Summary of Study ST003134
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 PR001947. The data can be accessed directly via it's Project DOI: 10.21228/M82431 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 | ST003134 |
| Study Title | Targeting SOX13 inhibits the assembly of respiratory chain supercomplexes to overcome ferroptosis-resistance in gastric cancer |
| Study Summary | Therapeutic resistance represents a bottleneck to treatment in advanced gastric cancer (GC). Ferroptosis is an iron-dependent form of non-apoptotic cell death and is associated with anti-cancer therapeutic efficacy. Further investigations are required to clarify the underlying mechanisms. Ferroptosis-resistant GC cell lines are constructed. Dysregulated mRNAs between ferroptosis-resistant and parental cell lines are identified. The expression of SOX13/SCAF1 is manipulated in GC cell lines where relevant biological and molecular analyses are performed. Molecular docking and computational screening are performed to screen potential inhibitors of SOX13. We show that SOX13 boosts protein remodeling of electron transport chain (ETC) complexes by directly transactivating SCAF1. This leads to increased supercomplexes (SCs) assembly, mitochondrial respiration, mitochondrial energetics and chemo- and immune-resistance. Zanamivir, reverts the ferroptosis-resistant phenotype via directly targeting SOX13 and promoting TRIM25-mediated ubiquitination and degradation of SOX13. Here we show, SOX13/SCAF1 are important in ferroptosis-resistance, and targeting SOX13 with zanamivir has therapeutic potential. We conducted untargeted metabolomic analysis of Erastin-resis SNU-668 cells transfected with shRNA-SOX13 or shRNA-NC. |
| Institute | Fudan University Shanghai Cancer Center |
| Last Name | Ma |
| First Name | Mingzhe |
| Address | lingling road, xuhui district, shanghai, China |
| mmz666@163.com, ding@bioinformatics.com.cn | |
| Phone | 13917006049 |
| Submit Date | 2024-03-20 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | raw(Thermo) |
| Analysis Type Detail | LC-MS |
| Release Date | 2024-04-12 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Combined analysis:
| Analysis ID | AN005144 |
|---|---|
| Analysis type | MS |
| Chromatography type | Reversed phase |
| Chromatography system | Agilent 1260 |
| Column | Waters ACQUITY UPLC BEH Amide (100 x 2.1mm,1.7um) |
| MS Type | ESI |
| MS instrument type | Orbitrap |
| MS instrument name | Thermo Q Exactive Orbitrap |
| Ion Mode | POSITIVE |
| Units | m/z |
MS:
| MS ID: | MS004880 |
| Analysis ID: | AN005144 |
| Instrument Name: | Thermo Q Exactive Orbitrap |
| Instrument Type: | Orbitrap |
| MS Type: | ESI |
| MS Comments: | MS analysis was carried out on the Q-Exactive MS/MS in both positive and negative ion modes. 1) Set the relevant tuning parameters for the probe as listed: aux gas heater temperature, 400 °C; sheath gas, 40; auxiliary gas, 13; spray voltage, 3.5 kV for positive mode and negative mode. Set the capillary temperature at 350 °C, and S-lens at 55. 2) Build a DDA method as follows: Full scan range: 60 to 900 (m/z); resolution for MS1 and ddMS2: 70,000 and 17,500 respectively; maximum injection time for MS1 and ddMS2: 100 ms and 45 ms; automatic gain control (AGC) for MS1 and ddMS2: 3e6 and 2e5; isolation window: 1.6 m/z; normalized collision energies (NCE): 10, 17, 25 or 30, 40, 50. 3) Build a full scan method as follows: Full scan range: 60 to 900 (m/z); resolution: 140,000; maximum injection time: 100ms; automatic gain control (AGC): 3e6 ions. Raw files were submitted to Thermo Compound Discover 2.1, (CD), and processed with Untargeted Metabolomics workflow with minor modification to find and identify the differences between samples: Performs retention time alignment, unknown compound detection, and compound grouping across all samples. Predicts elemental compositions for all compounds, fills gaps across all sam ples, and hides chemical background (using Blank samples). Identifies compounds using mzCloud (ddMS2) and ChemSpider (formula or exact mass). Also performs similarity search for all com pounds with ddMS2 data using mzCloud. Maps compounds to biological pathways using KEGG database For retention time alignment, the max time shift was 2 mins, and a tolerance of 0.5 min was used for grouping unknown compounds. Mass tolerance were set as 10 ppm for feature detection and 5 ppm for compound annotation. The exact mass of each feature was submitted to ChemSpider with 4 databases selected (BioCyc; Human Metabolome Database; KEGG; LipidMAPS). Results from Compound Discover, the compound table, was exported as .xsls file, and then analysed with R. |
| Ion Mode: | POSITIVE |
| Analysis Protocol File: | FUSCC_methods.pdf |
