Patient-Derived Models of Cancer in the NCI PDMC Consortium: Selection, Pitfalls, and Practical Recommendations.

For over a century, early researchers sought to study biological organisms in a laboratory setting, leading to the generation of both in vitro and in vivo model systems. Patient-derived models of cancer (PDMCs) have more recently come to the forefront of preclinical cancer models and are even finding their way into clinical practice as part of functional precision medicine programs. The PDMC Consortium, supported by the Division of Cancer Biology in the National Cancer Institute of the National Institutes of Health, seeks to understand the biological principles that govern the various PDMC behaviors, particularly in response to perturbagens, such as cancer therapeutics. Based on collective experience from the consortium groups, we provide insight regarding PDMCs established both in vitro and in vivo, with a focus on practical matters related to developing and maintaining key cancer models through a series of vignettes. Although every model has the potential to offer valuable insights, the choice of the right model should be guided by the research question. However, recognizing the inherent constraints in each model is crucial. Our objective here is to delineate the strengths and limitations of each model as established by individual vignettes. Further advances in PDMCs and the development of novel model systems will enable us to better understand human biology and improve the study of human pathology in the lab.

Distinguishing metabolic signals of liver tumors from surrounding liver cells using hyperpolarized 13 C MRI and gadoxetate.

PURPOSE: To use the hepatocyte-specific gadolinium-based contrast agent gadoxetate combined with hyperpolarized (HP) [1-13 C]pyruvate MRI to selectively suppress metabolic signals from normal hepatocytes while preserving the signals arising from tumors. METHODS: Simulations were performed to determine the expected changes in HP 13 C MR signal in liver and tumor under the influence of gadoxetate. CC531 colon cancer cells were implanted into the livers of five Wag/Rij rats. Liver and tumor metabolism were imaged at 3 T using HP [1-13 C] pyruvate chemical shift imaging before and 15 min after injection of gadoxetate. Area under the curve for pyruvate and lactate were measured from voxels containing at least 75% of normal-appearing liver or tumor. RESULTS: Numerical simulations predicted a 36% decrease in lactate-to-pyruvate (L/P) ratio in liver and 16% decrease in tumor. In vivo, baseline L/P ratio was 0.44 ± 0.25 in tumors versus 0.21 ± 0.08 in liver (p = 0.09). Following administration of gadoxetate, mean L/P ratio decreased by an average of 0.11 ± 0.06 (p < 0.01) in normal-appearing liver. In tumors, mean L/P ratio post-gadoxetate did not show a statistically significant change from baseline. Compared to baseline levels, the relative decrease in L/P ratio was significantly greater in liver than in tumors (-0.52 ± 0.16 vs. -0.19 ± 0.25, p < 0.05). CONCLUSIONS: The intracellular hepatobiliary contrast agent showed a greater effect suppressing HP 13 C MRI metabolic signals (through T1 shortening) in normal-appearing liver when compared to tumors. The combined use of HP MRI with selective gadolinium contrast agents may allow more selective imaging in HP 13 C MRI.

Hyperpolarized [1-13 C] pyruvate MRSI to detect metabolic changes in liver in a methionine and choline-deficient diet rat model of fatty liver disease.

PURPOSE: Nonalcoholic fatty liver disease is an important cause of chronic liver disease. There are limited methods for monitoring metabolic changes during progression to steatohepatitis. Hyperpolarized 13 C MRSI (HP 13 C MRSI) was used to measure metabolic changes in a rodent model of fatty liver disease. METHODS: Fifteen Wistar rats were placed on a methionine- and choline-deficient (MCD) diet for 1-18 weeks. HP 13 C MRSI, T2 -weighted imaging, and fat-fraction measurements were obtained at 3 T. Serum aspartate aminotransaminase, alanine aminotransaminase, and triglycerides were measured. Animals were sacrificed for histology and measurement of tissue lactate dehydrogenase (LDH) activity. RESULTS: Animals lost significant weight (13.6% ± 2.34%), an expected characteristic of the MCD diet. Steatosis, inflammation, and mild fibrosis were observed. Liver fat fraction was 31.7% ± 4.5% after 4 weeks and 22.2% ± 4.3% after 9 weeks. Lactate-to-pyruvate and alanine-to-pyruvate ratios decreased significantly over the study course; were negatively correlated with aspartate aminotransaminase and alanine aminotransaminase (r = -[0.39-0.61]); and were positively correlated with triglycerides (r = 0.59-0.60). Despite observed decreases in hyperpolarized lactate signal, LDH activity increased by a factor of 3 in MCD diet-fed animals. Observed decreases in lactate and alanine hyperpolarized signals on the MCD diet stand in contrast to other studies of liver injury, where lactate and alanine increased. Observed hyperpolarized metabolite changes were not explained by alterations in LDH activity, suggesting that changes may reflect co-factor depletion known to occur as a result of oxidative stress in the MCD diet. CONCLUSION: HP 13 C MRSI can noninvasively measure metabolic changes in the MCD model of chronic liver disease.

Parallel detection of chemical reactions in a microfluidic platform using hyperpolarized nuclear magnetic resonance.

The sensitivity of NMR may be enhanced by more than four orders of magnitude via dissolution dynamic nuclear polarization (dDNP), potentially allowing real-time, in situ analysis of chemical reactions. However, there has been no widespread use of the technique for this application and the major limitation has been the low experimental throughput caused by the time-consuming polarization build-up process at cryogenic temperatures and fast decay of the hyper-intense signal post dissolution. To overcome this limitation, we have developed a microfluidic device compatible with dDNP-MR spectroscopic imaging methods for detection of reactants and products in chemical reactions in which up to 8 reactions can be measured simultaneously using a single dDNP sample. Multiple MR spectroscopic data sets can be generated under the same exact conditions of hyperpolarized solute polarization, concentration, pH, and temperature. A proof-of-concept for the technology is demonstrated by identifying the reactants in the decarboxylation of pyruvate via hydrogen peroxide (e.g. 2-hydroperoxy-2-hydroxypropanoate, peroxymonocarbonate and CO2). dDNP-MR allows tracing of fast chemical reactions that would be barely detectable at thermal equilibrium by MR. We envisage that dDNP-MR spectroscopic imaging combined with microfluidics will provide a new high-throughput method for dDNP enhanced MR analysis of multiple components in chemical reactions and for non-destructive in situ metabolic analysis of hyperpolarized substrates in biological samples for laboratory and preclinical research.

Clinically Translatable Hyperpolarized 13C Bicarbonate pH Imaging Method for Use in Prostate Cancer.

Solid tumors such as prostate cancer (PCa) commonly develop an acidic microenvironment with pH 6.5-7.2, owing to heterogeneous perfusion, high metabolic activity, and rapid cell proliferation. In preclinical prostate cancer models, disease progression is associated with a decrease in tumor extracellular pH, suggesting that pH imaging may reflect an imaging biomarker to detect aggressive and high-risk disease. Therefore, we developed a hyperpolarized carbon-13 MRI method to image the tumor extracellular pH (pHe) and prepared it for clinical translation for detection and risk stratification of PCa. This method relies on the rapid breakdown of hyperpolarized (HP) 1,2-glycerol carbonate (carbonyl-13C) via base-catalyzed hydrolysis to produce HP 13CO32-, which is neutralized and converted to HP H13CO3-. After injection, HP H13CO3- equilibrates with HP 13CO2 in vivo and enables the imaging of pHe. Using insights gleaned from mechanistic studies performed in the hyperpolarized state, we solved issues of polarization loss during preparation in a clinical polarizer system. We successfully customized a reaction apparatus suitable for clinical application, developed clinical standard operating procedures, and validated the radiofrequency pulse sequence and imaging data acquisition with a wide range of animal models. The results demonstrated that we can routinely produce a highly polarized and safe HP H13CO3- contrast agent suitable for human injection. Preclinical imaging studies validated the reliability and accuracy of measuring acidification in healthy kidney and prostate tumor tissue. These methods were used to support an Investigational New Drug application to the U.S. Food and Drug Administration. This methodology is now ready to be implemented in human trials, with the ultimate goal of improving the management of PCa.

Co-Clinical Imaging Metadata Information (CIMI) for Cancer Research to Promote Open Science, Standardization, and Reproducibility in Preclinical Imaging.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute's (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

Metabolite-Specific Echo Planar Imaging for Preclinical Studies with Hyperpolarized 13C-Pyruvate MRI.

Metabolite-specific echo-planar imaging (EPI) sequences with spectral-spatial (spsp) excitation are commonly used in clinical hyperpolarized [1-13C]pyruvate studies because of their speed, efficiency, and flexibility. In contrast, preclinical systems typically rely on slower spectroscopic methods, such as chemical shift imaging (CSI). In this study, a 2D spspEPI sequence was developed for use on a preclinical 3T Bruker system and tested on in vivo mice experiments with patient-derived xenograft renal cell carcinoma (RCC) or prostate cancer tissues implanted in the kidney or liver. Compared to spspEPI sequences, CSI were found to have a broader point spread function via simulations and exhibited signal bleeding between vasculature and tumors in vivo. Parameters for the spspEPI sequence were optimized using simulations and verified with in vivo data. The expected lactate SNR and pharmacokinetic modeling accuracy increased with lower pyruvate flip angles (less than 15°), intermediate lactate flip angles (25° to 40°), and temporal resolution of 3 s. Overall SNR was also higher with coarser spatial resolution (4 mm isotropic vs. 2 mm isotropic). Pharmacokinetic modelling used to fit kPL maps showed results consistent with the previous literature and across different sequences and tumor xenografts. This work describes and justifies the pulse design and parameter choices for preclinical spspEPI hyperpolarized 13C-pyruvate studies and shows superior image quality to CSI.

Animal Models and Their Role in Imaging-Assisted Co-Clinical Trials.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients' tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

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.

Improving multiparametric MR-transrectal ultrasound guided fusion prostate biopsies with hyperpolarized 13 C pyruvate metabolic imaging: A technical development study.

PURPOSE: To develop techniques and establish a workflow using hyperpolarized carbon-13 (13 C) MRI and the pyruvate-to-lactate conversion rate (kPL ) biomarker to guide MR-transrectal ultrasound fusion prostate biopsies. METHODS: The integrated multiparametric MRI (mpMRI) exam consisted of a 1-min hyperpolarized 13 C-pyruvate EPI acquisition added to a conventional prostate mpMRI exam. Maps of kPL values were calculated, uploaded to a picture archiving and communication system and targeting platform, and displayed as color overlays on T2 -weighted anatomic images. Abdominal radiologists identified 13 C research biopsy targets based on the general recommendation of focal lesions with kPL >0.02(s-1 ), and created a targeting report for each study. Urologists conducted transrectal ultrasound-guided MR fusion biopsies, including the standard 1 H-mpMRI targets as well as 12-14 core systematic biopsies informed by the research 13 C-kPL targets. All biopsy results were included in the final pathology report and calculated toward clinical risk. RESULTS: This study demonstrated the safety and technical feasibility of integrating hyperpolarized 13 C metabolic targeting into routine 1 H-mpMRI and transrectal ultrasound fusion biopsy workflows, evaluated via 5 men (median age 71 years, prostate-specific antigen 8.4 ng/mL, Cancer of the Prostate Risk Assessment score 2) on active surveillance undergoing integrated scan and subsequent biopsies. No adverse event was reported. Median turnaround time was less than 3 days from scan to 13 C-kPL targeting, and scan-to-biopsy time was 2 weeks. Median number of 13 C targets was 1 (range: 1-2) per patient, measuring 1.0 cm (range: 0.6-1.9) in diameter, with a median kPL of 0.0319 s-1 (range: 0.0198-0.0410). CONCLUSIONS: This proof-of-concept work demonstrated the safety and feasibility of integrating hyperpolarized 13 C MR biomarkers to the standard mpMRI workflow to guide MR-transrectal ultrasound fusion biopsies.

Development of specialized magnetic resonance acquisition techniques for human hyperpolarized [13 C,15 N2 ]urea + [1-13 C]pyruvate simultaneous perfusion and metabolic imaging.

PURPOSE: This study aimed to develop and demonstrate the in vivo feasibility of a 3D stack-of-spiral balanced steady-state free precession(3D-bSSFP) urea sequence, interleaved with a metabolite-specific gradient echo (GRE) sequence for pyruvate and metabolic products, for improving the SNR and spatial resolution of the first hyperpolarized 13 C-MRI human study with injection of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea. METHODS: A metabolite-specific bSSFP urea imaging sequence was designed using a urea-specific excitation pulse, optimized TR, and 3D stack-of-spiral readouts. Simulations and phantom studies were performed to validate the spectral response of the sequence. The image quality of urea data acquired by the 3D-bSSFP sequence and the 2D-GRE sequence was evaluated with 2 identical injections of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea formula in a rat. Subsequently, the feasibility of the acquisition strategy was validated in a prostate cancer patient. RESULTS: Simulations and phantom studies demonstrated that 3D-bSSFP sequence achieved urea-only excitation, while minimally perturbing other metabolites (<1%). An animal study demonstrated that compared to GRE, bSSFP sequence provided an ∼2.5-fold improvement in SNR without perturbing urea or pyruvate kinetics, and bSSFP approach with a shorter spiral readout reduced blurring artifacts caused by J-coupling of [13 C,15 N2 ]urea. The human study demonstrated the in vivo feasibility and data quality of the acquisition strategy. CONCLUSION: The 3D-bSSFP urea sequence with a stack-of-spiral acquisition demonstrated significantly increased SNR and image quality for [13 C,15 N2 ]urea in co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea imaging studies. This work lays the foundation for future human studies to achieve high-quality and high-SNR metabolism and perfusion images.

Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology.

In this study, the objective was to characterize the MR signatures of the various benign prostate tissues and to differentiate them from cancer. Data was from seventy prostate cancer patients who underwent multiparametric MRI (mpMRI) and subsequent prostatectomy. The scans included T2-weighted imaging (T2W), diffusion weighted imaging, dynamic contrast-enhanced MRI (DCE MRI), and MR spectroscopic imaging. Histopathology tissue information was translated to MRI images. The mpMRI parameters were characterized separately per zone and by tissue type. The tissues were ordered according to trends in tissue parameter means. The peripheral zone tissue order was cystic atrophy, high grade prostatic intraepithelial neoplasia (HGPIN), normal, atrophy, inflammation, and cancer. Decreasing values for tissue order were exhibited by ADC (1.8 10-3 mm2/s to 1.2 10-3 mm2/s) and T2W intensity (3447 to 2576). Increasing values occurred for DCE MRI peak (143% to 157%), DCE MRI slope (101%/min to 169%/min), fractional anisotropy (FA) (0.16 to 0.19), choline (7.2 to 12.2), and choline / citrate (0.3 to 0.9). The transition zone tissue order was cystic atrophy, mixed benign prostatic hyperplasia (BPH), normal, atrophy, inflammation, stroma, anterior fibromuscular stroma, and cancer. Decreasing values occurred for ADC (1.6 10-3 mm2/s to 1.1 10-3 mm2/s) and T2W intensity (2863 to 2001). Increasing values occurred for DCE MRI peak (143% to 150%), DCE MRI slope (101%/min to 137%/min), FA (0.18 to 0.25), choline (7.9 to 11.7), and choline / citrate (0.3 to 0.7). Logistic regression was used to create parameter model fits to differentiate cancer from benign prostate tissues. The fits achieved AUCs ≥0.91. This study quantified the mpMRI characteristics of benign prostate tissues and demonstrated the capability of mpMRI to discriminate among benign as well as cancer tissues, potentially aiding future discrimination of cancer from benign confounders.

Clinical translation of hyperpolarized 13 C pyruvate and urea MRI for simultaneous metabolic and perfusion imaging.

PURPOSE: The combined hyperpolarized (HP) 13 C pyruvate and urea MRI has provided a simultaneous assessment of glycolytic metabolism and tissue perfusion for improved cancer diagnosis and therapeutic evaluation in preclinical studies. This work aims to translate this dual-probe HP imaging technique to clinical research. METHODS: A co-polarization system was developed where [1-13 C]pyruvic acid (PA) and [13 C, 15 N2 ]urea in water solution were homogeneously mixed and polarized on a 5T SPINlab system. Physical and chemical characterizations and toxicology studies of the combined probe were performed. Simultaneous metabolic and perfusion imaging was performed on a 3T clinical MR scanner by alternatively applying a multi-slice 2D spiral sequence for [1-13 C]pyruvate and its downstream metabolites and a 3D balanced steady-state free precession (bSSFP) sequence for [13 C, 15 N2 ]urea. RESULTS: The combined PA/urea probe has a glass-formation ability similar to neat PA and can generate nearly 40% liquid-state 13 C polarization for both pyruvate and urea in 3-4 h. A standard operating procedure for routine on-site production was developed and validated to produce 40 mL injection product of approximately 150 mM pyruvate and 35 mM urea. The toxicology study demonstrated the safety profile of the combined probe. Dynamic metabolite-specific imaging of [1-13 C]pyruvate, [1-13 C]lactate, [1-13 C]alanine, and [13 C, 15 N2 ]urea was achieved with adequate spatial (2.6 mm × 2.6 mm) and temporal resolution (4.2 s), and urea images showed reduced off-resonance artifacts due to the JCN coupling. CONCLUSION: The reported technical development and translational studies will lead to the first-in-human dual-agent HP MRI study and mark the clinical translation of the first HP 13 C MRI probe after pyruvate.

Specialized computational methods for denoising, B1 correction, and kinetic modeling in hyperpolarized 13 C MR EPSI studies of liver tumors.

PURPOSE: To develop a novel post-processing pipeline for hyperpolarized (HP) 13 C MRSI that integrates tensor denoising and B1+ correction to measure pyruvate-to-lactate conversion rates (kPL ) in patients with liver tumors. METHODS: Seven HP 13 C MR scans of progressing liver tumors were acquired using a custom 13 C surface transmit/receive coil and the echo-planar spectroscopic imaging (EPSI) data analysis included B0 correction, tensor rank truncation, and zero- and first-order phase corrections to recover metabolite signals that would otherwise be obscured by spectral noise as well as a correction for inhomogeneous transmit ( B1+ ) using a B1+ map aligned to the coil position for each patient scan. Processed HP data and corrected flip angles were analyzed with an inputless two-site exchange model to calculate kPL . RESULTS: Denoising averages SNR increases of pyruvate, lactate, and alanine were 37.4-, 34.0-, and 20.1-fold, respectively, with lactate and alanine dynamics most noticeably recovered and better defined. In agreement with Monte Carlo simulations, over-flipped regions underestimated kPL and under-flipped regions overestimated kPL . B1+ correction addressed this issue. CONCLUSION: The new HP 13 C EPSI post-processing pipeline integrated tensor denoising and B1+ correction to measure kPL in patients with liver tumors. These technical developments not only recovered metabolite signals in voxels that did not receive the prescribed flip angle, but also increased the extent and accuracy of kPL estimations throughout the tumor and adjacent regions including normal-appearing tissue and additional lesions.

Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294.

PURPOSE: A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.

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.

Tumor metabolism and neurocognition in CNS lymphoma.

BACKGROUND: The mechanistic basis for neurocognitive deficits in central nervous system (CNS) lymphoma and other brain tumors is incompletely understood. We tested the hypothesis that tumor metabolism impairs neurotransmitter pathways and neurocognitive function. METHODS: We performed serial cerebrospinal fluid (CSF) metabolomic analyses using liquid chromatography-electrospray tandem mass spectrometry to evaluate changes in the tumor microenvironment in 14 patients with recurrent CNS lymphoma, focusing on 18 metabolites involved in neurotransmission and bioenergetics. These were paired with serial mini-mental state examination (MMSE) and MRI studies for tumor volumetric analyses. Patients were analyzed in the setting of the phase I trial of lenalidomide/rituximab. Associations were assessed by Pearson and Spearman correlation coefficient. Generalized estimating equation (GEE) models were also established, adjusting for within-subject repeated measures. RESULTS: Of 18 metabolites, elevated CSF lactate correlated most strongly with lower MMSE score (P < 8E-8, ρ = -0.67). High lactate was associated with lower gamma-aminobutyric acid (GABA), higher glutamate/GABA ratio, and dopamine. Conversely, high succinate correlated with higher MMSE scores. Serial analysis demonstrated a reproducible, time-dependent, reciprocal correlation between changes in lactate and GABA concentrations. While high lactate and low GABA correlated with tumor contrast-enhancing volume, they correlated more significantly with lower MMSE scores than tumor volumes. CONCLUSIONS: We provide evidence that lactate production and Warburg metabolism may impact neurotransmitter dysregulation and neurocognition in CNS lymphomas. We identify novel metabolomic biomarkers that may be applied in future studies of neurocognition in CNS lymphomas. Elucidation of mechanistic interactions between lymphoma metabolism, neurotransmitter imbalance, and neurocognition may promote interventions that preserve cognitive function.

Modeling hyperpolarized lactate signal dynamics in cells, patient-derived tissue slice cultures and murine models.

Determining the aggressiveness of renal cell carcinoma (RCC) noninvasively is a critical part of the diagnostic workup for treating this disease that kills more than 15,000 people annually in the USA. Recently, we have shown that not only the amount of lactate produced, as a consequence of the Warburg effect, but also its efflux out of the cell, is a critical marker of RCC aggressiveness and differentiating RCCs from benign renal tumors. Enzymatic conversions can now be measured in situ with hyperpolarized (HP) 13 C magnetic resonance (MR) on a sub-minute time scale. Using RCC models, we have shown that this technology can interrogate in real time both lactate production and compartmentalization, which are associated with tumor aggressiveness. The dynamic HP MR data have enabled us to robustly characterize parameters that have been elusive to measure directly in intact living cells and murine tumors thus far. Specifically, we were able to measure the same intracellular lactate longitudinal relaxation time in three RCC cell lines of 16.42 s, and lactate efflux rate ranging from 0.14 to 0.8 s-1 in the least to the most aggressive RCC cell lines and correlate it to monocarboxylate transporter isoform 4 expression. We also analyzed dynamic HP lactate and pyruvate data from orthotopic murine RCC tumors using a simplified one-compartment model, and showed comparable apparent pyruvate to lactate conversion rate (kPL ) values with those measured in vitro. This kinetic modeling was then extended to characterize the lactate dynamics in patient-derived living RCC tissue slices; and even without direct measurement of the extracellular lactate signal the efflux parameter was still assessed and was distinct between the benign renal tumors and RCCs. Across all these preclinical models, the rate parameters of kPL and lactate efflux correlated to cancer aggressiveness, demonstrating the validity of our modeling approach for noninvasive assessment of RCC aggressiveness.

Hyperpolarized 13 C MRI data acquisition and analysis in prostate and brain at University of California, San Francisco.

Based on the expanding set of applications for hyperpolarized carbon-13 (HP-13 C) MRI, this work aims to communicate standardized methodology implemented at the University of California, San Francisco, as a primer for conducting reproducible metabolic imaging studies of the prostate and brain. Current state-of-the-art HP-13 C acquisition, data processing/reconstruction and kinetic modeling approaches utilized in patient studies are presented together with the rationale underpinning their usage. Organized around spectroscopic and imaging-based methods, this guide provides an extensible framework for handling a variety of HP-13 C applications, which derives from two examples with dynamic acquisitions: 3D echo-planar spectroscopic imaging of the human prostate and frequency-specific 2D multislice echo-planar imaging of the human brain. Details of sequence-specific parameters and processing techniques contained in these examples should enable investigators to effectively tailor studies around individual-use cases. Given the importance of clinical integration in improving the utility of HP exams, practical aspects of standardizing data formats for reconstruction, analysis and visualization are also addressed alongside open-source software packages that enhance institutional interoperability and validation of methodology. To facilitate the adoption and further development of this methodology, example datasets and analysis pipelines have been made available in the supporting information.