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.
Study ID | ST001119 |
Study Title | Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability |
Study 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. W GCIS 306, Chicago, Illinois, 60637, USA |
muir.alexander@gmail.com | |
Phone | 5104950975 |
Submit Date | 2019-01-03 |
Raw Data Available | Yes |
Raw Data File Type(s) | raw(Thermo) |
Analysis Type Detail | LC-MS |
Release Date | 2019-03-06 |
Release Version | 1 |
Select appropriate tab below to view additional metadata details:
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 |
---|---|---|
SA077680 | 1234 KPK 3 TIF | Keap1_mutant_lung_subcutaneous |
SA077681 | 1234 KPK 4 TIF | Keap1_mutant_lung_subcutaneous |
SA077682 | 1234 KPK 5 TIF | Keap1_mutant_lung_subcutaneous |
SA077683 | 1234 KPK 1 TIF | Keap1_mutant_lung_subcutaneous |
SA077684 | 1233 KPK 1 TIF | Keap1_mutant_lung_subcutaneous |
SA077685 | 1233 KPK 6 TIF | Keap1_mutant_lung_subcutaneous |
SA077686 | 1233 KPK 5 TIF | Keap1_mutant_lung_subcutaneous |
SA077687 | 1234 KPK 6 TIF | Keap1_mutant_lung_subcutaneous |
SA077688 | 1233 KP 5 TIF | lung_subcutaneous |
SA077689 | 1233 KP 6 TIF | lung_subcutaneous |
SA077690 | 1234 KP 1 TIF | lung_subcutaneous |
SA077691 | 1233 KP 4 TIF | lung_subcutaneous |
SA077692 | 1234 KP 2 TIF | lung_subcutaneous |
SA077693 | 1233 KP 3 TIF | lung_subcutaneous |
SA077694 | 1234 KP 4 TIF | lung_subcutaneous |
SA077695 | 1234 KP 3 TIF | lung_subcutaneous |
SA077696 | 1234 KP 5 TIF | lung_subcutaneous |
SA077697 | 1234 KP 6 TIF | lung_subcutaneous |
SA077698 | 5197 TIF repeat | pancreatic ductal adenocarcinoma |
SA077699 | 58 TIF | pancreatic ductal adenocarcinoma |
SA077700 | 172 TIF repeat | pancreatic ductal adenocarcinoma |
SA077701 | AL1 TIF repeat | pancreatic ductal adenocarcinoma |
SA077702 | 268 TIF repeat | pancreatic ductal adenocarcinoma |
SA077703 | 1339 TIF repeat | pancreatic ductal adenocarcinoma |
SA077704 | 142 TIF repeat | pancreatic ductal adenocarcinoma |
SA077705 | 922 TIF | pancreatic ductal adenocarcinoma |
SA077706 | 142 TIF | pancreatic ductal adenocarcinoma |
SA077707 | 268 TIF | pancreatic ductal adenocarcinoma |
SA077708 | AL1 TIF | pancreatic ductal adenocarcinoma |
SA077709 | 5197 TIF | pancreatic ductal adenocarcinoma |
SA077710 | 172 TIF | pancreatic ductal adenocarcinoma |
SA077711 | 1339 TIF | pancreatic ductal adenocarcinoma |
SA077712 | TBt0 plasma 711 | pancreatic ductal adenocarcinoma plasma |
SA077713 | TBt0 plasma 712 | pancreatic ductal adenocarcinoma plasma |
SA077714 | TBt0 plasma 705 | pancreatic ductal adenocarcinoma plasma |
SA077715 | TBt0 plasma 710 | pancreatic ductal adenocarcinoma plasma |
SA077716 | TBt0 plasma 707 | pancreatic ductal adenocarcinoma plasma |
SA077717 | TBt0 plasma 708 | pancreatic ductal adenocarcinoma plasma |
SA077718 | 4198_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077719 | 4300_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077720 | X3_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077721 | X4_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077722 | 3731_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077723 | B0_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077724 | X2_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077725 | B2_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077726 | B1_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077727 | A1_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077728 | A0_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077729 | 58_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077730 | 5197_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077731 | AL1_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077732 | 172_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077733 | 922_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077734 | 142_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077735 | 268_Plasma | pancreatic ductal adenocarcinoma plasma cardiac puncture |
SA077736 | X2 TIF | pancreatic ductal adenocarcinoma subcutaneous |
SA077737 | X1 TIF | pancreatic ductal adenocarcinoma subcutaneous |
SA077738 | X4 TIF | pancreatic ductal adenocarcinoma subcutaneous |
SA077739 | X5 TIF | pancreatic ductal adenocarcinoma subcutaneous |
SA077740 | X3 TIF | pancreatic 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) |
Column Temperature: | 25 |
Flow Gradient: | 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. |
Flow Rate: | 0.150 mL/min |
Solvent A: | 100% water; 20 mM ammonium carbonate, 0.1% ammonium hydroxide |
Solvent B: | 100% acetonitrile |
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 |