Summary of Study ST003201

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 PR001995. The data can be accessed directly via it's Project DOI: 10.21228/M8VB2V 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	ST003201
Study Title	Molecular signatures of xenograft colon cancer models treated with topotecan: A Mass Spectrometry-Based Study
Study Summary	Colorectal cancer (CRC) is one of the most common cancers worldwide. Despite improvement in standardized screening methods and the development of promising therapies, the 5-year survival rates are as low as 10% in the metastatic setting. Metabolomics, the study of metabolites on a large scale, has provided new insight into disease diagnosis and biomarkers identification. We chose topotecan as an anti-cancer drug in this context because, as far as we know, there are no studies examining the effect of this anti-cancer drug on metabolic alterations in CRC. In this study, untargeted metabolomic analysis study was performed to compare between four animal groups; HCT-116 xenograft models treated with topotecan, untreated HCT-116 xenograft models (vehicle controls), positive controls, and negative controls, using UHPLC-ESIQTOF-MS platform. One way ANOVA analysis discovered 53 statistically significant metabolites among all four groups (p <0.05). T-test revealed that 15 metabolites were statistically significant among vehicle controls and negative controls. Also, 20 metabolites were statistically significant among the potential respondersto topotecan and the vehicle controls. In addition, only 1 metabolite was statistically significant among the positive and negative control. Ultimately, by analyzing metabolomic profiles, our findings can create a map that can be utilized to assess the anticancer activity of topotecan in CRC. More studies with larger number of models are needed to verify the implication of the significantly altered metabolites and metabolic pathways in diagnosing and treating CRC.
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	2024-05-13
Raw Data Available	Yes
Raw Data File Type(s)	d
Analysis Type Detail	LC-MS
Release Date	2024-06-04
Release Version	1

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Project:

Project ID:	PR001995
Project DOI:	doi: 10.21228/M8VB2V
Project Title:	Molecular signatures of xenograft colon cancer models treated with topotecan: A Mass Spectrometry-Based Study
Project Summary:	Prostate cancer poses a significant health risk, ranking as the second most common cancer among men in the United States. However, the effectiveness of current anti-prostate cancer drugs is limited due to increasing drug resistance and side effects. Consequently, there is a pressing need to develop new compounds and identify novel drug targets that can surpass these limitations. Due to their targeted mechanism, DNA minor groove binders (MGBs) are becoming more popular as a relatively safe and effective alternative. In our research, we employed multi-omics techniques to investigate the mechanism of action of a novel MGB compound (MGB4) through LC-MS/MS-based untargeted metabolomics combined with discovery proteomics analysis performed on LNCaP cells, which were treated with MGB4, doxorubicin, or a combination of both compounds. Through a one-way ANOVA test with a significance level of p-value < 0.05, we identified 99 metabolites and 1143 proteins associated with the treatments. Our findings indicate that treating LNCaP cells with doxorubicin or the MGB4 lead compound yielded similar effects, albeit not identical, on the cells. Both compounds deactivated the translation pathway in the cells. Furthermore, we observed alterations in sphingolipid and amino acid metabolic pathways, potentially contributing to the suppression of prostate cancer cell proliferation and division. Additionally, doxorubicin and combined treatments resulted in reduced metabolism of spermine and spermidine, likely stemming from decreased protein synthesis of key enzymes involved in their pathways. Moreover, the combined treatment exhibited a synergistic interaction between the two compounds, leading to altered purine metabolism and a more pronounced reduction in metabolite abundance compared to individual treatments. Overall, our study demonstrates the robustness of the multi-omics approach in elucidating the mechanism of action of promising drug candidates. It also suggests that MGB4 shows potential as a candidate for prostate cancer treatment.
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:	SU003320
Subject Type:	Mammal
Subject Species:	Mus musculus
Taxonomy ID:	10090
Gender:	Male
Species Group:	Mammals

Factors:

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

mb_sample_id	local_sample_id	Sample source	Group
SA348633	C5A2-02-8828	Blood Serum	Negative Control
SA348634	C5A2-01-8827	Blood Serum	Negative Control
SA348635	C5A1-02-8826	Blood Serum	Negative Control
SA348636	C5A3-02-8831	Blood Serum	Negative Control
SA348637	C5A4-02-8833	Blood Serum	Negative Control
SA348638	C5A5-02-8835	Blood Serum	Negative Control
SA348639	C5A5-01-8834	Blood Serum	Negative Control
SA348640	C5A1-01-8825	Blood Serum	Negative Control
SA348641	C5A4-01-8832	Blood Serum	Negative Control
SA348642	C5A3-01-8830	Blood Serum	Negative Control
SA348643	C4A1-01-8819	Blood Serum	Nonresponders
SA348644	C3A3-02-8816	Blood Serum	Nonresponders
SA348645	C3A1-02-8811	Blood Serum	Nonresponders
SA348646	C3A1-01-8810	Blood Serum	Nonresponders
SA348647	C4A2-02-8822	Blood Serum	Nonresponders
SA348648	C3A3-01-8815	Blood Serum	Nonresponders
SA348649	C6A2-02-8839	Blood Serum	Positive Control
SA348650	C6A2-01-8838	Blood Serum	Positive Control
SA348651	C6A1-02-8837	Blood Serum	Positive Control
SA348652	C6A3-01-8840	Blood Serum	Positive Control
SA348653	C6A3-02-8841	Blood Serum	Positive Control
SA348654	C6A4-02-8843	Blood Serum	Positive Control
SA348655	C6A4-01-8842	Blood Serum	Positive Control
SA348656	C6A1-01-8836	Blood Serum	Positive Control
SA348657	C6A5-02-8845	Blood Serum	Positive Control
SA348658	C6A5-01-8844	Blood Serum	Positive Control
SA348659	C4A2-01-8821	Blood Serum	Responders
SA348660	C4A3-01-8823	Blood Serum	Responders
SA348661	C3A2-01-8812	Blood Serum	Responders
SA348662	C3A2-02-8813	Blood Serum	Responders
SA348663	C4A1-02-8820	Blood Serum	Responders
SA348664	C3A4-01-8817	Blood Serum	Responders
SA348665	C3A4-02-8818	Blood Serum	Responders
SA348666	C4A3-02-8824	Blood Serum	Responders
SA348667	C1A1-02-8801	Blood Serum	Vehicle Control
SA348668	C1A2-01-8802	Blood Serum	Vehicle Control
SA348669	C2A1-02-8807	Blood Serum	Vehicle Control
SA348670	C2A2-01-8808	Blood Serum	Vehicle Control
SA348671	C2A2-02-8809	Blood Serum	Vehicle Control
SA348672	C1A1-01-8800	Blood Serum	Vehicle Control
SA348673	C2A1-01-8806	Blood Serum	Vehicle Control
SA348674	C1A3-01-8804	Blood Serum	Vehicle Control
SA348675	C1A3-02-8805	Blood Serum	Vehicle Control
SA348676	C1A2-02-8803	Blood Serum	Vehicle Control

Showing results 1 to 44 of 44

Showing results 1 to 44 of 44

Collection:

Collection ID:	CO003313
Collection Summary:	After 7-8 weeks from the beginning of the experiment, all mice were sacrificed for blood and tissues collection. First, mice were anaesthetized with inhalational anesthesia using 3% isoflurane for induction and 2% isoflurane for maintenance in a desiccator. Then, by puncturing the heart, blood was immediately collected in an Eppendorf tube, then centrifuged at 14000 RPM for 15 minutes to collect serum
Sample Type:	Blood (serum)
Storage Conditions:	-80℃

Treatment:

Treatment ID:	TR003329
Treatment Summary:	Topotecan hydrochloride hydrate (C23H26ClN3O6). HCl. H2O purchased from Sigma-Aldrich was kindly provided by Drug Design and Discovery research group. Based on literature, the administration schedule can significantly affect the pharmacodynamic effects of topotecan (efficacy and toxicity). It was found in a previous study that topotecan activity was at its optimum when administered at 0.625 mg/kg/day (d × 5) for 4 consecutive weeks schedule for ovarian carcinoma xenografts (Guichard et al., 2001). So, this dosing schedule was used in our study. 37 Omni calculator (Omni Calculator, n.d.) was used to calculate the required total daily dose to be administered to each mouse using animal weights. An average weight of 27 g was used to calculate the daily dose to be injected (0.016875 mg/mouse). This amount was multiplied by the number of animals that will be injected with the topotecan (12 animals), and by the number of days (20 days), the total needed amount was 4.05 mg. Topotecan was dissolved in 2% DMSO as an organic solvent, and 98% PBS, vortexed for 60 seconds, divided into 20 Eppendorf tubes and stored in the -80 °C, each tube for one day, for 12 animals (7 xenograft models and 5 positive controls), throughout the 20 days of treatment.

Treatment ID:

TR003329

Treatment Summary:

Topotecan hydrochloride hydrate (C23H26ClN3O6). HCl. H2O purchased from Sigma-Aldrich was kindly provided by Drug Design and Discovery research group. Based on literature, the administration schedule can significantly affect the pharmacodynamic effects of topotecan (efficacy and toxicity). It was found in a previous study that topotecan activity was at its optimum when administered at 0.625 mg/kg/day (d × 5) for 4 consecutive weeks schedule for ovarian carcinoma xenografts (Guichard et al., 2001). So, this dosing schedule was used in our study. 37 Omni calculator (Omni Calculator, n.d.) was used to calculate the required total daily dose to be administered to each mouse using animal weights. An average weight of 27 g was used to calculate the daily dose to be injected (0.016875 mg/mouse). This amount was multiplied by the number of animals that will be injected with the topotecan (12 animals), and by the number of days (20 days), the total needed amount was 4.05 mg. Topotecan was dissolved in 2% DMSO as an organic solvent, and 98% PBS, vortexed for 60 seconds, divided into 20 Eppendorf tubes and stored in the -80 °C, each tube for one day, for 12 animals (7 xenograft models and 5 positive controls), throughout the 20 days of treatment.

Sample Preparation:

Sampleprep ID:	SP003327
Sampleprep Summary:	100 µL o f each serum sample was added into Eppendorf tube, 300 µL of methanol (Wunstorfer Strasse, Seelze, Germany) was added to it, followed by vortex and incubation at - 20 °C for 2 hours. Next, samples were vortexed and then centrifuged at 14000 RPM for 15 minutes. Then, the supernatant was evaporated using speed vacuum evaporation at 35 - 40°C. Extract samples were then resuspended with 200 µL of 0.1% formic acid in Deionized Water-LC-MS CHROMASOLV from Honeywell (Wunstorfer Strasse, Seelze, Germany). Formic acid helps in dissolving the metabolites and donating a proton because the analysis was done in the positive ionization mode. Then, the supernatant was filtered using a 0.45 µm pore size hydrophilic nylon syringe filter for LC-MS/MS analysis and collected in an insert within LC glass vials.

Sampleprep ID:

SP003327

Sampleprep Summary:

100 µL o f each serum sample was added into Eppendorf tube, 300 µL of methanol (Wunstorfer Strasse, Seelze, Germany) was added to it, followed by vortex and incubation at - 20 °C for 2 hours. Next, samples were vortexed and then centrifuged at 14000 RPM for 15 minutes. Then, the supernatant was evaporated using speed vacuum evaporation at 35 - 40°C. Extract samples were then resuspended with 200 µL of 0.1% formic acid in Deionized Water-LC-MS CHROMASOLV from Honeywell (Wunstorfer Strasse, Seelze, Germany). Formic acid helps in dissolving the metabolites and donating a proton because the analysis was done in the positive ionization mode. Then, the supernatant was filtered using a 0.45 µm pore size hydrophilic nylon syringe filter for LC-MS/MS analysis and collected in an insert within LC glass vials.

Combined analysis:

Analysis ID	AN005251
Analysis type	MS
Chromatography type	Reversed phase
Chromatography system	Bruker Elute
Column	Hamilton Intensity Solo 2 C18 (100 x 2.1 mm, 1.8 um)
MS Type	ESI
MS instrument type	QTOF
MS instrument name	Bruker timsTOF
Ion Mode	POSITIVE
Units	AU

Chromatography:

Chromatography ID:	CH003976
Chromatography Summary:	Samples were chromatographically separated by inline reversed-phase chromatography using the Elute HPG 1300 pumps and Elute Autosampler (Bruker, Darmstadt, Germany) with solvent A 0.1% FA in HPLC grade water and solvent B 0.1% FA in ACN. A Hamilton Intensity Solo 2 C18 column (100 mm x 2.1 mm, 1.8µm beads) was maintained at 35C. For metabolomics, 10 µL was injected twice for each sample and eluted using a 30-minute gradient as follows: 1% ACN was held for 2 minutes, ramping to 99% ACN over 15 minutes, held at 99% ACN for 3 minutes before re-equilibrating to 1% ACN for 10 minutes. Flow rates were 250 µL/min for elution and 350 µL/min for re-equilibration.
Instrument Name:	Bruker Elute
Column Name:	Hamilton Intensity Solo 2 C18 (100 x 2.1 mm, 1.8 um)
Column Temperature:	35
Flow Gradient:	1%B to 99%B in 15 min
Flow Rate:	250 uL/min
Solvent A:	100% water; 0.1% formic acid
Solvent B:	100% acetonitrile; 0.1% formic acid
Chromatography Type:	Reversed phase

MS:

MS ID:	MS004984
Analysis ID:	AN005251
Instrument Name:	Bruker timsTOF
Instrument Type:	QTOF
MS Type:	ESI
MS Comments:	The MS analysis was performed using a TimsTOF (Bruker, Darmstadt, Germany) with Apollo II electrospray ionization (ESI) source. The drying gas was set to flow at 10 L/min and the drying temperature to 220C and the nebulizer pressure to 2.2 bar. The capillary voltage was 4500 V and the end plate offset 500V. For metabolomics the scan range was 20-1300 m/z. The collision energy was set to 20 eV, the cycle time to 0.5 seconds with a relative minimum intensity threshold of 400 counts per thousand and target intensity of 20,000. Sodium formate was injected as an external calibrant in the first 0.3 minutes of each LC-MS/MS run. MetaboScape 4.0 software was used for metabolite processing and statistical analysis (Bruker Daltonics). The following parameters for molecular feature identification and "bucketing" were set in the T-ReX 2D/3D workflow: For peak detection, a minimum intensity threshold of 1,000 counts is required, as well as a minimum peak duration of 7 spectra, with feature quantification determine using peak area. The file masses were recalibrated based on the external calibrant injected between 0-0.3 min.
Ion Mode:	POSITIVE