Summary of Study ST002160
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 PR001373. The data can be accessed directly via it's Project DOI: 10.21228/M87Q56 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 | ST002160 |
| Study Title | Global metabolomics analysis of neutrophils isolated from tumor |
| Study Summary | Pathologically activated neutrophils (PMN), termed myeloid-derived suppressor cells (PMN-MDSCs), are major negative regulators of anti-tumor immunity. The mechanisms responsible for the pathological activation of neutrophils upon infiltration into tumors are not well defined, thus limiting the selective targeting of these cells. Tumor cells and immune cells engage in bi-directional manipulation of their respective metabolism, thereby altering cell function to facilitate tumor progression. Targeting the metabolism of responding immune cells can improve cancer treatment when combined with existing therapeutic strategies. Here, we investigated the role of metabolism in the immunoinhibitory actions of tumor PMN-MDSCs. |
| Institute | The Wistar Institute |
| Last Name | Nefedova |
| First Name | Yulia |
| Address | 3601 Spruce St, Philadelphia, PA 19104 |
| ynefedova@wistar.org | |
| Phone | 215-495-6952 |
| Submit Date | 2022-05-04 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-05-05 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR001373 |
| Project DOI: | doi: 10.21228/M87Q56 |
| Project Title: | The study of metabolomics in tumor PMN-MDSCs |
| Project Summary: | Pathologically activated neutrophils (PMN), termed myeloid-derived suppressor cells (PMN-MDSCs), are major negative regulators of anti-tumor immunity. The mechanisms responsible for the pathological activation of neutrophils upon infiltration into tumors are not well defined, thus limiting the selective targeting of these cells. Tumor cells and immune cells engage in bi-directional manipulation of their respective metabolism, thereby altering cell function to facilitate tumor progression. Targeting the metabolism of responding immune cells can improve cancer treatment when combined with existing therapeutic strategies. Here, we investigated the role of metabolism in the immunoinhibitory actions of tumor PMN-MDSCs. |
| Institute: | The Wistar Institute |
| Last Name: | Nefedova |
| First Name: | Yulia |
| Address: | 3601 Spruce St, Philadelphia, PA 19104 |
| Email: | 215-495-6952 |
| Phone: | ynefedova@wistar.org |
Subject:
| Subject ID: | SU002246 |
| 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 | Alox12/15 Status |
|---|---|---|
| SA207153 | KO-1 | KO |
| SA207154 | KO-2 | KO |
| SA207155 | KO-3 | KO |
| SA207160 | QC-2 | n/a |
| SA207161 | QC-3 | n/a |
| SA207162 | QC-1 | n/a |
| SA207156 | WT-4 | WT |
| SA207157 | WT-3 | WT |
| SA207158 | WT-2 | WT |
| SA207159 | WT-1 | WT |
| Showing results 1 to 10 of 10 |
Collection:
| Collection ID: | CO002239 |
| Collection Summary: | Single-cell suspensions from tumor tissues were prepared using Mouse Tumor Dissociation Kit according to the manufacturer’s recommendation (Miltenyi). PMN-MDSCs were sorted using FACS Aria Ⅱ (CD11b+Ly6G+Ly6Clo). |
| Sample Type: | Tumor cells |
Treatment:
| Treatment ID: | TR002258 |
| Treatment Summary: | n/a |
Sample Preparation:
| Sampleprep ID: | SP002252 |
| Sampleprep Summary: | Briefly, polar metabolites were extracted from 1 million isolated neutrophils with 50 µl ice-cold 80% methanol (20 million cells/ml final), and deproteinated supernatants were stored at -80 °C prior to analysis. A quality control (QC) sample was generated by pooling equal volumes of all samples after extraction. |
Combined analysis:
| Analysis ID | AN003539 |
|---|---|
| Analysis type | MS |
| Chromatography type | HILIC |
| Chromatography system | Thermo Vanquish |
| Column | SeQuant ZIC-HILIC (150 x 2.1mm,5um) |
| MS Type | ESI |
| MS instrument type | Orbitrap |
| MS instrument name | Thermo Q Exactive HF-X Orbitrap |
| Ion Mode | UNSPECIFIED |
| Units | Normalized MS Peak Area |
Chromatography:
| Chromatography ID: | CH002613 |
| Chromatography Summary: | Hydrophilic interaction liquid chromatography (HILIC) was performed at 0.2 ml/min on a ZIC-pHILIC column (2.1 mm × 150 mm, EMD Millipore) at 45 °C. Solvent A was 20 mM ammonium carbonate, 0.1% ammonium hydroxide, pH 9.2, and solvent B was acetonitrile. The gradient was 85% B for 2 min, 85% B to 20% B over 15 min, 20% B to 85% B over 0.1 min, and 85% B for 8.9 min. The autosampler was held at 4 °C. For each analysis, 4 µl of sample was injected. |
| Instrument Name: | Thermo Vanquish |
| Column Name: | SeQuant ZIC-HILIC (150 x 2.1mm,5um) |
| Flow Gradient: | 85% B for 2 min, 85% B to 20% B over 15 min, 20% B to 85% B over 0.1 min, and 85% B for 8.9 min. |
| Solvent A: | 100% water; 20 mM ammonium carbonate; 0.1% ammonium hydroxide, pH 9.4 |
| Solvent B: | 100% acetonitrile |
| Chromatography Type: | HILIC |
MS:
| MS ID: | MS003297 |
| Analysis ID: | AN003539 |
| Instrument Name: | Thermo Q Exactive HF-X Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | The following parameters were used for the MS analysis: sheath gas flow rate, 40; auxiliary gas flow rate, 10; sweep gas flow rate, 2; auxiliary gas heater temperature, 350 °C; spray voltage, 3.5 kV for positive mode and 3.2 kV for negative mode; capillary temperature, 325 °C; and funnel RF level, 40. All samples were analyzed by full MS with polarity switching. The QC sample was analyzed at the start of the sample sequence and after every 3-4 samples. The QC sample was also analyzed by data-dependent MS/MS with separate runs for positive and negative ion modes. Full MS scans were acquired at 120,000 resolution with a scan range of 65-975 m/z. Data-dependent MS/MS scans were acquired for the top 10 highest intensity ions at 15,000 resolution with an isolation width of 1.0 m/z and stepped normalized collision energy of 20-40-60. Data analysis was performed using Compound Discoverer 3.1 (ThermoFisher Scientific) with separate analyses for positive and negative polarities. Retention time alignment used the adaptative curve model with 0.3 min maximum shift, 5 ppm mass tolerance, and 3 S/N threshold. Peak detection required less than 5 ppm mass error for extracted ion chromatograms with a 100,000 minimum peak intensity. [M+H]+1 and [M-H]-1 adducts were considered. Peaks were required to have a width at half height less than 1.0 min and a minimum of 5 scans. Components that had only a monoisotopic peak and no further isotopes were discarded. The maximum element count for isotope pattern modeling was C90 H190 N10 O20 P3 S5. Compounds were grouped across samples with 5 ppm mass error and 0.2 min retention time shift. Peaks not detected initially in a given sample were determined using the fill gaps algorithm with 5 ppm mass error and 1.5 S/N threshold with real peak detection. The gap function uses a priority system to determine missing values: 1) matching detected ions based on expected m/z and retention time regardless of adduct assignment, 2) re-detecting peaks at lower thresholds, 3) simulating peaks based on expected m/z, and 4) imputing spectrum noise based on detection limit values. Compound quantifications were corrected for instrument drift by QC areas using the cubic spline regression model. Each compound was required to be detected in all QC runs with an RSD less than 40%. Metabolites were identified by accurate mass (5 ppm mass error) and retention time (0.3 min shift) using a database generated from pure standards or by accurate mass and MS2 spectra using the mzCloud spectral database (mzCloud.org), specifically the ‘Endogenous Metabolites’ and ‘Steroids/Vitamins/Hormones’ compound classes, and selecting the best matches with HighChem HighRes identity search match factors of 50 or greater. Results were manually processed to remove entries with apparent peak mis-integrations and correct commonly misannotated metabolites. Positive and negative data sets of identified compounds were merged, and the preferred polarity was selected for compounds identified in both polarities. Compound quantifications were normalized to the summed area of identified metabolites in each sample. For compounds identified multiple times at different retention times, a single entry was selected with priority given to standards database matches followed by greater mzCloud match factors and peak areas. |
| Ion Mode: | UNSPECIFIED |
