Metabolic Profiling Comparison of Human Pancreatic Ductal Epithelial Cells and Three Pancreatic Cancer Cell Lines using NMR Based Metabonomics

Fatty acids abrogate the growth-suppressive effects induced by inhibition of cholesterol flux in pancreatic cancer cells

BACKGROUND

Despite therapeutic advances, the prognosis of pancreatic ductal adenocarcinoma (PDAC) remains extremely poor. Metabolic reprogramming is increasingly recognized as a key contributor to tumor progression and therapy resistance in PDAC. One of the main metabolic changes essential for tumor growth is altered cholesterol flux. Targeting cholesterol flux appears an attractive therapeutic approach, however, the complex regulation of cholesterol balance in PDAC cells remains poorly understood.

METHODS

The lipid content in human pancreatic duct epithelial (HPDE) cells and human PDAC cell lines (BxPC-3, MIA PaCa-2, and PANC-1) was determined. Cells exposed to eight different inhibitors targeting different regulators of lipid flux, in the presence or absence of oleic acid (OA) stimulation were assessed for changes in viability, proliferation, migration, and invasion. Intracellular content and distribution of cholesterol was assessed. Lastly, proteome profiling of PANC-1 exposed to the sterol O-acyltransferase 1 (SOAT1) inhibitor avasimibe, in presence or absence of OA, was performed.

RESULTS

PDAC cells contain more free cholesterol but less cholesteryl esters and lipid droplets than HPDE cells. Exposure to different lipid flux inhibitors increased cell death and suppressed proliferation, with different efficiency in the tested PDAC cell lines. Avasimibe had the strongest ability to suppress proliferation across the three PDAC cell lines. All inhibitors showing cell suppressive effect disturbed intracellular cholesterol flux and increased cholesterol aggregation. OA improved overall cholesterol balance, reduced free cholesterol aggregation, and reversed cell death induced by the inhibitors. Treatment with avasimibe changed the cellular proteome substantially, mainly for proteins related to biosynthesis and metabolism of lipids and fatty acids, apoptosis, and cell adhesion. Most of these changes were restored by OA.

CONCLUSIONS

The study reveals that disturbing the cholesterol flux by inhibiting the actions of its key regulators can yield growth suppressive effects on PDAC cells. The presence of fatty acids restores intracellular cholesterol balance and abrogates the alternations induced by cholesterol flux inhibitors. Taken together, targeting cholesterol flux might be an attractive strategy to develop new therapeutics against PDAC. However, the impact of fatty acids in the tumor microenvironment must be taken into consideration.

Statistical considerations and database limitations in NMR-based metabolic profiling studies

INTRODUCTION

Interpretation and analysis of NMR-based metabolic profiling studies is limited by substantially incomplete commercial and academic databases. Statistical significance tests, including p-values, VIP scores, AUC values and FC values, can be largely inconsistent. Data normalization prior to statistical analysis can cause erroneous outcomes.

OBJECTIVES

The objectives were (1) to quantitatively assess consistency among p-values, VIP scores, AUC values and FC values in representative NMR-based metabolic profiling datasets, (2) to assess how data normalization can impact statistical significance outcomes, (3) to determine resonance peak assignment completion potential using commonly used databases and (4) to analyze intersection and uniqueness of metabolite space in these databases.

METHODS

P-values, VIP scores, AUC values and FC values, and their dependence on data normalization, were determined in orthotopic mouse model of pancreatic cancer and two human pancreatic cancer cell lines. Completeness of resonance assignments were evaluated using Chenomx, the human metabolite database (HMDB) and the COLMAR database. The intersection and uniqueness of the databases was quantified.

RESULTS

P-values and AUC values were strongly correlated compared to VIP or FC values. Distributions of statistically significant bins depended strongly on whether or not datasets were normalized. 40-45% of peaks had either no or ambiguous database matches. 9-22% of metabolites were unique to each database.

CONCLUSIONS

Lack of consistency in statistical analyses of metabolomics data can lead to misleading or inconsistent interpretation. Data normalization can have large effects on statistical analysis and should be justified. About 40% of peak assignments remain ambiguous or impossible with current databases. 1D and 2D databases should be made consistent to maximize metabolite assignment confidence and validation.

Anticancer Activity of Sunitinib Analogues in Human Pancreatic Cancer Cell Cultures under Normoxia and Hypoxia

Pancreatic cancer remains one of the deadliest cancer types. It is usually characterized by high resistance to chemotherapy. However, cancer-targeted drugs, such as sunitinib, recently have shown beneficial effects in pancreatic in vitro and in vivo models. Therefore, we chose to study a series of sunitinib derivatives developed by us, that were proven to be promising compounds for cancer treatment. The aim of our research was to evaluate the anticancer activity of sunitinib derivatives in human pancreatic cancer cell lines MIA PaCa-2 and PANC-1 under normoxia and hypoxia. The effect on cell viability was determined by the MTT assay. The compound effect on cell colony formation and growth was established by clonogenic assay and the activity on cell migration was estimated using a ‘wound healing’ assay. Six out of 17 tested compounds at 1 µM after 72 h of incubation reduced cell viability by 90% and were more active than sunitinib. Compounds for more detailed experiments were chosen based on their activity and selectivity towards cancer cells compared to fibroblasts. The most promising compound EMAC4001 was 24 and 35 times more active than sunitinib against MIA PaCa-2 cells, and 36 to 47 times more active against the PANC-1 cell line in normoxia and hypoxia. It also inhibited MIA PaCa-2 and PANC-1 cell colony formation. Four tested compounds inhibited MIA PaCa-2 and PANC-1 cell migration under hypoxia, but none was more active than sunitinib. In conclusion, sunitinib derivatives possess anticancer activity in human pancreatic adenocarcinoma MIA PaCa-2 and PANC-1 cell lines, and they are promising for further research.

Enhanced effect of X-rays in the presence of a static magnetic field within a 3D pancreatic cancer model

OBJECTIVE

To evaluate the impact of static magnetic field (SMF) presence on the radiation response of pancreatic cancer cells in polyurethane-based highly macro-porous scaffolds in hypoxic (1% O2) and normoxic (21% O2) conditions, towards understanding MR-guided radiotherapy, shedding light on the potential interaction phenomenon between SMF and radiation in a three-dimensional (3D) microenvironment.

METHODS

Pancreatic cancer cells (PANC-1, ASPC-1) were seeded into fibronectin-coated highly porous polyethene scaffolds for biomimicry and cultured for 4 weeks in in vitro normoxia (21% O2) followed by a 2-day exposure to either in vitro hypoxia (1% O2) or maintenance in in vitro normoxia (21% O2). The samples were then irradiated with 6 MV photons in the presence or absence of a 1.5 T field. Thereafter, in situ post-radiation monitoring (1 and 7 days post-irradiation treatment) took place via quantification of (i) live dead and (ii) apoptotic profiles.

RESULTS

We report: (i) pancreatic ductal adenocarcinoma hypoxia-associated radioprotection, in line with our previous findings, (ii) an enhanced effect of radiation in the presence of SMFin in vitro hypoxia (1% O2) for both short- (1 day) and long-term (7 days) post -radiation analysis and (iii) an enhanced effect of radiation in the presence of SMF in in vitro normoxia (21% O2) for long-term (7 days) post-radiation analysis within a 3D pancreatic cancer model.

CONCLUSION

With limited understanding of the potential interaction phenomenon between SMF and radiation, this 3D system allows combination evaluation for a cancer in which the role of radiotherapy is still evolving.

ADVANCES IN KNOWLEDGE

This study examined the use of a 3D model to investigate MR-guided radiotherapy in a hypoxic microenvironment, indicating that this could be a useful platform to further understanding of SMF influence on radiation.

Multimodal evaluation of 19F-BPA internalization in pancreatic cancer cells for boron capture and proton therapy potential applications

PURPOSE

One of the obstacles to the application of Boron Neutron Capture Therapy (BNCT) and Proton Boron Fusion Therapy (PBFT) concerns the measurement of borated carriers' biodistribution. The objective of the present study was to evaluate the in vitro internalization of the ¹⁹F-labelled p-boronophenylalanine (¹⁹F-BPA) in the human cancer pancreatic cell line (PANC-1) for the potential application of BNCT and PBFT in pancreatic cancer. The ¹⁹F-BPA carrier has the advantage that its bio-distribution may be monitored in vivo using ¹⁹F-Nuclear Magnetic Resonance (¹⁹F NMR).

MATERIALS AND METHODS

The ¹⁹F-BPA internalization in PANC-1 cells was evaluated using three independent techniques on cellular samples left in contact with growing medium enriched with 13.6 mM ¹⁹F-BPA corresponding to a ¹¹B concentration of 120 ppm: neutron autoradiography, which quantifies boron; liquid chromatography hyphenated to tandem mass spectrometry and UV-Diode Array Detection (UV-DAD), which quantifies ¹⁹F-BPA molecule; and ¹⁹F NMR spectroscopy, which detects fluorine nuclei.

RESULTS

Our studies suggested that ¹⁹F-BPA is internalized by PANC-1 cells. The three methods provided consistent results of about 50% internalization fraction at 120 ppm of ¹¹B. Small variations (less than 15%) in internalization fraction are mainly dependent on the proliferation state of the cells.

CONCLUSIONS

The ability of ¹⁹F NMR spectroscopy to study ¹⁹F-BPA internalization was validated by well-established independent techniques. The multimodal approach we used suggests ¹⁹F-BPA as a promising BNCT/PBFT carrier for the treatment of pancreatic cancer. Since the quantification is performed at doses useful for BNCT/PBFT, ¹⁹F NMR can be envisaged to monitor ¹⁹F-BPA bio-distribution during the therapy.

1H-Nuclear Magnetic Resonance Analysis of Urine as Diagnostic Tool for Organic Acidemias and Aminoacidopathies

The utility of low-resolution 1H-NMR analysis for the identification of biomarkers provided evidence for rapid biochemical diagnoses of organic acidemia and aminoacidopathy. 1H-NMR, with a sensitivity expected for a field strength of 400 MHz at 64 scans was used to establish the metabolomic urine sample profiles of an infant population diagnosed with small molecule Inborn Errors of Metabolism (smIEM) compared to unaffected individuals. A qualitative differentiation of the 1H-NMR spectral profiles of urine samples obtained from individuals affected by different organic acidemias and aminoacidopathies was achieved in combination with GC-MS. The smIEM disorders investigated in this study included phenylalanine metabolism; isovaleric, propionic, 3-methylglutaconicm and glutaric type I acidemia; and deficiencies in medium chain acyl-coenzyme and holocarboxylase synthase. The observed metabolites were comparable and similar to those reported in the literature, as well as to those detected with higher-resolution NMR. In this study, diagnostic marker metabolites were identified for the smIEM disorders. In some cases, changes in metabolite profiles differentiated post-treatments and follow-ups while allowing for the establishment of different clinical states of a biochemical disorder. In addition, for the first time, a 1H-NMR-based biomarker profile was established for holocarboxylase synthase deficiency spectrum.

3D Collagen-Nanocellulose Matrices Model the Tumour Microenvironment of Pancreatic Cancer

Three-dimensional (3D) cancer models are invaluable tools designed to study tumour biology and new treatments. Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest types of cancer, has been progressively explored with bioengineered 3D approaches by deconstructing elements of its tumour microenvironment. Here, we investigated the suitability of collagen-nanocellulose hydrogels to mimic the extracellular matrix of PDAC and to promote the formation of tumour spheroids and multicellular 3D cultures with stromal cells. Blending of type I collagen fibrils and cellulose nanofibres formed a matrix of controllable stiffness, which resembled the lower profile of pancreatic tumour tissues. Collagen-nanocellulose hydrogels supported the growth of tumour spheroids and multicellular 3D cultures, with increased metabolic activity and matrix stiffness. To validate our 3D cancer model, we tested the individual and combined effects of the anti-cancer compound triptolide and the chemotherapeutics gemcitabine and paclitaxel, resulting in differential cell responses. Our blended 3D matrices with tuneable mechanical properties consistently maintain the growth of PDAC cells and its cellular microenvironment and allow the screening of anti-cancer treatments.

Bioinformatics and Functional Analyses Implicate Potential Roles for EOGT and L-fringe in Pancreatic Cancers

Notch signaling receptors, ligands, and their downstream target genes are dysregulated in pancreatic ductal adenocarcinoma (PDAC), suggesting a role of Notch signaling in pancreatic tumor development and progression. However, dysregulation of Notch signaling by post-translational modification of Notch receptors remains poorly understood. Here, we analyzed the Notch-modifying glycosyltransferase involved in the regulation of the ligand-dependent Notch signaling pathway. Bioinformatic analysis revealed that the expression of epidermal growth factor (EGF) domain-specific O-linked N-acetylglucosamine (EOGT) and Lunatic fringe (LFNG) positively correlates with a subset of Notch signaling genes in PDAC. The lack of EOGT or LFNG expression inhibited the proliferation and migration of Panc-1 cells, as observed by the inhibition of Notch activation. EOGT expression is significantly increased in the basal subtype, and low expression of both EOGT and LFNG predicts better overall survival in PDAC patients. These results imply potential roles for EOGT- and LFNG-dependent Notch signaling in PDAC.

LDL, HDL and endocrine-related cancer: From pathogenic mechanisms to therapies

Cholesterol is essential for a variety of functions in endocrine-related cells, including hormone and steroid production. We have reviewed the progress to date in research on the role of the main cholesterol-containing lipoproteins; low-density lipoprotein (LDL) and high-density lipoprotein (HDL), and their impact on intracellular cholesterol homeostasis and carcinogenic pathways in endocrine-related cancers. Neither LDL-cholesterol (LDL-C) nor HDL-cholesterol (HDL-C) was consistently associated with endocrine-related cancer risk. However, preclinical studies showed that LDL receptor plays a critical role in endocrine-related tumor cells, mainly by enhancing circulating LDL-C uptake and modulating tumorigenic signaling pathways. Although scavenger receptor type BI-mediated uptake of HDL could enhance cell proliferation in breast, prostate, and ovarian cancer, these effects may be counteracted by the antioxidant and anti-inflammatory properties of HDL. Moreover, 27-hydroxycholesterol a metabolite of cholesterol promotes tumorigenic processes in breast and epithelial thyroid cancer. Furthermore, statins have been reported to reduce the incidence of breast, prostate, pancreatic, and ovarian cancer in large clinical trials, in part because of their ability to lower cholesterol synthesis. Overall, cholesterol homeostasis deregulation in endocrine-related cancers offers new therapeutic opportunities, but more mechanistic studies are needed to translate the preclinical findings into clinical therapies.

Circadian Dysregulation of the TGFβ/SMAD4 Pathway Modulates Metastatic Properties and Cell Fate Decisions in Pancreatic Cancer Cells

Impairment of circadian rhythms impacts carcinogenesis. SMAD4, a clock-controlled gene and central component of the TGFβ canonical pathway, is frequently mutated in pancreatic ductal adenocarcinoma (PDA), leading to decreased survival. Here, we used an in vitro PDA model of SMAD4-positive and SMAD4-negative cells to investigate the interplay between circadian rhythms, the TGFβ canonical signaling pathway, and its impact on tumor malignancy. Our data show that TGFβ1, SMAD3, SMAD4, and SMAD7 oscillate in a circadian fashion in SMAD4-positive PDA cells, whereas altering the clock impairs the mRNA dynamics of these genes. Furthermore, the expression of the clock genes DEC1, DEC2, and CRY1 varied depending on SMAD4 status. TGFβ pathway activation resulted in an altered clock, cell-cycle arrest, accelerated apoptosis rate, enhanced invasiveness, and chemosensitivity. Our data suggest that the impact of TGFβ on the clock is SMAD4-dependent, and S MAD3, SMAD4, DEC1, and CRY1 involved in this cross-talk affect PDA patient survival.

Tuned near infrared fluorescent hyaluronic acid conjugates for delivery to pancreatic cancer for intraoperative imaging

The prognosis of pancreatic cancer remains poor. Intraoperative fluorescence imaging of tumors could improve staging and surgical resection, thereby improving prognosis. However, imaging pancreatic cancer with macromolecular delivery systems, is often hampered by nonspecific organ accumulation.

Methods: We describe the rational development of hyaluronic acid (HA) conjugates that vary in molecular weight and are conjugated to near infrared fluorescent (NIRF) dyes that have differences in hydrophilicity, serum protein binding affinity, and clearance mechanism. We systematically investigated the roles of each of these properties on tumor accumulation, relative biodistribution, and the impact of intraoperative imaging of orthotopic, syngeneic pancreatic cancer.

Results: Each HA-NIRF conjugate displayed intrapancreatic tumor enhancement. Regardless of HA molecular weight, Cy7.5 conjugation directed biodistribution to the liver, spleen, and bowels. Conjugation of IRDye800 to 5 and 20 kDa HA resulted in low liver and spleen signal while enhancing the tumor up to 14-fold compared to healthy pancreas, while 100 kDa HA conjugated to IRDye800 resulting in liver and spleen accumulation.

Conclusion: These studies demonstrate that by tuning HA molecular weight and the physicochemical properties of the conjugated moiety, in this case a NIRF probe, peritoneal biodistribution can be substantially altered to achieve optimized delivery to tumors intraoperative abdominal imaging.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Influence of Drying Method on NMR-Based Metabolic Profiling of Human Cell Lines

Metabolic profiling of cell line and tissue extracts involves sample processing that includes a drying step prior to re-dissolving the cell or tissue extracts in a buffer for analysis by GC/LC-MS or NMR. Two of the most commonly used drying techniques are centrifugal evaporation under vacuum (SpeedVac) and lyophilization. Here, NMR spectroscopy was used to determine how the metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, MiaPaCa-2, Panc-1 and AsPC-1, were influenced by the choice of drying technique. In each of the three cell lines, 40-50 metabolites were identified as having statistically significant differences in abundance in redissolved extract samples depending on the drying technique used during sample preparation. In addition to these differences, some metabolites were only present in the lyophilized samples, for example, n-methyl-α-aminoisobutyric acid, n-methylnicotimamide, sarcosine and 3-hydroxyisovaleric acid, whereas some metabolites were only present in SpeedVac dried samples, for example, trimethylamine. This research demonstrates that the choice of drying technique used during the preparation of samples of human cell lines or tissue extracts can significantly influence the observed metabolome, making it important to carefully consider the selection of a drying method prior to preparation of such samples for metabolic profiling.

Gold Nanoparticles sensitize pancreatic cancer cells to gemcitabine

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid cancers with dismal prognosis. Several mechanisms that are mainly responsible for aggressiveness and therapy resistance of PDAC cells include epithelial to mesenchymal transition (EMT), stemness and Mitogen Activated Protein Kinase (MAPK) signaling. Strategies that inhibit these mechanisms are critically important to improve therapeutic outcome in PDAC. In the current study, we wanted to investigate whether gold nanoparticles (AuNPs) could sensitize pancreatic cancer cells to the chemotherapeutic agent gemcitabine. We demonstrated that treatment with AuNPs of 20 nm diameter inhibited migration and colony forming ability of pancreatic cancer cells. Pre-treatment with AuNPs sensitized pancreatic cancer cells to gemcitabine in both viability and colony forming assays. Mechanistically, pre-treatment of pancreatic cancer cells with AuNPs decreased gemcitabine induced EMT, stemness and MAPK activation. Taken together, these findings suggest that AuNPs could be considered as a potential agent to sensitize pancreatic cancer cells to gemcitabine.

RANCM: a new ranking scheme for assigning confidence levels to metabolite assignments in NMR-based metabolomics studies

INTRODUCTION

The Metabolomics Standards Initiative has recommended four categories for metabolite assignments in NMR-based metabolic profiling studies. The "putatively annotated compound" category is most commonly reported by metabolomics investigators. However, there is significant ambiguity in reliability of "putatively annotated compound" assignments, which can range from low confidence made on minimal corroborating data to high confidence made on substantial corroborating data.

OBJECTIVES

To introduce a new ranking system, Rank and AssigN Confidence to Metabolites (RANCM), to assign confidence levels to "putatively annotated compound" assignments in NMR-based metabolic profiling studies.

METHODS

The ranking system was constructed with three confidence levels ranging from Rank 1 for the lowest confidence assignment level to Rank 3 for the highest confidence assignment level. A decision tree was constructed to guide rank selection for each metabolite assignment.

RESULTS

Examples are provided from experimental data demonstrating how to use the decision tree to make confidence level assignments to "putatively annotated compounds" in each of the three rank levels. A standard Excel sheet template is provided to facilitate decision-making, documentation and submission to data repositories.

CONCLUSION

RANCM is intended to reduce the ambiguity in "putatively annotated compound" assignments, to facilitate effective communication of the degree of confidence in "putatively annotated compound" assignments, and to make it easier for non-experts to evaluate the significance and reliability of NMR-based metabonomics studies. The system is straightforward to implement, based on the most common datasets collected in NMR-based metabolic profiling studies, and can be used with equal rigor and significance with any set of NMR datasets.

Metabolomics and Biomarker Discovery

Recently, metabolomics-the study of metabolite profiles within biological samples-has found a wide range of applications. This chapter describes the different techniques available for metabolomic analysis, the various samples that can be utilised for analysis and applications of both global and targeted metabolomic analysis to biomarker discovery in medicine.

Bitter melon juice exerts its efficacy against pancreatic cancer via targeting both bulk and cancer stem cells

Pancreatic cancer (PanC) is one of the deadliest malignancies worldwide and frontline treatment with gemcitabine becomes eventually ineffective due to increasing PanC resistance, suggesting additional approaches are needed to manage PanC. Recently, we have shown the efficacy of bitter melon juice (BMJ) against PanC cells, including those resistant to gemcitabine. As cancer stem cells (CSCs) are actively involved in PanC initiation, progression, relapse and drug-resistance, here we assessed BMJ ability in targeting pancreatic cancer-associated cancer stem cells (PanC-CSCs). We found BMJ efficacy against CD44+ /CD24+ /EpCAMhigh enriched PanC-CSCs in spheroid assays; BMJ also increased the sensitivity of gemcitabine-resistant PanC-CSCs. Exogenous addition of BMJ to PanC-CSC generated spheroids (not pre-exposed to BMJ) also significantly reduced spheroid number and size. Mechanistically, BMJ effects were associated with a decrease in the expression of genes and proteins involved in PanC-CSC renewal and proliferation. Specifically, immunofluorescence staining showed that BMJ decreases protein expression/nuclear localization of CSC-associated transcription factors SOX2, OCT4 and NANOG, and CSC marker CD44. Immunohistochemical analysis of MiaPaCa2 xenografts from BMJ treated animals also showed a significant decrease in the levels of CSC-associated transcription factors. Together, these results show BMJ potential in targeting PanC-CSC pool and associated regulatory pathways, suggesting the need for further investigation of its efficacy against PanC growth and progression including gemcitabine-resistant PanC.

NMR-based metabolic profiling of urine, serum, fecal, and pancreatic tissue samples from the Ptf1a-Cre; LSL-KrasG12D transgenic mouse model of pancreatic cancer

Pancreatic cancer is the third leading cause of cancer deaths in the United States with more than 53,000 expected to be diagnosed with the disease in 2018. The median survival time after diagnosis is four to six months. The poor survival statistics are due in part to the fact that pancreatic cancer is typically asymptomatic until it reaches advanced stages of the disease. Although surgical resection provides the best chance of survival, pancreatic cancer is rarely detected when surgery is still possible due, in part, to lack of effective biomarkers for early detection. The goal of the research reported here was to determine if it was possible to identify metabolic biomarkers for detection of pre-cancerous pancreatic intraepithelial neoplasia (PanIN) that precede pancreatic adenocarcinoma. The transgenic Ptf1a-Cre; LSL-KrasG12D mouse strain was used as a model of pancreatic cancer progression. Nuclear magnetic resonance (NMR) spectroscopy was employed to compare metabolic profiles of urine, sera, fecal extracts, and pancreatic tissue extracts collected from control and study mice aged 5, 11, and 15 months, including 47 mice with tumors. We were able to identify the following potential biomarkers: decreased 3-indoxylsulfate, benzoate and citrate in urine, decreased glucose, choline, and lactate in blood, and decreased phenylalanine and benzoate and increased acetoin in fecal extracts. Potential biomarkers were validated by p-values, PLS-DA VIP scores, and accuracies based on area under ROC curve analyses. Essentially, all of the metabolic profiling changes could be explained as being associated with the consequences of bicarbonate wasting caused by a complete substitution of the normal pancreatic acinar tissue by tissue entirely composed of PanIN. Given the nature of the mouse model used here, our results indicate that it may be possible to use NMR-based metabolic profiling to identify biomarkers for detection of precancerous PanIN that immediately precede pancreatic cancer.

Influence of media selection on NMR based metabolic profiling of human cell lines

INTRODUCTION

Comparative metabolic profiling of different human cancer cell lines can reveal metabolic pathways up-regulated or down-regulated in each cell line, potentially providing insight into distinct metabolism taking place in different types of cancer cells. It is noteworthy, however, that human cell lines available from public repositories are deposited with recommended media for optimal growth, and if cell lines to be compared are cultured on different growth media, this introduces a potentially serious confounding variable in metabolic profiling studies designed to identify intrinsic metabolic pathways active in each cell line.

OBJECTIVES

The goal of this study was to determine if the culture media used to grow human cell lines had a significant impact on the measured metabolic profiles.

METHODS

NMR-based metabolic profiles of hydrophilic extracts of three human pancreatic cancer cell lines, AsPC-1, MiaPaCa-2 and Panc-1, were compared after culture on Dulbecco's Modified Eagle Medium (DMEM) or Roswell Park Memorial Institute (RPMI-1640) medium.

RESULTS

Comparisons of the same cell lines cultured on different media revealed that the concentrations of many metabolites depended strongly on the choice of culture media. Analyses of different cell lines grown on the same media revealed insight into their metabolic differences.

CONCLUSION

The choice of culture media can significantly impact metabolic profiles of human cell lines and should be considered an important variable when designing metabolic profiling studies. Also, the metabolic differences of cells cultured on media recommended for optimal growth in comparison to a second growth medium can reveal critical insight into metabolic pathways active in each cell line.

The separate effects of lipids and proteins on brain MRI contrast revealed through tissue clearing

Despite the widespread use of magnetic resonance imaging (MRI) of the brain, the relative contribution of different biological components (e.g. lipids and proteins) to structural MRI contrasts (e.g., T1, T2, T2*, proton density, diffusion) remains incompletely understood. This limitation can undermine the interpretation of clinical MRI and hinder the development of new contrast mechanisms. Here, we determine the respective contribution of lipids and proteins to MRI contrast by removing lipids and preserving proteins in mouse brains using CLARITY. We monitor the temporal dynamics of tissue clearance via NMR spectroscopy, protein assays and optical emission spectroscopy. MRI of cleared brain tissue showed: 1) minimal contrast on standard MRI sequences; 2) increased relaxation times; and 3) diffusion rates close to free water. We conclude that lipids, present in myelin and membranes, are a dominant source of MRI contrast in brain tissue.

Designing a bio-inspired biomimetic in vitro system for the optimization of ex vivo studies of pancreatic cancer

Pancreatic cancer is one of the most aggressive and lethal human malignancies. Drug therapies and radiotherapy are used for treatment as adjuvants to surgery, but outcomes remain disappointing. Advances in tissue engineering suggest that 3D cultures can reflect the in vivo tumor microenvironment and can guarantee a physiological distribution of oxygen, nutrients, and drugs, making them promising low-cost tools for therapy development. Here, we review crucial structural and environmental elements that should be considered for an accurate design of an ex vivo platform for studies of pancreatic cancer. Furthermore, we propose environmental stress response biomarkers as platform readouts for the efficient control and further prediction of the pancreatic cancer response to the environmental and treatment input.

Metabolomics in cell culture--a strategy to study crucial metabolic pathways in cancer development and the response to treatment

Metabolomics is a comprehensive tool for monitoring processes within biological systems. Thus, metabolomics may be widely applied to the determination of diagnostic biomarkers for certain diseases or treatment outcomes. There is significant potential for metabolomics to be implemented in cancer research because cancer may modify metabolic pathways in the whole organism. However, not all biological questions can be answered solely by the examination of small molecule composition in biofluids; in particular, the study of cellular processes or preclinical drug testing requires ex vivo models. The major objective of this review was to summarise the current achievement in the field of metabolomics in cancer cell culture-focusing on the metabolic pathways regulated in different cancer cell lines-and progress that has been made in the area of drug screening and development by the implementation of metabolomics in cell lines.