Summary of Study ST004280

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 PR002704. The data can be accessed directly via it's Project DOI: 10.21228/M84K1C 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	ST004280
Study Title	Exploring the Impact of Doxorubicin and Paclitaxel on HCT-116 Cancer Cells: A Comprehensive Multi-Omics Analysis Using Mass Spectrometry
Study Summary	Background: Colorectal cancer is the second leading cause of cancer-related mortality worldwide and ranks as the third most prevalent cancer in the United Arab Emirates. CRC presents a formidable challenge due to its high metastatic potential and limited treatment options. This study investigates the effects of paclitaxel and doxorubicin on the HCT-116 cancer cell line, utilizing a multi-omics approach to identify molecular alterations induced by these treatments. Methodology: Metabolomics and proteomics analysis were employed on HCT-116 cells treated with paclitaxel, doxorubicin, and a combination of both agents. Analyses were conducted using TIMS-QTOF-UHPLC-MS, with four biological replicates per treatment condition. Results: Following a two-tailed independent Student’s t-test with q-value <0.05, paclitaxel treatment yielded 9 altered metabolites and 46 dysregulated proteins, while doxorubicin treatment resulted in 9 metabolites and 238 dysregulated proteins. The combination therapy led to the dysregulation of 19 metabolites and 308 proteins. Enrichment analysis highlighted significant effects on purine metabolism by both treatments, with doxorubicin also impacting citric acid and gluconeogenesis pathways. Paclitaxel uniquely influenced spermidine and spermine biosynthesis, whereas combined treatment showed an additive impact on amino acid metabolism, including alterations in aspartate, proline, and arginine pathways. Both compounds were observed to deactivate RNA processing, translation, and ribosome biogenesis, effectively impairing protein synthesis and reducing cancer cell proliferation and survival. Conclusion: Paclitaxel and doxorubicin induce distinct metabolic and proteomic alterations in CRC cells, impacting critical pathways for cancer survival. Combined therapy offers enhanced disruption of amino acid metabolism, highlighting its potential for improved therapeutic efficacy in CRC 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
Submit Date	2025-09-25
Raw Data Available	Yes
Raw Data File Type(s)	mzML, d
Analysis Type Detail	LC-MS
Release Date	2025-11-03
Release Version	1

Select appropriate tab below to view additional metadata details:

Project:

Project ID:	PR002704
Project DOI:	doi: 10.21228/M84K1C
Project Title:	Exploring the Impact of Doxorubicin and Paclitaxel on HCT-116 Cancer Cells: A Comprehensive Multi-Omics Analysis Using Mass Spectrometry
Project Summary:	Background: Colorectal cancer is the second leading cause of cancer-related mortality worldwide and ranks as the third most prevalent cancer in the United Arab Emirates. CRC presents a formidable challenge due to its high metastatic potential and limited treatment options. This study investigates the effects of paclitaxel and doxorubicin on the HCT-116 cancer cell line, utilizing a multi-omics approach to identify molecular alterations induced by these treatments. Methodology: Metabolomics and proteomics analysis were employed on HCT-116 cells treated with paclitaxel, doxorubicin, and a combination of both agents. Analyses were conducted using TIMS-QTOF-UHPLC-MS, with four biological replicates per treatment condition. Results: Following a two-tailed independent Student’s t-test with q-value <0.05, paclitaxel treatment yielded 9 altered metabolites and 46 dysregulated proteins, while doxorubicin treatment resulted in 9 metabolites and 238 dysregulated proteins. The combination therapy led to the dysregulation of 19 metabolites and 308 proteins. Enrichment analysis highlighted significant effects on purine metabolism by both treatments, with doxorubicin also impacting citric acid and gluconeogenesis pathways. Paclitaxel uniquely influenced spermidine and spermine biosynthesis, whereas combined treatment showed an additive impact on amino acid metabolism, including alterations in aspartate, proline, and arginine pathways. Both compounds were observed to deactivate RNA processing, translation, and ribosome biogenesis, effectively impairing protein synthesis and reducing cancer cell proliferation and survival. Conclusion: Paclitaxel and doxorubicin induce distinct metabolic and proteomic alterations in CRC cells, impacting critical pathways for cancer survival. Combined therapy offers enhanced disruption of amino acid metabolism, highlighting its potential for improved therapeutic efficacy in CRC 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:	SU004433
Subject Type:	Cultured cells
Subject Species:	Homo sapiens
Taxonomy ID:	9606
Gender:	Male

Factors:

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

mb_sample_id	local_sample_id	Treatment	Sample source
SA498294	PD04-02-14313	Combined	HCT cell line-Colon
SA498295	PD04-01-14312	Combined	HCT cell line-Colon
SA498296	PD03-02-14311	Combined	HCT cell line-Colon
SA498297	PD03-01-14310	Combined	HCT cell line-Colon
SA498298	PD02-02-14309	Combined	HCT cell line-Colon
SA498299	PD02-01-14308	Combined	HCT cell line-Colon
SA498300	PD01-02-14307	Combined	HCT cell line-Colon
SA498301	PD01-01-14306	Combined	HCT cell line-Colon
SA498302	C01-02-14279	Control	HCT cell line-Colon
SA498303	C01-01-14278	Control	HCT cell line-Colon
SA498304	C02-01-14280	Control	HCT cell line-Colon
SA498305	C02-02-14281	Control	HCT cell line-Colon
SA498306	C03-01-14288	Control	HCT cell line-Colon
SA498307	C03-02-14283	Control	HCT cell line-Colon
SA498308	C04-01-14286	Control	HCT cell line-Colon
SA498309	C04-02-14287	Control	HCT cell line-Colon
SA498310	D02-02-14301	Doxorubicin	HCT cell line-Colon
SA498311	D01-01-14298	Doxorubicin	HCT cell line-Colon
SA498312	D03-02-14303	Doxorubicin	HCT cell line-Colon
SA498313	D04-01-14304	Doxorubicin	HCT cell line-Colon
SA498314	D04-02-14305	Doxorubicin	HCT cell line-Colon
SA498315	D02-01-14300	Doxorubicin	HCT cell line-Colon
SA498316	D03-01-14302	Doxorubicin	HCT cell line-Colon
SA498317	D01-02-14299	Doxorubicin	HCT cell line-Colon
SA498318	P04-01-14295	Paclitaxel	HCT cell line-Colon
SA498319	P04-02-14296	Paclitaxel	HCT cell line-Colon
SA498320	P03-02-14294	Paclitaxel	HCT cell line-Colon
SA498321	P03-01-14293	Paclitaxel	HCT cell line-Colon
SA498322	P02-02-14292	Paclitaxel	HCT cell line-Colon
SA498323	P02-01-14291	Paclitaxel	HCT cell line-Colon
SA498324	P01-02-14290	Paclitaxel	HCT cell line-Colon
SA498325	P01-01-14289	Paclitaxel	HCT cell line-Colon

Showing results 1 to 32 of 32

Showing results 1 to 32 of 32

Collection:

Collection ID:	CO004426
Collection Summary:	The HCT-116 human colorectal cancer cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 Medium, supplemented with 10 % fetal bovine serum (FBS) from Sigma Aldrich, Germany. The growth media RPMI/FBS was further enriched with a 1 % combination of penicillin and streptomycin antibiotics. The cells were cultured in a humidified incubator at 37 °C and 5 % CO2.
Sample Type:	Colon
Storage Conditions:	-80℃

Treatment:

Treatment ID:	TR004442
Treatment Summary:	Four biological replicates were prepared for each treatment condition (DOX, PTX, combination therapy, and control) using T75 cm² flasks. Approximately 2×106 HCT-116 cells were seeded per replicate, ensuring uniformity across samples. Treatments were administered individually with DOX or PTX, or in combination, using the IC50 concentrations reported in the literature. The cells were incubated for 24 hours under standardized conditions to maintain consistency. Post-treatment, cells were washed twice with phosphate-buffered saline (PBS) to remove residual media and compounds. Trypsinization was performed to detach the cells, which were then centrifuged at 1200 rpm for 10 min at room temperature. The resulting cell pellets were collected and stored at -80°C for downstream analyses. To minimize variability, all samples were processed simultaneously, and identical experimental conditions were maintained throughout the study.

Treatment ID:

TR004442

Treatment Summary:

Four biological replicates were prepared for each treatment condition (DOX, PTX, combination therapy, and control) using T75 cm² flasks. Approximately 2×106 HCT-116 cells were seeded per replicate, ensuring uniformity across samples. Treatments were administered individually with DOX or PTX, or in combination, using the IC50 concentrations reported in the literature. The cells were incubated for 24 hours under standardized conditions to maintain consistency. Post-treatment, cells were washed twice with phosphate-buffered saline (PBS) to remove residual media and compounds. Trypsinization was performed to detach the cells, which were then centrifuged at 1200 rpm for 10 min at room temperature. The resulting cell pellets were collected and stored at -80°C for downstream analyses. To minimize variability, all samples were processed simultaneously, and identical experimental conditions were maintained throughout the study.

Sample Preparation:

Sampleprep ID:	SP004439
Sampleprep Summary:	We employed a biphasic extraction method using methanol and chloroform for simultaneous proteome and metabolome from a single sample aliquot. 400 µL mixture containing a lysis buffer with protease inhibitor was added for each sample. After a 10-min rest, the samples were vortexed for 2–4 min and sonicated with a COPLEY probe-sonicator for 30 s at a 30 % amplifier. The samples were then centrifuged for 5 min at 14,000 rpm. The resulting supernatant was transferred to another Eppendorf tube, to which we added 400 µL of methanol and 300 µL of chloroform. Two layers containing metabolites were obtained following a 30 s vortex and a subsequent 5 min centrifugation at 14,000 rpm. After transferring the upper layer of each sample to glass vials, we added 400 µL of methanol, followed by vortexing and centrifugation. The remaining supernatant was then transferred to the initial glass vials used for the drying step, while the remaining protein pellets were air-dried for proteomics. The dried metabolomics samples were resuspended in 200 µL (0.1 % formic acid in water) and injected after filtration into HPLC for analysis by Q-TOF MS.

Sampleprep ID:

SP004439

Sampleprep Summary:

We employed a biphasic extraction method using methanol and chloroform for simultaneous proteome and metabolome from a single sample aliquot. 400 µL mixture containing a lysis buffer with protease inhibitor was added for each sample. After a 10-min rest, the samples were vortexed for 2–4 min and sonicated with a COPLEY probe-sonicator for 30 s at a 30 % amplifier. The samples were then centrifuged for 5 min at 14,000 rpm. The resulting supernatant was transferred to another Eppendorf tube, to which we added 400 µL of methanol and 300 µL of chloroform. Two layers containing metabolites were obtained following a 30 s vortex and a subsequent 5 min centrifugation at 14,000 rpm. After transferring the upper layer of each sample to glass vials, we added 400 µL of methanol, followed by vortexing and centrifugation. The remaining supernatant was then transferred to the initial glass vials used for the drying step, while the remaining protein pellets were air-dried for proteomics. The dried metabolomics samples were resuspended in 200 µL (0.1 % formic acid in water) and injected after filtration into HPLC for analysis by Q-TOF MS.

Combined analysis:

Analysis ID	AN007119
Chromatography ID	CH005409
MS ID	MS006815
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:	CH005409
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:	MS006815
Analysis ID:	AN007119
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