Summary of Study ST003194

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 PR001990. The data can be accessed directly via it's Project DOI: 10.21228/M8H14D 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	ST003194
Study Title	Multi-Omics Analysis Revealed Significant Metabolic Changes in Brain Cancer Cells Treated with Paclitaxel and/or Topotecan
Study Summary	Glioblastoma (GB) is the most common primary malignant brain tumor, representing approximately 57% of all gliomas and 48% of all primary malignant central nervous system (CNS) tumors. Despite the best standard therapies, glioblastoma survivors have a brief survival time, about 24 months on average. The treatment is troublesome because the cancer cells may not respond well to specific therapies as they grow within an extensive network of blood vessels. A multi-omics approach to provide information on biomolecules from multiple layers appears promising for systematically and holistically understanding complex biology. However, till now, only few studies have utilized omics analysis to investigate the impact of anticancer drugs on GBM. Our study aimed to evaluate the impacts of the anticancer medications (paclitaxel 5.3 μg/mL and topotecan 0.26 μM) solely and in pairwise combination on the metabolic and proteomic signatures of the U87 cell line while utilizing the accurate ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS) analytical technology. The studied cancer cells wear treated with DMSO (control group), paclitaxel 5.3 µM, topotecan 0.26 µM, and a combination of paclitaxel 5.3 µM and topotecan 0.26 µM. Using One-way ANOVA, we observed 14 significantly altered metabolites compared to those cells treated with DMSO. For combination treatment (paclitaxel and topotecan), 10 metabolites were significantly dysregulated. The sparse partial least squares-discriminant analysis (sPLS-DA) showed minimal overlapping, indicating a difference between the four groups. While for proteomics, a total of 79 proteins were significantly dysregulated among the groups. These findings can aid in identifying new biomarkers associated with the utilized drugs and creating a map for targeted therapy. EIF3F, GNB2L1, HINT2, and RPA3 were shown to be significantly upregulated in the combination group when compared to the control. Moreover, ribosome, apoptosis, HIF-1 signaling, arginine and proline, glutathione, purine metabolism, apelin signaling pathway, and glycolysis were significantly altered in the combination group.
Institute	Sharjah Institute for Medical Research
Last Name	Facility
First Name	Core
Address	M32, SIMR, College of Pharmacy, Health Sciences, University of Sharjah, Sharjah, UAE, Sharjah, 000, United Arab Emirates
Email	tims-tof@sharjah.ac.ae
Phone	+971 6 5057656
Submit Date	2024-04-30
Raw Data Available	Yes
Raw Data File Type(s)	d
Analysis Type Detail	LC-MS
Release Date	2024-11-01
Release Version	1

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Project:

Project ID:	PR001990
Project DOI:	doi: 10.21228/M8H14D
Project Title:	Multi-Omics Analysis Revealed Significant Metabolic Changes in Brain Cancer Cells Treated with Paclitaxel and/or Topotecan
Project Summary:	Glioblastoma (GB) is the most common primary malignant brain tumor, representing approximately 57% of all gliomas and 48% of all primary malignant central nervous system (CNS) tumors. Despite the best standard therapies, glioblastoma survivors have a brief survival time, about 24 months on average. The treatment is troublesome because the cancer cells may not respond well to specific therapies as they grow within an extensive network of blood vessels. A multi-omics approach to provide information on biomolecules from multiple layers appears promising for systematically and holistically understanding complex biology. However, till now, only few studies have utilized omics analysis to investigate the impact of anticancer drugs on GBM. Our study aimed to evaluate the impacts of the anticancer medications (paclitaxel 5.3 μg/mL and topotecan 0.26 μM) solely and in pairwise combination on the metabolic and proteomic signatures of the U87 cell line while utilizing the accurate ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS) analytical technology. The studied cancer cells wear treated with DMSO (control group), paclitaxel 5.3 µM, topotecan 0.26 µM, and a combination of paclitaxel 5.3 µM and topotecan 0.26 µM. Using One-way ANOVA, we observed 14 significantly altered metabolites compared to those cells treated with DMSO. For combination treatment (paclitaxel and topotecan), 10 metabolites were significantly dysregulated. The sparse partial least squares-discriminant analysis (sPLS-DA) showed minimal overlapping, indicating a difference between the four groups. While for proteomics, a total of 79 proteins were significantly dysregulated among the groups. These findings can aid in identifying new biomarkers associated with the utilized drugs and creating a map for targeted therapy. EIF3F, GNB2L1, HINT2, and RPA3 were shown to be significantly upregulated in the combination group when compared to the control. Moreover, ribosome, apoptosis, HIF-1 signaling, arginine and proline, glutathione, purine metabolism, apelin signaling pathway, and glycolysis were significantly altered in the combination group
Institute:	Sharjah Institute for Medical Research
Last Name:	Facility
First Name:	Core
Address:	M32, SIMR, College of Pharmacy, Health Sciences, University of Sharjah, Sharjah, UAE, Sharjah, 000, United Arab Emirates
Email:	tims-tof@sharjah.ac.ae
Phone:	+971 6 5057656

Subject:

Subject ID:	SU003313
Subject Type:	Cultured cells
Subject Species:	Homo sapiens
Taxonomy ID:	9606

Factors:

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

mb_sample_id	local_sample_id	Treatment	Sample source
SA347935	U87 A1-01-4711	DMSO	Brain Cancer cells
SA347936	U87 B1-02-4714	DMSO	Brain Cancer cells
SA347937	U87 B1-01-4713	DMSO	Brain Cancer cells
SA347938	U87 A1-02-4712	DMSO	Brain Cancer cells
SA347939	U87 A3-02-4720	Etoposide	Brain Cancer cells
SA347940	U87 B3-02-4722	Etoposide	Brain Cancer cells
SA347941	U87 B3-01-4721	Etoposide	Brain Cancer cells
SA347942	U87 A3-01-4719	Etoposide	Brain Cancer cells
SA347943	U87 B4-01-4725	Paclitaxel and etoposide	Brain Cancer cells
SA347944	U87 B4-02-4726	Paclitaxel and etoposide	Brain Cancer cells
SA347945	U87 A4-02-4724	Paclitaxel and etoposide	Brain Cancer cells
SA347946	U87 A4-01-4723	Paclitaxel and etoposide	Brain Cancer cells
SA347947	U87 A2-01-4715	Paclitaxel	Brain Cancer cells
SA347948	U87 B2-01-4717	Paclitaxel	Brain Cancer cells
SA347949	U87 A2-02-4716	Paclitaxel	Brain Cancer cells
SA347950	U87 B2-02-4718	Paclitaxel	Brain Cancer cells

Showing results 1 to 16 of 16

Showing results 1 to 16 of 16

Collection:

Collection ID:	CO003306
Collection Summary:	Since the U87 cell line is one of the most frequently used and thoroughly defined brain cancer cell lines, it was chosen as the in-vitro model for this study. This investigation used the DMEM medium supplemented with 10% fetal bovine serum and 1% penicillin/streptomycin to cultivate the U87 cell line as monolayers Sigma-Aldrich (Louis, USA). All cultures were grown at 37 °C in a humid environment with 5% CO2.
Sample Type:	Cultured brain cancer cells

Treatment:

Treatment ID:	TR003322
Treatment Summary:	For each treatment condition, every 75 cm2 tissue culture flask contained two million cells, which were then incubated for 24 hours. The cells were subsequently given a 24-hour treatment of paclitaxel 5.3 μM and/or topotecan 0.26 μM. According to cytotoxicity assay results, these doses correspond to the IC50 of these substances for the U87 cell line. The control group was Dimethyl sulfoxide (DMSO) at a 0.5% concentration for 24 hours. After the incubation period, cells were washed twice with phosphate-buffered saline solution (PBS) then collected by trypsinization and resuspended in 1 mL of the media for further analysis. Cells were then separated into pellets by centrifugation for 5 minutes at room temperature at 1300 rpm.

Treatment ID:

TR003322

Treatment Summary:

For each treatment condition, every 75 cm2 tissue culture flask contained two million cells, which were then incubated for 24 hours. The cells were subsequently given a 24-hour treatment of paclitaxel 5.3 μM and/or topotecan 0.26 μM. According to cytotoxicity assay results, these doses correspond to the IC50 of these substances for the U87 cell line. The control group was Dimethyl sulfoxide (DMSO) at a 0.5% concentration for 24 hours. After the incubation period, cells were washed twice with phosphate-buffered saline solution (PBS) then collected by trypsinization and resuspended in 1 mL of the media for further analysis. Cells were then separated into pellets by centrifugation for 5 minutes at room temperature at 1300 rpm.

Sample Preparation:

Sampleprep ID:	SP003320
Sampleprep Summary:	First, one tablet of protease inhibitor was prepared in 10 mL lysis buffer, and 400 μL of the mixture was added to each sample. Then the samples were rested for 10 minutes and transferred into 10 mL tubes, followed by vortex for 2 minutes and sonication using a COPLEY probe-sonicator (QSONICA SONICATOR, USA) for 30 seconds while utilizing a 30% amplifier in an ice bath. Next, the samples were transferred to Eppendorf tubes and centrifuged at 14000 rpm for 5 minutes. Next, the supernatant was transferred to the new Eppendorf, and 400 μL of methanol and 300 μL of chloroform were added to the supernatant. Then we vortexed the samples for 30 seconds and centrifuged them at 14000 rpm for 5 minutes. Afterward, a white disk appeared. Finally, we collected the upper layer into a new glass vial, added 300 μL of methanol to the bottom layer and white disk, and vortexed until the white disk was broken and precipitated. Then we centrifuged the samples at 14000 rpm for 3 minutes and transferred the supernatant to the previously prepared glass vials for metabolomics analysis using UHPLC-QTOF-MS.

Sampleprep ID:

SP003320

Sampleprep Summary:

First, one tablet of protease inhibitor was prepared in 10 mL lysis buffer, and 400 μL of the mixture was added to each sample. Then the samples were rested for 10 minutes and transferred into 10 mL tubes, followed by vortex for 2 minutes and sonication using a COPLEY probe-sonicator (QSONICA SONICATOR, USA) for 30 seconds while utilizing a 30% amplifier in an ice bath. Next, the samples were transferred to Eppendorf tubes and centrifuged at 14000 rpm for 5 minutes. Next, the supernatant was transferred to the new Eppendorf, and 400 μL of methanol and 300 μL of chloroform were added to the supernatant. Then we vortexed the samples for 30 seconds and centrifuged them at 14000 rpm for 5 minutes. Afterward, a white disk appeared. Finally, we collected the upper layer into a new glass vial, added 300 μL of methanol to the bottom layer and white disk, and vortexed until the white disk was broken and precipitated. Then we centrifuged the samples at 14000 rpm for 3 minutes and transferred the supernatant to the previously prepared glass vials for metabolomics analysis using UHPLC-QTOF-MS.

Combined analysis:

Analysis ID	AN005242
Analysis type	MS
Chromatography type	Reversed phase
Chromatography system	Bruker Elute
Column	Bruker Hamilton Intensity Solo 2 C18 (100 x 2.1mm, 1.8um)
MS Type	ESI
MS instrument type	QTOF
MS instrument name	Bruker timsTOF
Ion Mode	POSITIVE
Units	AU

Chromatography:

Chromatography ID:	CH003969
Chromatography Summary:	Elute UHPLC, Hamilton® Intensity Solo 2 C18 column (100 mm × 2.1 mm, 1.8 um beads), autosampler (Elute UHPLC), solvent delivery pump (HPG 1300) were utilized to separate and detect the metabolites and peptides using inline reversed-phase chromatography with solvent A 0.1% formic acid in HPLC grade water and solvent B 0.1% formic acid in ACN. in the cells (Bruker, Bremen, Germany). The metabolomics samples were injected twice and eluted using a 30-min gradient as follows: 1% ACN for 2 minutes, ramping to 99% ACN for 15 minutes, retained at 99% ACN for 3 minutes, then re-equilibration to 1% ACN for ten minutes.
Instrument Name:	Bruker Elute
Column Name:	Bruker Hamilton Intensity Solo 2 C18 (100 x 2.1mm, 1.8um)
Column Temperature:	35°C
Flow Gradient:	0-2.0 min, 1% B; 2.0-17.0 min, 1-99% B; 17.0-20.0 min, 99% B; 20.0-30.0 min, 99-1% B
Flow Rate:	For elution, the flow rate was 250 L/min, and for re-equilibration, it was 350 L/min. A 10 L/min flow of drying gas
Solvent A:	100% Water; 0.1% Formic Acid
Solvent B:	100% Acetonitrile; 0.1% Formic Acid
Chromatography Type:	Reversed phase

MS:

MS ID:	MS004975
Analysis ID:	AN005242
Instrument Name:	Bruker timsTOF
Instrument Type:	QTOF
MS Type:	ESI
MS Comments:	The data was processed using MetaboScape® 4.0 software (Bruker, Bremen, Germany) [19]. In the T-ReX 2D/3D workflow, the following settings were applied to molecular feature detection: a minimum intensity threshold of 1,000 counts, a maximum peak duration of seven spectra, and a maximum peak area. The mass recalibration was completed within a retention time range of 0 to 0.3 minutes. Only features found in at six four of the 24 samples (per cell type) were considered. Similarly, the MS/MS import method was set to be averaged. Accordingly, we assigned the following bucketing parameters to the data: retention duration of 0.3 to 25 minutes and mass range of 50 to 1,000 m/z. For accurate identification, the following standards were set up: Initially unknown compounds from QTOF MS data were characterized using MS/MS spectra and retention time (RT). The Human Metabolome Database (HMDB) 4.0, a database of annotated metabolomics resources, spectrum library, was used to annotate compounds that made it past the screening and exhibited MS/MS or MS/MS in conjunction with RT [20]. This collection served as a benchmark against which all finally chosen chemicals were evaluated. To determine which metabolites were present, we mapped MS/MS spectra and retention durations using the HMDB 4.0. When multiple features matched a single database entry, the metabolites were filtered by selecting the entry of each metabolite with the highest annotation quality score (AQ score), i.e. the best fit with the most factors including retention time, MS/MS, m/z values, analyte list, msigma, and spectral library. Furthermore, for analysis, metabolite data was saved as CSV files and integrated into the complete metabolomics platform MetaboAnalyst 5.0 software (https://www.metaboanalyst.ca) [21]. For each medication, two-tailed independent student t-tests were employed to identify significantly different metabolites from DMSO. For each condition, a volcano plot illustrating statistical significance and fold change for cellular metabolite dysregulation was created. Through the use of a one-way analysis of variance, many groups were compared (ANOVA). The threshold for significance was fixed at p <0.05. Using the software MetaboAnalyst 5.0, the Principal Component Analysis (PCA) was also performed to compare the two groups. The false discovery rate was used to eliminate false positives and fix multiple hypothesis testing (FDR). Enrichment analysis, joint pathway analysis, and heatmaps were also created using MetaboAnalyst.
Ion Mode:	POSITIVE