor tissues from mice treated with sIFN-I (Supplementary Fig. S5).

Figure 5.

sIFN-I exhibits potent antisolid tumor effects in xenotransplanted tumor models. A, A549 or HT-29 xenograft tumors were treated with intratumoral injection of sIFN-I or IFNα-2b (5 mg/kg) every other day for the indicated days; in the HT-29 model, 5 mg/kg mitomycin (MMC) treatment as a positive control. n.s., not significant. The tumor volume was measured and calculated as follows: tumor volume (mm3) = (length × width2)/2. B and C, Indicated cancer cell lines (human lung cancer cells SPC-A4, A549, human colon adenocarcinoma cell HT-29, murine colorectal cancer cell line MC38, and murine primary melanoma cell line YUMM) and WISH cells were treated with 1 μg/mL (B) or 50 μg/mL (C) IFNs for 4 days. Cell viability and proliferation were assessed by WST1 assay. *, P < 0.05; **, P < 0.01; ***, P < 0.001, versus mock group; #, P < 0.05; ###, P < 0.001, versus IFNα-2b group.

Figure 5.

sIFN-I exhibits potent antisolid tumor effects in xenotransplanted tumor models. A, A549 or HT-29 xenograft tumors were treated with intratumoral injection of sIFN-I or IFNα-2b (5 mg/kg) every other day for the indicated days; in the HT-29 model, 5 mg/kg mitomycin (MMC) treatment as a positive control. n.s., not significant. The tumor volume was measured and calculated as follows: tumor volume (mm3) = (length × width2)/2. B and C, Indicated cancer cell lines (human lung cancer cells SPC-A4, A549, human colon adenocarcinoma cell HT-29, murine colorectal cancer cell line MC38, and murine primary melanoma cell line YUMM) and WISH cells were treated with 1 μg/mL (B) or 50 μg/mL (C) IFNs for 4 days. Cell viability and proliferation were assessed by WST1 assay. *, P < 0.05; **, P < 0.01; ***, P < 0.001, versus mock group; #, P < 0.05; ###, P < 0.001, versus IFNα-2b group.

Close modal

When tested for growth inhibition in vitro, both IFNα-2b and sIFN-I exhibited robust effects on human WISH cells at the dose of 1 μg/mL (Fig. 5B). A greater dose (50 μg/mL) was required to detect modest inhibitory effect of either of these IFN1 agents on growth of A549, HT-29 human cancer cells, and MC38 mouse cancer cell line. Under these conditions, sIFN-I was slightly more efficient than IFNα-2b, while growth of some of human (SPC-A4) or mouse (YUMM) cancer cell lines in vitro was not inhibited by IFN1 even at 50 μg/mL (Fig. 5C). Given that IFN1 can act on tumor vascularization and antitumor immunity (45), it is plausible that these indirect mechanisms may contribute to potent antitumorigenic effects of sIFN-I observed in vivo.

sIFN-I suppresses angiogenesis and stimulates antitumor immunity

Treatment of C57BL/6 mice bearing a syngeneic B16F10 melanoma with sIFN-I but not IFNα-2b resulted in suppression of tumor growth (Supplementary Fig. S6A). sIFN-I also suppressed tumor growth in mice burdened with syngeneic colorectal (MC38) or lung (LLC) adenocarcinomas (Supplementary Fig. S6B and S6C). These results suggest that sIFN-I can elicit its antitumorigenic activities in immunocompetent hosts.

To further understand the antitumor effects of sIFN-I on tumor host, we tested its action in immunocompetent C57BL/6 mice inoculated with syngeneic murine melanoma cell line YUMM (BrafV600E/+/PtenΔ/Δ/Cdkn2aΔ/Δ). Administration of sIFN-I into tumor-bearing Ifnar1+/+ mice led to a dramatic suppression of growth of transplanted tumor. Importantly, when Ifnar1 knockout animals were chosen as hosts, tumors grew more aggressively and did not respond to treatment with sIFN-I (Fig. 6A). Given this Ifnar1-dependent difference in responses to sIFN-I and the fact that YUMM cells were poorly sensitive to growth inhibition by sIFN-I in vitro (Fig. 5B and C), these results suggest that sIFN-I can suppress tumor growth through affecting tumor stromal compartment.

Figure 6.

Antitumorigenic, antiangiogenic, and immunostimulating effects of sIFN-I in immunocompetent mouse models. A, YUMM (BrafV600E/+; PtenΔ/Δ; CDKN2A−/−) cells were injected subcutaneously into Ifnar1+/+ and Ifnar1−/− mice to establish transplantable tumor model. sIFN-I or IFNα-2b (5 mg/kg) was injected intraperitoneally every other day for the indicated days. The tumor volume was measured and calculated. B, H&E and immunofluorescence staining of YUMM tumors isolated from mice after sIFN-I treatment. Arrows, vessels in tumor tissue. Scale bar, 100 μm. C, Quantification of the positive CD31+ vessel number in the fields (n = 7) and CD3+CD8+ T cells infiltrated in YUMM allograft tumor microenvironment (n = 10). D, Melanocyte-specific Cre activity was induced in adult mice (BrafCA/+Ptenf/f) by topical application of 4-HT to shaved back skin. Melanoma growth was measured after intraperitoneal injection with sIFN-I every other day. E, Volume of melanoma tumors that grew in BrafV600E/+; PtenΔ/Δ mice to initial volume (“−,” blue circles). After that, mice were randomly assigned to two groups treated with PBS (black squares, left mouse in the inset) or sIFN-I (red triangles, right mouse at inset) for 32 days. P < 0.001 between PBS and sIFN-I group. F, Immunofluorescence staining of the tumor isolated from BrafV600E/+; PtenΔ/Δ mice after sIFN-I treatment. Bottom, quantification of the average positive CD31+ vessel number in the fields (n = 10) and the double positive CD3+CD8+ cells in the fields (n = 10) presenting infiltrated effector T cells in tumors from BrafV600E; PtenΔ/Δ mice. Scale bar, 100 μm. G, H&E staining of the tumors and superficial lymph nodes (n = 12) isolated from BrafV600E/+; PtenΔ/Δ mice after sIFN-I treatment. Bottom, quantification on the number of metastatic tumors in lymph node (LN). Scale bar, 100 μm.

Figure 6.

Antitumorigenic, antiangiogenic, and immunostimulating effects of sIFN-I in immunocompetent mouse models. A, YUMM (BrafV600E/+; PtenΔ/Δ; CDKN2A−/−) cells were injected subcutaneously into Ifnar1+/+ and Ifnar1−/− mice to establish transplantable tumor model. sIFN-I or IFNα-2b (5 mg/kg) was injected intraperitoneally every other day for the indicated days. The tumor volume was measured and calculated. B, H&E and immunofluorescence staining of YUMM tumors isolated from mice after sIFN-I treatment. Arrows, vessels in tumor tissue. Scale bar, 100 μm. C, Quantification of the positive CD31+ vessel number in the fields (n = 7) and CD3+CD8+ T cells infiltrated in YUMM allograft tumor microenvironment (n = 10). D, Melanocyte-specific Cre activity was induced in adult mice (BrafCA/+Ptenf/f) by topical application of 4-HT to shaved back skin. Melanoma growth was measured after intraperitoneal injection with sIFN-I every other day. E, Volume of melanoma tumors that grew in BrafV600E/+; PtenΔ/Δ mice to initial volume (“−,” blue circles). After that, mice were randomly assigned to two groups treated with PBS (black squares, left mouse in the inset) or sIFN-I (red triangles, right mouse at inset) for 32 days. P < 0.001 between PBS and sIFN-I group. F, Immunofluorescence staining of the tumor isolated from BrafV600E/+; PtenΔ/Δ mice after sIFN-I treatment. Bottom, quantification of the average positive CD31+ vessel number in the fields (n = 10) and the double positive CD3+CD8+ cells in the fields (n = 10) presenting infiltrated effector T cells in tumors from BrafV600E; PtenΔ/Δ mice. Scale bar, 100 μm. G, H&E staining of the tumors and superficial lymph nodes (n = 12) isolated from BrafV600E/+; PtenΔ/Δ mice after sIFN-I treatment. Bottom, quantification on the number of metastatic tumors in lymph node (LN). Scale bar, 100 μm.

Close modal

Consistent with this possibility, compared with untreated animals or treated Ifnar1−/− mice, tumors from sIFN-I–treated Ifnar1+/+ mice contained fewer blood vessels and were less positive for endothelial marker CD31 (Fig. 6B and C). Furthermore, these tumors contained a greater number of CD3+CD8+ cytotoxic lymphocytes (Fig. 6B and C). These results support a notion that sIFN acts on tumor stromal compartment and may impede tumor growth via inhibiting tumor angiogenesis and increasing tumor infiltration by CD3+CD8+ cytotoxic lymphocytes (indicative of reversing tumor immunosuppression) in an IFNAR1-dependent manner.

Having observed a robust therapeutic effect of sIFN-I in transplanted tumors, we sought to determine whether this agent can also be active in genetically engineered models. To this end, we induced melanoma tumors in BrafV600E/+; PtenΔ/Δ mice and started the treatment after establishing tumors with the average size of 51 mm3 in both groups. Administration of sIFN-I notably suppressed growth of these tumors (Fig. 6D). When all control mice receiving vehicle had to be sacrificed for humane reasons (i.e., tumor size reaching the limit required by IACUC), animals receiving sIFN-I exhibited either stable disease or partial/complete tumor regression (Fig. 6D and E).

In this model, sIFN-I did not noticeably affect infiltration of tumors with CD31-positive cells. However, consistent with tumor regression, we observed significant increase of infiltrating cytotoxic lymphocytes in tumors treated with sIFN-I in genetically engineered mouse melanomas (Fig. 6F and Supplementary Fig. S7). Furthermore, sIFN-I notably suppressed metastases of genetically engineered melanoma into the lymph nodes (Fig. 6G). These results strongly suggest that sIFN-I exhibits a potent antitumorigenic effect against primary tumors and metastatic disease.

Endogenous IFN1 plays an important role in protection against tumors due to their antiproliferative, antiangiogenic, and immunostimulating activities (2). The response rate and therapeutic efficacy of IFN1-based pharmaceutical agents is limited, especially in solid tumors (4, 6) because oncogene signaling, tumor microenvironment stress, unfolded protein response, and inflammation can decrease the levels of IFNAR1 available for ligand interaction (19–21, 46, 47). Besides developing means to reverse downregulation of IFNAR1, additional solutions for optimizing IFN1 therapy can be based on the observation that antitumorigenic efficacy of diverse IFN1 subtypes parallels affinity of these types for IFNAR1 (48, 49). Here, we describe sIFN-I, a novel recombinant IFN1 exhibiting increased affinity for IFNAR1 and potent antitumorigenic properties.

Intriguingly, although it tightly binds to IFNAR1, sIFN-I exhibits a lesser affinity for IFNAR2 (normally a chain with greater affinity for endogenous ligands; ref. 48) compared with its “parental” molecule IFNα-2b (Fig. 1), which is different from the other reported IFN variants, such as IFN-YNS and IFN-YNS-α8tail (24). The latter variants displayed enhanced ligand binding affinity to both IFNAR1/2, and also showed enhanced anti-proliferation activity for cancer cells in vitro (28). Whereas in vitro activities of sIFN-I are relatively underwhelming, sIFN-I exerts its potent antitumor effect in vivo (Figs. 5A and 6 and Supplementary Fig. S4A).

sIFN-I elicits notable activation of STAT proteins and ensuing induction of ISGs (Figs. 2 and 3F); importantly, all these effects of sIFN-I depend on integrity of the IFNAR1/IFNAR2–JAK pathway (Fig. 3). Furthermore, tumor-bearing mice lacking Ifnar1 are poorly responsive to antitumorigenic activities of sIFN-I (Fig. 6). These results suggest that despite (or because of) potentially altered ligand–IFNAR1–IFNAR2 complex, sIFN-I robustly activates this receptor and downstream IFN1 signaling pathway.

Remarkably, compared with human IFNα-2b, the effects of sIFN-I appear to transcend the species differences. Data presented here reveal that sIFN-I elicits the IFN1-stimulated gene induction responses in primary mouse cells and mice in vivo (Figs. 4 and 5). Furthermore, in terms of pharmacokinetics in mouse, sIFN-I exhibited longer half-life and lower peak drug concentration in serum compared with IFNα-2b (Fig. 4). Intriguingly, there was a two-step serum increase for sIFN-I; this phenomenon was not observed for IFNα-2b injected into mice. These differences could be attributed to the different binding model for sIFN-I toward plasma protein or lipoprotein in blood, which lead to re-release of sIFN-I from the sIFN-I/plasma protein or sIFN-I/lipoprotein dynamic binding complex (50). Such possibility would be consistent with two peaks in concentration–time curve for serum concentration of 2′5-OAS (a well-known downstream marker of the pharmacodynamic activity of IFN) observed in blood after sIFN-I subcutaneous injection for the healthy volunteers (51). Altered pharmacokinetic characteristics of sIFN-I may contribute to greater ISG induction and improved antitumorigenic activities in vivo (Fig. 5) and, furthermore, may potentially cause lesser side effects. These possibilities in humans will be revealed by clinical trials of sIFN-I in Singapore (CTC1300056) and United States (NCT02464007) that are currently conducted in patients with solid tumors.

Previous published data suggested that sIFN-I can suppress the tumor growth in some isolated clinical cases in human patients (52). Our current data demonstrate greater efficacy of sIFN-I over IFNα-2b against human tumors xenotransplanted into immunocompromised mice (Fig. 5A). Given a robust response of mouse tissues to sIFN-I, this response may at least in part be attributed to the effects of sIFN-I on mouse stromal cells. Indeed, in immunocompetent syngeneic transplantation or genetically engineered mouse melanoma models, sIFN-I notably suppressed angiogenesis and/or increased tumor infiltration with cytotoxic lymphocytes. These antiangiogenic and immunostimulatory effects of sIFN-I are likely to contribute to robust antitumorigenic efficacy of sIFN-I that elicit stable disease or/and tumor regression in very aggressive melanoma tumors (Fig. 6). Detailed studies of the mechanisms underlying immunostimulatory and other effects of sIFN-I are ongoing. These studies will be instrumental in designing clinical trials in humans that will address clinical efficacy of sIFN-I alone or in combination with traditional, molecularly targeted or immune-targeted therapies.

G.-W. Wei holds ownership interest (including patents) in Sichuan Huiyang Life Science & Technology Corp. X.-J. Liu is a consultant/advisory board member for Sichuan Huiyang Life Science & Technology Corp. No potential conflicts of interest were disclosed by the other authors.

Conception and design: K.-J. Zhang, X.-Y. Liu, S.Y. Fuchs

Development of methodology: K.-J. Zhang, H.-L. Li, X.-L. Fang, Y.V. Katlinskaya, G.-W. Wei, D.-C. Wang, X.-Y. Liu

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): K.-J. Zhang, X.-F. Yin, Y.-Q. Yang, J. Xiao, K.V. Katlinski, Y.V. Katlinskaya, G.-W. Wei, D.-C. Wang, X.-Y. Liu

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): K.-J. Zhang, X.-F. Yin, X.-J. Liu, K.V. Katlinski, D.-C. Wang, X.-Y. Liu, S.Y. Fuchs

Writing, review, and/or revision of the manuscript: K.-J. Zhang, X.-F. Yin, L. Chu, R.-B. Guo, G.-W. Wei, D.-C. Wang, X.-Y. Liu, S.Y. Fuchs

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): K.-J. Zhang, Y.-N. Xu, L.-Y. Chen, X.-J. Liu, S.-J. Yuan, X.-L. Fang, S. Wu, H.-N. Xu, G.-W. Wei, D.-C. Wang, X.-Y. Liu, S.Y. Fuchs

Study supervision: K.-J. Zhang, X.-Y. Liu, S.Y. Fuchs

We are grateful to Drs. McMahon (UCSF), Bosenberg (Yale University), Jiang (Peking University), Melissa Wong (Oregon Health and Science University), and Stark (Cleveland Clinics) for sharing the reagents and to members of Fuchs and Liu labs for insightful comments.

This work was supported by NIH/NCI grant CA092900(to S.Y. Fuchs), Sichuan Science and Technology project 2013ZZ0004 (to K.-J. Zhang), Shanghai Institutes for Biological Science, Chinese Academy of Sciences, and Sichuan Huiyang Life Science and Technology Corp. research program Y363S21763 (to X.-Y. Liu), National Basic Research Program of China 973 Program, no. 2011CB510104 (to X.-Y. Liu), Zhejiang Sci-Tech University grant 1204807-Y(to X.-Y. Liu), Chinese Ministry of Science and Technology fund 2014CB964704(to X.-Y. Liu), and grant from the Sino-American joint laboratory between Conba Group and Zhejiang Sci-Tech University(to X.-Y. Liu).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Zitvogel
L
,
Galluzzi
L
,
Kepp
O
,
Smyth
MJ
,
Kroemer
G
. 
Type I interferons in anticancer immunity
.
Nat Rev Immunol
2015
;
15
:
405
14
.
2.
Borden
EC
,
Sen
GC
,
Uze
G
,
Silverman
RH
,
Ransohoff
RM
,
Foster
GR
, et al
Interferons at age 50: past, current and future impact on biomedicine
.
Nat Rev Drug Discov
2007
;
6
:
975
90
.
3.
Pestka
S
,
Krause
CD
,
Walter
MR
. 
Interferons, interferon-like cytokines, and their receptors
.
Immunol Rev
2004
;
202
:
8
32
.
4.
Kirkwood
JM
,
Ernstoff
MS
. 
Interferons in the treatment of human cancer
.
J Clin Oncol
1984
;
2
:
336
52
.
5.
Borden
EC
,
Lindner
D
,
Dreicer
R
,
Hussein
M
,
Peereboom
D
. 
Second-generation interferons for cancer: clinical targets
.
Semin Cancer Biol
2000
;
10
:
125
44
.
6.
Bracarda
S
,
Eggermont
AM
,
Samuelsson
J
. 
Redefining the role of interferon in the treatment of malignant diseases
.
Eur J Cancer
2010
;
46
:
284
97
.
7.
Fuchs
SY
. 
Hope and fear for interferon: the receptor-centric outlook on the future of interferon therapy
.
J Interferon Cytokine Res
2013
;
33
:
211
25
.
8.
Uze
G
,
Schreiber
G
,
Piehler
J
,
Pellegrini
S
. 
The receptor of the type I interferon family
.
Curr Topics Microbiol Immunol
2007
;
316
:
71
95
.
9.
Carbone
CJ
,
Fuchs
SY
. 
Eliminative signaling by Janus kinases: role in the downregulation of associated receptors
.
J Cell Biochem
2014
;
115
:
8
16
.
10.
Fuchs
SY
. 
Ubiquitination-mediated regulation of interferon responses
.
Growth Factors
2012
;
30
:
141
8
.
11.
Eguchi
H
,
Nagano
H
,
Yamamoto
H
,
Miyamoto
A
,
Kondo
M
,
Dono
K
, et al
Augmentation of antitumor activity of 5-fluorouracil by interferon alpha is associated with up-regulation of p27Kip1 in human hepatocellular carcinoma cells
.
Clin Cancer Res
2000
;
6
:
2881
90
.
12.
Mejia
C
,
Navarro
S
,
Colamonici
OR
,
Pellin
A
,
Castel
V
,
Llombart-Bosch
A
. 
Expression of type I interferon receptor and its relation with other prognostic factors in human neuroblastoma
.
Oncol Rep
1999
;
6
:
149
53
.
13.
Vitale
G
,
van Eijck
CH
,
van Koetsveld Ing
PM
,
Erdmann
JI
,
Speel
EJ
,
van der Wansem Ing
K
, et al
Type I interferons in the treatment of pancreatic cancer: mechanisms of action and role of related receptors
.
Ann Surg
2007
;
246
:
259
68
.
14.
Huangfu
WC
,
Fuchs
SY
. 
Ubiquitination-dependent regulation of signaling receptors in cancer
.
Genes Cancer
2010
;
1
:
725
34
.
15.
Kumar
KG
,
Tang
W
,
Ravindranath
AK
,
Clark
WA
,
Croze
E
,
Fuchs
SY
. 
SCF(HOS) ubiquitin ligase mediates the ligand-induced down-regulation of the interferon-alpha receptor
.
EMBO J
2003
;
22
:
5480
90
.
16.
Kumar
KG
,
Krolewski
JJ
,
Fuchs
SY
. 
Phosphorylation and specific ubiquitin acceptor sites are required for ubiquitination and degradation of the IFNAR1 subunit of type I interferon receptor
.
J Biol Chem
2004
;
279
:
46614
20
.
17.
Kumar
KG
,
Barriere
H
,
Carbone
CJ
,
Liu
J
,
Swaminathan
G
,
Xu
P
, et al
Site-specific ubiquitination exposes a linear motif to promote interferon-alpha receptor endocytosis
.
J Cell Biol
2007
;
179
:
935
50
.
18.
Liu
J
,
HuangFu
WC
,
Kumar
KG
,
Qian
J
,
Casey
JP
,
Hamanaka
RB
, et al
Virus-induced unfolded protein response attenuates antiviral defenses via phosphorylation-dependent degradation of the type I interferon receptor
.
Cell Host Microbe
2009
;
5
:
72
83
.
19.
Bhattacharya
S
,
HuangFu
WC
,
Dong
G
,
Qian
J
,
Baker
DP
,
Karar
J
, et al
Anti-tumorigenic effects of Type 1 interferon are subdued by integrated stress responses
.
Oncogene
2013
;
32
:
4214
21
.
20.
Huangfu
WC
,
Qian
J
,
Liu
C
,
Liu
J
,
Lokshin
AE
,
Baker
DP
, et al
Inflammatory signaling compromises cell responses to interferon alpha
.
Oncogene
2012
;
31
:
161
72
.
21.
HuangFu
WC
,
Qian
J
,
Liu
C
,
Rui
H
,
Fuchs
SY
. 
Melanoma cell-secreted soluble factor that stimulates ubiquitination and degradation of the interferon alpha receptor and attenuates its signaling
.
Pigment Cell Melanoma Res
2010
;
23
:
838
40
.
22.
Katlinskaya
YV
,
Katlinski
KV
,
Yu
Q
,
Ortiz
A
,
Beiting
DP
,
Brice
A
, et al
Suppression of type I interferon signaling overcomes oncogene-induced senescence and mediates melanoma development and progression
.
Cell Rep
2016
;
15
:
171
80
.
23.
Kalie
E
,
Jaitin
DA
,
Podoplelova
Y
,
Piehler
J
,
Schreiber
G
. 
The stability of the ternary interferon-receptor complex rather than the affinity to the individual subunits dictates differential biological activities
.
J Biol Chem
2008
;
283
:
32925
36
.
24.
Levin
D
,
Harari
D
,
Schreiber
G
. 
Stochastic receptor expression determines cell fate upon interferon treatment
.
Mol Cell Biol
2011
;
31
:
3252
66
.
25.
Moraga
I
,
Harari
D
,
Schreiber
G
,
Uze
G
,
Pellegrini
S
. 
Receptor density is key to the alpha2/beta interferon differential activities
.
Mol Cell Biol
2009
;
29
:
4778
87
.
26.
Jaks
E
,
Gavutis
M
,
Uze
G
,
Martal
J
,
Piehler
J
. 
Differential receptor subunit affinities of type I interferons govern differential signal activation
.
J Mol Biol
2007
;
366
:
525
39
.
27.
Jaitin
DA
,
Roisman
LC
,
Jaks
E
,
Gavutis
M
,
Piehler
J
,
Van der Heyden
J
, et al
Inquiring into the differential action of interferons (IFNs): an IFN-alpha2 mutant with enhanced affinity to IFNAR1 is functionally similar to IFN-beta
.
Mol Cell Biol
2006
;
26
:
1888
97
.
28.
Kalie
E
,
Jaitin
DA
,
Abramovich
R
,
Schreiber
G
. 
An interferon alpha2 mutant optimized by phage display for IFNAR1 binding confers specifically enhanced antitumor activities
.
J Biol Chem
2007
;
282
:
11602
11
.
29.
Lavoie
TB
,
Kalie
E
,
Crisafulli-Cabatu
S
,
Abramovich
R
,
DiGioia
G
,
Moolchan
K
, et al
Binding and activity of all human alpha interferon subtypes
.
Cytokine
2011
;
56
:
282
9
.
30.
Thomas
C
,
Moraga
I
,
Levin
D
,
Krutzik
PO
,
Podoplelova
Y
,
Trejo
A
, et al
Structural linkage between ligand discrimination and receptor activation by type I interferons
.
Cell
2011
;
146
:
621
32
.
31.
Subramanian
GM
,
Fiscella
M
,
Lamouse-Smith
A
,
Zeuzem
S
,
McHutchison
JG
. 
Albinterferon alpha-2b: a genetic fusion protein for the treatment of chronic hepatitis C
.
Nat Biotechnol
2007
;
25
:
1411
9
.
32.
Yang
X
,
Zhang
X
,
Fu
ML
,
Weichselbaum
RR
,
Gajewski
TF
,
Guo
Y
, et al
Targeting the tumor microenvironment with interferon-beta bridges innate and adaptive immune responses
.
Cancer Cell
2014
;
25
:
37
48
.
33.
Ceaglio
N
,
Etcheverrigaray
M
,
Conradt
HS
,
Grammel
N
,
Kratje
R
,
Oggero
M
. 
Highly glycosylated human alpha interferon: an insight into a new therapeutic candidate
.
J Biotechnol
2010
;
146
:
74
83
.
34.
Harari
D
,
Abramovich
R
,
Zozulya
A
,
Smith
P
,
Pouly
S
,
Koster
M
, et al
Bridging the species divide: transgenic mice humanized for type-I interferon response
.
PLoS One
2014
;
9
:
e84259
.
35.
Zhang
W
,
Tong
X
,
Nakasone
T
,
Yue
XT
,
Yamamoto
N
,
Liu
XY
, et al
Activity of superior interferon alpha against HIV-1 in severe combined immunodeficient mice reconstituted with human peripheral blood leukocytes
.
Chin Med J
2011
;
124
:
396
400
.
36.
Pencheva
N
,
Buss
CG
,
Posada
J
,
Merghoub
T
,
Tavazoie
SF
. 
Broad-spectrum therapeutic suppression of metastatic melanoma through nuclear hormone receptor activation
.
Cell
2014
;
156
:
986
1001
.
37.
Shalem
O
,
Sanjana
NE
,
Hartenian
E
,
Shi
X
,
Scott
DA
,
Mikkelsen
TS
, et al
Genome-scale CRISPR-Cas9 knockout screening in human cells
.
Science
2014
;
343
:
84
7
.
38.
Dankort
D
,
Curley
DP
,
Cartlidge
RA
,
Nelson
B
,
Karnezis
AN
,
Damsky
WE
 Jr
, et al
Braf(V600E) cooperates with Pten loss to induce metastatic melanoma
.
Nat Genet
2009
;
41
:
544
52
.
39.
Czyrski
A
,
Kondys
K
,
Szalek
E
,
Karbownik
A
,
Grzeskowiak
E
. 
The pharmacokinetic interaction between levofloxacin and sunitinib
.
Pharmacol Rep
2015
;
67
:
542
4
.
40.
Radhakrishnan
R
,
Walter
LJ
,
Hruza
A
,
Reichert
P
,
Trotta
PP
,
Nagabhushan
TL
, et al
Zinc mediated dimer of human interferon-alpha 2b revealed by X-ray crystallography
.
Structure
1996
;
4
:
1453
63
.
41.
Symons
JA
,
Alcami
A
,
Smith
GL
. 
Vaccinia virus encodes a soluble type I interferon receptor of novel structure and broad species specificity
.
Cell
1995
;
81
:
551
60
.
42.
Jiang
CL
,
Son
LX
,
Lu
CL
,
You
ZD
,
Wang
YX
,
Sun
LY
, et al
Analgesic effect of interferon-alpha via mu opioid receptor in the rat
.
Neurochem Int
2000
;
36
:
193
6
.
43.
Wang
YX
,
Jiang
CL
,
Lu
CL
,
Song
LX
,
You
ZD
,
Shao
XY
, et al
Distinct domains of IFNalpha mediate immune and analgesic effects respectively
.
J Neuroimmunol
2000
;
108
:
64
7
.
44.
Wang
YX
,
Xu
WG
,
Sun
XJ
,
Chen
YZ
,
Liu
XY
,
Tang
H
, et al
Fever of recombinant human interferon-alpha is mediated by opioid domain interaction with opioid receptor inducing prostaglandin E2
.
J Neuroimmunol
2004
;
156
:
107
12
.
45.
Platanias
LC
. 
Mechanisms of type-I- and type-II-interferon-mediated signalling
.
Nat Rev Immunol
2005
;
5
:
375
86
.
46.
Kumar
KG
,
Liu
J
,
Li
Y
,
Yu
D
,
Thomas-Tikhonenko
A
,
Herlyn
M
, et al
Raf inhibitor stabilizes receptor for the type I interferon but inhibits its anti-proliferative effects in human malignant melanoma cells
.
Cancer Biol Ther
2007
;
6
:
1437
41
.
47.
Zheng
H
,
Qian
J
,
Carbone
CJ
,
Leu
NA
,
Baker
DP
,
Fuchs
SY
. 
Vascular endothelial growth factor-induced elimination of the type 1 interferon receptor is required for efficient angiogenesis
.
Blood
2011
;
118
:
4003
6
.
48.
Schreiber
G
,
Piehler
J
. 
The molecular basis for functional plasticity in type I interferon signaling
.
Trends Immunol
2015
;
36
:
139
49
.
49.
Piehler
J
,
Thomas
C
,
Garcia
KC
,
Schreiber
G
. 
Structural and dynamic determinants of type I interferon receptor assembly and their functional interpretation
.
Immunol Rev
2012
;
250
:
317
34
.
50.
Wasan
KM
,
Brocks
DR
,
Lee
SD
,
Sachs-Barrable
K
,
Thornton
SJ
. 
Impact of lipoproteins on the biological activity and disposition of hydrophobic drugs: implications for drug discovery
.
Nat Rev Drug Discov
2008
;
7
:
84
99
.
51.
Zeng
J
,
Yu
Q
,
Liang
M
,
Duan
J
,
Zheng
Y
. 
Study on pharmacokinetics and bioequivalence of rSIFN-co in healthy volunteers
.
Mod Prev Med
2008
;
35
:
982
4
.
52.
Liu
X-Y
,
Wei
G-W
,
Yang
D-Q
,
Liu
L-X
,
Ma
L
,
Li
X
, et al
Possibility to win the war against cancer
.
In
:
Liu
X-Y
,
Pestka
S
,
Shi
Y-F
,
editors
.
Recent advance in cancer research and therapy
.
Amsterdam, Netherlands
:
Elsevier
; 
2012
.