Multiparametric Magnetic Resonance Imaging and Metabolic Characterization of Patient-Derived Xenograft Models of Clear Cell Renal Cell Carcinoma.

Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T2-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-13C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-13C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies.

Resistance to Androgen Deprivation Leads to Altered Metabolism in Human and Murine Prostate Cancer Cell and Tumor Models.

Currently, no clinical methods reliably predict the development of castration-resistant prostate cancer (CRPC) that occurs almost universally in men undergoing androgen deprivation therapy. Hyperpolarized (HP) 13C magnetic resonance imaging (MRI) could potentially detect the incipient emergence of CRPC based on early metabolic changes. To characterize metabolic shifts occurring upon the transition from androgen-dependent to castration-resistant prostate cancer (PCa), the metabolism of [U-13C]glucose and [U-13C]glutamine was analyzed by nuclear magnetic resonance spectroscopy. Comparison of steady-state metabolite concentrations and fractional enrichment in androgen-dependent LNCaP cells and transgenic adenocarcinoma of the murine prostate (TRAMP) murine tumors versus castration-resistant PC-3 cells and treatment-driven CRPC TRAMP tumors demonstrated that CRPC was associated with upregulation of glycolysis, tricarboxylic acid metabolism of pyruvate; and glutamine, glutaminolysis, and glutathione synthesis. These findings were supported by 13C isotopomer modeling showing increased flux through pyruvate dehydrogenase (PDH) and anaplerosis; enzymatic assays showing increased lactate dehydrogenase, PDH and glutaminase activity; and oxygen consumption measurements demonstrating increased dependence on anaplerotic fuel sources for mitochondrial respiration in CRPC. Consistent with ex vivo metabolomic studies, HP [1-13C]pyruvate distinguished androgen-dependent PCa from CRPC in cell and tumor models based on significantly increased HP [1-13C]lactate.

NMR quantification of lactate production and efflux and glutamate fractional enrichment in living human prostate biopsies cultured with [1,6-13 C2 ]glucose.

PURPOSE: Image-guided prostate biopsies are routinely acquired in the diagnosis and treatment monitoring of prostate cancer, yielding useful tissue for identifying metabolic biomarkers and therapeutic targets. We developed an optimized biopsy tissue culture protocol in combination with [1,6-13 C2 ]glucose labeling and quantitative high-resolution NMR to measure glycolysis and tricarboxcylic acid (TCA) cycle activity in freshly acquired living human prostate biopsies. METHODS: We acquired 34 MRI-ultrasound fusion-guided prostate biopsies in vials on ice from 22 previously untreated patients. Within 15 min, biopsies were transferred to rotary tissue culture in 37°C prostate medium containing [1,6-13 C2 ]glucose. Following 24 h of culture, tissue lactate and glutamate pool sizes and fractional enrichments were quantified using quantitative 1 H high resolution magic angle spinning Carr-Purcell-Meiboom-Gill (CPMG) spectroscopy at 1°C with and without 13 C decoupling. Lactate effluxed from the biopsy tissue was quantified in the culture medium using quantitative solution-state high-resolution NMR. RESULTS: Lactate concentration in low-grade cancer (1.15 ± 0.78 nmol/mg) and benign (0.74 ± 0.15 nmol/mg) biopsies agreed with prior published measurements of snap-frozen biopsies. There was substantial fractional enrichment of [3-13 C]lactate (≈70%) and [4-13 C]glutamate (≈24%) in both low-grade cancer and benign biopsies. Although a significant difference in tissue [3-13 C]lactate fractional enrichment was not observed, lactate efflux was significantly higher (P < 0.05) in low-grade cancer biopsies (0.55 ± 0.14 nmol/min/mg) versus benign biopsies (0.31 ± 0.04 nmol/min/mg). CONCLUSION: A protocol was developed for quantification of lactate production-efflux and TCA cycle activity in single living human prostate biopsies, allowing metabolic labeling on a wide spectrum of human tissues (e.g., metastatic, post-non-surgical therapy) from patients not receiving surgery.

Molecular detection of inflammation in cell models using hyperpolarized 13C-pyruvate.

The detection and treatment monitoring of inflammatory states remain challenging in part due to the multifactorial mechanisms of immune activation and spectrum of clinical manifestations. Currently, diagnostic strategies tend to be subjective and limited quantitative tools exist to monitor optimal treatment strategies. Pro-inflammatory M1 polarized macrophages exhibit a distinct metabolic glycolytic phenotype compared to the continuum of M2 polarization states. In the present study, the distinct metabolic phenotypes of resting and activated macrophages were successfully characterized and quantified using hyperpolarized carbon-13 (13C) labeled pyruvate and its metabolic products, i.e. lactate, as a biomarker of resting, disease and treated states. Methods: Mouse macrophage J774A.1 cells were used as a model system in an NMR compatible bioreactor to facilitate dynamic hyperpolarized 13C measurements. The glycolytic metabolism of the cells in the quiescent or resting state were compared with macrophages stimulated by lipopolysaccharide, a classical M1 activator using hyperpolarized 13C labeled pyruvate. Additionally, the activated macrophages were also treated with a non-steroidal anti-inflammatory drug to assess the changes in hyperpolarized lactate signal. The hyperpolarized lactate signals were then correlated using biochemical and molecular assays. Results: We first validated our model system of inflammatory cells by the hallmarks of M1 polarization using steady state metabolic profiling with high resolution NMR in conjunction with nitric oxide Greiss assay, enzyme activity, and mRNA expression. Subsequently, we clearly showed that the cutting edge technology of hyperpolarized 13C NMR can be used to detect elevated lactate levels in M1 polarized macrophages in comparison to control and non-steroidal anti-inflammatory drug treated M2 states. Conclusion: Hyperpolarized 13C lactate has the potential to serve as a biomarker to non-invasively detect and quantify pro-inflammatory state of immune regulatory cells and its response to therapy.

Detection of Bacteria-Specific Metabolism Using Hyperpolarized [2-13C]Pyruvate.

The differentiation of bacterial infection from other causes of inflammation is difficult in clinical practice and is critical where patient outcomes rely heavily on early interventions. In addition to physical exam and laboratory markers, several imaging modalities are frequently employed, but these techniques generally target the host immune response, rather than the living microorganisms themselves. Here, we describe a method to detect bacteria-specific metabolism using hyperpolarized (HP) 13C magnetic resonance spectroscopy. This technology allows visualization of the real-time conversion of enriched 13C substrates to their metabolic products, identified by their distinct chemical shifts. We have identified the rapid metabolism of HP [2-13C]pyruvate to [1-13C]acetate as a metabolic signature of common bacterial pathogens. We demonstrate this conversion in representative Gram-negative and Gram-positive bacteria, namely, Escherichia coli and Staphylococcus aureus, and its absence in key mammalian cell types. Furthermore, this conversion was successfully modulated in three mutant strains, corresponding to deletions of relevant enzymes.

Targeted Molecular Imaging of Cancer Cells Using MS2-Based (129)Xe NMR.

We have synthesized targeted, selective, and highly sensitive (129)Xe NMR nanoscale biosensors using a spherical MS2 viral capsid, Cryptophane A molecules, and DNA aptamers. The biosensors showed strong binding specificity toward targeted lymphoma cells (Ramos line). Hyperpolarized (129)Xe NMR signal contrast and hyper-CEST (129)Xe MRI image contrast indicated its promise as highly sensitive hyperpolarized (129)Xe NMR nanoscale biosensor for future applications in cancer detection in vivo.

Genetically encoded reporters for hyperpolarized xenon magnetic resonance imaging.

Magnetic resonance imaging (MRI) enables high-resolution non-invasive observation of the anatomy and function of intact organisms. However, previous MRI reporters of key biological processes tied to gene expression have been limited by the inherently low molecular sensitivity of conventional (1)H MRI. This limitation could be overcome through the use of hyperpolarized nuclei, such as in the noble gas xenon, but previous reporters acting on such nuclei have been synthetic. Here, we introduce the first genetically encoded reporters for hyperpolarized (129)Xe MRI. These expressible reporters are based on gas vesicles (GVs), gas-binding protein nanostructures expressed by certain buoyant microorganisms. We show that GVs are capable of chemical exchange saturation transfer interactions with xenon, which enables chemically amplified GV detection at picomolar concentrations (a 100- to 10,000-fold improvement over comparable constructs for (1)H MRI). We demonstrate the use of GVs as heterologously expressed indicators of gene expression and chemically targeted exogenous labels in MRI experiments performed on living cells.