Summary of Study ST002408

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 PR001550. The data can be accessed directly via it's Project DOI: 10.21228/M8BM6G This work is supported by NIH grant, U2C- DK119886.

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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 IDST002408
Study TitleMulti-omic Analysis of ClpP Activation in Triple-Negative Breast Cancer Cells
Study SummaryThe ClpP activators ONC201 and related small molecules (TR compounds, Madera Therapeutics), have demonstrated significant anti-cancer potential in an array of in vitro cell models and in vivo studies, including clinical trials for refractory solid tumors. Though progress has been made in identifying specific phenotypic outcomes following ClpP activation, the exact mechanism by which ClpP activation leads to broad anti-cancer activity has yet to be fully elucidated. In this study, we utilized a multi-omics approach to identify the ClpP-dependent proteomic, transcriptomic, and metabolomic changes resulting from ONC201 or the TR compound TR-57 in triple-negative breast cancer cells (TNBC). Applying mass spectrometry- based methods of proteomics and metabolomics, we identified ~8000 proteins and 588 metabolites, respectively. From proteomics data, approximately 3400 (ONC201) and 3000 (TR-57) proteins increased and ~4600 (ONC201) and ~4800 (TR-57) proteins decreased in this study. Additionally, gene ontological analysis revealed strong similarities between proteins up- or downregulated by ONC201 or TR-57 treatment. Notably, this included the downregulation of many mitochondrial processes and proteins, including mitochondrial translation and mitochondrial matrix proteins. We also performed a large-scale transcriptomic analysis of WT SUM159 cells, identifying ~7700 transcripts (~3600 and 3800 increasing, ~4000 and 3900 decreasing in ONC201 and TR-57 treated cells, respectively). Less than 21% of these genes were affected by these compounds in ClpP null cells. Gene ontological analysis of these data demonstrated additional similarity of response to ONC201 and TR-57. Many of the same gene ontology processes and cellular components were identified, including a decrease in transcripts related to the mitochondrial inner membrane and matrix, the cell cycle, and the nucleus, as well as increases in other nuclear transcripts and transcripts related to metal-ion binding. Comparative analysis demonstrated a highly analogous response in all -omics datasets. Analysis of metabolites also revealed significant similarities between ONC201 and TR-57 with increases in α-ketoglutarate and 2-hydroxyglutaric acid and decreased levels of ureidosuccinic acid, L-ascorbic acid, L-serine, and cytidine observed following ClpP activation in TNBC cells. Further analysis identified multiple pathways that were specifically impacted by ClpP activation, including ATF4 activation, heme biosynthesis, and the citrulline/urea cycle. In summary the results of our studies demonstrate that ONC201 and TR-57 induce highly similar and broad effects against multiple mitochondrial processes required for cell proliferation.
Institute
University of North Carolina at Chapel Hill
Last NameGraves
First NameLee
Address4111 Genetic Medicine Building, 120 Mason Farm Rd, Chapel Hill, NC 27514
Emaillmg@med.unc.edu
Phone(919) 966-0915
Submit Date2022-12-13
Raw Data AvailableYes
Raw Data File Type(s)raw(Thermo)
Analysis Type DetailLC-MS
Release Date2023-12-18
Release Version1
Lee Graves Lee Graves
https://dx.doi.org/10.21228/M8BM6G
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Project:

Project ID:PR001550
Project DOI:doi: 10.21228/M8BM6G
Project Title:Multi-omic Analysis of ClpP Activation in Triple-Negative Breast Cancer Cells
Project Summary:The ClpP activators ONC201 and related small molecules (TR compounds, Madera Therapeutics), have demonstrated significant anti-cancer potential in an array of in vitro cell models and in vivo studies, including clinical trials for refractory solid tumors. Though progress has been made in identifying specific phenotypic outcomes following ClpP activation, the exact mechanism by which ClpP activation leads to broad anti-cancer activity has yet to be fully elucidated. In this study, we utilized a multi-omics approach to identify the ClpP-dependent proteomic, transcriptomic, and metabolomic changes resulting from ONC201 or the TR compound TR-57 in triple-negative breast cancer cells (TNBC). Applying mass spectrometry- based methods of proteomics and metabolomics, we identified ~8000 proteins and 588 metabolites, respectively. From proteomics data, approximately 3400 (ONC201) and 3000 (TR-57) proteins increased and ~4600 (ONC201) and ~4800 (TR-57) proteins decreased in this study. Additionally, gene ontological analysis revealed strong similarities between proteins up- or downregulated by ONC201 or TR-57 treatment. Notably, this included the downregulation of many mitochondrial processes and proteins, including mitochondrial translation and mitochondrial matrix proteins. We also performed a large-scale transcriptomic analysis of WT SUM159 cells, identifying ~7700 transcripts (~3600 and 3800 increasing, ~4000 and 3900 decreasing in ONC201 and TR-57 treated cells, respectively). Less than 21% of these genes were affected by these compounds in ClpP null cells. Gene ontological analysis of these data demonstrated additional similarity of response to ONC201 and TR-57. Many of the same gene ontology processes and cellular components were identified, including a decrease in transcripts related to the mitochondrial inner membrane and matrix, the cell cycle, and the nucleus, as well as increases in other nuclear transcripts and transcripts related to metal-ion binding. Comparative analysis demonstrated a highly analogous response in all -omics datasets. Analysis of metabolites also revealed significant similarities between ONC201 and TR-57 with increases in a-ketoglutarate and 2-hydroxyglutaric acid and decreased levels of ureidosuccinic acid, L-ascorbic acid, L-serine, and cytidine observed following ClpP activation in TNBC cells. Further analysis identified multiple pathways that were specifically impacted by ClpP activation, including ATF4 activation, heme biosynthesis, and the citrulline/urea cycle. In summary the results of our studies demonstrate that ONC201 and TR-57 induce highly similar and broad effects against multiple mitochondrial processes required for cell proliferation.
Institute:University of North Carolina at Chapel Hill
Last Name:Rushing
First Name:Blake
Address:500 Laureate Way, Kannapolis, NC, 28081, USA
Email:blake_rushing@unc.edu
Phone:+1 (704) 250-5000

Subject:

Subject ID:SU002497
Subject Type:Cultured cells
Subject Species:Homo sapiens
Taxonomy ID:9606
Species Group:Mammals

Factors:

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

mb_sample_id local_sample_id Cell line Treatment
SA241232S_16ClpP KO 0.1% DMSO
SA241233S_4ClpP KO 0.1% DMSO
SA241234S_10ClpP KO 0.1% DMSO
SA241235S_11ClpP KO 10 uM ONC201
SA241236S_5ClpP KO 10 uM ONC201
SA241237S_17ClpP KO 10 uM ONC201
SA241238S_18ClpP KO 150 nM TR57
SA241239S_12ClpP KO 150 nM TR57
SA241240S_6ClpP KO 150 nM TR57
SA241228SP_1_1- -
SA241229SP_1_2- -
SA241230SP_1_3- -
SA241231SP_1_4- -
SA241241S_7WT 0.1% DMSO
SA241242S_1WT 0.1% DMSO
SA241243S_13WT 0.1% DMSO
SA241244S_2WT 10 uM ONC201
SA241245S_8WT 10 uM ONC201
SA241246S_14WT 10 uM ONC201
SA241247S_3WT 150 nM TR57
SA241248S_9WT 150 nM TR57
SA241249S_15WT 150 nM TR57
Showing results 1 to 22 of 22

Collection:

Collection ID:CO002490
Collection Summary:The human triple-negative breast cancer (TNBC) cell line SUM159 was cultured in Dulbecco’s modified Eagle’s medium: Nutrient Mixture F-12 (DMEM/F-12, Gibco, 11330-032) supplemented with 5% fetal bovine serum (VWR-Seradigm, 97068-085), 1% antibiotic/antimycotic (ThermoFisher Scientific, 15240062), 5 μg/mL insulin (Gibco, 12585014), and 1 μg/mL hydrocortisone. CRISPRi was used to generate CLPP-knockout SUM159 cells. WT MDA-MB-231 cells were cultured in RPMI 1640 media (Gibco, 11875-093) supplemented with 10% FBS and 1% antibiotic/antimycotic. Cells were incubated at 5% CO2 and 37°C and periodically tested for mycoplasma.
Sample Type:Cultured cells

Treatment:

Treatment ID:TR002509
Treatment Summary:SUM159 (WT and ClpP-KO) cells were plated in a 10 cm2 dish (Corning) and allowed to adhere overnight. Cells were then treated with 0.1% DMSO, 10 μM ONC201, or 150 nM TR-57 for 24 hours.

Sample Preparation:

Sampleprep ID:SP002503
Sampleprep Summary:SUM159 (WT and ClpP-KO) cells were plated as described for proteomics analysis. Cells were washed 3 x 5 mL ice-cold DPBS. 1 mL -20°C acetonitrile and 750 μL ice cold H2O were added to washed plates and cells were mechanically scraped and transferred to 15 mL conical tubes and stored at -80°C until extraction was performed. To extract metabolites, ~five 2mm zirconia beads were added to each 15 mL conical followed by 500 μL chloroform (-20°C) and samples were vortexed 3 x 30 seconds. Samples were then centrifuged in a 4°C swing-bucket centrifuge (3,700g, 60 minutes). The aqueous layer was then transferred to a 2 mL Lo-Bind tube and the organic layer to a glass vial. Remaining samples were transferred to a 1.5 mL Lo-Bind tube and 15 mL conicals were washed with 300 μL 2:1 chloroform:methanol solution (-20°C) and transferred to corresponding 1.5 mL Lo-Bind tube and centrifuged at 4°C (15,000g, 20 minutes). Aqueous and organic layers were transferred to corresponding 2 mL Lo-Bind tube and glass vial for each sample and frozen at -80°C. Aqueous fractions of cell extracts were dried by speed vac and reconstituted using 200 μL of reconstitution solution (95:5 water:methanol), and 150 μL of the reconstituted extract was transferred to new tubes. An aliquot of 20 μL was taken from each extract and combined to make a total study pool (SP). All samples and the SP were centrifuged at 4 °C and 16,000 x g for 10 minutes, and the supernatants were transferred to LC-MS vials. An injection volume of 5 μL was used for LC-MS analysis.

Combined analysis:

Analysis ID AN003925
Analysis type MS
Chromatography type Reversed phase
Chromatography system Thermo Vanquish
Column Waters ACQUITY UPLC HSS T3 (100 x 2.1mm,1.8um)
MS Type ESI
MS instrument type Orbitrap
MS instrument name Thermo Q Exactive HF-X Orbitrap
Ion Mode POSITIVE
Units Normalized intensity

Chromatography:

Chromatography ID:CH002904
Instrument Name:Thermo Vanquish
Column Name:Waters ACQUITY UPLC HSS T3 (100 x 2.1mm,1.8um)
Column Temperature:50 ℃
Flow Gradient:Time(min) Flow Rate %A %B Curve 1. 0 0.4 99.0 1.0 5 2. 1.00 0.4 99.0 1.0 5 3. 16.00 0.4 1.0 99.0 5 4. 19.00 0.4 1.0 99.0 5 5. 19.50 0.4 99.0 1.0 5 6. 22.00 0.4 99.0 1.0 5
Flow Rate:0.4 mL/min
Solvent A:100% water; 0.1% formic acid
Solvent B:100% methanol; 0.1% formic acid
Chromatography Type:Reversed phase

MS:

MS ID:MS003663
Analysis ID:AN003925
Instrument Name:Thermo Q Exactive HF-X Orbitrap
Instrument Type:Orbitrap
MS Type:ESI
MS Comments:Metabolomics data were acquired on a Vanquish UHPLC system coupled to a Q Exactive™ HF-X Hybrid Quadrupole-Orbitrap Mass Spectrometer (Thermo Fisher Scientific, San Jose, CA). Metabolites were separated via an HSS T3 C18 column (2.1 × 100 mm, 1.7 µm, Waters Corporation) at 50 °C with binary mobile phase of water (A) and methanol (B), each containing 0.1% formic acid (v/v). The UHPLC linear gradient started from 2% B, and increased to 100% B in 16 min, then held for 4 min, with the flow rate at 400 µL/min. The untargeted data was acquired from 70 to 1050 m/z using the data-dependent acquisition mode. Method blanks and SP injections were placed after every 6 samples (n=3 each). Progenesis QI (version 2.1, Waters Corporation) was used for peak picking, alignment, and normalization. Background signals were filtered out by removing peaks with a fold change less than 3 in the total SP vs the blank injections. Samples were then normalized in Progenesis QI using the “normalize to all” feature. Coefficient of variation (CV) values were calculated across the total SP replicates for each peak and those with CV >30% were removed. Filtered, normalized data was exported and multivariate analysis was performed using SIMCA 16.
Ion Mode:POSITIVE
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