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.
| Study ID | ST002248 |
| Study Title | Quantitative multi-Omics analysis of paclitaxel-loaded Poly(lactide-co-glycolide) nanoparticles for identification of potential biomarkers for head and neck cancer |
| Study Summary | The 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 |
| Department | Sharjah institute of medical research |
| Laboratory | Drug Delivery |
| Last Name | Jagal |
| First Name | Jayalakshmi |
| Address | Sharjah |
| jjagal@sharjh.ac.ae | |
| Phone | 0552863009 |
| Submit Date | 2022-07-14 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | d |
| Analysis Type Detail | LC-MS |
| Release Date | 2023-07-14 |
| Release Version | 1 |
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Collection:
| Collection ID: | CO002327 |
| Collection Summary: | The process of extracting metabolites from FaDu cells was carried out in a manner that was similar to that which was utilized for the extraction of proteins. Following the addition of PTX (40 μM), PTX-PLGA NPs (40 μM), and drug-free PLGA NPs to the culture medium, the media was changed to PBS, and the cells were scraped off the plates using cell scrapers. After that, the detached cell pellets were collected by centrifuging them at a speed of 15000 rpm for ten minutes at a temperature of 4 degrees Celsius using a Universal 320R Benchtop Centrifuge (Hettich, Beverly, Massachusetts, United States). The collected cell pellets were first treated with 0.1 % FA in methanol, which was followed by sonication using a probe ultrasonicator Q500 (Terra Universal, Inc., Fullerton, California, USA) for 30 seconds at 30 %amplitude 16. This was done in order to release a wide variety of metabolites. After that, the samples were centrifuged at 15,000 rpm for 10 minutes at 4 degrees Celsius, and the upper phase was transferred into LC vials so that it could be dried further using a Genevac evaporator (SP Industries, Warminster, PA, USA). After the reaction was halted with formic acid (FA) at a concentration of one percent, it was dried using a Genevac evaporator. In preparation for subsequent LC-MS/MS examination, the dried samples were kept at a temperature of 80 degrees Celsius. The version 4.0 of MetaboScape was used for both the processing and the statistical analysis (Bruker Daltonics). Analyte bucketing and identification were accomplished by using the software that was made available to us called T-ReX 2D/3D workflow. The settings that were used were as follows: an intensity threshold of larger than 1000 counts and a peak duration of equal to 7 spectra or higher. Quantification of features was carried out by calculating peak area and for statistical analysis, only characteristics that were present in at least three out of twelve samples for each cell type were taken into account. On import, the spectra of the analyte were averaged, and additional consideration was given to just those features that eluted between 0.3 and 25 minutes and had mz values between 50 and 1000. Using a two-tailed independent Student’s t-test, a comparison was made between each drug treatment condition and DMSO-only treated controls. It was shown that there were significantly differently abundant metabolites between the two groups. As a result of this, volcano plots were developed in order to visualize and display the significance (p-value) of dysregulation of cellular metabolites, along with the fold changes associated with each condition. Metabo analyst, which can be found at https://www.metaboanalyst.ca, was used in order to carry out functional enrichment studies. Analyte metabolite identification was carried out by making use of both MS2 spectra and retention time (RT), although the MS/MS spectra were required as a bare minimum for a valid identification to be made. We conducted annotation using Bruker's version of the Human Metabolome Database (HMDB-4.0) for the set of compounds that satisfied this requirement, either by using MS/MS alone or by utilizing MS/MS plus RT. All of the chosen compounds were then compared to this library to find a match. These putatively matching features were filtered by considering for those each feature with the highest annotation quality score (AQ score) among other putative matches for the same metabolite, i.e., those features exhibiting the best fit across the greatest number of factors such as retention time, MS/MS, m/z values, analyte list, and spectral library matching were ranked first for the associated identifier. |
| Sample Type: | Head and neck Cancer cell line |
