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.

Rapid nuclear magnetic resonance data acquisition with improved resolution and sensitivity for high-throughput metabolomic analysis.

Nuclear magnetic resonance (NMR)-based metabolomics has witnessed rapid advancements in recent years with the continuous development of new methods to enhance the sensitivity, resolution, and speed of data acquisition. Some of the approaches were earlier used for peptide and protein resonance assignments and have now been adapted to metabolomics. At the same time, new NMR methods involving novel data acquisition techniques, suited particularly for high-throughput analysis in metabolomics, have been developed. In this review, we focus on the different sampling strategies or data acquisition methods that have been developed in our laboratory and other groups to acquire NMR spectra rapidly with high sensitivity and resolution for metabolomics. In particular, we focus on the use of multiple receivers, phase modulation NMR spectroscopy, and fast-pulsing methods for identification and assignments of metabolites.

Prostate Cancer Energetics and Biosynthesis.

Cancers must alter their metabolism to satisfy the increased demand for energy and to produce building blocks that are required to create a rapidly growing tumor. Further, for cancer cells to thrive, they must also adapt to an often changing tumor microenvironment, which can present new metabolic challenges (ex. hypoxia) that are unfavorable for most other cells. As such, altered metabolism is now considered an emerging hallmark of cancer. Like many other malignancies, the metabolism of prostate cancer is considerably different compared to matched benign tissue. However, prostate cancers exhibit distinct metabolic characteristics that set them apart from many other tumor types. In this chapter, we will describe the known alterations in prostate cancer metabolism that occur during initial tumorigenesis and throughout disease progression. In addition, we will highlight upstream regulators that control these metabolic changes. Finally, we will discuss how this new knowledge is being leveraged to improve patient care through the development of novel biomarkers and metabolically targeted therapies.

Real-Time Interrogation of Aspirin Reactivity, Biochemistry, and Biodistribution by Hyperpolarized Magnetic Resonance Spectroscopy.

Hyperpolarized magnetic resonance spectroscopy enables quantitative, non-radioactive, real-time measurement of imaging probe biodistribution and metabolism in vivo. Here, we investigate and report on the development and characterization of hyperpolarized acetylsalicylic acid (aspirin) and its use as a nuclear magnetic resonance (NMR) probe. Aspirin derivatives were synthesized with single- and double-13 C labels and hyperpolarized by dynamic nuclear polarization with 4.7 % and 3 % polarization, respectively. The longitudinal relaxation constants (T1 ) for the labeled acetyl and carboxyl carbonyls were approximately 30 seconds, supporting in vivo imaging and spectroscopy applications. In vitro hydrolysis, transacetylation, and albumin binding of hyperpolarized aspirin were readily monitored in real time by 13 C-NMR spectroscopy. Hyperpolarized, double-labeled aspirin was well tolerated in mice and could be observed by both 13 C-MR imaging and 13 C-NMR spectroscopy in vivo.

Hyperpolarized Porous Silicon Nanoparticles: Potential Theragnostic Material for 29 Si Magnetic Resonance Imaging.

Porous silicon nanoparticles have recently garnered attention as potentially-promising biomedical platforms for drug delivery and medical diagnostics. Here, we demonstrate porous silicon nanoparticles as contrast agents for 29 Si magnetic resonance imaging. Size-controlled porous silicon nanoparticles were synthesized by magnesiothermic reduction of silica nanoparticles and were surface activated for further functionalization. Particles were hyperpolarized via dynamic nuclear polarization to enhance their 29 Si MR signals; the particles demonstrated long 29 Si spin-lattice relaxation (T1 ) times (∼25 mins), which suggests potential applicability for medical imaging. Furthermore, 29 Si hyperpolarization levels were sufficient to allow 29 Si MRI in phantoms. These results underscore the potential of porous silicon nanoparticles that, when combined with hyperpolarized magnetic resonance imaging, can be a powerful theragnostic deep tissue imaging platform to interrogate various biomolecular processes in vivo.

A fast NMR method for resonance assignments: application to metabolomics.

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled ((12)C) or (13)C-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D [(13)C, (1)H] HSQC-TOCSY, (2) 2D (1)H-(1)H TOCSY and (3) 2D (13)C-(1)H HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D [(13)C, (1)H] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete (1)H and (13)C assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.

Rapid characterization of molecular diffusion by NMR spectroscopy.

An NMR-based approach for rapid characterization of translational diffusion of molecules has been developed. Unlike the conventional method of acquiring a series of 2D (13)C and (1)H spectra, the proposed approach involves a single 2D NMR spectrum, which can be acquired in minutes. Using this method, it was possible to detect the presence of intermediate oligomeric species of diphenylalanine in solution during the process of its self-assembly to form nanotubular structures.

NMR studies of preimplantation embryo metabolism in human assisted reproductive techniques: a new biomarker for assessment of embryo implantation potential.

There has been growing interest in understanding energy metabolism in human embryos generated using assisted reproductive techniques (ART) for improving the overall success rate of the method. Using NMR spectroscopy as a noninvasive tool, we studied human embryo metabolism to identify specific biomarkers to assess the quality of embryos for their implantation potential. The study was based on estimation of pyruvate, lactate and alanine levels in the growth medium, ISM1, used in the culture of embryos. An NMR study involving 127 embryos from 48 couples revealed that embryos transferred on Day 3 (after 72 h in vitro culture) with successful implantation (pregnancy) exhibited significantly (p < 10(-5) ) lower pyruvate/alanine ratios compared to those that failed to implant. Lactate levels in media were similar for all embryos. This implies that in addition to lactate production, successfully implanted embryos use pyruvate to produce alanine and other cellular functions. While pyruvate and alanine individually have been used as biomarkers, the present study highlights the potential of combining them to provide a single parameter that correlates strongly with implantation potential.

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.

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.

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.

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.

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.

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.

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.

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.

Fast NMR Methods for Identification of Resonances and Metabolic Pathways.

High-throughput analysis of NMR data in metabolomics involves both rapid data acquisition and analysis. We describe here a data collection and analysis protocol, which enables fast multidimensional NMR data acquisition and automated analysis of NMR spectra to rapidly identify the metabolites and assign them to active metabolic pathways in the system.

Assessing Therapeutic Efficacy in Real-time by Hyperpolarized Magnetic Resonance Metabolic Imaging.

Precisely measuring tumor-associated alterations in metabolism clinically will enable the efficient assessment of therapeutic responses. Advances in imaging technologies can exploit the differences in cancer-associated cell metabolism as compared to normal tissue metabolism, linking changes in target metabolism to therapeutic efficacy. Metabolic imaging by Positron Emission Tomography (PET) employing 2-fluoro-deoxy-glucose ([18F]FDG) has been used as a routine diagnostic tool in the clinic. Recently developed hyperpolarized Magnetic Resonance (HP-MR), which radically increases the sensitivity of conventional MRI, has created a renewed interest in functional and metabolic imaging. The successful translation of this technique to the clinic was achieved recently with measurements of 13C-pyruvate metabolism. Here, we review the potential clinical roles for metabolic imaging with hyperpolarized MRI as applied in assessing therapeutic intervention in different cancer systems.

Laser assisted zona hatching does not lead to immediate impairment in human embryo quality and metabolism.

Laser assisted zona hatching (LAH) is a routinely used therapeutic intervention in assisted reproductive technology for patients with poor prognosis. However, results are not conclusive in demonstrating the benefits of zona hatching in improving the pregnancy rate. Recent observations on LAH induced genetic instability in animal embryos prompted us to look into the effects of laser assisted zona hatching on the human preimplantation embryo quality and metabolic uptake using high resolution nuclear magnetic resonance (NMR) technology. This experimental prospective study included fifty embryos from twenty-five patients undergoing intra cytoplasmic sperm injection. Embryo quality assessment followed by profiling of spent media for the non-invasive evaluation of metabolites was performed using NMR spectroscopy 24 hours after laser treatment and compared with that of non-treated sibling embryos. Both cell number and embryo quality on day 3 of development did not vary significantly between the two groups at 24 hours post laser treatment interval. Time lapse monitoring of the embryos for 24 hours did not reveal blastomere fragmentation adjacent to the point of laser treatment. Similarly, principal component analysis of metabolites did not demonstrate any variation across the groups. These results suggest that laser assisted zona hatching does not affect human preimplantation embryo morphology and metabolism at least until 24 hours post laser assisted zona hatching. However, studies are required to elucidate laser induced metabolic and developmental changes at extended time periods. ABBREVIATIONS: AH: assisted hatching; ART: assisted reproductive technology; DNA: deoxy-ribo nucleic acid; LAH: laser assisted hatching; MHz: megahertz; NMR: nuclear magnetic resonance; PCA: principal component analysis; PGD: preimplantation genetic diagnosis; TLM: time lapse monitoring.