Summary of study ST001119

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000750. The data can be accessed directly via it's Project DOI: 10.21228/M8QX2G This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

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Study IDST001119
Study TitleQuantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability
Study SummaryCancer cell metabolism is heavily influenced by microenvironmental factors, including nutrient availability. Therefore, knowledge of microenvironmental nutrient levels is essential to understand tumor metabolism. To measure the extracellular nutrient levels available to tumors, we developed a quantitative metabolomics method to measure the absolute concentrations of >118 metabolites in plasma and tumor interstitial fluid, the extracellular fluid that perfuses tumors. Comparison of nutrient levels in tumor interstitial fluid and plasma revealed that the nutrients available to tumors differ from those present in circulation. Further, by comparing interstitial fluid nutrient levels between autochthonous and transplant models of murine pancreatic and lung adenocarcinoma, we found that tumor type, anatomical location and animal diet affect local nutrient availability. These data provide a comprehensive characterization of the nutrients present in the tumor microenvironment of widely used models of lung and pancreatic cancer and identify factors that influence metabolite levels in tumors.
Institute
University of Chicago
Last NameMuir
First NameAlexander
Address929 E 57th St. W GCIS 306, Chicago, Illinois, 60637, USA
Emailmuir.alexander@gmail.com
Phone5104950975
Submit Date2019-01-03
Raw Data AvailableYes
Raw Data File Type(s).raw
Analysis Type DetailLC-MS
Release Date2019-03-06
Release Version1
Alexander Muir Alexander Muir
https://dx.doi.org/10.21228/M8QX2G
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR000750
Project DOI:doi: 10.21228/M8QX2G
Project Title:Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability
Project Summary:Cancer cell metabolism is heavily influenced by microenvironmental factors, including nutrient availability. Therefore, knowledge of microenvironmental nutrient levels is essential to understand tumor metabolism. To measure the extracellular nutrient levels available to tumors, we developed a quantitative metabolomics method to measure the absolute concentrations of >118 metabolites in plasma and tumor interstitial fluid, the extracellular fluid that perfuses tumors. Comparison of nutrient levels in tumor interstitial fluid and plasma revealed that the nutrients available to tumors differ from those present in circulation. Further, by comparing interstitial fluid nutrient levels between autochthonous and transplant models of murine pancreatic and lung adenocarcinoma, we found that tumor type, anatomical location and animal diet affect local nutrient availability. These data provide a comprehensive characterization of the nutrients present in the tumor microenvironment of widely used models of lung and pancreatic cancer and identify factors that influence metabolite levels in tumors.
Institute:University of Chicago
Last Name:Muir
First Name:Alexander
Address:929 E 57th St. GCIS W 306, Chicago, Illinois, 60637, USA
Email:muir.alexander@gmail.com
Phone:5104950975

Subject:

Subject ID:SU001176
Subject Type:Mammal
Subject Species:Mus musculus
Taxonomy ID:10090

Factors:

Subject type: Mammal; Subject species: Mus musculus (Factor headings shown in green)

mb_sample_id local_sample_id Sample Type
SA0776801234 KPK 3 TIFKeap1_mutant_lung_subcutaneous
SA0776811234 KPK 4 TIFKeap1_mutant_lung_subcutaneous
SA0776821234 KPK 5 TIFKeap1_mutant_lung_subcutaneous
SA0776831234 KPK 1 TIFKeap1_mutant_lung_subcutaneous
SA0776841233 KPK 1 TIFKeap1_mutant_lung_subcutaneous
SA0776851233 KPK 6 TIFKeap1_mutant_lung_subcutaneous
SA0776861233 KPK 5 TIFKeap1_mutant_lung_subcutaneous
SA0776871234 KPK 6 TIFKeap1_mutant_lung_subcutaneous
SA0776881233 KP 5 TIFlung_subcutaneous
SA0776891233 KP 6 TIFlung_subcutaneous
SA0776901234 KP 1 TIFlung_subcutaneous
SA0776911233 KP 4 TIFlung_subcutaneous
SA0776921234 KP 2 TIFlung_subcutaneous
SA0776931233 KP 3 TIFlung_subcutaneous
SA0776941234 KP 4 TIFlung_subcutaneous
SA0776951234 KP 3 TIFlung_subcutaneous
SA0776961234 KP 5 TIFlung_subcutaneous
SA0776971234 KP 6 TIFlung_subcutaneous
SA0776985197 TIF repeatpancreatic ductal adenocarcinoma
SA07769958 TIFpancreatic ductal adenocarcinoma
SA077700172 TIF repeatpancreatic ductal adenocarcinoma
SA077701AL1 TIF repeatpancreatic ductal adenocarcinoma
SA077702268 TIF repeatpancreatic ductal adenocarcinoma
SA0777031339 TIF repeatpancreatic ductal adenocarcinoma
SA077704142 TIF repeatpancreatic ductal adenocarcinoma
SA077705922 TIFpancreatic ductal adenocarcinoma
SA077706142 TIFpancreatic ductal adenocarcinoma
SA077707268 TIFpancreatic ductal adenocarcinoma
SA077708AL1 TIFpancreatic ductal adenocarcinoma
SA0777095197 TIFpancreatic ductal adenocarcinoma
SA077710172 TIFpancreatic ductal adenocarcinoma
SA0777111339 TIFpancreatic ductal adenocarcinoma
SA077712TBt0 plasma 711pancreatic ductal adenocarcinoma plasma
SA077713TBt0 plasma 712pancreatic ductal adenocarcinoma plasma
SA077714TBt0 plasma 705pancreatic ductal adenocarcinoma plasma
SA077715TBt0 plasma 710pancreatic ductal adenocarcinoma plasma
SA077716TBt0 plasma 707pancreatic ductal adenocarcinoma plasma
SA077717TBt0 plasma 708pancreatic ductal adenocarcinoma plasma
SA0777184198_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA0777194300_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077720X3_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077721X4_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA0777223731_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077723B0_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077724X2_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077725B2_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077726B1_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077727A1_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077728A0_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA07772958_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA0777305197_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077731AL1_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077732172_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077733922_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077734142_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077735268_Plasmapancreatic ductal adenocarcinoma plasma cardiac puncture
SA077736X2 TIFpancreatic ductal adenocarcinoma subcutaneous
SA077737X1 TIFpancreatic ductal adenocarcinoma subcutaneous
SA077738X4 TIFpancreatic ductal adenocarcinoma subcutaneous
SA077739X5 TIFpancreatic ductal adenocarcinoma subcutaneous
SA077740X3 TIFpancreatic ductal adenocarcinoma subcutaneous
Showing results 1 to 61 of 61

Collection:

Collection ID:CO001170
Collection Summary:Isolation of tumor interstitial fluid (TIF) TIF was isolated from tumors using a previously described centrifugal method (Eil et al., 2016; Haslene-Hox et al., 2011; Ho et al., 2015; Wiig et al., 2003). Briefly, tumor bearing animals were euthanized by cervical dislocation and tumors were rapidly dissected from the animals. Dissections took <1 min. to complete. Blood was collected from the same animal via cardiac puncture, and was immediately placed in EDTA-tubes (Sarstedt, North Rhine-Westphalia, Germany) and centrifuged at 845 x g for 10 minutes at 4°C to separate plasma. Plasma was frozen in liquid nitrogen and stored at -80°C until further analysis. Tumors were then weighed and briefly rinsed in room temperature saline (150mM NaCl) and blotted on filter paper (VWR, Radnor, PA, 28298-020). The entire process of preparing the tumor prior to isolation of TIF took ~2 min. The tumors were then put onto 20µm nylon filters (Spectrum Labs, Waltham, MA, 148134) affixed atop 50mL conical tubes, and centrifuged for 10 min. at 4°C at 106 x g. TIF was then collected from the conical tube, frozen in liquid nitrogen and stored at -80°C until further analysis.
Sample Type:Interstitial Fluid

Treatment:

Treatment ID:TR001191
Treatment Summary:N/A

Sample Preparation:

Sampleprep ID:SP001184
Sampleprep Summary:Quantification of metabolite levels in TIF and plasma In order to quantitate metabolites in TIF and plasma samples, we first constructed a library of 149 chemical standards of plasma polar metabolites (see Supplementary File 1 for suppliers for each chemical standard). These compounds were selected to encompass a number of metabolic processes and have previously been included in efforts to profile plasma polar metabolites by LC/MS (Cantor et al., 2017; Evans et al., 2009; Lawton et al., 2008; Mazzone et al., 2016). We pooled these metabolites into 7 separate chemical standard pools (Supplementary File 1). To do this, each metabolite in a given pool was weighed and then mixed (6 cycles of 1 min. mixing at 25 Hz followed by 3 min. resting) using a Mixer Mill MM301 (Retsch, Düsseldorf, Germany), and mixed metabolite powder stocks were stored at -20°C prior to resuspension and analysis. Stock solutions of the mixed standards pools containing ~5mM, ~1mM, ~300µM, ~100µM, ~30µM, ~10µM, ~3µM and ~1µM of each metabolite were made in HPLC grade water and were stored at -80°C (see Supplementary File 1 for the concentration of each metabolite in the external standard pools). We refer to these stock solutions as “external standard pools” throughout. External standard pools were used to confirm the retention time and m/z for each analyte and provide standards to quantitate concentrations of stable isotope labeled internal standards used in downstream analysis, as well as to quantitate metabolite concentrations in TIF and plasma samples directly where internal standards were not available (see below for details). To extract polar metabolites from plasma, TIF or the external standard pools, 5µL of TIF, plasma or external sample pools was mixed with 45uL of acetonitrile:methanol:formic acid (75:25:0.1) extraction buffer including the following isotopically labeled internal standards: 13C labeled yeast extract (Cambridge Isotope Laboratory, Andover, MA, ISO1), 13C3 lactate (Sigma Aldrich, Darmstadt, Germany, 485926), 13C3 glycerol (Cambridge Isotope Laboratory, Andover, MA, CLM-1510), 13C6 15N2 cystine (Cambridge Isotope Laboratory, Andover, MA, CNLM-4244), 2H9 choline (Cambridge Isotope Laboratory, Andover, MA, DLM-549), 13C4 3-hydroxybutyrate (Cambridge Isotope Laboratory, Andover, MA, CLM-3853), 13C6 glucose (Cambridge Isotope Laboratory, Andover, MA, CLM-1396), 13C2 15N taurine (Cambridge Isotope Laboratory, Andover, MA, CNLM-10253), 2H3 creatinine (Cambridge Isotope Laboratory, Andover, MA, DLM-3653), 8-13C adenine (Cambridge Isotope Laboratory, Andover, MA, CLM-1654), 13C5 hypoxanthine (Cambridge Isotope Laboratory, Andover, MA, CLM-8042), 8-13C guanine (Cambridge Isotope Laboratory, Andover, MA, CLM-1019), 13C3 serine (Cambridge Isotope Laboratory, Andover, MA, CLM-1574) and 13C2 glycine (Cambridge Isotope Laboratory, Andover, MA, CLM-1017). All solvents used in the extraction buffer were HPLC grade. Samples were then vortexed for 10 min. at 4°C and insoluble material was sedimented by centrifugation at 15kg for 10 min. at 4°C. 20µL of the soluble polar metabolite extract was taken for LC/MS analysis.

Combined analysis:

Analysis ID AN001830 AN001831
Analysis type MS MS
Chromatography type HILIC HILIC
Chromatography system Thermo Dionex Ultimate 3000 Thermo Dionex Ultimate 3000
Column SeQuant ZIC- pHILIC (150 x 2.1mm, 5um) SeQuant ZIC- pHILIC (150 x 2.1mm, 5um)
MS Type ESI ESI
MS instrument type Orbitrap Orbitrap
MS instrument name Thermo Q Exactive Orbitrap Thermo Q Exactive Orbitrap
Ion Mode POSITIVE NEGATIVE
Units micromoles/L micromoles/L

Chromatography:

Chromatography ID:CH001296
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:SeQuant ZIC- pHILIC (150 x 2.1mm, 5um)
Chromatography Type:HILIC

MS:

MS ID:MS001691
Analysis ID:AN001830
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:LC/MS analysis was performed using a QExactive orbitrap mass spectrometer using an Ion Max source and heated electrospray ionization (HESI) probe coupled to a Dionex Ultimate 3000 UPLC system (Thermo Fisher Scientific, Waltham, MA). External mass calibration was performed every 7 days. 2μL of each sample was injected onto a ZIC-pHILIC 2.1 × 150 mm analytical column equipped with a 2.1 × 20 mm guard column (both 5 μm particle size, EMD Millipore). The autosampler and column oven were held at 4°C and 25°C, respectively. Buffer A was 20 mM ammonium carbonate, 0.1% ammonium hydroxide; buffer B was acetonitrile. The chromatographic gradient was run at a flow rate of 0.150 mL/min as follows: 0-20 min: linear gradient from 80% to 20% B; 20-20.5 min: linear gradient from 20% to 80% B; 20.5-28min: hold at 80% B. The mass spectrometer was operated in full scan, polarity-switching mode with the spray voltage set to 3.0 kV, the heated capillary held at 275°C, and the HESI probe held at 350°C. The sheath gas flow rate was set to 40 units, the auxiliary gas flow was set to 15 units, and the sweep gas flow was set to 1 unit. The MS data acquisition was performed in a range of 70-1000 m/z, with the resolution set to 70,000, the AGC target at 1e6, and the maximum injection time at 20 msec. Metabolite identification and quantification was performed with XCalibur 2.2 software (Thermo Fisher Scientific, Waltham, MA) using a 5ppm mass accuracy and a 0.5 min. retention time window. For metabolite identification, external standard pools were used for assignment of metabolites to peaks at given m/z and retention time, and to determine the limit of detection for each metabolite (see Supplementary File 1 for the m/z, retention time and limit of detection for each metabolite analyzed). Metabolite quantification was performed by two separate methods. Where internal standards were available, first, comparison of the peak areas of the stable isotope labeled internal standards with the external standard pools allowed for quantification of the concentration of labeled internal standards in the extraction buffer. Subsequently, we compared the peak area of a given metabolite in the TIF and plasma samples with the peak area of the internal standard to quantitate the concentration of that metabolite in the TIF or plasma sample. 70 metabolites were quantitated using this internal standard method (see Supplementary File 1 for the metabolites quantitated with internal standards). For metabolites without internal standards, the peak area of each analyte was normalized to the peak area of a labeled amino acid internal standard that eluted at roughly the same retention time to account for differences in recovery between samples (see Supplementary File 1 for the labeled amino acid paired to each metabolite analyzed without an internal standard). From the normalized peak areas of metabolites in the external standard pools, we generated a standard curve describing the relationship between metabolite concentration and normalized peak area. The standard curves were linear with fits typically at or above r2=0.95. Metabolites which did not meet these criteria were excluded from further analysis. These equations were then used to convert normalized peak areas of analytes in the TIF or plasma samples into analyte concentration in the samples. 74 metabolites were quantitated using this method. The relationship between metabolite concentration and normalized peak area is matrix dependent, and the external standards are prepared in water, which is a different matrix than either TIF or plasma. Therefore, we consider metabolite measurements using this external standard method semi-quantitative.
Ion Mode:POSITIVE
  
MS ID:MS001692
Analysis ID:AN001831
Instrument Name:Thermo Q Exactive Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:LC/MS analysis was performed using a QExactive orbitrap mass spectrometer using an Ion Max source and heated electrospray ionization (HESI) probe coupled to a Dionex Ultimate 3000 UPLC system (Thermo Fisher Scientific, Waltham, MA). External mass calibration was performed every 7 days. 2μL of each sample was injected onto a ZIC-pHILIC 2.1 × 150 mm analytical column equipped with a 2.1 × 20 mm guard column (both 5 μm particle size, EMD Millipore). The autosampler and column oven were held at 4°C and 25°C, respectively. Buffer A was 20 mM ammonium carbonate, 0.1% ammonium hydroxide; buffer B was acetonitrile. The chromatographic gradient was run at a flow rate of 0.150 mL/min as follows: 0-20 min: linear gradient from 80% to 20% B; 20-20.5 min: linear gradient from 20% to 80% B; 20.5-28min: hold at 80% B. The mass spectrometer was operated in full scan, polarity-switching mode with the spray voltage set to 3.0 kV, the heated capillary held at 275°C, and the HESI probe held at 350°C. The sheath gas flow rate was set to 40 units, the auxiliary gas flow was set to 15 units, and the sweep gas flow was set to 1 unit. The MS data acquisition was performed in a range of 70-1000 m/z, with the resolution set to 70,000, the AGC target at 1e6, and the maximum injection time at 20 msec. Metabolite identification and quantification was performed with XCalibur 2.2 software (Thermo Fisher Scientific, Waltham, MA) using a 5ppm mass accuracy and a 0.5 min. retention time window. For metabolite identification, external standard pools were used for assignment of metabolites to peaks at given m/z and retention time, and to determine the limit of detection for each metabolite (see Supplementary File 1 for the m/z, retention time and limit of detection for each metabolite analyzed). Metabolite quantification was performed by two separate methods. Where internal standards were available, first, comparison of the peak areas of the stable isotope labeled internal standards with the external standard pools allowed for quantification of the concentration of labeled internal standards in the extraction buffer. Subsequently, we compared the peak area of a given metabolite in the TIF and plasma samples with the peak area of the internal standard to quantitate the concentration of that metabolite in the TIF or plasma sample. 70 metabolites were quantitated using this internal standard method (see Supplementary File 1 for the metabolites quantitated with internal standards). For metabolites without internal standards, the peak area of each analyte was normalized to the peak area of a labeled amino acid internal standard that eluted at roughly the same retention time to account for differences in recovery between samples (see Supplementary File 1 for the labeled amino acid paired to each metabolite analyzed without an internal standard). From the normalized peak areas of metabolites in the external standard pools, we generated a standard curve describing the relationship between metabolite concentration and normalized peak area. The standard curves were linear with fits typically at or above r2=0.95. Metabolites which did not meet these criteria were excluded from further analysis. These equations were then used to convert normalized peak areas of analytes in the TIF or plasma samples into analyte concentration in the samples. 74 metabolites were quantitated using this method. The relationship between metabolite concentration and normalized peak area is matrix dependent, and the external standards are prepared in water, which is a different matrix than either TIF or plasma. Therefore, we consider metabolite measurements using this external standard method semi-quantitative.
Ion Mode:NEGATIVE
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