Unlocking ferroptosis in prostate cancer - the road to novel therapies and imaging markers.

Ferroptosis is a distinct form of regulated cell death that is predominantly driven by the build-up of intracellular iron and lipid peroxides. Ferroptosis suppression is widely accepted to contribute to the pathogenesis of several tumours including prostate cancer. Results from some studies reported that prostate cancer cells can be highly susceptible to ferroptosis inducers, providing potential for an interesting new avenue of therapeutic intervention for advanced prostate cancer. In this Perspective, we describe novel molecular underpinnings and metabolic drivers of ferroptosis, analyse the functions and mechanisms of ferroptosis in tumours, and highlight prostate cancer-specific susceptibilities to ferroptosis by connecting ferroptosis pathways to the distinctive metabolic reprogramming of prostate cancer cells. Leveraging these novel mechanistic insights could provide innovative therapeutic opportunities in which ferroptosis induction augments the efficacy of currently available prostate cancer treatment regimens, pending the elimination of major bottlenecks for the clinical translation of these treatment combinations, such as the development of clinical-grade inhibitors of the anti-ferroptotic enzymes as well as non-invasive biomarkers of ferroptosis. These biomarkers could be exploited for diagnostic imaging and treatment decision-making.

Enhancing Cancer Diagnosis with Real-Time Feedback: Tumor Metabolism through Hyperpolarized 1-13C Pyruvate MRSI.

This review article discusses the potential of hyperpolarized (HP) 13C magnetic resonance spectroscopic imaging (MRSI) as a noninvasive technique for identifying altered metabolism in various cancer types. Hyperpolarization significantly improves the signal-to-noise ratio for the identification of 13C-labeled metabolites, enabling dynamic and real-time imaging of the conversion of [1-13C] pyruvate to [1-13C] lactate and/or [1-13C] alanine. The technique has shown promise in identifying upregulated glycolysis in most cancers, as compared to normal cells, and detecting successful treatment responses at an earlier stage than multiparametric MRI in breast and prostate cancer patients. The review provides a concise overview of the applications of HP [1-13C] pyruvate MRSI in various cancer systems, highlighting its potential for use in preclinical and clinical investigations, precision medicine, and long-term studies of therapeutic response. The article also discusses emerging frontiers in the field, such as combining multiple metabolic imaging techniques with HP MRSI for a more comprehensive view of cancer metabolism, and leveraging artificial intelligence to develop real-time, actionable biomarkers for early detection, assessing aggressiveness, and interrogating the early efficacy of therapies.

Exploiting metabolic vulnerabilities after anti-VEGF antibody therapy in ovarian cancer.

Despite modest clinical improvement with anti-vascular endothelial growth factor antibody (AVA) therapy in ovarian cancer, adaptive resistance is ubiquitous and additional options are limited. A dependence on glutamine metabolism, via the enzyme glutaminase (GLS), is a known mechanism of adaptive resistance and we aimed to investigate the utility of a GLS inhibitor (GLSi). Our in vitro findings demonstrated increased glutamine abundance and a significant cytotoxic effect in AVA-resistant tumors when GLSi was administered in combination with bevacizumab. In vivo, GLSi led to a reduction in tumor growth as monotherapy and when combined with AVA. Furthermore, GLSi initiated after the emergence of resistance to AVA therapy resulted in a decreased metabolic conversion of pyruvate to lactate as assessed by hyperpolarized magnetic resonance spectroscopy and demonstrated robust antitumor effects with a survival advantage. Given the increasing population of patients receiving AVA therapy, these findings justify further development of GLSi in AVA resistance.

Post-Acquisition Hyperpolarized 29Silicon Magnetic Resonance Image Processing for Visualization of Colorectal Lesions Using a User-Friendly Graphical Interface.

Medical imaging devices often use automated processing that creates and displays a self-normalized image. When improperly executed, normalization can misrepresent information or result in an inaccurate analysis. In the case of diagnostic imaging, a false positive in the absence of disease, or a negative finding when disease is present, can produce a detrimental experience for the patient and diminish their health prospects and prognosis. In many clinical settings, a medical technical specialist is trained to operate an imaging device without sufficient background information or understanding of the fundamental theory and processes involved in image creation and signal processing. Here, we describe a user-friendly image processing algorithm that mitigates user bias and allows for true signal to be distinguished from background. For proof-of-principle, we used antibody-targeted molecular imaging of colorectal cancer (CRC) in a mouse model, expressing human MUC1 at tumor sites. Lesion detection was performed using targeted magnetic resonance imaging (MRI) of hyperpolarized silicon particles. Resulting images containing high background and artifacts were then subjected to individualized image post-processing and comparative analysis. Post-acquisition image processing allowed for co-registration of the targeted silicon signal with the anatomical proton magnetic resonance (MR) image. This new methodology allows users to calibrate a set of images, acquired with MRI, and reliably locate CRC tumors in the lower gastrointestinal tract of living mice. The method is expected to be generally useful for distinguishing true signal from background for other cancer types, improving the reliability of diagnostic MRI.

A mechanistic modeling framework reveals the key principles underlying tumor metabolism.

While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, we show that the inhibition of phosphofructokinase by excess ATP in the cytoplasm can drive a preference for aerobic glycolysis in fast-proliferating tumor cells. The differing rates of ATP utilization by tumor cells can therefore drive heterogeneity with respect to the presentation of the Warburg effect. Building upon this idea, we couple the metabolic phenotype of tumor cells to their migratory phenotype, and show that our model predictions are in agreement with previous experiments. Next, we report that the reliance of proliferating cells on different anaplerotic pathways depends on the relative availability of glucose and glutamine, and can further drive metabolic heterogeneity. Finally, using treatment of melanoma cells with a BRAF inhibitor as an example, we show that our model can be used to predict the metabolic and gene expression changes in cancer cells in response to drug treatment. By making predictions that are far more generalizable and interpretable as compared to previous tumor metabolism modeling approaches, our framework identifies key principles that govern tumor cell metabolism, and the reported heterogeneity and plasticity. These principles could be key to targeting the metabolic vulnerabilities of cancer.

Identifying the Metabolic Signatures of PPARD-Overexpressing Gastric Tumors.

Peroxisome proliferator-activated receptor delta (PPARD) is a nuclear receptor known to play an essential role in regulation of cell metabolism, cell proliferation, inflammation, and tumorigenesis in normal and cancer cells. Recently, we found that a newly generated villin-PPARD mouse model, in which PPARD is overexpressed in villin-positive gastric progenitor cells, demonstrated spontaneous development of large, invasive gastric tumors as the mice aged. However, the role of PPARD in regulation of downstream metabolism in normal gastric and tumor cells is elusive. The aim of the present study was to find PPARD-regulated downstream metabolic changes and to determine the potential significance of those changes to gastric tumorigenesis in mice. Hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy, nuclear magnetic resonance spectroscopy, and liquid chromatography-mass spectrometry were employed for metabolic profiling to determine the PPARD-regulated metabolite changes in PPARD mice at different ages during the development of gastric cancer, and the changes were compared to corresponding wild-type mice. Nuclear magnetic resonance spectroscopy-based metabolomic screening results showed higher levels of inosine monophosphate (p = 0.0054), uracil (p = 0.0205), phenylalanine (p = 0.017), glycine (p = 0.014), and isocitrate (p = 0.029) and lower levels of inosine (p = 0.0188) in 55-week-old PPARD mice than in 55-week-old wild-type mice. As the PPARD mice aged from 10 weeks to 35 weeks and 55 weeks, we observed significant changes in levels of the metabolites inosine monophosphate (p = 0.0054), adenosine monophosphate (p = 0.009), UDP-glucose (p = 0.0006), and oxypurinol (p = 0.039). Hyperpolarized [1-13C] pyruvate magnetic resonance spectroscopy performed to measure lactate flux in live 10-week-old PPARD mice with no gastric tumors and 35-week-old PPARD mice with gastric tumors did not reveal a significant difference in the ratio of lactate to total pyruvate plus lactate, indicating that this PPARD-induced spontaneous gastric tumor development does not require glycolysis as the main source of fuel for tumorigenesis. Liquid chromatography-mass spectrometry-based measurement of fatty acid levels showed lower linoleic acid, palmitic acid, oleic acid, and steric acid levels in 55-week-old PPARD mice than in 10-week-old PPARD mice, supporting fatty acid oxidation as a bioenergy source for PPARD-expressing gastric tumors.

Metabolic Imaging Using Hyperpolarization for Assessment of Premalignancy.

There is an unmet need for noninvasive surrogate markers that can help identify premalignant lesions across different tumor types. Here we describe the methodology and technical details of protocols employed for in vivo 13C pyruvate metabolic imaging experiments. The goal of the method described is to identify and understand metabolic changes, to enable detection of pancreatic premalignant lesions, as a proof of concept of the high sensitivity of this imaging modality.

29Si Isotope-Enriched Silicon Nanoparticles for an Efficient Hyperpolarized Magnetic Resonance Imaging Probe.

Silicon particles have garnered attention as promising biomedical probes for hyperpolarized 29Si magnetic resonance imaging and spectroscopy. However, due to the limited levels of hyperpolarization for nanosized silicon particles, microscale silicon particles have primarily been the focus of dynamic nuclear polarization (DNP) applications, including in vivo magnetic resonance imaging (MRI). To address these current challenges, we developed a facile synthetic method for partially 29Si-enriched porous silicon nanoparticles (NPs) (160 nm) and examined their usability in hyperpolarized 29Si MRI agents with enhanced signals in spectroscopy and imaging. Hyperpolarization characteristics, such as the build-up constant, the depolarization time (T1), and the overall enhancement of the 29Si-enriched silicon NPs (10 and 15%), were thoroughly investigated and compared with those of a naturally abundant NP (4.7%). During optimal DNP conditions, the 15% enriched silicon NPs showed more than 16-fold higher enhancements─far beyond the enrichment ratio─than the naturally abundant sample, further improving the signal-to-noise ratio in in vivo 29Si MRI. The 29Si-enriched porous silicon NPs used in this work are potentially capable to serve as drug-delivery vehicles in addition to hyperpolarized 29Si in vivo, further enabling their potential future applicability as a theragnostic platform.

Measuring the Metabolic Evolution of Glioblastoma throughout Tumor Development, Regression, and Recurrence with Hyperpolarized Magnetic Resonance.

Rapid diagnosis and therapeutic monitoring of aggressive diseases such as glioblastoma can improve patient survival by providing physicians the time to optimally deliver treatment. This research tested whether metabolic imaging with hyperpolarized MRI could detect changes in tumor progression faster than conventional anatomic MRI in patient-derived glioblastoma murine models. To capture the dynamic nature of cancer metabolism, hyperpolarized MRI, NMR spectroscopy, and immunohistochemistry were performed at several time-points during tumor development, regression, and recurrence. Hyperpolarized MRI detected significant changes of metabolism throughout tumor progression whereas conventional MRI was less sensitive. This was accompanied by aberrations in amino acid and phospholipid lipid metabolism and MCT1 expression. Hyperpolarized MRI can help address clinical challenges such as identifying malignant disease prior to aggressive growth, differentiating pseudoprogression from true progression, and predicting relapse. The individual evolution of these metabolic assays as well as their correlations with one another provides context for further academic research.

Beyond Colonoscopy: Exploring New Cell Surface Biomarkers for Detection of Early, Heterogenous Colorectal Lesions.

Colorectal cancer (CRC) is the third leading cause of cancer-related deaths among both men and women in the United States. Early detection and surgical removal of high-risk lesions in the colon can prevent disease from developing and spreading. Despite implementation of programs aimed at early detection, screening colonoscopies fail to detect a fraction of potentially aggressive colorectal lesions because of their location or nonobvious morphology. Optical colonoscopies, while highly effective, rely on direct visualization to detect changes on the surface mucosa that are consistent with dysplasia. Recent advances in endoscopy techniques and molecular imaging permit microscale visualization of the colonic mucosa. These technologies can be combined with various molecular probes that recognize and target heterogenous lesion surfaces to achieve early, real-time, and potentially non-invasive, detection of pre-cancerous lesions. The primary goal of this review is to contextualize existing and emergent CRC surface biomarkers and assess each's potential as a candidate marker for early marker-based detection of CRC lesions. CRC markers that we include were stratified by the level of support gleaned from peer-reviewed publications, abstracts, and databases of both CRC and other cancers. The selected biomarkers, accessible on the cell surface and preferably on the luminal surface of the colon tissue, are organized into three categories: (1) established biomarkers (those with considerable data and high confidence), (2) emerging biomarkers (those with increasing research interest but with less supporting data), and (3) novel candidates (those with very recent data, and/or supportive evidence from other tissue systems). We also present an overview of recent advances in imaging techniques useful for visual detection of surface biomarkers, and discuss the ease with which these methods can be combined with microscopic visualization.

Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer.

BACKGROUND: There is an unmet need for noninvasive imaging markers that can help identify the aggressive subtype(s) of pancreatic ductal adenocarcinoma (PDAC) at diagnosis and at an earlier time point, and evaluate the efficacy of therapy prior to tumor reduction. In the past few years, there have been two major developments with potential for a significant impact in establishing imaging biomarkers for PDAC and pancreatic cancer premalignancy: (1) hyperpolarized metabolic (HP)-magnetic resonance (MR), which increases the sensitivity of conventional MR by over 10,000-fold, enabling real-time metabolic measurements; and (2) applications of artificial intelligence (AI). OBJECTIVE: Our objective of this review was to discuss these two exciting but independent developments (HP-MR and AI) in the realm of PDAC imaging and detection from the available literature to date. METHODS: A systematic review following the PRISMA extension for Scoping Reviews (PRISMA-ScR) guidelines was performed. Studies addressing the utilization of HP-MR and/or AI for early detection, assessment of aggressiveness, and interrogating the early efficacy of therapy in patients with PDAC cited in recent clinical guidelines were extracted from the PubMed and Google Scholar databases. The studies were reviewed following predefined exclusion and inclusion criteria, and grouped based on the utilization of HP-MR and/or AI in PDAC diagnosis. RESULTS: Part of the goal of this review was to highlight the knowledge gap of early detection in pancreatic cancer by any imaging modality, and to emphasize how AI and HP-MR can address this critical gap. We reviewed every paper published on HP-MR applications in PDAC, including six preclinical studies and one clinical trial. We also reviewed several HP-MR-related articles describing new probes with many functional applications in PDAC. On the AI side, we reviewed all existing papers that met our inclusion criteria on AI applications for evaluating computed tomography (CT) and MR images in PDAC. With the emergence of AI and its unique capability to learn across multimodal data, along with sensitive metabolic imaging using HP-MR, this knowledge gap in PDAC can be adequately addressed. CT is an accessible and widespread imaging modality worldwide as it is affordable; because of this reason alone, most of the data discussed are based on CT imaging datasets. Although there were relatively few MR-related papers included in this review, we believe that with rapid adoption of MR imaging and HP-MR, more clinical data on pancreatic cancer imaging will be available in the near future. CONCLUSIONS: Integration of AI, HP-MR, and multimodal imaging information in pancreatic cancer may lead to the development of real-time biomarkers of early detection, assessing aggressiveness, and interrogating early efficacy of therapy in PDAC.

Directed evolution of cyclic peptides for inhibition of autophagy.

In recent decades it has become increasingly clear that induction of autophagy plays an important role in the development of treatment resistance and dormancy in many cancer types. Unfortunately, chloroquine (CQ) and hydroxychloroquine (HCQ), two autophagy inhibitors in clinical trials, suffer from poor pharmacokinetics and high toxicity at therapeutic dosages. This has prompted intense interest in the development of targeted autophagy inhibitors to re-sensitize disease to treatment with minimal impact on normal tissue. We utilized Scanning Unnatural Protease Resistant (SUPR) mRNA display to develop macrocyclic peptides targeting the autophagy protein LC3. The resulting peptides bound LC3A and LC3B-two essential components of the autophagosome maturation machinery-with mid-nanomolar affinities and disrupted protein-protein interactions (PPIs) between LC3 and its binding partners in vitro. The most promising LC3-binding SUPR peptide accessed the cytosol at low micromolar concentrations as measured by chloroalkane penetration assay (CAPA) and inhibited starvation-mediated GFP-LC3 puncta formation in a concentration-dependent manner. LC3-binding SUPR peptides re-sensitized platinum-resistant ovarian cancer cells to cisplatin treatment and triggered accumulation of the adapter protein p62 suggesting decreased autophagic flux through successful disruption of LC3 PPIs in cell culture. In mouse models of metastatic ovarian cancer, treatment with LC3-binding SUPR peptides and carboplatin resulted in almost complete inhibition of tumor growth after four weeks of treatment. These results indicate that SUPR peptide mRNA display can be used to develop cell-penetrating macrocyclic peptides that target and disrupt the autophagic machinery in vitro and in vivo.

Hyperpolarized MRI with silicon micro and nanoparticles: Principles and applications.

Silicon-based micro and nanoparticles are ideally suited for use as biomedical imaging agents because of their biocompatibility, biodegradability, and simple surface chemistry that facilitates drug loading and targeting. A method to hyperpolarize silicon particles using dynamic nuclear polarization (DNP), which increases magnetic resonance (MR) imaging signals by several orders-of-magnitude through enhanced nuclear spin alignment, was developed to allow silicon particles to function as contrast agents for in vivo magnetic resonance imaging. In this review, we describe the application of the DNP technique to silicon particles and nanoparticles for background-free real-time molecular MR imaging. This review provides a summary of the state-of-the-science in silicon particle hyperpolarization with a detailed protocol for hyperpolarizing silicon particles. This information will foster awareness and spur interest in this emerging area of nanoimaging and provide a path to new developments and discoveries to further advance the field. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery > Emerging Technologies.

Excess exogenous pyruvate inhibits lactate dehydrogenase activity in live cells in an MCT1-dependent manner.

Cellular pyruvate is an essential metabolite at the crossroads of glycolysis and oxidative phosphorylation, capable of supporting fermentative glycolysis by reduction to lactate mediated by lactate dehydrogenase (LDH) among other functions. Several inherited diseases of mitochondrial metabolism impact extracellular (plasma) pyruvate concentrations, and [1-13C]pyruvate infusion is used in isotope-labeled metabolic tracing studies, including hyperpolarized magnetic resonance spectroscopic imaging. However, how these extracellular pyruvate sources impact intracellular metabolism is not clear. Herein, we examined the effects of excess exogenous pyruvate on intracellular LDH activity, extracellular acidification rates (ECARs) as a measure of lactate production, and hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates across a panel of tumor and normal cells. Combined LDH activity and LDHB/LDHA expression analysis intimated various heterotetrameric isoforms comprising LDHA and LDHB in tumor cells, not only canonical LDHA. Millimolar concentrations of exogenous pyruvate induced substrate inhibition of LDH activity in both enzymatic assays ex vivo and in live cells, abrogated glycolytic ECAR, and inhibited hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates in cellulo. Of importance, the extent of exogenous pyruvate-induced inhibition of LDH and glycolytic ECAR in live cells was highly dependent on pyruvate influx, functionally mediated by monocarboxylate transporter-1 localized to the plasma membrane. These data provided evidence that highly concentrated bolus injections of pyruvate in vivo may transiently inhibit LDH activity in a tissue type- and monocarboxylate transporter-1-dependent manner. Maintaining plasma pyruvate at submillimolar concentrations could potentially minimize transient metabolic perturbations, improve pyruvate therapy, and enhance quantification of metabolic studies, including hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging and stable isotope tracer experiments.

NMR Spectroscopy-Based Metabolomics of Platelets to Analyze Brain Tumors.

"Tumor-educated platelets" have recently generated substantial interest for the diagnosis of cancer. We hypothesized that tumor educated platelets from patients with brain tumors will reflect altered metabolism compared to platelets from healthy volunteers. Here, in a pilot study, we have employed nuclear magnetic resonance (NMR) spectroscopy in platelets from brain tumor patients to demonstrate altered metabolism compared to the platelets obtained from healthy volunteers.

Melanoma Evolves Complete Immunotherapy Resistance through the Acquisition of a Hypermetabolic Phenotype.

Despite the clinical success of T-cell checkpoint blockade, most patients with cancer still fail to have durable responses to immunotherapy. The molecular mechanisms driving checkpoint blockade resistance, whether preexisting or evolved, remain unclear. To address this critical knowledge gap, we treated B16 melanoma with the combination of CTLA-4, PD-1, and PD-L1 blockade and a Flt3 ligand vaccine (≥75% curative), isolated tumors resistant to therapy, and serially passaged them in vivo with the same treatment regimen until they developed complete resistance. Using gene expression analysis and immunogenomics, we determined the adaptations associated with this resistance phenotype. Checkpoint resistance coincided with acquisition of a "hypermetabolic" phenotype characterized by coordinated upregulation of the glycolytic, oxidoreductase, and mitochondrial oxidative phosphorylation pathways. These resistant tumors flourished under hypoxic conditions, whereas metabolically starved T cells lost glycolytic potential, effector function, and the ability to expand in response to immunotherapy. Furthermore, we found that checkpoint-resistant versus -sensitive tumors could be separated by noninvasive MRI imaging based solely on their metabolic state. In a cohort of patients with melanoma resistant to both CTLA-4 and PD-1 blockade, we observed upregulation of pathways indicative of a similar hypermetabolic state. Together, these data indicated that melanoma can evade T-cell checkpoint blockade immunotherapy by adapting a hypermetabolic phenotype.

Hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion is rate-limited by monocarboxylate transporter-1 in the plasma membrane.

Hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging (MRSI) is a noninvasive metabolic-imaging modality that probes carbon flux in tissues and infers the state of metabolic reprograming in tumors. Prevailing models attribute elevated hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates in aggressive tumors to enhanced glycolytic flux and lactate dehydrogenase A (LDHA) activity (Warburg effect). By contrast, we find by cross-sectional analysis using genetic and pharmacological tools in mechanistic studies applied to well-defined genetically engineered cell lines and tumors that initial hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates as well as global conversion were highly dependent on and critically rate-limited by the transmembrane influx of [1-13C]pyruvate mediated predominately by monocarboxylate transporter-1 (MCT1). Specifically, in a cell-encapsulated alginate bead model, induced short hairpin (shRNA) knockdown or overexpression of MCT1 quantitatively inhibited or enhanced, respectively, unidirectional pyruvate influxes and [1-13C]pyruvate-to-[1-13C]lactate conversion rates, independent of glycolysis or LDHA activity. Similarly, in tumor models in vivo, hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion was highly dependent on and critically rate-limited by the induced transmembrane influx of [1-13C]pyruvate mediated by MCT1. Thus, hyperpolarized [1-13C]pyruvate MRSI measures primarily MCT1-mediated [1-13C]pyruvate transmembrane influx in vivo, not glycolytic flux or LDHA activity, driving a reinterpretation of this maturing new technology during clinical translation. Indeed, Kaplan-Meier survival analysis for patients with pancreatic, renal, lung, and cervical cancers showed that high-level expression of MCT1 correlated with poor overall survival, and only in selected tumors, coincident with LDHA expression. Thus, hyperpolarized [1-13C]pyruvate MRSI provides a noninvasive functional assessment primarily of MCT1 as a clinical biomarker in relevant patient populations.

Interleukin-17-induced neutrophil extracellular traps mediate resistance to checkpoint blockade in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy with an immunosuppressive microenvironment that is resistant to most therapies. IL17 is involved in pancreatic tumorigenesis, but its role in invasive PDAC is undetermined. We hypothesized that IL17 triggers and sustains PDAC immunosuppression. We inhibited IL17/IL17RA signaling using pharmacological and genetic strategies alongside mass cytometry and multiplex immunofluorescence techniques. We uncovered that IL17 recruits neutrophils, triggers neutrophil extracellular traps (NETs), and excludes cytotoxic CD8 T cells from tumors. Additionally, IL17 blockade increases immune checkpoint blockade (PD-1, CTLA4) sensitivity. Inhibition of neutrophils or Padi4-dependent NETosis phenocopies IL17 neutralization. NMR spectroscopy revealed changes in tumor lactate as a potential early biomarker for IL17/PD-1 combination efficacy. Higher expression of IL17 and PADI4 in human PDAC corresponds with poorer prognosis, and the serum of patients with PDAC has higher potential for NETosis. Clinical studies with IL17 and checkpoint blockade represent a novel combinatorial therapy with potential efficacy for this lethal disease.

Therapeutic efficacy of liposomal Grb2 antisense oligodeoxynucleotide (L-Grb2) in preclinical models of ovarian and uterine cancer.

BACKGROUND: Adaptor proteins such as growth factor receptor-bound protein-2 (Grb2) play important roles in cancer cell signaling. In the present study, we examined the biological effects of liposomal antisense oligodeoxynucleotide that blocks Grb2 expression (L-Grb2) in gynecologic cancer models. MATERIALS AND METHODS: Murine orthotopic models of ovarian (OVCAR5 and SKOV3ip1) and uterine (Hec1a) cancer were used to study the biological effects of L-Grb2 on tumor growth. In vitro experiments (cell viability assay, Western blot analysis, siRNA transfection, and reverse phase protein array) were carried out to elucidate the mechanisms and potential predictors of tumor response to L-Grb2. FINDINGS: Treatment with L-Grb2 decreased tumor growth and metastasis in orthotopic models of ovarian cancer (OVCAR5, SKOV3ip1) by reducing angiogenesis and increasing apoptosis at a dose of 15 mg/kg with no effect on mouse body weight. Treatment with L-Grb2 and paclitaxel led to the greatest decrease in tumor weight (mean ± SEM, 0.17 g ± 0.10 g) compared with that in control mice (0.99 g ± 0.35 g). We also observed a reduction in tumor burden after treatment with L-Grb2 and the anti-VEGF antibody B-20 (86% decrease in tumor weight compared with that in controls). Ovarian cancer cells with ErbB2 amplification (OVCAR8 and SKOV3ip1) were the most sensitive to Grb2 downregulation. Reverse phase protein array analysis identified significant dysregulation of metabolites (LDHA, GAPDH, and TCA intermediates) in ovarian cancer cells after Grb2 downregulation. INTERPRETATION: L-Grb2 has therapeutic efficacy in preclinical models of ovarian and uterine cancer. These findings support further clinical development of L-Grb2.