Summary of Study ST002847

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 PR001782. The data can be accessed directly via it's Project DOI: 10.21228/M8CB14 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	ST002847
Study Title	Targeting Pancreatic Cancer Metabolic Dependencies through Glutamine Antagonism.
Study Summary	Pancreatic ductal adenocarcinoma (PDAC) cells utilize glutamine (Gln) to support proliferation and redox balance. Earlier attempts to inhibit Gln metabolism using glutaminase inhibitors resulted in rapid metabolic reprogramming and therapeutic resistance. Here, we demonstrated that treating PDAC cells with a Gln antagonist, 6-Diazo-5-oxo-L-norleucine (DON), led to a metabolic crisis in vitro. In addition, we observed a profound decrease in tumor growth in various in vivo models using DRP-104 (sirpiglenastat), a pro-drug version of DON that was designed to circumvent DON associated toxicity. We found that ERK signaling is increased as a compensatory mechanism. Combinatorial treatment of DRP-104 and Trametinib led to a significant increase in survival in a syngeneic model PDAC. These proof-of-concept studies suggested that broadly targeting Gln metabolism could provide a therapeutic avenue for PDAC. The combination with an ERK signaling pathway inhibitor could further improve the therapeutic outcome.
Institute	New York University
Last Name	Encarnacion Rosado
First Name	Joel
Address	Smilow Research Building Room 907G New York, NY 10016
Email	jencarnacionrosado@salk.edu, Alec.Kimmelman@nyulangone.org
Phone	646-501-8984
Submit Date	2023-09-06
Raw Data Available	Yes
Raw Data File Type(s)	mzXML
Analysis Type Detail	LC-MS
Release Date	2024-09-08
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR001782
Project DOI:	doi: 10.21228/M8CB14
Project Title:	Targeting Pancreatic Cancer Metabolic Dependencies through Glutamine Antagonism.
Project Type:	Manuscript
Project Summary:	Pancreatic ductal adenocarcinoma (PDAC) cells utilize glutamine (Gln) to support proliferation and redox balance. Earlier attempts to inhibit Gln metabolism using glutaminase inhibitors resulted in rapid metabolic reprogramming and therapeutic resistance. We demonstrated that treating PDAC cells with a Gln antagonist, 6-Diazo-5-oxo-L-norleucine (DON), led to a metabolic crisis in vitro. In addition, we observed a profound decrease in tumor growth in various in vivo models using DRP-104 (sirpiglenastat), a pro-drug version of DON designed to circumvent DON-associated toxicity.
Institute:	New York University
Department:	Radiation Oncology
Laboratory:	Alec C Kimmelman
Last Name:	Encarnacion Rosado
First Name:	Joel
Address:	Smilow Research Building Room 907G New York, NY 10016
Email:	jencarnacionrosado@salk.edu, Alec.Kimmelman@nyulangone.org
Phone:	646-501-8984

Subject:

Subject ID:	SU002959
Subject Type:	Cultured cells
Subject Species:	Mus musculus
Taxonomy ID:	10090
Gender:	Not applicable

Factors:

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

mb_sample_id	local_sample_id	Vehicle
SA308547	HY19_DON_3	DON
SA308548	HY19_DON_1	DON
SA308549	HY19_DON_2	DON
SA308550	HY19_DRP104_3	DRP-104
SA308551	HY19_DRP104_2	DRP-104
SA308552	HY19_DRP104_1	DRP-104
SA308553	HY19_CNT_2	Vehicle
SA308554	HY19_CNT_3	Vehicle
SA308555	HY19_CNT_1	Vehicle

Showing results 1 to 9 of 9

Showing results 1 to 9 of 9

Collection:

Collection ID:	CO002952
Collection Summary:	As described in Parker, et al (https://doi.org/10.1038/s41467-021-25228-9), xtraction of metabolites from cell pellets— Metabolites were initially extracted from samples by quickly aspirating the cell culture media and adding 1 mL of extraction buffer, consisting of 80% methanol (Fisher Scientific) and 500 nM metabolomics amino acid mix standard (Cambridge Isotope Laboratories). To effectively scale all harvested samples to equivalent volumes of extraction buffer, samples were fully dried down by Speedvac (Thermo Fisher, Waltham, MA) and reconstituted volumetrically by mixing the entire dried cell pellet sample with 1 mL of 80% methanol without QC standards in 2.0 mL screw cap vials containing ~100 µL of disruption beads (Research Products International, Mount Prospect, IL). Samples were scaled to a ratio of 1e6 cells to 1 mL of extraction solvent with all steps being carried out in a cold room. Each was homogenized for 10 cycles on a bead blaster homogenizer (Benchmark Scientific, Edison, NJ). Cycling consisted of a 30 sec homogenization time at 6 m/s followed by a 30 sec pause. Samples were subsequently spun at 21,000 × g for 3 min at 4 °C. A set volume of each (450 µL) was transferred to a 1.5 mL tube and dried down by Speedvac concentration. Samples were reconstituted in 50 µL of Optima LC/MS grade water (Fisher Scientific, Waltham, MA). Samples were sonicated for 2 min, then centrifuged at 21,000 × g for 3 min at 4 °C. Twenty microliters were transferred to LC vials containing glass inserts for analysis. The remaining sample was placed at −80 °C for long-term storage. Samples were subjected to an LC-MS analysis to detect and quantify known peaks. A metabolite extraction was carried out on each sample by quickly aspirating experimental media and adding 1 mL of 80% methanol containing internal QC standards. A MilliporeTM ZIC-pHILIC (2.1 × 150 mm, 5 μm) LC column was coupled to a Dionex Ultimate 3000TM system. The column oven temperature and flow rate were set to 25 °C and 100 μL/min, respectively, for the following gradient elution: 80–20%B (0–30 min), 20–80%B (30–31 min), 80–80%B (31–42 min). Mobile phase compositions were: (A) 10 mM ammonium carbonate in water, pH 9.0 and (B) neat acetonitrile; and an injection volume of 2 μL was used for all analyses. The LC system was coupled to a Thermo Q Exactive HFTM mass spectrometer operating in heated electrospray ionization mode (HESI) for LC-MS analysis. A 30-m polarity switching data-dependent Top 5 method was used for both positive and negative modes. The following parameters were also set: spray voltage of 3.5 kV, capillary temperature at 320 °C, sheath gas flow rate of 35, aux gas rate of 10, and max spray current of 100 μA. Full MS scan parameters for both positive and negative modes were set as followed: scan range of 67–1000 m/z, resolution of 120,000, AGC target of 3e6, and maximum IT of 100 ms. Tandem MS spectra for both positive and negative modes used a resolution of 15,000, fixed first mass of 50 m/z, isolation window of 0.4 m/z, isolation offset of 0.1 m/z, AGC target of 1e5, minimum AGC target of 1e4, intensity threshold of 2e5, maximum IT of 50 ms, and three-way multiplexed normalized collision energies (nCE) of 10, 30, 80. All data were acquired in profile mode. ThermoTM RAW files were read using ThermoFisher CommonCore RawFileReader. An in-house python script (Skeleton) was used for detection and quantification of sample peaks and internal standards based on a retention time and accurate mass library adapted from the Whitehead Institute94 and verified with authentic standards and/or high-resolution MS/MS spectra manually curated using the NIST14MS/MS95 and METLIN (2017)96 tandem mass spectral libraries. For feature-based analysis, an in-house python script (Ungrid) was used to detect MS1 peaks across all samples using the following parameters: a m/z discrimination threshold of 20 ppm, a minimum peak intensity of 1e5, a minimum signal-to-noise ratio of 10, and a retention time threshold of 2 min. Metabolite and feature peaks extracted in this manner were defined by either the detected feature m/z or the theoretical m/z of the expected ion type for the standard in the library (e.g., [M+H]+). The following parameters were applied: a ±5 part-per-million (ppm) tolerance, an initial retention time search window of ±0.5 min across all samples, and a ±7.5 s peak apex retention time tolerance within individual samples. An in-house statistical pipeline, Metabolize (version 1.0), was used to process the resulting data matrix of metabolite intensities for all samples and blank controls. A final peak detection was calculated based on a signal-to-noise ratio (S/N) or 3× blank controls with a floor of 1e5 (arb. units). The threshold value was input for any sample where the calculated peak intensity was lower than the blank threshold for any statistical comparisons. The resulting blank corrected data matrix was used for all group-wise comparisons. T-tests were performed using the Python SciPy library (version 1.1.0)97 to test for differences and generate statistics. Any metabolite with p-value < 0.05 was considered significantly regulated (up or down). Volcano plots were generated utilizing Prism (GraphPad). The R package DESeq2 (1.24.0)98 was used to adjust for covariate effects (as applicable) and to calculate the adjusted p-value in the covariate model. Zero values were input for non-detected values instead of the blank threshold to avoid false positive.
Sample Type:	Cultured cells

Treatment:

Treatment ID:	TR002968
Treatment Summary:	HY19636 cells were plated in a six-well plate at 2.0x10^5 cells/well and allowed to attach overnight in DMEM. Next, cells were washed with PBS twice and cultured for 24 hours in DMEM supplemented with 10% dialyzed serum was added. Cells were pre-treated with DON (25µM) or DRP-104 (25µM) overnight, media was removed and washed with PBS. Then, cells were frozen in -80C and until metabolite extraction

Treatment ID:

TR002968

Treatment Summary:

HY19636 cells were plated in a six-well plate at 2.0x10^5 cells/well and allowed to attach overnight in DMEM. Next, cells were washed with PBS twice and cultured for 24 hours in DMEM supplemented with 10% dialyzed serum was added. Cells were pre-treated with DON (25µM) or DRP-104 (25µM) overnight, media was removed and washed with PBS. Then, cells were frozen in -80C and until metabolite extraction

Sample Preparation:

Sampleprep ID:	SP002965
Sampleprep Summary:	Extraction of metabolites from cell pellets— Metabolites were initially extracted from samples by quickly aspirating the cell culture media and adding 1 mL of extraction buffer, consisting of 80% methanol (Fisher Scientific) and 500 nM metabolomics amino acid mix standard (Cambridge Isotope Laboratories). To effectively scale all harvested samples to equivalent volumes of extraction buffer, samples were fully dried down by Speedvac (Thermo Fisher, Waltham, MA) and reconstituted volumetrically by mixing the entire dried cell pellet sample with 1 mL of 80% methanol without QC standards in 2.0 mL screw cap vials containing ~100 µL of disruption beads (Research Products International, Mount Prospect, IL). Samples were scaled to a ratio of 1e6 cells to 1 mL of extraction solvent with all steps being carried out in a cold room. Each was homogenized for 10 cycles on a bead blaster homogenizer (Benchmark Scientific, Edison, NJ). Cycling consisted of a 30 sec homogenization time at 6 m/s followed by a 30 sec pause. Samples were subsequently spun at 21,000 × g for 3 min at 4 °C. A set volume of each (450 µL) was transferred to a 1.5 mL tube and dried down by Speedvac concentration. Samples were reconstituted in 50 µL of Optima LC/MS grade water (Fisher Scientific, Waltham, MA). Samples were sonicated for 2 min, then centrifuged at 21,000 × g for 3 min at 4 °C. Twenty microliters were transferred to LC vials containing glass inserts for analysis. The remaining sample was placed at −80 °C for long-term storage.

Sampleprep ID:

SP002965

Sampleprep Summary:

Extraction of metabolites from cell pellets— Metabolites were initially extracted from samples by quickly aspirating the cell culture media and adding 1 mL of extraction buffer, consisting of 80% methanol (Fisher Scientific) and 500 nM metabolomics amino acid mix standard (Cambridge Isotope Laboratories). To effectively scale all harvested samples to equivalent volumes of extraction buffer, samples were fully dried down by Speedvac (Thermo Fisher, Waltham, MA) and reconstituted volumetrically by mixing the entire dried cell pellet sample with 1 mL of 80% methanol without QC standards in 2.0 mL screw cap vials containing ~100 µL of disruption beads (Research Products International, Mount Prospect, IL). Samples were scaled to a ratio of 1e6 cells to 1 mL of extraction solvent with all steps being carried out in a cold room. Each was homogenized for 10 cycles on a bead blaster homogenizer (Benchmark Scientific, Edison, NJ). Cycling consisted of a 30 sec homogenization time at 6 m/s followed by a 30 sec pause. Samples were subsequently spun at 21,000 × g for 3 min at 4 °C. A set volume of each (450 µL) was transferred to a 1.5 mL tube and dried down by Speedvac concentration. Samples were reconstituted in 50 µL of Optima LC/MS grade water (Fisher Scientific, Waltham, MA). Samples were sonicated for 2 min, then centrifuged at 21,000 × g for 3 min at 4 °C. Twenty microliters were transferred to LC vials containing glass inserts for analysis. The remaining sample was placed at −80 °C for long-term storage.

Combined analysis:

Analysis ID	AN004665
Analysis type	MS
Chromatography type	HILIC
Chromatography system	Thermo Dionex Ultimate 3000
Column	SeQuant ZIC- pHILIC (150 x 2.1mm, 5um)
MS Type	ESI
MS instrument type	Orbitrap
MS instrument name	Thermo Q Exactive HF hybrid Orbitrap
Ion Mode	UNSPECIFIED
Units	ion counts

Chromatography:

Chromatography ID:	CH003511
Instrument Name:	Thermo Dionex Ultimate 3000
Column Name:	SeQuant ZIC- pHILIC (150 x 2.1mm, 5um)
Column Temperature:	25
Flow Gradient:	The gradient profile was as follows; 80-20%B (0-30 min), 20-80%B (30-31 min), 80-80%B (31-42 min)
Flow Rate:	100 uL/min
Solvent A:	10 mM ammonium carbonate in water, pH 9.0
Solvent B:	acetonitrile
Chromatography Type:	HILIC

MS:

MS ID:	MS004412
Analysis ID:	AN004665
Instrument Name:	Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:	Orbitrap
MS Type:	ESI
MS Comments:	The LC system was coupled to a Thermo Q Exactive HFTM mass spectrometer operating in heated electrospray ionization mode (HESI) for LC-MS analysis. A 30-m polarity switching data-dependent Top 5 method was used for both positive and negative modes. The following parameters were also set: spray voltage of 3.5 kV, capillary temperature at 320 °C, sheath gas flow rate of 35, aux gas rate of 10, and max spray current of 100 μA. Full MS scan parameters for both positive and negative modes were set as followed: scan range of 67–1000 m/z, resolution of 120,000, AGC target of 3e6, and maximum IT of 100 ms. Tandem MS spectra for both positive and negative modes used a resolution of 15,000, fixed first mass of 50 m/z, isolation window of 0.4 m/z, isolation offset of 0.1 m/z, AGC target of 1e5, minimum AGC target of 1e4, intensity threshold of 2e5, maximum IT of 50 ms, and three-way multiplexed normalized collision energies (nCE) of 10, 30, 80. All data were acquired in profile mode. ThermoTM RAW files were read using ThermoFisher CommonCore RawFileReader. An in-house python script (Skeleton) was used for detection and quantification of sample peaks and internal standards based on a retention time and accurate mass library adapted from the Whitehead Institute94 and verified with authentic standards and/or high-resolution MS/MS spectra manually curated using the NIST14MS/MS95 and METLIN (2017)96 tandem mass spectral libraries.
Ion Mode:	UNSPECIFIED