IgE-Based Therapeutic Combination Enhances Antitumor Response in Preclinical Models of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Approximately 48,000 people will die of PDAC in 2021 (1). Late diagnosis and chemoresistance underlie the reduced survival rate of 10% (2). Unlike other solid tumors, PDAC has proven to be refractory, primarily to single-agent immunotherapeutic approaches (3–5). These studies suggest that more profound immunosuppression exists in pancreatic cancer compared with other solid tumors (6, 7). Thus, multipronged therapeutic strategies are expected to overcome the immunosuppressive microenvironment and provide superior survival benefits for patients with pancreatic cancer. The current immunotherapeutic strategies against PDAC primarily focus on checkpoint blockades to activate CD8 T cells. However, ipilimumab or tremelimumab checkpoint blockades demonstrated only a partial response in clinical trials when combined with gemcitabine. Notably, a granulocyte-macrophage colony-stimulating factor (GM-CSF) gene-transfected tumor cell vaccine (GVAX) improved PDAC patient disease-free survival (DFS) when combined with radiotherapy or 5-fluorouracil (5-FU)-based chemoradiation in Phase I and Phase II trials, respectively (8–10). However, other immunotherapies, including DNA or peptide vaccines, have failed to demonstrate clinical benefits in patients with PDAC. All these immunotherapeutic approaches have largely ignored other immunosuppressed innate immune players, such as natural killer cells (NK), that are not MHC-restricted and respond to tumor insults by generating IFNγ for T-cell activation. Although NK cell-based therapeutics have shown some promising efficacies against hematologic malignancies (11), the success of these strategies is yet to be examined against solid tumors. To date, only a few NK cell-targeted strategies have been employed in the preclinical models for solid tumors (12, 13). Hence the therapeutic combination that boosts both cytotoxic T cell (CTL)- and NK cell-mediated antitumor response has not yet been studied and may provide long-lasting therapeutic benefits in PDAC.

Epidemiologic evidence indicates that individuals with allergies have a lower incidence of pancreatic cancer (14, 15). These suggest that distinct immune surveillance underlies protection against pancreatic cancer observed in allergic individuals (16). A previous study reported the existence of tumor antigen specific IgE antibodies in the serum of PDAC patients. Interestingly, these patients did not exhibit any allergic symptoms. Also, IgE isolated from the serum of PDAC patients showed peripheral blood mononuclear cell-mediated antibody-dependent cell cytotoxicity (ADCC) against human pancreatic cancer cells (HPAC) in ex vivo assays (17). In addition, a Phase I clinical trial of MOv18 IgE (IgE antibody targeting the folate receptor alpha) has shown antitumor benefits in advanced cancers (18). Given the myriads of immune cells expressing IgE receptors, we hypothesized that therapeutic targeting of tumor antigens with IgE antibody would provide robust antitumor benefits against pancreatic cancer.

MUC1 is a critical therapeutic target in solid tumors, whose C-terminal domain contributes to immune evasion (19). To date, successful MUC1-based immunotherapies have remained elusive. Hence, we investigated a MUC1-targeted IgE antibody (mouse/human chimeric anti-MUC1.IgE) in combination with a toll-like receptor 3 (TLR3) agonist (PolyICLC) and anti-PD-L1 against pancreatic tumors in double transgenic (dTg) mice that express human MUC1 and human IgE antibody receptor I α subunit (FcϵRIα). Our study demonstrated that anti-MUC1.IgE+anti-PD-L1+PolyICLC combination promotes NK and CD8 T-cell-mediated antigen-specific immune responses that restrict pancreatic tumor growth in an otherwise immunosuppressed preclinical model of PDAC. We also noted that this combination promoted MUC1 antigen cross-presentation to CD8 T cells and NK cell-mediated tumor killing in ex vivo assays. Of note, we also demonstrate that Ovalbumin (OVA)-induced IgE is inefficient in controlling tumor growth in the PDAC model. Overall, these studies will open new avenues for IgE-based therapeutics against pancreatic cancer.

hMUC1/hFcϵRIα dTg C57Bl/6J mice were generated by breeding hMUC1single Tg mice and hFcϵRIα single Tg mice. hMUC1 Tg mice have been described earlier (20). hFcϵRIα Tg mice (stock no: 010506) were purchased from The Jackson laboratory. Panc02.MUC1 (expressing human MUC1), Panc02.Neo and KPC.MUC1 (expressing human MUC1) cells have been described earlier (20). All cell lines were authenticated from University of Arizona Genetics Core by STR profiling. C57BL/6-congenic KPC cells are derived from the spontaneous PDAC model with Kras and p53 mutations. All animal studies included equal number of male and female mice. All the animal studies were conducted in accordance with, and with the approval of the Institutional Animal Care and Use Committee (IACUC) guidelines. Mice were genotyped for Fcer1a and Muc1 expression using primers as mentioned in Table 1.

CHO-K1–3C6 cell line expressing chimeric mouse/human anti-MUC1.IgE was provided by OncoQuest Pharmaceuticals Inc. (21). Amino acid sequences for the heave and light chains of the antihuman MUC1.IgE-3C6 are shown in Supplementary Fig. S1. The cell line was cultured in DMEM/F12 media supplemented with 10% FBS and weaned to DMEM with 5% FBS. The murine myeloma cell line Sp2/0-Ag14 expressing mouse/human chimeric anti-prostate-specific antigen (PSA).IgE (22) was a gift from OncoQuest Pharmaceuticals Inc and was cultured in Isocove's Modified Eagle Medium (IMDM) with 5% FBS. The antibody conditioned culture supernatants were collected from the above cell lines and filtered through 0.25 μm PMSF filters. Anti-MUC1.IgE and anti-PSA.IgE conditioned media were eluted from a human IgE capture liquid chromatography column prepared with bound omalizumab (Xolair; Novartis Pharmaceuticals Ltd./Genentech, Inc.). Subsequently, all antibody eluate peaks were dialyzed against 300 buffer changes of PBS in 10K MWCO Slide-A-Lyzer G2 dialysis cassettes (Catalog No. 87732; Thermo Fisher Scientific Inc.). Dialysates were quantified by 280 nm absorbance via a NanoDrop One spectrophotometer. Western blot as well as ELISA confirmed antigenicity. Purified antibody lots were lyophilized for long-term storage. Murine monoclonal antihuman MUC1.IgG1 (AR20.5) antibody is described earlier (20).

Panc02.MUC1 cells (1 × 10⁶ cells/100 μL) were challenged subcutaneously (s.c.) between the scapulae in hMUC1/hFcϵRIα dTg mice. Post challenge, mice were randomized into different experimental groups (Saline control; anti-PD-L1; PolyICLC; anti-MUC1.IgE; anti-PD-L1+PolyICLC; anti-MUC1.IgE+anti-PD-L1; anti-MUC1.IgE + PolyICLC; and anti-MUC1.IgE + PolyICLC + anti-PD-L1, n = 8 mice per group), and treated with respective antibodies. Anti-PD-L1 was purchased from BioXcell (Cat: BE0101, BioXcell Inc.), whereas OncoQuest Inc. provided PolyICLC for the animal studies. Post treatment, mice were monitored for overall survival and tumor growth using established protocols (20). Tumor diameters (two/tumor) were measured weekly for tumor volume measurement [V = (length × width²)/2]. Mice were euthanized as per the IACUC requirements. For orthotopic studies, KPC.MUC1 tumor cells (3 × 10³ cells/30 μL) were implanted in the pancreas of 8- to 9-week-old immunocompetent hMUC1/hFcϵRIα dTg mice using established protocols (23). Equal number of male and female mice were used in the study. Post implantation mice were randomized into different experimental groups and treated with the respective antibodies and monitored for tumor growth [V = (length × width²)/2] using vernier calipers as per the institutional IACUC guidelines. In the OVA-PDAC model, KPC tumor cells (3 × 10³ cells/30 μL) were implanted in the pancreas of 8- to 9-week-old immunocompetent C57BL/6J mice. Subsequently, mice were monitored for tumor growth using ultrasound imaging with the Vevo 3100 system and euthanized on day 42 as per the institutional IACUC guidelines. Tumor volume was calculated using the Vevo LAB imaging software (VisualSonics Inc.) integrated in Vevo 3100 system. CD8, CD4, and NK cell depletion studies were performed as described in a previous study (20).

C57BL/6J mice (JAX:000664) were sensitized and challenged to OVA as previously described with modifications (24). For sensitization, 20 μg OVA was mixed with 2 mg of Al (OH)³ (Thermo Fisher Inc.) in 0.2 mL saline and administered intraperitoneally. Nonsensitized animals received saline only. Mice were implanted with the tumor cells in the pancreas on days as mentioned in figure legend. Mice were challenged with nebulized 1.5% OVA in saline or saline alone (saline challenged groups), for 20 minutes twice a week until the end of the study. Allergic phenotype was validated by IgE quantitation in the serum using ELISA Kit (Catalog No. 501128838; eBioscience Inc.) as per the manufacturer's protocol. Bronchoalveolar lavage fluid (BALF) was collected from the airways and differential counting for eosinophil was performed on cytospin-prepared slides using DiffQuick (Siemens Healthineer Inc.) as described previously (24).

Freshly harvested tumor tissues from tumor-bearing mice were processed for tumor-infiltrating lymphocytes (TIL) and IHC (formalin-fixed) analyses using established protocols (25). Tissue sections were stained for Ki67 and cleaved caspase-3. All the antibodies are described in Table 2. Stained slides were imaged using a Leica microscope equipped with a LAS-AF processing system and quantitated using ImageJ software (24). PDAC and metastasis tumor tissue slides were acquired through RAPID autopsy program at UNMC and stained for FcϵRI antibody (LS-B3150). Stained slides were quantitated blindly by lab technician using a formula, histologic score = [1 × (% cells 1+) + 2 × (% cells 2+) + 3 × (% cells 3+)], where 1+, 2+, and 3+ corresponds to weak, moderate, and strong staining intensity respectively, as described previously (26).

MUC1-specific binding ability of anti-MUC1.IgE antibody was confirmed using Panc02.MUC1 in the in vitro assay. Here, Panc02.MUC1 were incubated with or without anti-MUC1.IgE antibody for 12 hours. Post-incubation, cells were harvested and stained for epsilon (ϵ) and kappa (κ) chains using florescent conjugated anti-epsilon (ϵ; goat antihuman IgE Fc-FITC) and anti-kappa (κ; antihuman kappa APC) antibodies.

Antigen peptide uptake assay for dendritic cells (DCs) using FITC-MUC1 peptide was performed as described previously (27). For the assay, FITC-MUC1 peptide (Hi Lyte Fluor 488-GVTSAPDTRPAPGSTA-OH) was custom synthesized (AnaSpec Inc.). ELISpot assay was performed using mouse IFNγ ELISpot Kit (Catalog No.: EL485; RnD Systems, Inc.) as per manufacturer's protocol. CFSE-based proliferation assay was utilized to measure CD8 T-cell proliferation upon co-culture with antigen-antibody loaded DCs using established protocols (27). CD107a-based degranulation assay was performed to determine the functional activity of NK cells, as described previously (28).

PDAC normalized expression data from Bailey and colleagues was collected and boxplots plotted for each pancreatic subtype using Matlab (MATLAB, RRID:SCR_001622) (29). Outliers are plotted as data points that reside approximately 2.7 SDs beyond the mean expression. Statistical analysis comparing PDAC subtypes was performed using one-way ANOVA for multiple comparisons. Primary pancreatic tumor tissues were procured through institutional RAPID autopsy program. Freshly harvested tumor tissues were minced into small pieces and incubated in digestion buffer (complete DMEM containing 2% Collagenase A (Roche 11088793001) and 0.25 U/mL of DNAse I (Roche 11284932001 for 20 minutes at 37°C with constant shaking. Subsequently, the digest was filtered through a 70 μm nylon strainer and centrifuged at 2,000 rpm for 5 minutes. Finally, the cells were washed with 1× PBS and stained with live/dead dye. Post staining, cells were washed with buffer (1 × PBS with 0.5% BSA) and stained with Flourochrome conjugated antibodies corresponding to different immune cell subsets. Samples were acquired by BD Bioscience LSRII flow cytometer and data were analyzed by FlowJo Version 8.8.7 software by TreeStar.

Survival differences were plotted using Kaplan–Meier plots and differences between experimental groups were assessed using log-rank tests using Prism 6 software. Tumor volume measurements over time were compared using two-way ANOVA analyses with repeated measurement (Bonferroni post hoc test). The percentage of immune subsets in different mice groups was measured using one-way ANOVA with a Bonferroni post hoc test adjustment for multiple measurements in Prism 6 software (GraphPad Prism, RRID:SCR_002798, GraphPad Software Inc.). All the P values ≤ 0.05 were considered significant.

The FcϵRI receptor is a high-affinity IgE receptor, which consists of one α subunit, one β subunit, and two γ subunits in mice and human. In humans, FcϵRI can also exists in an alternate trimeric form (αγ₂) (30). Although the extracellular domain of the α subunit binds to IgE heavy chain, the β and γ subunits relay the signal to downstream pathways (31). To examine the feasibility of IgE-based therapeutics, we first determined the FcϵRI expression in pancreatic tumor tissues. In our study (Fig. 1A), the normal tissue adjacent to the tumor displays a notable expression of FcγRIII and FcϵRI. Although FcγRIII, also known as CD16, is a receptor for monomeric IgG-type antibodies, FcϵRI binds to the Fc region of IgE antibody class with high affinity (30, 32). Next, we investigated the expression of IgG and IgE receptor genes (FCER1A, FCER1G, FCGR3A, and FCGR1A) in different subtypes of PDAC by using previously published expression data (29). Herein, we noted significant enrichment of the FCGR3A in the squamous subtype of PDAC (Fig. 1B). Similarly, FCER1G displayed a significant enrichment in the squamous subtype of PDAC. In contrast, FCER1A demonstrated a uniform expression, albeit low compared with FCGR3A, in all the subtypes of PDAC. Subsequently, we assessed the cell types that express FcϵRIα subunit in the pancreatic tumor by using a flow cytometer. Herein, we noted the abundance of FcϵRIα positive mast cells, monocytes, and a small fraction of eosinophils inside the pancreatic tumor (Fig. 1C and D; Supplementary Fig. S2). Subsequently, we assessed the expression of FcϵRI in the primary tumor and matched liver metastatic tissue specimens. Our study demonstrated a significant upregulation of FcϵRI expression in primary tumors as compared with the normal pancreas. In contrast, we did not observe a significant difference in FcϵRI expression between the primary tumors and metastatic liver lesions (Fig. 1E).

Upon confirmation of FcϵRI expression in PDAC tumors, we examined the therapeutic efficacy of mouse/human chimeric anti-MUC1.IgE antibody in the preclinical model of PDAC by utilizing hMUC1/hFcϵRIα dTg mice. Our antibody targets the PDTRPAP sequence in the tandem repeat of the human MUC1 antigen (Fig. 2A). This antibody specifically binds to the MUC1 antigen on pancreatic tumor cells (Fig. 2C and D). Furthermore, our data demonstrate FcϵRIα expression on mast cells, DCs, but not on T cells in dTg mice (Fig. 2D). Next, we investigated the therapeutic efficacy of anti-MUC1.IgE in combination with the TLR3 agonist (PolyICLC) and a checkpoint inhibitor (anti-PD-L1) against s.c. Panc02.MUC1 tumors (Fig. 2E). This combination is based on previously published data where we demonstrated improved efficacy of anti-MUC1.IgG1 isotype in combination with PolyICLC and anti-PD-L1 against PDAC tumors (20). In our pilot experiment, three single intraperitoneal injections of anti-MUC1.IgE (40 μg) to healthy dTg mice at 10 days interval did not display any adverse effects, such as anaphylactic shock in mice. In our in vivo study, a significant proportion of anti-MUC1.IgE + PolyICLC + anti-PD-L1-treated mice rejected Panc02.MUC1 and remained tumor-free. Overall, anti-MUC1.IgE-based triple combination-treated mice displayed increased survival as compared with saline-treated control mice. Furthermore, anti-MUC1.IgE-combination-treated mice that failed to reject tumor displayed significantly attenuated tumor growth compared with other treatment groups (Fig. 2F and G). Next, we performed a tumor rechallenge experiment by implanting Panc02.Neo control and Panc02.MUC1 tumor cells on the opposite flanks of anti-MUC1.IgE-combination-treated tumor-free mice. We monitored these mice for tumor rejection and tumor growth over time. Herein, unchallenged treatment-naïve dTg animals served as controls (Fig. 2H). Panc02.Neo and Panc02.MUC1 cell lines exhibit indistinguishable growth rates in the in vitro system (20). In our experiment, we did not see the rejection of Panc02.MUC1 and Panc02.Neo tumor cells upon rechallenge in previously anti-MUC1.IgE-combination-treated tumor-free mice. However, these mice demonstrated a significantly slower growth rate of Panc02.MUC1 tumors compared with Panc02.Neo tumors (Fig. 2I). Contrastingly, both the tumors grew at indistinguishable rates in treatment-naïve dTg mice. Overall, our data demonstrate that anti-MUC1.IgE + PolyICLC + anti-PD-L1 combination provides a MUC1-specific immune response that delays tumor appearance and hinders tumor growth in heterotopic models.

Next, we assessed the therapeutic benefits of anti-MUC1.IgE-based combination in an aggressive model of PDAC, which mimics the pathologic features of human PDAC (33). We utilized KPC.MUC1 tumor cells and employed antihuman PSA.IgE (22) as a control for our studies as PSA is not expressed in pancreatic tumors. In our study, treatment with anti-MUC1.IgE+anti-PD-L1+PolyICLC combination significantly delayed tumor growth and prolonged survival of orthotopic tumor-bearing dTg mice compared with control mice (Fig. 3A and B). Furthermore, anti-MUC1.IgE-based combination significantly reduced tumor burden and provided superior survival benefits compared with anti-PD-L1+PolyICLC or anti-PSA.IgE+anti-PD-L1+PolyICLC treatments (Fig. 3C and D). Interestingly, anti-MUC1.IgE+anti-PD-L1+PolyICLC combination displayed an improved, but not significant, antitumor response as compared to anti-MUC1.IgG1-based combination. The above data suggest that although anti-MUC1.IgG1 and anti-MUC1.IgE-combination triggers similar antitumor pathways, anti-MUC1.IgE activates additional antitumor players that contribute to improved therapeutic benefits. To further dissect the critical role of FcϵRIα-MUC1 in the underlying antitumor response of anti-MUC1.IgE, we examined the efficacies of anti-MUC1.IgE and anti-MUC1.IgG1(AR20.5)-based combination in different transgenic mice, that is, hFcϵRIα single Tg and hMUC1 single Tg mice. As hFcϵRIα Tg mice do not express human MUC1, we utilized KPC cells without human MUC1 in an orthotopic implantation study. Contrastingly, hMUC1 Tg mice were implanted with KPC.MUC1 cells. Given the absence of hMUC1 antigen in hFcϵRIα Tg mice, tumor growth rates were indistinguishable in all the treatment groups. Importantly, anti-MUC1.IgE-based combination exhibited tumor protective benefits only in hMUC1/hFcϵRIα dTg mice. In the absence of FcϵRIα, anti-MUC1.IgE-based combination displayed attenuated antitumor response in hMUC1Tg mice (Fig. 3E and F). Hence, the requirement of the FcϵRIα–dependent pathway underlies the improved therapeutic efficacy of anti-MUC1.IgE-based combination over anti-MUC1.IgG1-based therapy in pancreatic tumor-bearing dTg mice. Next, our study demonstrated that anti-MUC1.IgE-based combination treatment significantly attenuated the tumor cell proliferation in treated mice (Fig. 3G–H). Interestingly, anti-MUC1.IgE-based combination treatment also showed a trend toward increased apoptosis of tumor cells in the treated mice as compared with controls (Fig. 3G–H).

Next, we interrogated the key immune subsets that underlie the therapeutic efficacy of anti-MUC1.IgE + PolyICLC + anti-PD-L1 combination. Elimination of NK and CD8 T cells reduced the survival of anti-MUC1.IgE-combination treated Panc02.MUC1 subcute and KPC.MUC1 orthotopic tumor-bearing mice (Fig. 4A and B). Previously, anti-MUC1.IgG1-based combination showed CD8 T-mediated antitumor response against pancreatic cancer in MUC1.Tg mice (20). Hence, we compared the efficacy of anti-MUC1.IgG1 and anti-MUC1.IgE-based combination therapy in the presence or absence of NK cells in dTg mice. NK cell depletion did not alter the antitumor response of anti-MUC1.IgG1+anti-PD-L1+ PolyICLC treatment, but significantly attenuated the prolonged survival benefits of anti-MUC1.IgE-based combination therapy in orthotopic tumor-bearing mice (Fig. 4C). Surprisingly, the TILs assessment showed that anti-MUC1.IgE+anti-PD-L1+PolyICLC does not alter the total number of NK and CD8 T cells. However, this combination significantly reduces the proportion of PD-1⁺ TIGIT⁺ NK cells in treated tumors compared with other control counterparts (Fig. 4D). In addition, our study showed a significant increase in CD103⁺ DC, but no significant alteration in macrophages and Myeloid-derived suppressor cells (MDSCs) percentages in anti-MUC1.IgE+anti-PD-L1+PolyICLC treated tumors compared with other groups. CD103⁺DCs are conventional type cDC1s that cross-present tumor antigens to the CD8 T cells (34). As DCs also express FcϵRI receptors, we posit that increased CD103⁺DCs in anti-MUC1.IgE-combination treated mice indicate DC-mediated activation of CD8 T cells. To support this idea, we performed an antigen–antibody immune complex uptake assay using FITC labeled MUC1 peptide (16-mer containing PDTRPAP sequence) and anti-MUC1.IgE antibody. Our data demonstrate increased uptake of peptide-antibody uptake by DCs and increased proliferation (CFSE dilution) of CD8 T cells upon incubation with immune complex-loaded DCs (Fig. 4E and F). In parallel, we demonstrated increased CD8 T-cell activity (IFNγ production) from the spleen of anti-MUC1.IgE+anti-PD-L1+ PolyICLC mice upon incubation with KPC.MUC1 cells in the ex vivo ELISpot assay (Fig. 4G). In addition, we assessed the splenic NK function in the ex vivo CD107a-based degranulation assays. Extracellular appearance of CD107a, (LAMP1), suggests the fusion of lysosome with the plasma membrane in NK cells, transporting lytic granule outside for cytotoxic killing of target cells (35). Notably, NK cells from anti-MUC1.IgE+anti-PD-L1+PolyICLC mice demonstrated increased degranulation as compared with control mice (Fig. 4H and I). Altogether, our data explain that while both anti-MUC1.IgG1 and anti-MUC1.IgE promoted CD8 T-cell-mediated efficacy, additional enhancement of NK cell activity provided improved (but not significant) therapeutic efficiency of anti-MUC1.IgE + PolyICLC + anti-PD-L1 against pancreatic cancer.

Earlier, meta-analysis studies indicated an inverse relationship between allergy and the incidence of pancreatic cancer (14, 15). However, it is not known if IgE antibodies generated in response to allergic reactions can mount an immune response against the pancreatic tumor antigens. To determine the role of allergen-induced IgE responses, we investigated tumor growth of KPC mouse-derived tumor cell line before and after the sensitization and aerosol challenges with OVA in OVA-induced allergic model (Fig. 5A and G). OVA challenges significantly increased circulating IgE in both naïve and pancreatic tumor-bearing mice compared with saline-challenged control mice (Fig. 5B and H). Furthermore, we noted increased proportion of eosinophils in the bronchial alveolar lavage (BAL) fluid of OVA-challenged tumor-bearing mice but not in control counterparts (Fig. 5C and I). However, there was no impact of OVA-induced IgE on the growth of the pancreatic tumor in the preclinical model of pancreatic cancer. There was no significant difference in the pancreatic tumor growth, weight, and volume between saline and OVA-challenged mice in both the early- and late-tumor models (Fig. 5D–F and J–L). Together, our data imply that OVA-induced IgE is ineffective in limiting pancreatic tumor growth in preclinical model of pancreatic tumor in immunocompetent C57BL/6J mice. Hence, our data suggest the significance of tumor-specificity of IgE antibodies in controlling pancreatic tumor growth.

Multiple studies have highlighted the potential of IgE-based therapeutics in cancer. For example, an anti-HER2/neu IgE significantly prolongs the survival of D2F2/E2 tumor-bearing hFcϵRIα Tg mice, anti-PSA.IgE significantly extends the survival of hFcϵRIα mice harboring CT26-PSA tumors (22, 36). Also, chimeric mouse/human anti-MOv18 IgE (anti-folate receptor-α IgE) combined with human PBMCs prolongs the survival of ovarian cancer xenograft-bearing mice (37). Recently, clinical data from the Phase I trial demonstrate that anti-MOv18.IgE is well tolerated; only minor toxicities including, urticaria, were seen among the anti-MOv18.IgE-treated patients (18). In patients with PDAC, tumor antigen-specific IgE in peripheral circulation is already reported (17). More recently, a study showed a significant accumulation of IgE⁺ memory B cells and IgE antibodies in the pancreatic tumors of KPC mice (38). Taken this, we interrogated the potential utilization of tumor antigen-specific IgE against pancreatic cancer in the preclinical model of PDAC, which has not been examined so far.

This study demonstrated the uniform expression of the FcϵRI receptor in primary pancreatic and metastatic tumors. Our study verified the expression of FcϵRIα subunit of the FcϵRI on CD14⁺ monocytes, mast cells, and eosinophils in primary pancreatic tumors. Subsequently, we demonstrated FcϵRIα expression on mast cells and DCs in hMUC1/hFcϵRIα dTg mice. Next, we demonstrated that anti-MUC1.IgE+anti-PD-L1+PolyICLC combination induced MUC1-specific cellular immune responses that mediate rejection of Panc02.MUC1 tumors in a s.c. model of PDAC. The anti-MUC1.IgE, utilized here, recognizes the tandem repeat domain of human MUC1 and binds to the corresponding human FcϵRIα subunit of the FcϵRI receptor (21). In addition, we demonstrated that anti-MUC1.IgE+anti-PD-L1+ PolyICLC significantly restricted the growth of KPC.MUC1 orthotopic tumors as compared to anti-PD-L1+PolyICLC and anti-PSA.IgE+anti-PD-L1+PolyICLC treatment. Anti-PD-L1 and PolyICLC combination has previously been shown to restrict the growth of solid tumors, including melanoma (39). Interestingly, the addition of anti-MUC1.IgE to anti-PD-L1 and PolyICLC combination further enhances the antitumor immunity as depicted by attenuated tumor burden in triple combination-treated tumor-bearing mice. Noteworthy, we did not observe any rejection of orthotopic tumors with anti-MUC1.IgE-based combination treatment. Compared with s.c. tumors, C57BL/6-congenic KPC tumor cell-derived orthotopic tumors exhibit rapid proliferation, which provides a smaller time window for therapeutic combinations to be efficacious. Furthermore, the extensive desmoplasia in orthotopic models may somewhat decrease the entry of therapeutics into the tumor. Our study further demonstrated the critical importance of tumor-targeted specificity of IgE-FcϵRIα interaction by showing the efficacy of IgE-based therapy in tumor-bearing dTg mice but not in hMUC1Tg and hFcϵRIαTg mice. Tumor protective benefits of anti-MUC1.IgE requires both the MUC1 antigen and FcϵRIα receptor in our preclinical model. Earlier, we reported the efficacy of anti-MUC1.IgG1, in combination with anti-PD-L1+PolyICLC in the preclinical model of PDAC (20). Anti-MUC1.IgG1, used in the previous study, is a mouse antibody that targets the DTRPAP sequence in the tandem repeat of extracellular MUC1 protein. Anti-MUC1.IgE (mouse/human chimeric) also targets the same variable in the tandem repeat of human MUC1 as the IgG. Upon comparison, anti-MUC1.IgE-based combination therapy demonstrated moderately improved antitumor immunity as compared with anti-MUC1.IgG1-based combination in dTg mice. Both IgE and IgG combinations utilize antitumor CD8 T cell responses. It is noteworthy that although intratumoral CD8 T cells were comparable between anti-MUC1.IgG1 and anti-MUC1.IgE combination-treated tumors, a significant increase in the proportion of CD103⁺DCs were observed in the tumors from anti-MUC1.IgE combination-treated mice. It is well established that DCs express FcϵRIα and cross-present antigens to CD8 T cells (27). Our study also showed that splenic DCs from dTg mice could take up anti-MUC1.IgE-MUC1-peptide complex and stimulate CD8 T-cell proliferation. Hence, our data suggest that CD103⁺DC-CD8 T-cell interactions underlie the cell-mediated immune response of anti-MUC1.IgE+anti-PD-L1+ PolyICLC treatment.

In this report, we demonstrate an additional component of NK cell activity in anti-MUC1.IgE combination-treated mice. NK cell depletion abrogated the therapeutic efficacy of anti-MUC1.IgE- but not anti-MUC1.IgG1-based combination in pancreatic tumor-bearing mice. Although the total proportion of NK cells remained unaltered, our study showed a significant drop in the TIGIT⁺ and PD-1⁺ NK cells in anti-MUC1.IgE combination-treated tumors compared with control counterparts. PD-1 and TIGIT are checkpoint inhibitors that are common between CD8 and NK cells (40). TIGIT restricts NK cell function, and blockade of TIGIT increases the antitumor response of NK cells against trastuzumab-coated breast cancer cells (41, 42). Thus, our data suggest that anti-MUC1.IgE-based combination increases NK cell activity in pancreatic tumor-bearing mice. Macrophages and DCs can regulate NK cell function (43, 44). As such, macrophages and DCs express FcϵRIα (45). In an earlier report, anti-MOv18.IgE treatment has been shown to modulate the behavior of macrophages toward the antitumor phenotype (46). Surprisingly, previous studies have not explored the effect of IgE on NK cells in their in vivo model. Hence our study is novel in demonstrating the therapeutic benefits of IgE-based therapy in enhancing NK cell-mediated antitumor response in the preclinical model of PDAC. Our data warrant further investigations to understand the mechanism that underlies NK cell-mediated antitumor response in anti-MUC1.IgE+anti-PD-L1+ PolyICLC treated tumor-bearing mice.

Next, our study shows that the antigen specificity of IgE play a vital role in executing the antitumor response as nonspecific IgE, induced by OVA, failed to restrict tumor growth in the preclinical model of PDAC. Furthermore, our data demonstrate that pancreatic tumor burden does not alter OVA-induced IgE levels in the circulation. Our findings in the OVA-induced allergic asthma-PDAC model in mice contrast to the epidemiologic studies suggesting that allergic phenotype could reduce the risk of developing pancreatic cancer. Interestingly, another in vivo study demonstrates that OVA-induced allergic inflammation does not impact the growth of carcinogen-induced lung tumorigenesis in BALB/c mice (47). It is important to highlight that although our study is limited to only OVA-induced acute model of asthma, epidemiologic studies gathered evidences from the myriad of allergic diseases, including hay fever, skin allergy, and allergic rhinitis (14). Furthermore, though OVA-based models are frequently used to study pulmonary inflammation in mice, OVA is scarcely implicated in triggering human asthma (48). Moreover, the OVA-challenged mice exhibit an altered pattern of pulmonary inflammation, which is variant from that found in asthmatic individuals (49). Given the limitations of the OVA-based asthma model, other murine models of allergen-induced disease, including the house dust mite, cockroach, or alternaria model, might shed additional insight into the relationship between allergy/asthma conditions and risk of developing PDAC. Nonetheless, we successfully demonstrate that OVA-induced IgE (nonspecific IgE) is ineffective in restricting pancreatic tumor growth in immunocompetent mice. Moreover, our study provides crucial data on the pancreatic tumor growth in OVA-sensitized/challenged mice, which will provide a foundation for future investigations to understand the cross-talk between allergy and PDAC.

In conclusion, our study provides direct evidence that anti-MUC1.IgE has antitumor activity in the preclinical model of pancreatic cancer, and both the NK cell and T-cell axis contribute to the effect in this system. The NK cell effect was unexpected and hence needs further evaluation in the context of both other models of IgE and cancer.

J.A. Grunkemeyer reports grants from NIH during the conduct of the study. P.K. Singh reports grants from NIH/NCI during the conduct of the study. R. Madiyalakan reports other support from OncoQuest Inc. during the conduct of the study; also has a patent for OncoQuest Inc pending and issued. M.L. Penichet reports grants from NIH/NCI during the conduct of the study. J.A. Poole reports grants from NIEHS and NIOSH during the conduct of the study; other support from Astra Zeneca and Takeda; and personal fees from AgriSafety outside the submitted work. E.M. Jaffee reports other support from Abmeta; personal fees from Genocea, Achilles, DragonFly, CSTONE, Candel Therapeutics, Adaptive Biotech, Lustgarten, PICI, NextCure, and Stimit; grants from BMS and Genentech outside the submitted work. M.A. Hollingsworth has ownership of Oncocare Therapeutics stock. K. Mehla reports grants from OncoQuest Inc. during the conduct of the study; also has a patent 63237634 pending. No disclosures were reported by the other authors.

S.D. Markov: Conceptualization, data curation, formal analysis, investigation, methodology, writing–review and editing. T.C. Caffrey: Data curation, formal analysis, investigation, methodology, writing–review and editing. K.A. O'Connell: Investigation. J.A. Grunkemeyer: Investigation. S. Shin: Data curation, investigation. R. Hanson: Data curation, formal analysis. P.P. Patil: Data curation, investigation. S.K. Shukla: Data curation, investigation. D. Gonzalez: Data curation, investigation. A.J. Crawford: Data curation. K.E. Vance: Data curation. Y. Huang: Investigation. K.C. Eberle: Investigation. P. Radhakrishnan: Investigation, writing–review and editing. P.M. Grandgenett: Resources, funding acquisition. P.K. Singh: Resources, supervision, funding acquisition, writing–review and editing. R. Madiyalakan: Conceptualization, resources, writing–review and editing. T.R. Daniels-Wells: Conceptualization, writing–review and editing. M.L. Penichet: Conceptualization, writing–review and editing. C.F. Nicodemus: Conceptualization, writing–review and editing. J.A. Poole: Resources, funding acquisition, methodology, writing–review and editing. E.M. Jaffee: Conceptualization, writing–review and editing. M.A. Hollingsworth: Conceptualization, resources, supervision, funding acquisition, writing–review and editing. K. Mehla: Conceptualization, formal analysis, supervision, funding acquisition, investigation, methodology, writing–original draft, writing–review and editing.

We would like to thank the University of Nebraska Medical Center Rapid Autopsy Pancreatic Program and the patients who generously donated their samples. We would also like to thank Jonathan Pester for his help in the pilot animal experiments. Besides, we would like to thank Camila G. Pacheco and Amy J. Nelson for their technical help in the animal studies.

K. Mehla was supported by NCI-SPORE P50 CA127297 Career Development Award. This study was also funded in part by the support of grants from the NIH grant under the project numbers R01CA163649, R01CA210439, and R01CA216853 to P.K. Singh, and R01CA181115 to M.P. the Specialized Programs for Research Excellence (SPORE, NCI) under the project number 2P50 CA127297 to M.A. Hollingsworth and P.K. Singh, NCI Research Specialist award (5R50CA211462) to P.M. Grandgenett and the Pancreatic cancer detection consortium U01CA210240 to M.A. Hollingsworth. This work was also supported by grants from the National Institute of Environmental Health Sciences (R01ES019325) and National Institute for Occupational Safety and Health (U54OH010162) to J.A. Poole. This study was also funded in part by the support of award from OncoQuest Pharmaceuticals Inc.

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