Summary of Study ST002248

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 PR001436. The data can be accessed directly via it's Project DOI: 10.21228/M83Q6B 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.

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Study IDST002248
Study TitleQuantitative multi-Omics analysis of paclitaxel-loaded Poly(lactide-co-glycolide) nanoparticles for identification of potential biomarkers for head and neck cancer
Study SummaryThe narrow therapeutic index and significant potential for toxicity of chemotherapeutic drugs are two of the factors that restrict their use. Because of the usage of nanoparticles (NPs) as carriers for chemotherapeutic agents, the therapeutic efficacy of these treatments has been significantly boosted. This was accomplished by increasing the bioavailability of the pharmaceuticals and changing the bio-distribution profile of the drugs. Untargeted metabolomics has recently risen to the forefront as a potentially useful method for better comprehending the growth of tumours and the treatment outcomes of many kinds of cancer cells. In the current study, we used LCMS/MS-based untargeted metabolomics to identify differences in the metabolic profile of head and neck squamous cell carcinomas FaDu that were treated with the anticancer drug paclitaxel (PTX) delivered as free drug versus paclitaxel-loaded poly(lactide-co-glycolide) nanoparticles (PXT-PLGA-NPs). The experimental design consisted of four groups: those treated with DMSO (serving as a control), those treated with drug-free PXT, those treated with PXT-PLGA-NPs, and those treated with PLGA-NPs that lacked PTX. MetaboScape (V4, Bruker Daltonics) was used as the platform for the data analysis, and the results were compared to the Bruker Human Metabolome Data Base (HMDB) spectrum library 2.0. We found a total of 162 metabolites with a high level of confidence ascribed to them. The principal component analysis of the metabolites showed that PTX-free drugs grouped along with PXT-PLGA-NPs, but the control and PLGA-NPs without PXT clustered apart from drug-treated cells but together with each other. In further group pairwise comparisons, it was shown that 37 metabolites were substantially dysregulated (p 0.05) between the PTX-free medication and the PXT-PLGA-NPs. Out of these, it is important to call attention to the metabolites that became more abundant as a result of treatment with PXT-PLGA-NPs. These include 5-Thymidyclic acid with a 7.8-fold change (FC) and 3,4,5-Trimethoxycinnamic acid, both of which have been linked in the past to effective anticancer drug treatment (Quinn et al. 2015; Anantharaju et al. 2017). The findings suggest a more successful anti-drug therapy that makes use of NP, and also indicate a number of metabolites that have the potential to serve as indicators for determining how well an antidrug treatment is working. Our previous findings are consistent with these findings.
Institute
University of Sharjah
DepartmentSharjah institute of medical research
LaboratoryDrug Delivery
Last NameJagal
First NameJayalakshmi
AddressSharjah
Emailjjagal@sharjh.ac.ae
Phone0552863009
Submit Date2022-07-14
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2023-07-14
Release Version1
Jayalakshmi Jagal Jayalakshmi Jagal
https://dx.doi.org/10.21228/M83Q6B
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

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Factors:

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

mb_sample_id local_sample_id Treatment
SA216190Control 02_2_8_1_938Control
SA216191Control 01_2_7_1_936Control
SA216192Control 03_1_9_1_939Control
SA216193Control 04_1_10_1_941Control
SA216194Control 04_2_10_1_942Control
SA216195Control 01_1_7_1_935Control
SA216196Control 03_2_9_1_940Control
SA216197Control 02_1_8_1_937Control
SA216198DF nP 02_2_16_1_954Drug Free PLGA Nanoparticle
SA216199DF nP 03_1_17_1_955Drug Free PLGA Nanoparticle
SA216200DF nP 02_1_16_1_953Drug Free PLGA Nanoparticle
SA216201DF nP 01_2_15_1_952Drug Free PLGA Nanoparticle
SA216202DF nP 01_1_15_1_951Drug Free PLGA Nanoparticle
SA216203DF nP 03_2_17_1_956Drug Free PLGA Nanoparticle
SA216204DF nP 04_1_18_1_957Drug Free PLGA Nanoparticle
SA216205DF nP 04_2_18_1_958Drug Free PLGA Nanoparticle
SA216206Free Drug 02_2_12_1_946Free PTX
SA216207Free Drug 01_2_11_1_944Free PTX
SA216208Free Drug 01_1_11_1_943Free PTX
SA216209Free Drug 03_1_13_1_947Free PTX
SA216210Free Drug 03_2_13_1_948Free PTX
SA216211Free Drug 02_1_12_1_945Free PTX
SA216212Free Drug 04_2_14_1_950Free PTX
SA216213Free Drug 04_1_14_1_949Free PTX
SA216214nP 04_1_22_1_965PTX-PLGA Nanoparticle
SA216215nP 03_2_21_1_964PTX-PLGA Nanoparticle
SA216216nP 03_1_21_1_963PTX-PLGA Nanoparticle
SA216217nP 04_2_22_1_966PTX-PLGA Nanoparticle
SA216218nP 01_2_19_1_960PTX-PLGA Nanoparticle
SA216219nP 01_1_19_1_959PTX-PLGA Nanoparticle
SA216220nP 02_2_20_1_962PTX-PLGA Nanoparticle
SA216221nP 02_1_20_1_961PTX-PLGA Nanoparticle
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