Summary of Study ST002853

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.

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Study IDST002853
Study TitleTargeting Pancreatic Cancer Metabolic Dependencies through Glutamine Antagonism (Lipidomics-human)
Study SummaryPancreatic 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 NameEncarnacion Rosado
First NameJoel
AddressSmilow Research Building Room 907G New York, NY 10016
Emailjoel.encarnacion-rosado@nyulangone.org
Phone646-501-8984
Submit Date2023-09-06
Raw Data AvailableYes
Raw Data File Type(s)mzXML
Analysis Type DetailLC-MS
Release Date2024-09-12
Release Version1
Joel Encarnacion Rosado Joel Encarnacion Rosado
https://dx.doi.org/10.21228/M8CB14
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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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:SU002965
Subject Type:Cultured cells
Subject Species:Homo sapiens
Taxonomy ID:9606
Gender:Not applicable

Factors:

Subject type: Cultured cells; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Treatment
SA3086588T-DON3DON
SA3086598T-DON2DON
SA3086608T-DON1DON
SA3086618T-CNT2Vehicle
SA3086628T-CNT3Vehicle
SA3086638T-CNT1Vehicle
Showing results 1 to 6 of 6

Collection:

Collection ID:CO002958
Collection Summary:Samples were subjected to an LCMS analysis to detect and identify phospholipid molecules and quantify the relative levels of identified lipids. A lipid extraction was carried out on each sample based on the method by Vorkas et. al., cite#1and#2. The dried samples were resolubilized in 10 μL of a 4:3:1 mixture (isopropanol:acetonitrile:water) and analyzed by UPLC-MS/MS with a polarity switching method modified from Vorkas et. al., cite #1. The LC column was a WatersTM CSH-C18 (2.1 x100 mm, 1.7 μm) coupled to a Dionex Ultimate 3000TM system and the column oven temperature was set to 55oC for the gradient elution. The flow rate of 0.3 mL/min was used with the following buffers; A) 60:40 acetonitrile:water, 10 mM ammonium formate, 0.1% formic acid and B) 90:10 isopropanol:acetonitrile, 10 mM ammonium formate, 0.1% formic acid. The gradient profile was as follows; 40-43%B (0-1.25 min), 43-50%B (1.25-2 min), 50-54%B (2-11 min), 54-70%B (11-12 min), 70-99%B (12-18 min), 70-99%B (18-32min), 99-40%B (23-24 min), hold 40%B (1 min). Injection volume was set to 1 μL for all analyses (25 min total run time per injection). MS analyses were carried out by coupling the LC system to a Thermo Q Exactive HFTM mass spectrometer operating in heated electrospray ionization mode (HESI). Method duration was 20 min with a polarity switching data-dependent Top 10 method for both positive and negative modes. Spray voltage for both positive and negative modes was 3.5kV and capillary temperature was set to 320oC with a sheath gas rate of 35, aux gas of 10, and max spray current of 100 μA. The full MS scan for both polarities utilized 120,000 resolution with an AGC target of 3e6 and a maximum IT of 100 ms, and the scan range was from 350-2000 m/z. Tandem MS spectra for both positive and negative mode used a resolution of 15,000, AGC target of 1e5, maximum IT of 50 ms, isolation window of 0.4 m/z, isolation offset of 0.1 m/z, fixed first mass of 50 m/z, and 3-way multiplexed normalized collision energies (nCE) of 10, 35, 80. The minimum AGC target was 5e4 with an intensity threshold of 1e6. All data were acquired in profile mode. The resulting lipids were identified by searching the LipidBlast tandem mass spectral library of lipids cite #3. The top scoring structure match for each data-dependent spectrum was returned using an in-house script for MSPepSearch_x64. Putative lipids were sorted from high to low by their reverse dot scores, and duplicate structures were discarded, retaining only the top-scoring MS2 spectrum and the neutral chemical formula, detected m/z, and detected polarity (+ or -) of the putative lipid was recorded. References 1. Vorkas, P. A. et al. Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease. Anal. Chem. 87, 4184–4193 (2015). 2. Vorkas, P. A. et al. Metabolic phenotyping of atherosclerotic plaques reveals latent associations between free cholesterol and ceramide metabolism in atherogenesis. J. Proteome Res. 14, 1389–1399 (2015). 3. https://www.ncbi.nlm.nih.gov/pubmed/23817071
Sample Type:Cultured cells

Treatment:

Treatment ID:TR002974
Treatment Summary:PaTu-8988T cells were plated in a six-well plate at 1.5x10^6 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) overnight, media was removed and washed with PBS. Then, cells were frozen in -80C and until metabolite extraction.

Sample Preparation:

Sampleprep ID:SP002971
Sampleprep Summary:Samples were analyzed with the global and untargeted lipidomics LCMS assays after scaling the lipid extraction to a measured aliquot (~5e6/mL) for each of the 6 samples. SPLASH® LIPIDOMIX® Mass Spec Standard was used as an extraction standard.

Combined analysis:

Analysis ID AN004674
Analysis type MS
Chromatography type HILIC
Chromatography system Thermo Dionex Ultimate 3000
Column WatersTM CSH-C18 (2.1 x100 mm, 1.7 μm)
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:CH003517
Instrument Name:Thermo Dionex Ultimate 3000
Column Name:WatersTM CSH-C18 (2.1 x100 mm, 1.7 μm)
Column Temperature:55C
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:1 μL for all analyses (25 min total run time per injection)
Solvent A:The flow rate of 0.3 mL/min was used with the following buffers; A) 60:40 acetonitrile:water, 10 mM ammonium formate, 0.1% formic acid and B) 90:10 isopropanol:acetonitrile, 10 mM ammonium formate, 0.1% formic acid. The gradient profile was as follows; 40-43%B (0-1.25 min), 43-50%B (1.25-2 min), 50-54%B (2-11 min), 54-70%B (11-12 min), 70-99%B (12-18 min), 70-99%B (18-32min), 99-40%B (23-24 min), hold 40%B (1 min)
Solvent B:acetonitrile
Chromatography Type:HILIC

MS:

MS ID:MS004421
Analysis ID:AN004674
Instrument Name:Thermo Q Exactive HF hybrid Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:MS analyses were carried out by coupling the LC system to a Thermo Q Exactive HFTM mass spectrometer operating in heated electrospray ionization mode (HESI). Method duration was 20 min with a polarity switching data-dependent Top 10 method for both positive and negative modes. Spray voltage for both positive and negative modes was 3.5kV and capillary temperature was set to 320C with a sheath gas rate of 35, aux gas of 10, and max spray current of 100 μA. The full MS scan for both polarities utilized 120,000 resolution with an AGC target of 3e6 and a maximum IT of 100 ms, and the scan range was from 350-2000 m/z. Tandem MS spectra for both positive and negative mode used a resolution of 15,000, AGC target of 1e5, maximum IT of 50 ms, isolation window of 0.4 m/z, isolation offset of 0.1 m/z, fixed first mass of 50 m/z, and 3-way multiplexed normalized collision energies (nCE) of 10, 35, 80. The minimum AGC target was 5e4 with an intensity threshold of 1e6. All data were acquired in profile mode. The resulting lipids were identified by searching the LipidBlast tandem mass spectral library of lipids. The top scoring structure match for each data-dependent spectrum was returned using an in-house script for MSPepSearch_x64. Putative lipids were sorted from high to low by their reverse dot scores, and duplicate structures were discarded, retaining only the top-scoring MS2 spectrum and the neutral chemical formula, detected m/z, and detected polarity (+ or -) of the putative lipid was recorded. 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 “-” is for not-detected peaks. After the correction, zero values were input for non-detected values instead of the blank threshold to avoid false positive.
Ion Mode:UNSPECIFIED
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