Iron Chelation Therapy Elicits Innate Immune Control of Metastatic Ovarian Cancer

doi:10.21203/rs.3.rs-3399219/v1

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Iron Chelation Therapy Elicits Innate Immune Control of Metastatic Ovarian Cancer

https://doi.org/10.21203/rs.3.rs-3399219/v1

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published 28 Jul, 2024

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Iron accumulation in cancer cells contributes to malignant progression and chemoresistance. While disrupting this process can influence various hallmarks of cancer, the immunomodulatory effects of chelating iron in tumors remain undefined. Here, we report that treatment with deferiprone, an FDA-approved iron chelator, elicits innate immune responses that control metastatic ovarian cancer. Deferiprone reprogrammed ovarian cancer cells towards an immunostimulatory state characterized by enhanced production of type I interferon (IFN) and surface overexpression of molecules that activate natural killer (NK) cells. Mechanistically, this reprogramming was driven by innate sensing of mitochondrial DNA in the cytosol and concomitant activation of nuclear DNA damage responses evoked upon iron chelation. Deferiprone administration synergized with chemotherapy and prolonged the survival of mice bearing metastatic ovarian cancer by bolstering intratumoral NK cell infiltration and type I IFN responses. Iron chelation may represent an alternative immunotherapeutic approach for malignancies that are normally refractory to T cell-centric modalities.

Biological sciences/Cancer/Gynaecological cancer/Ovarian cancer

Biological sciences/Immunology/Immunotherapy

Iron is an essential micronutrient implicated in the homeostatic regulation of key cellular processes such as protein folding, mitochondrial respiration, DNA replication, proliferation, and metabolism¹. Disruption of iron homeostasis is associated with the initiation and maintenance of diverse pathologies, including cancer². Malignant cells have evolved strategies that enable them to thrive under adverse conditions, but at the cost of an elevated bioenergetic and metabolic demand that is highly dependent on iron utilization^3-5. Therefore, cancer cells employ multiple mechanisms to ensure sustained iron availability, including overexpression of iron uptake and storage pathways, as well as downregulation of iron export proteins^3-5.

High-grade serous ovarian cancer (HGSOC), the most common and aggressive form of ovarian cancer⁶, is resistant to standard treatments and refractory to current immunotherapies that harness the anti-tumor activity of T cells^6,7. Disruptive therapeutic strategies are urgently needed in the clinic to improve the dismal survival of women with this disease. Interestingly, HGSOC is the prototypical iron-addicted malignancy^8,9. Tumor specimens from HGSOC patients demonstrate increased expression of transferrin receptor (TFR1) -an iron importer- and decreased levels of the iron efflux pump ferroportin (FPN) compared with normal ovarian tissue or low-grade serous ovarian tumors^8,9. Previous studies indicate that iron augments the proliferative and invasive capacities of ovarian tumor-initiating cells, and that ectopic overexpression of FPN in this population compromises peritoneal tumor growth in immunodeficient mice⁸. Nonetheless, the therapeutic potential of targeting iron overload in metastatic ovarian cancer, and the mechanistic basis through which iron chelation may represent a central vulnerability for these malignant cells, have not been established.

Here, we sought to investigate the functional requirements of ovarian cancer cells on iron availability, and evaluate the potential anti-ovarian cancer effects of the intracellular iron chelator deferiprone as a new therapeutic strategy that could be rapidly translated into a clinical setting given the widespread use of this FDA-approved agent for the treatment of patients with transfusional iron-overload¹⁰.

Our studies reveal that treatment with deferiprone blocks mitochondrial respiration while concurrently activating nuclear DNA damage responses in ovarian cancer cells. This dual effect unleashes innate immune programs mediated by type I interferon (IFN) signaling and natural killer (NK) cells that impair metastatic progression and enhance the efficacy of fist-line chemotherapy. Our findings suggest that deferiprone might be repurposed as a new immunotherapeutic agent to treat patients with metastatic ovarian cancer, which is generally insensitive to T cell-based immunotherapy^6,7

Expression of iron-related gene signatures is associated with poor prognosis in HGSOC patients.

Ovarian tumors demonstrate a distinctive iron-dependent phenotype⁸, but whether the expression status of iron-related gene signatures in HGSOC specimens predicts prognosis is unknown. We exploited published single-cell RNA-seq data generated from metastatic tumor samples of HGSOC patients¹¹ and analyzed the expression of gene programs involved in iron homeostasis, transport, accumulation, and function. Compared with immune and stromal cells in the same microenvironment, epithelial ovarian cancer (EOC) cells demonstrated a significant increase in diverse iron-related gene signatures, especially the iron sequestration signature (Fig. 1a). Further analysis of deconvoluted bulk RNA-seq and clinical data from 292 HGSOC patients in The Cancer Genome Atlas (TCGA)^12,13 revealed that the presence of gene signatures involved in transmembrane iron transport or import across the plasma membrane, as well as high scores of a ferrous iron binding gene signature in cancer cells, is associated with a reduced overall survival in HGSOC patients (Fig. 1b).

Women with advanced ovarian cancer often present with accumulation of ascites, a malignant and immunosuppressive peritoneal fluid associated with drug resistance and metastatic disease¹⁴. Proteomic analyses of patient-derived ascites samples revealed that this fluid is enriched for proteins implicated in iron transport and metabolism, including serotransferrin (TF), α-1-antitrypsin (PI), ceruloplasmin (CP), the hepcidin-binding protein α-2-macroglobulin (A2M), and apolipoprotein B-100 (SERPIN1), among several others (Fig. 1c and Table S1 and S2). We also found that ~ 50% of the clinical ascites samples analyzed contained total iron levels higher than the range typically found in human serum (Fig. 1d). Unbiased analyses of cytokines and chemokines in the same samples further indicated that the total iron concentration in this fluid positively correlate with the levels of multiple tumorigenic factors such as vascular endothelial growth factor A (VEGFα), C-X-C motif chemokine ligand 5 (ENA-78, CXCL5), C-X-C motif chemokine ligand 8 (CXCL8, IL-8), platelet derived growth factor receptor beta (PDGF), and C-C motif chemokine ligand 7 (MCP-3, CCL-7)^15–18 (Fig. 1e).

These data uncover that iron-related gene signatures are overexpressed by malignant cells within metastatic HGSOC tumors, and that iron transport-related gene signatures are particularly associated with reduced patient survival. In addition, our analyses indicate that the ascites may function as a local source of iron that is readily available to ovarian cancer cells overexpressing iron-related transporters.

Therapeutic effects of iron chelation in ovarian cancer hosts.

We sought to determine the potential anti-tumor effects of targeting iron accumulation in mouse models of metastatic ovarian cancer. To this end, we used the orthotopic ID8-Defb29/Vegfa model, which engenders a highly chemoresistant and immunosuppressive peritoneal carcinomatosis that recapitulates the advanced stages of human ovarian cancer^19–21. Consistent with our observations in patient specimens, we found progressive accumulation of iron in the peritoneal cavity of mice developing ID8-Defb29/Vegfa tumors (Fig. 2, a and b). scRNA-seq analyses also revealed that diverse malignant cell states residing in this anatomical location present high enrichment scores for several iron-related gene signatures, compared with immune and stromal cell types present in the same milieu (Fig. 2, c and d). Thus, we evaluated whether the dietary iron levels may influence metastatic disease progression. To this end, mice were intraperitoneally challenged with parental ID8 ovarian tumors and three days later, isocaloric diets containing low, normal, or high amounts of iron (3, 45, or 300 ppm, respectively) were provided ad libitum until endpoint. Altering the iron content of diet did not affect the progression of these peritoneal tumors as all experimental groups demonstrated similar survival rates (Fig. S1a). Hence, we sought to assess whether blocking iron accumulation in the ovarian cancer microenvironment using a pharmacological approach might elicit therapeutic effects.

Deferiprone is an FDA-approved intracellular iron chelator used to treat transfusional iron overload in patients with β-thalassemia^10,22. This agent has also been tested in patients with diverse neurological disorders characterized by dysregulated iron accumulation (NCT01539837, NCT03234686, NCT02728843, NCT00530127, NCT02164253, NCT00943748, NCT02174848), but its potential activity against ovarian cancer has not been evaluated. Due to the enrichment of multiple iron-related gene signatures in human EOC cells (Fig. 1a) and in chemoresistant malignant cells naturally found in mice bearing ID8-Defb29/Vegfa ovarian tumors (Fig. 2d), we sought to evaluate the therapeutic effects of deferiprone in this model when administered alone or in combination with cisplatin, which is the first-line chemotherapy used in the clinic for this disease (Fig. 2e). Consistent with the intrinsic chemoresistant nature of ID8-based tumors^19,20,23, cisplatin had a minor impact on disease progression (Fig. 2, f-i) and minimally extended overall host survival (Fig. 2j). In contrast, deferiprone administration was sufficient to decrease the number of malignant cells in the peritoneal cavity while simultaneously reducing ascites accumulation, omental metastases, and tumor-induced splenomegaly (Fig. 2, f-i). Strikingly, tumor-bearing mice receiving deferiprone demonstrated a ~ 25% increase in their median survival rates in comparison with untreated mice, and this therapeutic benefit was doubled upon combination treatment with cisplatin (Fig. 2j). The therapeutic effects of deferiprone were dose-dependent (Fig. S1b), and a comparable survival benefit was attained when the drug was administered either intraperitoneally or orally (Fig. S1c).

To further confirm these findings, we used the PPNM model of high-grade serous tubo-ovarian carcinoma (HGSC) that carries the most common genetic abnormalities present in human HGSOC²⁴. In this independent system, deferiprone also induced significant therapeutic effects characterized by reduced peritoneal carcinomatosis (Fig. 2, k and l) and increased host survival (Fig. 2m), which was drastically augmented upon combination with cisplatin (Fig. 2m). Importantly, mice bearing ID8 or PPNM metastatic ovarian tumors did not show major signs of toxicity or weight loss during treatment with deferiprone, both as a single agent and in combination with cisplatin (Fig. S1, d-e).

Hence, we conclude that ovarian cancer progression is characterized by iron accumulation in the peritoneal cavity and an enrichment of iron-related gene signatures in malignant cells present in this milieu. Moreover, treatment with deferiprone induces significant responses against ovarian cancer that enhance the effects of first-line chemotherapy in two independent mouse models of metastatic disease.

Treatment with deferiprone promotes NK cell-dependent control of metastatic ovarian cancer.

We next sought to determine whether deferiprone administration impacts the aggressive microenvironment of metastatic ovarian cancer. To this end, female mice bearing peritoneal ID8-Defb29/Vegfa tumors were treated with deferiprone, alone or in combination with cisplatin as shown in Fig. 2e, and mice were euthanized 24 hours after the last treatment for FACS-based analysis (Fig. S2) of peritoneal immune infiltrates and histological assessment of metastatic omental lesions. When given alone or in combination with cisplatin, deferiprone increased the proportion of peritoneal macrophages in tumor-bearing mice (Fig. S3a). Deferiprone also augmented the percentage of monocytes in the peritoneum while modestly altering dendritic cell (DC), B cell, and T cell infiltration (Fig. S3, b-f). The therapeutic effects of deferiprone, alone or in combination with cisplatin, remained unaltered in Rag2^−/− mice that lack T and B cells (Fig. S3, g-h), demonstrating that the observed survival benefit was not mediated by improved adaptive immunity. Strikingly, iron chelation using deferiprone significantly increased the proportion of NK cells in the peritoneal cavity (Fig. 3a) while eliciting robust NK cell infiltration into metastatic omental lesions (Fig. 3, b and c, and Fig. S4). These changes were specific to malignant sites, as negligible changes in splenic NK cell proportions were found in treated mice (Fig. S3i). To define whether NK cells mediated the therapeutic effects of deferiprone, we used antibody-mediated depletion of this population in tumor-bearing mice (Fig. 3d). NK cell ablation did not affect the overall survival rates of mice receiving vehicle control or cisplatin (Fig. 3e), yet it reduced the therapeutic effects of deferiprone when administered alone and more drastically, upon combination with cisplatin (Fig. 3, f and g). These data reveal that, at least in mice, deferiprone elicits major T and B cell-independent therapeutic responses against metastatic ovarian cancer that are partly mediated by NK cells.

Deferiprone induces immunostimulatory gene programs in ovarian cancer cells.

We sought to dissect the mechanisms mediating the surprising immunomodulatory effects of deferiprone in ovarian cancer hosts. To this end, we first identified the main molecular processes that this agent altered in ovarian cancer cells. Viability assays indicated that deferiprone did not induce direct cytotoxic effects at concentrations below 200 µM in multiple murine ovarian cancer cell lines, even when exposed to the compound for up to 48 hours (Fig. S5a). In addition, the combination of deferiprone and cisplatin did not exert synergistic cytotoxic activity in these models (Fig. S5b). Hence, we evaluated whether deferiprone could alter global gene expression profiles in ovarian cancer cells. RNA sequencing (RNA-seq) analyses identified 995 differentially expressed genes, of which 97 were downregulated and 898 were upregulated, in ID8-Defb29/Vegfa cells exposed to deferiprone for 12 hours compared with their control counterparts treated with vehicle (fold change > 2.0; FDR < 5%; P-value < 0.05) (Table S3). We next examined the differentially expressed genes by ingenuity pathway analysis (IPA) to identify potential upstream regulators mediating the observed transcriptomic changes. As expected, the transferrin receptor (TFRC) emerged as a top regulator whose downstream target genes were inhibited upon deferiprone exposure (Fig. 4a). Surprisingly, gene programs controlled by immunosuppressive TGFb, IL-10, and prostaglandin signaling (PTGER4) were repressed in deferiprone-treated cancer cells (Fig. 4a), while diverse elements mediating the production and biological activity of type I IFN (MYD88, STING1, TBK1, IRF3, IFNB1, IFNAR1 and STAT1) were enriched in cells responding to deferiprone (Fig. 4a). Hypoxia inducible factor 1 subunit alpha (HIF1A) and activating transcription factor 4 (ATF4), which have been shown to coordinate mitochondrial stress responses^25,26, also emerged as upstream regulators activated by deferiprone (Fig. 4a). Interestingly, gene networks controlled by PARP1 and NCOA2, which orchestrate DNA damage responses (DDR) and maintain genome integrity, were also predicted to be activated in ovarian cancer cells treated with deferiprone (Fig. 4a). Further examination of the differentially expressed genes based on these analyses revealed that deferiprone upregulated several transcripts implicated in cytokine-to-cytokine receptor interactions, type I IFN signaling, mitophagy, and NK cell activation (Fig. 4b). Of note, within these categories, we observed marked overexpression of Fas and Tnfrsf10b (encoding the death receptors FAS and DR5)²⁷, type I IFN-stimulated genes (ISGs) such as Rsad2, Cxcl10, Ddx58, and Mx1, mitochondrial stress markers (Pink1, Atgb9, Bnip3, and Ddit4), as well as genes encoding diverse NKG2D ligands (Ulbp1/MULT1 and H60b) (Fig. 4b). Indeed, in vitro deferiprone exposure rapidly upregulated surface expression of DR5 while triggering a dose- and time-dependent overexpression of MULT1 on multiple ovarian cancer cell lines (Fig. S5, c-e).

To validate these findings, female mice with established ID8-Defb29/Vegfa tumors were treated with vehicle control or deferiprone for three consecutive days, and metastatic cancer cells were sorted from peritoneal lavage samples 24 hours after the last treatment. Deferiprone administration upregulated Tnfrsf10b, Fas, Ulbp1, Ddit4, and multiple type I IFN-related genes such as Ifna, Ifnb1, Isg15 and Ifit1 in malignant cells progressing in vivo (Fig. 4c). Accordingly, tumor-bearing mice treated with deferiprone showed surface overexpression of DR5 on ovarian cancer cells (Fig. 4d) and increased levels of IFN-β1 and the type I-IFN-dependent chemokines CCL12, CCL20, and CX3CL1 (Fig. 4e) in the peritoneal cavity, compared with their control counterparts receiving vehicle. These results were further validated using primary cultures of ovarian cancer organoids (n = 4) generated from patients with advanced disease (Table S4). Notably, deferiprone exposure triggered a dose-dependent overexpression of ATG9B, TNFRSF10B, type I IFN transcripts, ISGs, and genes encoding NKG2D ligands such as MICA, MICB, and ULBP1-3 in 75% of the independent organoids analyzed (Fig. 4f).

Hence, deferiprone-treated ovarian cancer cells upregulate gene programs involved in mitochondrial stress and DNA damage responses while concurrently overexpressing factors that promote NK cell activation and type I IFN production and sensing.

Deferiprone triggers innate immune signaling in malignant cells.

Iron is an essential element involved in diverse cellular homeostatic and metabolic processes²⁸. Enzymes containing iron-sulfur (Fe-S) clusters play a crucial role in the regulation of electron transport and mitochondrial respiration²⁹. Iron chelation provokes mitochondrial anomalies in malignant cells³⁰, but the potential immunomodulatory consequences of this process are unknown. Importantly, disruption of mitochondrial activity and/or integrity can ignite cell-intrinsic inflammatory programs via activation of cytosolic innate immune sensors that detect the leakage of mitochondrial DNA (mtDNA)³¹. Since our transcriptomic analyses indicated upregulation of mitochondrial stress responses in deferiprone-treated cancer cells (Fig. 4, a and b), we sought to determine whether mitochondrial perturbations provoked by this iron chelator mediated the observed induction of type I IFN and NK cell-activating factors.

Ovarian cancer cells overloaded with ammonium iron (II) sulfate demonstrated severe mitochondrial iron accumulation, which was effectively mitigated by treatment with deferiprone (Fig. S6, a and b). Hence, we examined whether deferiprone could affect mitochondrial respiration in ovarian cancer cells. Assessment of oxygen consumption rates (OCR) using extracellular flux analyzers determined that deferiprone rapidly causes a dose-dependent decrease in their basal respiration, maximal respiration, proton leak, coupling efficiency, and ATP production (Fig. 5, a and b). Furthermore, we observed that malignant cells treated with deferiprone exhibited increased amounts of mtDNA in their cytosol, as evidenced by quantification of DNA fragments corresponding to the mitochondrial cytochrome c oxidase (mt-Cox1) gene (Fig. 5c). Hence, deferiprone readily interrupts mitochondrial respiration and causes leakage of mtDNA into the cytosol of ovarian cancer cells.

mtDNA is sensed in the cytoplasm by the cyclic GMP-AMP synthase (cGAS)–stimulator of interferon genes (STING) system³², which leads to TBK1-mediated phosphorylation of the interferon regulatory factor 3 (IRF3) that enables the expression of genes encoding type I IFN^33,34. Thus, we next investigated whether activation of this innate immune pathway by leaked mtDNA mediated the induction of type I IFN genes in deferiprone-treated cancer cells. Deferiprone failed to induce Ifnb1 and the prototypical ISG Mx1 in ρ⁰ ovarian cancer cells devoid of mtDNA³⁵ (Fig. S6, c and d), confirming the role of mtDNA in this process. We also observed robust IRF3 phosphorylation in deferiprone-treated ovarian cancer cells (Fig. S6e), further suggesting activation of the cGAS-STING-IRF3 axis upon iron chelation. To functionally validate the role of this pathway, we used the STING inhibitor H-151 (Ref. ³⁶) and generated isogenic ovarian cancer cell lines in which IRF3 expression was abrogated via CRISPR-Cas9 (Fig. S6, f and g). Notably, suppressing STING activation (Fig. 5d) or ablating IRF3 (Fig. 5e) prevented the induction of Ifnb1 and Mx1 transcripts in ovarian cancer cells treated with deferiprone. These results indicate that deferiprone compromises mitochondrial respiration and causes release of mtDNA into the cytosol, evoking type I IFN expression in ovarian cancer cells via the cGAS-STING-IRF3 axis. Intriguingly, however, we observed that targeting STING or IRF3 did not affect the induction of Tnfrsf10b (DR5) or Ulbp1 (MULT1) in deferiprone-exposed ovarian cancer cells (Fig. S6, h and i), suggesting an independent, yet concurrent immunostimulatory mechanism ignited by this iron chelator.

Multiple DNA repair enzymes use iron as an central cofactor³⁷. Disruption of iron metabolism can therefore perturb DNA synthesis and repair, leading to the activation of the DNA damage response (DDR)³⁸. Ataxia-telangiectasia-mutated (ATM) and ataxia telangiectasia and Rad3-related (ATR) govern the DDR by activating their downstream checkpoint kinases CHK1 and CHK2^39,40. Importantly, these pathways have been shown to mediate the induction of NKG2D ligands on cancer cells undergoing canonical DNA damage⁴¹. Therefore, we sought to define whether the induction of DR5 and MULT1 on ovarian cancer cells treated with deferiprone was mediated by the DDR. Inhibiting ATR or CHK1/2 impaired the surface overexpression of DR5 and MULT1 in ovarian cancer cells responding to deferiprone, while ATM inhibition had negligible effects in this system (Fig. 5, f-i). Of note, similar effects were observed when ovarian cancer cells were exposed to the classical DNA polymerase inhibitor aphidicolin⁴² (Fig. S6, j-m).

Collectively, these results indicate that chelating intracellular iron with deferiprone evokes two mutually reinforcing immunostimulatory mechanisms in ovarian cancer cells: the leakage of mtDNA that drives type I IFN production via the cGAS-STING-IRF3 axis, and DDR activation that bolsters surface expression of NK cell-activating factors such as DR5 and MULT1.

Deferiprone-induced type I IFN supports NK cell responses by enhancing IL-15 expression in tumor-associated DCs.

We next evaluated whether the immunotherapeutic effects of deferiprone were indeed mediated by increased type I IFN signaling in the ovarian cancer microenvironment. To this end, female mice bearing peritoneal ID8-Defb29/Vegfa tumors were treated with deferiprone as a single agent or in combination with cisplatin, and mice further received antibodies blocking the interferon alpha and beta receptor subunit 1 (IFNAR1) or their corresponding isotype control (Fig. S7a). Hindering type I IFN signaling using this approach did not affect the overall survival rates of ovarian cancer-bearing mice left untreated or receiving cisplatin (Fig. 6a), yet it markedly reduced the therapeutic benefit conferred by deferiprone when administered alone and in combination with cisplatin (Fig. 6, b and c). Hence, type I IFN signaling operates as a dominant driver of the anti-ovarian cancer effects elicited by this intracellular iron chelator.

Type I IFN is crucial for the activation, expansion, and anti-tumor function of NK cells in cancer^43–45. We hypothesized that type I IFN elicited by deferiprone promoted NK cell accumulation at metastatic tumor sites. To test this, we focused on deferiprone and cisplatin cotreatment as their combination induced maximal immunotherapeutic effects mediated by NK cells (Fig. 3g). Notably, antibody-mediated blockade of IFNAR1 prevented NK cell accumulation at tumor sites in response to combination treatment (Fig. S7b and Fig. 6, d and e), establishing a major role for the type I-IFN-NK cell axis in this therapeutic setting.

How does type I IFN induced by deferiprone support NK cell accumulation at metastatic ovarian cancer locations? We focused on IL-15 as this cytokine promotes the survival, proliferation, and cytotoxicity of NK cells⁴⁶. Furthermore, type I IFN have been shown to induce expression of IL-15 by DCs, which possess a remarkable capacity to deliver this cytokine to neighboring NK cells^47–49. Indeed, we observed that bone marrow-derived DCs (BMDCs) generated from IL-15^2A−eGFP reporter mice⁵⁰ strongly produced IL-15 upon stimulation with recombinant IFN-β (Fig. S7c). We thus examined whether enhanced type I IFN production in the tumor microenvironment driven by deferiprone administration could induce IL-15 expression by DCs normally residing in the same malignant milieu^19,20,23. IL-15^2A−eGFP reporter mice bearing peritoneal ID8-Defb29/Vegfa carcinomatosis were acutely treated with vehicle control, cisplatin, deferiprone, or the combination of both drugs, as shown in Fig. S7d, and immunophenotyping analyses were conducted thereafter. Confirming our initial observations (Fig. 3a), deferiprone was sufficient to increase the proportion of NK cells at tumor locations, compared with control groups receiving vehicle or cisplatin alone (Fig. 6f), and these effects correlated with the levels of IFN-β1 in the peritoneal cavity (Fig. 6g). Ovarian cancer-bearing mice treated with deferiprone − alone or in combination with cisplatin − exhibited a significant increase in the proportion of tumor-associated DCs (tDCs) expressing high levels of IL-15 compared with their control counterparts (Fig. 6, h-j). Notably, high IL-15 expression by tDCs correlated with the levels of IFN-β1 at tumor sites (Fig. 6k) and these effects diminished when experiments were repeated under IFNAR1 blockade (Fig. S7b and Fig. 6, l-n).

Hence, we conclude that deferiprone evokes therapeutic innate type I IFN signaling at metastatic tumor locations, increasing IL-15 expression by tDCs and sustaining NK cell-mediated responses that hinder malignant progression.

In this study, we provide experimental evidence indicating that disruption of iron metabolism in ovarian cancer cells using a clinically available iron chelator represents a major opportunity to induce innate immune responses capable of delaying metastatic disease progression and enhancing the effects of first-line chemotherapy.

Multiple analyses reported herein uncover the clinical relevance of iron dysregulation in human ovarian cancer. First, evaluation of scRNA-seq and bulk RNA-seq data from HGSOC specimens identified the enrichment of iron-related signatures specifically in ovarian cancer cells, which had significant prognostic value in women with this disease. Second, we found high concentrations of iron in ascites samples obtained from ovarian cancer patients, which correlated with the intrinsic levels of previously reported tumorigenic factors. Third, we determined that iron-transporting and iron-capturing proteins are markedly enriched in this malignant fluid, indicating that iron is readily available for metastatic ovarian cancer cells that inhabit the peritoneal cavity.

In various cancer types, targeting the excessive utilization of iron has been explored through strategies aimed at inducing ferroptosis⁵¹. However, this approach demands specific conditions, including a defective anti-oxidant machinery and increased lipid peroxidation within the cancer cell, which may limit its full translational potential⁵². Conversely, iron chelation has been widely used in diseases characterized by abnormal iron accumulation⁵³. Various iron chelators have received FDA approval for clinical use⁵⁴. Importantly, deferiprone is the only one with intracellular chelation capabilities^55,56 that can facilitate iron redistribution within the organism, hence avoiding negative side effects associated with excessive iron excretion⁵⁵.

The complex microenvironments engendered by late-stage ovarian tumors that disseminate throughout the peritoneal cavity play a pivotal role as mediators of chemoresistance and immunosuppression^57,58. Our study unveils that deferiprone administration can drastically reshape the landscape of immune cells infiltrating this complex metastatic milieu, inducing significant accumulation of NK cells in the peritoneal cavity and the omentum that partly mediate the therapeutic effects of this drug. Since dysfunctional NK cells devoid of cytotoxic capacity are commonly found in the ascites of ovarian cancer patients^59,60, our findings suggest that treatment with deferiprone might represent a new strategy to reactivate these cells at strategic tumor sites.

Previous studies demonstrated that deferiprone can mitigate the adverse effects of inflammatory processes caused by mitochondrial iron accumulation^56,61. In the context of cancer, deferiprone has been linked to the induction of mitochondrial dysfunction leading to mitophagy and uncontrolled production of reactive oxygen species in malignant cells^30,62. Nonetheless, whether iron chelation could elicit immune-modulatory mechanisms in cancer hosts had not been established. Our research addressed this major gap in knowledge by revealing that deferiprone triggers cancer cell-intrinsic innate immune signaling driven by mtDNA sensing in the cytosol and activation of the nuclear DDR. These parallel effects culminate in the production of type I IFN and the upregulation of NK cell-activating molecules on ovarian cancer cells.

Type I IFN has been demonstrated to exert potent anti-cancer effects driven by the activation of both innate and adaptive immune responses⁶³. Importantly, we found that deferiprone bolstered IL-15 expression in tDCs by enhancing type I IFN production at tumor sites. Accordingly, blocking type I signaling impaired IL-15 expression by tDCs, compromised NK cell accumulation at tumor locations, and drastically reduced the overall survival benefit conferred by combination treatment with deferiprone and cisplatin.

Taken together, our results indicate that iron chelation therapy with deferiprone evokes relevant effects against metastatic ovarian cancer by activating the type I IFN-NK cell axis. Disrupting iron accumulation in the tumor microenvironment may therefore represent a new immunotherapeutic approach for aggressive malignancies, like ovarian cancer, that are refractory to current T cell-centric modalities such as immune checkpoint blockade and adoptive cellular therapy.

ACKNOWLEDGMENTS

We thank the Scientific Computing Unit, the Flow Cytometry Core Facility, the Proteomics and Metabolomics Core Facility, and the Genomics Resources Core Facility at Weill Cornell Medicine for their excellent assistance with multiple analyses. We are especially grateful to F.J. Carmona for providing critical comments and suggestions on this manuscript. This work was supported by NIH R01 NS114653, CA271619, and CA282072 (J.R.C-R.); NIH R01 CA271915 (L.G.); NIH R01 CA249054 (C.E.M.); U.S. Department of Defense W81XWH2010191, W81XWH-16-1-0438, W81XWH-22-OCRP-IIRA, W81XWH2110478, and W81XWH2110357 (J.R.C-R.); U.S. Department of Defense BC180476P1 and BC210945 (L.G.); NIH training grants T32 5T32AI134632-02 and F31CA257631 (A.E.); The Cancer Research Institute-Irvington Institute Postdoctoral Fellowship (C-S.C. and C.S.); The Sigrid Jusélius Foundation (A.V. and L.S.); The Cancer Foundation Finland (A.V. and L.S.); ERA PerMed JTC2020 PARIS/Academy of Finland project 344697l (A.V.); Foundation for the Finnish Cancer Institute (K. Albin Johansson Cancer Research Fellowship for A.V); European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101067835 (M.F.); The Ovarian Cancer Research Alliance (D.Z.); National Cancer Center, Korea NCC-19112605 (M.S); and National Research Foundation of Korea grants MSIT 2020R1C1C1010303 and RS-2023-00213292 (M.S).

COMPETING INTERESTS / DISCLOSURES

J.R.C.-R. holds patents on the use immune modulators for ovarian cancer treatment and serves as scientific consultant for Moderna, Immagene B.V., and Autoimmunity Biologic Solutions, Inc. D.Z. reports institutional grants from Merck, Genentech, AstraZeneca, Plexxikon, and Synthekine, and personal fees from AstraZeneca, Xencor, Memgen, Takeda, Synthekine, Immunos, Tessa Therapeutics, Miltenyi, and Calidi Biotherapeutics. D.Z. owns a patent on use of oncolytic Newcastle Disease Virus for cancer therapy. L.G. is/has been holding research contracts with Lytix Biopharma, Promontory and Onxeo, has received consulting/advisory honoraria from Boehringer Ingelheim, AstraZeneca, OmniSEQ, Onxeo, The Longevity Labs, Inzen, Imvax, Sotio, Promontory, Noxopharm, EduCom, and the Luke Heller TECPR2 Foundation, and holds Promontory stock options. All other authors declare no potential conflicts of interest.

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Survival analyses using TCGA patient cohorts

The bulk RNA-seq expression data from The Cancer Genome Atlas (TCGA) was deconvoluted with PRISM¹³ in order to separate signals from EOCs, immune cells, and fibroblasts. Clinical data for TCGA cohort¹² was downloaded from cBioPortal database (http://www.cbioportal.org/study/summary?id=ov_tcga_pub). Analysis was carried out on R version 4.0.3. Using the Molecular SIGnature Data Base (https://www.gsea-msigdb.org/) iron related signatures were evaluated and those with significant p-value were selected:

GO:0034755: GOBP_REGULATION_OF_IRON_ION_TRANSMEMBRANE_TRANSPORT; gene members: iron-sulfur cluster assembly enzyme (ISCU), homeostatic iron regulator (HFE), interferon gamma (IFNG), microRNA 210 (MIR210), ATPase copper transporting alpha (ATP7A), beta-2-microglobulin (B2M), transferrin (TF)

GO:0098711: GOBP_IRON_ION_IMPORT_ACROSS_PLASMA_MEMBRANE; gene members: iron-sulfur cluster assembly enzyme (ISCU), STEAP2 metalloreductase (STEAP2), interferon gamma (IFNG), microRNA 210 (MIR210), solute carrier family 39 member 8 (SLC39A8).

GO:0008198: GOMF_FERROUS_IRON_BINDING; gene members: cysteine dioxygenase type 1 (CDO1), egl-9 family hypoxia inducible factor 2 (EGLN2), egl-9 family hypoxia inducible factor 3 (EGLN3), DnaJ heat shock protein family (Hsp40) member C24 (DNAJC24), alkB homolog 2, alpha-ketoglutarate dependent dioxygenase (ALKBH2), alkB homolog 3, alpha-ketoglutarate dependent dioxygenase (ALKBH3), ferrochelatase (FECH), iron-sulfur cluster assembly enzyme (ISCU), 3-hydroxyanthranilate 3,4-dioxygenase (HAAO), frataxin (FXN), ferritin heavy chain 1(FTH1), ferritin light chain (FTL), diphthamide biosynthesis 3 (DPH3), ferritin heavy chain 1 pseudogene 19 (FTH1P19), phytanoyl-CoA 2-hydroxylase (PHYH), ferritin heavy chain like 17 (FTHL17), acid phosphatase 5, tartrate resistant (ACP5), egl-9 family hypoxia inducible factor 1 (EGLN1), tet methylcytosine dioxygenase 2 (TET2), hypoxia inducible factor 1 subunit alpha inhibitor (HIF1AN), synuclein alpha (SNCA), transferrin (TF), tyrosine hydroxylase (TH), FTO alpha-ketoglutarate dependent dioxygenase (FTO), alkB homolog 1, histone H2A dioxygenase (ALKBH1), ferritin mitochondrial (FTMT), hephaestin (HEPH).

Signature expression scores for each deconvoluted cell type in each sample were calculated with AUCell version 1.12.0⁶⁴, which calculates the activity of a gene set using a rank-based method. Six genes (FTH1P19, MIR210, BOLA2B, ERFE, UQCRFS1P1 and CYP2G1P) present in the studied iron related signatures were not found in the bulk RNA-sequencing expression data. Gene set objects in R were created with the R package GSEABase version 1.52.1⁶⁵. Samples were generally divided into high and low signature score groups with the cutoffs set according to score tertiles: lowest tertile were annotated as “Low” and highest tertile were annotated as “High”. For the signatures "GOBP_REGULATION_OF_IRON_ION_TRANSMEMBRANE_TRANSPORT" and "GOBP_IRON_ION_IMPORT_ACROSS_PLASMA_MEMBRANE", the scores in EOC’s and fibroblasts were very low. Therefore, “Positive” samples were classified as samples with a non-zero score whereas “Negative” samples were classified as samples with a score of 0.

Survival analysis was done using Cox proportional hazards model from the R package survival version 3.2-10⁶⁶. Proportional hazards assumptions of the Cox regression were tested with cox.zph-function. Kaplan-Meier curves were plotted for visualization purposes using R package survminer version 0.4.9⁶⁷. p-values for survival analyses were adjusted using p.adjust-function from base R stats-package with method set to “fdr”.

Patient-derived specimens

Plasma samples from cancer-free women were obtained from the New York Blood Center, while malignant ascites fluid samples were obtained from patients with Stage III-IV HGSOC were procured through Surgical Pathology at Weill Cornell Medicine and Memorial Sloan-Kettering Cancer Center. All specimens were acquired with informed consent, classified as surgical discard, and kept totally de-identified for subsequent experimental analyses. The ascites fluid underwent initial processing by centrifugation at 4°C for 10 minutes at 400 rcf, with subsequent separation of supernatants from cell pellets and filtration through 0.22-μm filters to eliminate cellular debris. Processed samples were cryopreserved at -80°C in small aliquots to minimize freeze-thaw cycles. Sample information is described in Table S1.

Mice and experimental murine ovarian cancer models

Female mice were housed in pathogen-free microisolator cages at the animal facilities of Weill Cornell Medicine and used at 8-12 weeks of age. Mice were handled in compliance with the Institutional Animal Care and Use Committee procedures and guidelines under protocol 2011-0098. Wild type C57BL/6J and B6.Cg-Rag2^tm1.1Cgn/J were purchased from the Jackson laboratory. IL-15 translational reporter mice (IL-15^2A-eGFP) were kindly provided by Dr. Ross Kedl⁶⁸. Parental ID8 cells and the aggressive ID8-Defb29/Vegfa derivate were cultured and used as previously described^19,69. Both cell lines were obtained under MTA from Drs. K. Roby and J. Conejo-Garcia, respectively. The PPNM cell line (Trp53^−/−R172HPten^−/−Nf1^−/−Myc^OE) was generously provided by Dr. R. Weinberg under MTA²⁴. The MP cell line was generated as described⁷⁰. For tumor implantation, 1.5 × 10⁶ ID8-based ovarian cancer cells suspended in 200 ml of sterile PBS was intraperitoneally (i.p.) injected into mice. Alternatively, PPNM cells were suspended in PBS containing Matrigel (Corning Matrigel matrix, Cat# 47743-716) at 1:1 ratio, and 200 ml of the mix containing 1.0 × 10⁶ cells were administered i.p. into WT mice, as reported²⁴. Metastatic progression, ascites accumulation, and host survival were monitored over time. Tumor burden in the peritoneal cavity was assessed by live bioluminescent imaging. Briefly, PPNM-bearing mice were given a single i.p. injection of VivoGlo luciferin (2 mg/mouse. Promega, Cat# P1042) and then imaged on a Xenogen IVIS Spectrum In Vivo imaging system at the Weill Cornell Research Animal Resource Center. All cell lines were verified for mycoplasma contamination and maintained under prophylactic plasmocin supplementation (Invivogen, Cat# ant-mpt).

Nucleic acid extraction and quantitative PCR analyses

Mouse or human total RNA was isolated using the RNeasy Mini kit (Qiagen, Cat# 74106) or QIAzol lysis reagent (Qiagen, Cat# 79306) according to the manufacturer’s instructions. 0.1-1 μg of RNA was reverse transcribed to generate cDNA using the qScript cDNA synthesis kit (Quantabio, Cat# 95047). Quantitative RT-PCR was performed using PerfeCTa SYBR green fastmix (Quantabio, Cat# 95071) on a QuantStudio 6 Flex real-time PCR system (Applied Biosystems). Normalized gene expression was calculated by the comparative threshold cycle method using ACTB for human or Actb for mouse as endogenous controls. For cytosolic and mitochondrial DNA extraction, mitochondria were fisrt obtained using the mitochondria isolation kit for cultured cells (Thermo scientific, Cat# 89874) according to the manufacturer’s instructions. Then, DNA from cytosolic and mitochondrial fractions were extracted using the Dneasy blood & tissue kit (Qiagen. Cat# 69504) according to manufacturer’s instructions. Levels of mt-Cox1 was compared to that of genomic 18S.

Mouse RNA-sequencing

ID8-Defb29/Vegfa cells were treated with vehicle or deferiprone (Sigma-Aldrich, Cat# 379409) for 12 hours, and total RNA was subsequently isolated using the RNeasy MinElute kit (Qiagen, Cat# 74204) according to the manufacturer’s instructions. Quality control checks were conducted on all samples using an Agilent Bioanalyzer 2100 to ensure RNA integrity.

mRNA libraries were generated and sequenced at the Weill Cornell Genomics Resources core facility. Raw sequencing data underwent pre-processing and analysis using the Partek software, following a standard pipeline. RNA-seq data were aligned to the mm10 genome using GSNAP method, and Partek E/M was used to estimate read counts at gene level, leveraging ensemble transcriptome information. To assess differential gene expression between experimental groups, a GSA (Gene Set Analysis) method was applied. Gene expression changes were considered statistically significant if they met the False Discovery Rate (FDR) threshold of less than 5%. Additionally, gene set enrichment analysis was performed using Ingenuity Pathway Analysis (IPA, Qiagen) with a focus on "Upstream regulators." Regulators with a statistical significance level (P-value) lower than 10^-6 and with predicted activation or inhibition states (Z-score > 2) were reported. This analysis identified key molecular regulators associated with the observed gene expression changes induced by the experimental treatments. RNA-seq data were deposited under NCBI GEO Accession number (TBD).

Single cell RNA-sequencing

Human: For the analysis of single-cell RNA sequencing (scRNA-seq) data, preprocessed counts from 22 HGSOC tumor specimens¹¹ were downloaded from Gene Expression Omnibus (GEO) with accession code GSE165897. Individual cell scores for each signature were obtained using Ucell (v1.3.1)⁷¹ and a pairwise Wilcoxon test was performed to compare the average scores between fibroblasts, immune, and epithelial ovarian cancer cells (EOCs) in each sample.

Mouse: The cellular fraction of peritoneal lavage samples was isolated from mice bearing ID8-Defb29/Vegfa ovarian cancer for 35 days and subjected to scRNA-seq. Library preparation, sequencing, and raw data preprocessing were performed at the Weill Cornell Medicine Epigenomics Core Facility using the Illumina HiSeq2500 platform. Subsequently, the reads underwent processing and analysis utilizing Seurat 4.1.2⁷². After subsetting low quality data (min.cells=3, min.features=200, nFeature_RNA min=200 max=2500, percent.mt<5), 6,502 cells were obtained and log-normalized. Non-linear dimensional reduction using Uniform manifold approximation and projection (UMAP) with default parameters (dims=1:10, n_neighbors = 30, metric = cosine, n_trees = 50), was used to obtain cell clusters. The top 10 significant cluster’s markers were found (FindAllMarkers min.pct = 0 logfc.threshold = 0) to corroborate cell types. Lineage putative genes were used to identify the immune cell and the tumor cell clusters were designed according to the differential expressed genes using ingenuity pathway analysis (IPA, Qiagen) for the top cell function based on the following pre-determined categories: Invasive: cellular movement category [p-value= 1.05 x 10^-23, z-score 2.81 (92 members upregulated)], proliferative: cell cycle category [p-value= 1.24 x10^-14, z-score 2.23 (39 members upregulated)], Stem-like: embryonic development category [p-value= 5.76 x10^-12, z-score 1.87 (63 members upregulated)], also the expression of putative cancer stem cell genes was evaluated: glutathione S-transferase mu 2 (Gstm2, p-value 2.8 x10^-297, avg_Log(FC)= 1.22, aldehyde dehydrogenase 1 family member A1 (Aldh1a, p-value: 6.5 x10^-179, avg_Log(FC)= 0.68), SRY-box transcription factor 9 (Sox9, p-value: 3.63 x10^-137, avg_Log(FC)= 0.62), SRY-box transcription factor 4 (Sox4, p-value: 4.94 x10^-70, avg_Log(FC)= 0.38), Chemo-resistant: embryonic development category p-value= 2.70 x10^-22, z-score 1.61 (68 members upregulated) this cluster also exhibited high expression of the multidrug resistance ATP binding cassette subfamily B member 1 (Abcb1b, p-value: 1.20 x10^-257, avg_Log(FC)= 0.68).

Gene sets related to iron metabolism were obtained from the Molecular Signatures Database v7.5.1 (MSigDB) for Mus musculus in the ontology gene sets (C5), and signatures related to disease were excluded. Single Sample Gene Set Enrichment Analysis (ssGSEA) was used to calculate enrichment scores for iron-related gene sets. These scores were then obtained using Escape v.1.20 (enrichIt) and plotted for each cell type. Mouse scRNA-seq data were deposited under NCBI GEO Accession number (TBD).

Cytokine and chemokine quantification

Human undiluted ascites samples were submitted to Eve Technologies™ Assay Services for analysis using the Human Cytokine/Chemokine 71-Plex Discovery Assay® Array. To obtain peritoneal lavage samples from tumor-bearing mice, we injected 5 ml of sterile PBS, and the liquid was aspirated using a 10-ml syringe with a 20G1 ½ needle. During collection the needle was detached to avoid mechanical red blood cells lysis. Subsequently, the samples were concentrated utilizing 3K Amicon tubes (Millipore, Cat# UFC800324), and all samples were normalized to a final protein concentration of 5 mg/ml. Mouse samples were submitted to Eve Technologies™ Assay Services for analysis using the Mouse Cytokine/Chemokine 44-Plex Discovery Assay® Array.

Ovarian cancer organoid development, characterization, and maintenance

Patient-derived fresh tissue samples were collected with written informed patient consent with the approval of the Institutional Review Board (IRB #1305013903) at Weill Cornell Medicine. Patient-derived tumor organoids (PDTO) lines were developed as described⁷³ with some modifications. Briefly, fresh tissue samples were washed three times with transport media [DMEM (Gibco, Cat# 11971025) with 1X Glutamax (Invitrogen, Cat# 35050079), 100 U/mL penicillin, 100 μg/mL streptomycin (Gibco, Cat# 15140148), Primocin 100 μg/mL (InvivoGen, Cat# ant-pm), and 10 μmol/L Rock inhibitor Y-27632 (Selleck Chemical Inc., Cat# S1049)], and placed in a sterile 3-cm petri dish (Falcon) for mechanical dissection into smaller pieces (~2 mm diameter) prior to enzymatic digestion. Enzymatic digestion was done with collagenase media [DMEM (Gibco, Cat# 11971025, 100 U/mL penicillin, 100 μg/mL streptomycin (Gibco, Cat# 15140148), 250 U/mL collagenase IV (Life Technologies, Cat# 17104019), 100 μg/mL Primocin (InvivoGen, Cat# ant-pm), and 10 μmol/L Rock inhibitor Y-27632 (Selleck Chemical Inc., Cat# S1049)] in a volume of at least 20 times the tissue volume and incubated on a shaker at 200 rpm at 37°C until the digestion solution turned cloudy, typically 30-45 minutes. The suspension was centrifuged at 300 rcf for 3 minutes and the cell pellet was washed once with washing media [Advanced DMEM (Gibco, Cat# 12491023), 100 U/mL penicillin, 100 ug/mL streptomycin (Gibco, Cat# 15140148), 1x Glutamax (Cat# 35050079), and 1x HEPES (Invitrogen, Cat# 5630130)]. The cells were resuspended in a small volume of tissue-type specific primary culture media: Advanced DMEM (Gibco, Cat# 12491023) with 1x glutamax (Cat# 35050079), HEPES (Invitrogen, Cat# 5630130), B27 (Gibco, Cat# A1486701), 100 U/mL penicillin, 100 μg/mL streptomycin (Gibco, Cat# 15140148), 100 μg/mL Primocin (InvivoGen, Cat# ant-pm), 10% noggin conditioned media, 10% R-spondin conditioned media, 10 mM Nicotinamide (Sigma-Aldrich, Cat# Nicotinamide), 1.25 mM N-acetylcysteine (Sigma-Aldrich, Cat# A0737), 1ng/mL Recombinant Human FGF-b (Peprotech, Cat# 100-18B), 20ng/mL Recombinant Human FGF-10 (Peprotech, Cat# 100-26), 1 μM PGE2 (R&D Systems, Cat# 2296), 10 μM SB202190 (Sigma-Aldrich, Cat# S7067), 50ng/mL Mouse Recombinant EGF (Invitrogen, Cat# 315-09), 10 μM Y-27632 (Selleck Chemical Inc., Cat# S1049), 10 ng/mL Heregulin Beta-1 (Peprotech, Cat# 100-03), 500 nM A-83-01 (Tocris, Cat# 2939), and 100 uM Beta Estradiol (Sigma, Cat# E8875). Up to ten 100 μL drops of Matrigel/cell suspension were distributed into a 6-well cell suspension culture plate. The drops were allowed to polymerize for 30 min inside the incubator at 37°C and 5% CO2 and afterwards, 3-mL tumor type–specific primary culture media were added per well. Fresh culture media was replaced every 3 to 4 days. PDTOs at approximately 300 to 500 μm were passaged using TrypLE Express (Gibco, Cat# 12604013) for 10 minutes in the water bath at 37°C. Single cells and small cell clusters were replated according to the procedure described above. Monthly mycoplasma screening was performed using the PCR Mycoplasma Detection Kit (abm, Cat# G238).

Treatment of ovarian cancer organoids with deferiprone

50,000 cells obtained from disaggregated organoids were plated in a 100-μL cell culture media and Matrigel mix (v/v 2:1) in 6-well plates. Three domes were plated in each well of a 6-well plate. Plates were incubated for 30 minutes at 37°C to allow polymerization of the drops, and then 3 mL of tissue specific primary culture media described above was added to each well. After 72 hours of plating, the media was aspirated, replaced with 3 mL PBS, and incubated for 10 minutes. This PBS wash was repeated one more time and then 0, 100, 150, or 200 mM deferiprone (Sigma-Aldrich, Cat# 379409) was added in 3 mL of fresh media made without B27. After an incubation of 96 hours, cells were dissociated as described above and collected for downstream analysis.

In vitro drug treatments

Ovarian cancer cell lines were seeded and allowed to attach overnight. Subsequently, deferiprone (Sigma-Aldrich, Cat# 379409) or aphidicolin (Sigma-Aldrich, Cat# A0781) were added at a 2X concentration in fresh medium and incubated for the specified time intervals. After the incubation periods, cells were rinsed with PBS and then detached for downstream analysis. For treatment with inhibitors H-151 (1 mM, Invivogen, Cat# inh-h151), ATR inhibitor (1 mM, AZD6738, Selleckchem, Cat# S7693), ATM inhibitor (100 nM, AZD0156, Selleckchem, Cat# S8375), CHK1/2 inhibitor (300 nM, AZD7762, Selleckchem, Cat# S1532), cells were pre-incubated for 2 hours before treatment with deferiprone or aphidicolin. For all the experiments working solutions of deferiprone were freshly prepared in culture medium at a concentration of 10 mM, followed by the preparation of dilutions at the specified concentrations in culture medium.

MTT assay for cytotoxicity and synergy

Ovarian cancer cells were seeded at a density of 3x10³ cells per well in 96-well plates containing 100 µL of culture medium. These plates were then incubated overnight at 37°C with 5% CO2. On the following day, 100 µL of deferiprone (2x concentration) was added and incubated for the specified time points. After the treatment, the cells were rinsed with RPMI medium without phenol red. Then, 100 µL of RPMI without phenol red and 50 µL of 1 mg/mL Thiazolyl Blue Tetrazolium Bromide (MTT) in sterile water were added to each well. The cells were incubated for 2 hours, followed by centrifugation, and washed with cold PBS. The plates were dried, and 100 µL of DMSO was added. After incubating for 30 minutes with shaking, the absorbance was measured at 540 nm using a Spectramax iD3 instrument (Molecular Devices). For in vitro synergy analysis, serial dilutions of cisplatin (Sigma, Cat#479306) and deferiprone (Sigma-Aldrich, Cat# 379409) were prepared and mixed to the desired concentrations and incubated for 48 hours, then MTT was performed to calculate the percentage of viability and the Bliss synergy scores were calculated using synergy finder 3.0⁷⁴.

Seahorse analyses

ID8-Defb29/Vegf-A were plated at a density of 2.5x10⁵ cells per well overnight, next day cells were treated with vehicle or deferiprone (Sigma-Aldrich, Cat# 379409) at 100 or 200 mM for 6 hours, then the cells were washed and non-buffered XF base medium (Agilent, Cat# 102353-100) containing 25 mM glucose (Sigma, Cat# G7021), 2 mM L-glutamine (Gibco, Cat# 25030081), and 1 mM sodium pyruvate (Gibco, Cat# 11360070) pH= 7.4 was added. Cells were plated and OCR measurements were analyzed on an XFe96 Extracellular Flux Analyzer (Agilent). After, basal OCR measurements were obtained, an OCR trace was recorded in response to oligomycin (1 μM), carbonyl cyanide-p-(trifluoromethoxy) phenylhydrazone (FCCP, 1 μM), and rotenone and antimycin (0.5 μM each) following the XF Cell Mito Stress test kit (Agilent, Cat# 103010-100). After analysis, the cell numbers of each well were determined by nuclear DNA staining with Hoechst 33342 (Sigma, Cat# H3570) and OCR values were normalized accordingly. Finally, metabolic parameters were calculated using the seahorse Agilent Wave software (Agilent). At least ten technical replicates per treatment were examined.

Generation of IRF3-deficient ovarian cancer cell lines using CRISPR/Cas9

a 20-nucleotide sgRNAs directed against murine Irf3 (NM_016849.4) were designed to target the genomic sequences CCAGTGGTGCCTACACCCCG (IRF-3 sgRNA#1) and TGAACCGGAAAGAAGTGTTG (IRF-3sgRNA#2), (the 3 additional nucleotides highlighted in bold represent the protospacer adjacent motif, or PAM). These target sequences correspond to exon 3 of the murine Irf3 cDNA and were chosen using the Broad Institute’s CRISPick tool (https://portals.broadinstitute.org/gppx/crispick/public). As a control, a scrambled sgRNA (sg Ctrl) was used harboring a 20-nucleotide sequence that is computationally designed to be non-targeting within the murine genome. The RNA sequence for this non-targeting control was CGUUAAUCGCGUAUAAUACG. To generate Irf3-deficent Ovarian cancer lines, ID8-Defb29/Vegf-A were electroporated with ATTO-550-labeled sgRNA-Cas9 complexes using the Neon transfection system, according to the manufacturer’s protocol (IDT, Cat# 1075931). All materials for sgRNA-Cas9 complex generation were purchased from Integrated DNA Technologies (IDT) and prepared as instructed in the IDT protocols using NEON transfection system. Cells were electroporated with either scrambled sgRNA-Cas9 complexes, or the two Irf3 sgRNA-Cas9 complexes with sequences described above. 24 hours post-electroporation, fluorescently labeled ATTO-550⁺ single cells for each condition were sorted by FACS, expanded, and screened for Irf3 ablation separately. To screen for IRF-3 ablation, western blot analysis using rabbit anti-mouse IRF-3 (cell signaling technology Cat#D83B9) was performed on total protein isolated from cells electroporated with sgRNA-Cas9 complexes containing the Irf3 sgRNA-Cas9 described above. Following knock-out confirmation in 16 clones from the sgRNA#1 and 16 clones from the sgRNA#2, random clones from the IRF3 sgRNA#2 and the sgCtrl were used for deferiprone experiments.

Iron quantification

For total iron measurements, 50 μL of ascites fluid was digested in 50 μL 50% HNO₃ water with 0.1% digitonin. Digested ascites samples were subsequently diluted 1:50 in 0.2% HNO₃ water and 20 μL of sample or iron standard measured by graphite furnace atomic absorption spectroscopy. For heme iron measurements, a method based on the conversion of the heme moiety to its fluorescent porphyrin derivative by the removal of heme iron under acidic reducing conditions was used ^75,76. 200 μL of ascites fluid was centrifuged at 1000 rfc for 5 mins to remove cellular debris. Ascites supernatants were divided into two 100 μL aliquots and 500 μL 2M oxalic acid added to each. One aliquot was heated to 95°C for 30 minutes to release iron from heme and generate fluorescent protoporphyrin IX. The other aliquot was left at room temperature for 30 minutes. Both aliquots were centrifuged for 10 min at 1,000 rfc at 4°C to remove debris. 200 μL of the heated and unheated aliquots were placed into a black 96-well-clear bottomed cell culture microplate (Greiner bio-one, Cat# 655090, Lot: E19083A9) and the fluorescence read at ex404 nm / em630 nm. The background fluorescence of the unheated aliquot was subtracted from the heated aliquot and the extinction co-efficient of heme at 630nm (1 μM heme = 15,200 fluorescence units) was used to determine heme concentrations as previously described⁷⁶.

Proteomic analyses

Ascites samples were separated using SDS-PAGE and stained with SimplyBlue^TMSafeStain (Thermo scientific, Cat# LC6065), eight bands were identified and cutted. Individual bands were submitted to the Weill Cornell proteomics & metabolomics core facility. Proteins were then concentrated by centrifugation and buffer exchange using the Amicon Ultra-0.5 Centrifugal Filter Unit with Ultracel-3 membrane (Millipore, Cat# UFC5003), according to the manufacturer’s protocol, with the exchange buffer consisting of 4 M urea, 1 M thiourea and 50 mM TEAB at pH 8.5. Proteins were reduced with 10 mM dithiothreitol, incubated at 34 °C for 1 h, then alkylated with 58 mM iodoacetamide for 45 min in the dark at room temperature and then quenched by a final addition of 36 mM dithiothreitol. The solutions were then diluted with 50mM ammonium bicarbonate (pH 8.0) to a final buffer concentration of 1M urea before trypsin digestion. Each sample was digested with 0.8 μg of trypsin for 18 h at 37 °C. The digestion was stopped by addition of TFA to a final pH 2.2–2.5. The samples were then desalted with SOLA HRP SPE Cartridge (Thermo Scientific, Cat# 60109-001). First, the cartridges were conditioned with 1 × 0.5 mL 90% methanol, 0.1% TFA and equilibrated with 2 × 0.5 mL 0.1% TFA. The samples were diluted 1:1 with 0.2% TFA and were run slowly through cartridges. After washing with 2 × 0.5 mL of equilibration solution, peptides were eluted by 1 × 0.5 mL of 50% ACN, 0.1% TFA and dried in a speed-vacuum centrifuge. Samples were reconstituted in 60 μL of 50% ACN, 0.1% TFA and loaded onto columns right after the equilibration step allowing slow flow-through. Cartridges were washed three times with 1.0 mL of equilibration solution and peptides were eluted twice with 0.6 mL of 50% ACN, 0.1% TFA, after which they were dried down in a speed-vacuum centrifuge for further use. The nano-LC–MS/MS analysis was carried out using UltiMate3000 RSLCnano (Dionex) coupled to an Orbitrap Fusion (Thermo-Fisher Scientific) mass spectrometer equipped with a nanospray Flex Ion Source. Each sample was reconstituted in 22 μL of 0.5% formic acid and 10 μL was loaded onto an Acclaim PepMap 100 C18 trap column (5 μm, 100 μm × 20 mm, 100 Å, Thermo Fisher Scientific) with nanoViper Fittings at 20 μL/min of 0.5% formic acid for on-line desalting. After 2 min, the valve switched to allow peptides to be separated on an Acclaim PepMap C18 nano column (3 μm, 75 μm × 25 cm, Thermo Fisher Scientific). Mobile phase A consisted of 2% ACN, 0.1% formic acid in water, mobile phase B was 95% ACN, 0.1% formic acid in water and the 120 min gradient was as follows: 5% to 23% to 35% B at 300 nl/min (3 to 83 to 123 min, respectively), followed by a 9-min ramping to 90% B, a 9-min hold at 90% B and quick switch to 7% B in 1 min. The column was re-equilibrated with 5% B for 20 min before the next run. A 10-fmol injection of standard BSA digest mixture with a short 30-min gradient was run for quality-control purposes. The Orbitrap Fusion instrument was operating in positive-ion mode with nano-spray voltage set at 1.7 kV and source temperature at 275 °C. External calibration for Fourier transform, ion trap and quadrupole mass analyzers was performed before the analysis. The Orbitrap full MS survey scan (m/z 400–1,800) was followed by top-3-s, data-dependent higher collision dissociation (HCD) product-dependent electron-transfer dissociation (ETD) MS/MS scans for precursor peptides with 2–8 charges above a threshold-ion count of 50,000 with normalized collision energy of 32%. Mass spectrometry survey scans were acquired at a resolving power of 120,000 (full-width at half maximum at m/z 200), with automatic gain control (AGC) = 2 × 10⁵ and maximum injection time (maximum IT) = 50 ms, and HCD MS/MS scans at resolution 30,000 with AGC = 5 × 104, maximum IT = 60 ms and with Q isolation window (m/z) at 3 for the mass range m/z 105–2,000. Dynamic exclusion parameters were set at 1 within 60-s exclusion duration with ± 10 p.p.m. exclusion-mass width. The product-ion trigger list consisted of peaks at 204.0867 Da (HexNAc oxonium ion), 138.0545 Da (HexNAc fragment), 366.1396 Da (Hex-HexNAc oxonium ions) and 274.0927 Da (dehydrated N-acetylneuraminic acid). If one of the HCD product ions in the list was detected, two charge-dependent ETD MS/MS scans with HCD supplementary activation (SA for electron transfer and higher-energy collision dissociation (EThcD) scan) on the same precursor ion were triggered and collected in a linear ion trap. For doubly charged precursors, the ETD reaction time was set at 150 ms and the SA energy was set at 25%, and the same parameters set at 125 ms and 20%, respectively, were used for higher-charged precursors. For both ion-triggered scans, the fluoranthene ETD reagent target was set at 2 × 10⁵, the AGC target at 1 × 10⁴, maximum IT at 105 ms and isolation window at 3. All data were acquired under Xcalibur 3.0 operation software and Orbitrap Fusion Tune Application v.2.1 (Thermo Fisher Scientific). All mass spectrometry and MS/MS raw spectra from each sample were searched using Byonics v.2.8.2 (Protein Metrics) using Homo sapiens protein database containing 133,840 sequences and downloaded from Uniprot TrEMLB on 4 January 2016. The peptide search parameters were as follows: two missed cleavages for full trypsin digestion with fixed carbamidomethyl modification of cysteine, variable modifications of methionine oxidation and deamidation on asparagine and glutamine residues. The peptide-mass tolerance was 10 p.p.m. and fragment-mass tolerance values for HCD and EThcD spectra were 0.05 Da and 0.6 Da, respectively. The maximum number of common and rare modifications were both set at two. Identified peptides were filtered for maximum 2% FDR or 50 hits to the reverse database. The total abundance calculated as the sum of the intensity for each protein in all bands and the percentage was calculated from the total intensity.

Flow cytometry

Analyses were conducted using fluorochrome-conjugated antibodies purchased from BioLegend, unless stated otherwise. Cells were washed with PBS, Fc-gamma receptor-blocked using TruStain fcX^TM (anti-mouse CD16/32, 93) and then stained for surface markers at 4°C in the dark for 30 minutes using the following antibodies: anti-CD45 (30-F11, 1:200), anti-CD3 (17A2, 1:200), anti-CD4 (RM4-5, 1:200), anti-CD8α (53-6.7, 1:200), anti-CD11c (N418, 1:200), anti-I-A/I-E (M5/114.15.2, 1:400; Tonbo biosciences), anti-CD11b (M1/70, 1:200), anti-F4/80 (BM8, 1:200), anti-Ly6g (1A81 1:200), anti-Ly6c (HK1.4, 1:200), anti-NK1.1 (PK136, 1:200), anti-TER-119 (TER-119, 1:200), anti-CD19 (6D5, 1:200), anti-CD27 (LG.3A10, 1:200), anti-CD71 (CY1G4, 1:200), anti-ULBP-1/MULT-1 (237104; R&D systems; 1:50), Rat IgG2A Isotype Control (54447; R&D systems), anti-CD262 [DR5, TRAIL-R2] (MD5-1, 1:200) and Anti-IgG Isotype Ctrl (HTK888). Cells were then washed and stained with DAPI (Biolegend) or LIVE/DEAD^TMFixable Near-IR dead cell stain for live/dead discrimination (Invitrogen). Flow cytometry was performed on a LSRII or a Fortessa-X20 instruments (BD Biosciences). Cell populations were sorted from peritoneal lavage or ascites samples from Ovarian cancer -bearing mice using a FACSAria sorter (BD Biosciences) or a Sony MA900 (Sony) at the WCM CLC Flow Cytometry Core Facility, and flow cytometry data were analyzed using FlowJo v.10 (TreeStar).

Immunohistochemistry

Omentum samples were collected from tumor bearing mice and embedded in paraffin, then slides were generated in the Microscopy and Imaging Core Facility of Weill Cornell Medicine and stained for NKp46 in the Center of Comparative Medicine and Pathology-Laboratory of Comparative Pathology (LCP) of Memorial Sloan Kettering Cancer Center/Weill Cornell Medicine. Slides were scanned and processed in a Axioscan 7 instrument (Zeiss), and the images were analyzed in FIJI (ImageJ). NKp46 stained area and total tissue area were calculated by the color deconvolution function and NKp46 staining were expressed as percentage of total tissue area and the average of 3-5 fields per sample was reported.

Western blotting

Cancer cells were washed twice in 1X cold PBS and cell pellets were lysed using RIPA lysis and extraction buffer (Thermo Fisher Scientific, Cat# 89900) supplemented with a protease and phosphatase inhibitor tablet (Millipore, Cat# 11697498001 and Roche, Cat# 04906837001). Homogenates were centrifuged at 14,000 rpm for 30 min at 4°C, and the supernatants were collected. Protein concentrations were determined using a BCA protein assay kit (Thermo Fisher Scientific, Cat# 23225). Equivalent amounts of protein were separated via SDS-PAGE and transferred onto PVDF membranes following standard protocols. The following antibodies were used: anti-beta actin (Cell Signaling Technologies, Cat# 8457), anti-pTBK1 (Cell Signaling Technologies, Cat# 5483), anti-TBK1 (Cell Signaling Technologies, Cat# 3504), anti-pIRE3 (Cell Signaling Technologies Cat# 4947), anti-IRE3 (Cell Signaling Technologies, Cat# 4302), HRP-Conjugated Beta Actin Monoclonal Antibody (Thermo Fisher Scientific, Cat# MA5-15739-HRP), and goat anti-rabbit secondary antibodies conjugated with HRP (Thermo Fisher Scientific, Cat# 32460). SuperSignal West Pico (Thermo Fisher Scientific, Cat# 34580) or Femto chemiluminescent substrates (Thermo Fisher Scientific, Cat# 34095) were used to image blots in an iBright CL1000 instrument (Thermo Fisher Scientific), band intensity was measured using ImageJ Fiji.

In vivo treatments

Wild type B6, B6.Cg-Rag2tm1.1Cgn/J (Rag2) or IL-15^2A-eGFP reporter mice were implanted via i.p. injection with 1.5 x 10⁶ ID8-Defb29/Vegfa, or 1.0 x 10⁶PPNM ovarian cancer cells. After 7 days, mice were i.p. (or by oral gavage when specified) treated every day with 150 mg/kg of deferiprone (Sigma-Aldrich, Cat# 379409) and/or once per week 5 mg/kg cisplatin (Accord, Cat# 16729-288-11) during a span of 4 weeks, both drugs were prepared in sterile human grade saline and filtered. For the acuteadministration approach, mice bearing ovarian cancer for 21 days were i.p. treated with one dose of cisplatin (5mg/kg; Accord, Cat# 16729-288-11) and/or deferiprone (150 mg/kg; Sigma-Aldrich, Cat# 379409) every day for a span of seven consecutive days. For in vivo blocking of type-I IFN signaling two approaches were used: Survival approach: mice bearing ID8-Defb29/Vegfa tumors were i.p. treated every 3 days with isotype control antibodies (Bioxcell, Cat# BE0083) or anti-IFNAR blocking antibodies (Bioxcell, Cat# #BE0241) at 200 µg/mouse, starting 3 days after tumor implantation and until the mice reach end-point criteria. Simultaneously, the mice received cisplatin and/or deferiprone as mentioned above. Acute administration approach with IFNAR blockade: Mice bearing ID8-Defb29/Vegfa tumors for 18 days received a dose of isotype control antibodies (Bioxcell, Cat# BE0083) or anti-IFNAR blocking antibodies (Bioxcell, Cat# #BE0241) at 200 µg/mouse, at day 21 mice were i.p. treated with one dose of cisplatin (5mg/kg; Accord, Cat# 16729-288-11) and/or deferiprone (150 mg/kg; Sigma-Aldrich, Cat# 379409) every day for a span of seven consecutive days. At day 28 the mice were humanely sacrificed, and peritoneal lavage was performed to collect the infiltrating cells for downstream analysis. For in vivo depletion of NK cells, mice were i.p. treated every 6 days with PK136 (Bioxcell, Cat# BE0036) and mouse IgG2a isotype control (Bioxcell, Cat# BE0085) at 200 µg/mouse, starting 6 days after tumor implantation flowed by treatment with cisplatin and deferiprone as mentioned above. Initial preliminary in vivo experiments were conducted using deferiprone provided by ApoPharma Inc. under MTA. Subsequent therapeutic and mechanistic experiments were performed using deferiprone from Sigma-Aldrich (Cat# 379409)

Dietary iron experiments

Isocaloric modified AIN-93G rodent diet (Research Diets) containing 3, 45, or 300 ppm of iron-citrate were provided ad libitum one week prior to tumor challenge. 3.0 x 10⁶ ID8 parental cells were i.p implanted into wild type C57BL6/6J mice and mouse weight and status were monitored weekly or daily, until end-point when animals were humanely euthanized.

Mitochondrial iron content

To assess mitochondrial iron content, we utilized Mito-Ferro Green (#M489, Dojindo) following the manufacturer's guidelines. In brief, the cells were seeded overnight to allow attachment, underwent two rounds of washing with Hank's Balanced Salt Solution (HBSS) and were subsequently incubated with 5 μM Mito-Ferro Green (200 ml), prepared in HBSS for 30 minutes at 37 °C. The cells were washed twice with HBSS and 100 μM deferiprone (200 ml) was added to the cells and incubated for 30 minutes at 37 ^oC in 5% CO₂ incubator. The cells were washed twice with HBSS, subsequently 100 μM ammonium iron (II) sulfate (200 ml) was added to the cells and incubated for 1 hour at 37 ^oC in 5% CO₂ incubator. To visualize the cell nuclei, DAPI was used as a counterstain. After three HBSS washes, fluorescence was observed using a fluorescence microscope at the Microscopy and Imaging Core Facility of Weill Cornell Medicine. The fluorescence signal was quantified using ImageJ software.

Illustrations

Illustrations and schemes were created with BioRender.com under publication license.

Statistical analyses

All statistical analyses were performed using the GraphPad Prism software (Version 10.0.3). Significance for pairwise correlation analyses was calculated using the Spearman’s or Pearson correlation coefficient (r or r²). Comparisons between two groups were assessed using unpaired two-tailed Student’s t-test. Multiple comparisons were assessed by one-way ANOVA including Tukey’s multiple comparisons test or two-way ANOVA with Šidák’s multiple comparison test with single pooled variance. Host survival rates were compared using the Log-Rank (Mantel-Cox) test. For violin plots all data points, median and quartiles were showed, for bar plots data are presented as mean ± SEM. Unless otherwise stated, exact significant p-values are shown, and non-significant values were omitted.

Yes there is potential Competing Interest. J.R.C.-R. holds patents on the use immune modulators for ovarian cancer treatment and serves as scientific consultant for Moderna, Immagene B.V., and Autoimmunity Biologic Solutions, Inc. D.Z. reports institutional grants from Merck, Genentech, AstraZeneca, Plexxikon, and Synthekine, and personal fees from AstraZeneca, Xencor, Memgen, Takeda, Synthekine, Immunos, Tessa Therapeutics, Miltenyi, and Calidi Biotherapeutics. D.Z. owns a patent on use of oncolytic Newcastle Disease Virus for cancer therapy. L.G. is/has been holding research contracts with Lytix Biopharma, Promontory and Onxeo, has received consulting/advisory honoraria from Boehringer Ingelheim, AstraZeneca, OmniSEQ, Onxeo, The Longevity Labs, Inzen, Imvax, Sotio, Promontory, Noxopharm, EduCom, and the Luke Heller TECPR2 Foundation, and holds Promontory stock options. All other authors declare no potential conflicts of interest.

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published 28 Jul, 2024

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Iron Chelation Therapy Elicits Innate Immune Control of Metastatic Ovarian Cancer

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