Summary of Study ST002273

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 PR001454. The data can be accessed directly via it's Project DOI: 10.21228/M8S71T 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	ST002273
Study Title	Multi-Omics analysis revealed a significant alteration of critical metabolic pathways due to sorafenib-resistance in Hep3B cell lines
Study Type	MS- comparative metabolomic analysis
Study Summary	Hepatocellular carcinoma (HCC) is the second prominent cause of cancer-associated death worldwide. Usually, HCC is diagnosed in advanced stages, where sorafenib, a multiple target ty-rosine kinase inhibitor, is used as the first line of treatment. Unfortunately, resistance to sorafenib is usually encountered within six months of the treatment. Therefore, there is a critical need to identify the underlying reasons for drug resistance. In the present study, we investigated the proteomic and metabolomics alterations accompanying to sorafenib resistance in hepatocellular carcinoma Hep3B cells by employing ultra-high-performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). The Bruker Human Metabolome Database (HMDB) library was used to identify the differentially abundant metabolites through MetaboScape 4.0 software (Bruker). For protein annotation and identification, the Uniprot proteome for Homo sapiens (Human) da-tabase was utilised through MaxQuant. The results revealed that 27 metabolites and 18 proteins were significantly dysregulated due to sorafenib resistance in Hep3B cells compared to the parental phenotype. D-alanine, L-proline, o-tyrosine, succinic acid and phosphatidylcholine (PC, 16:0/16:0) were among the significantly altered metabolites. Ubiquitin carboxyl-terminal hydrolase isozyme L1, mitochondrial superoxide dismutase, UDP-glucose-6-dehydrogenase, sorbitol dehydrogenase and calpain small subunit 1 were among the significantly altered proteins. The findings revealed that resistant Hep3B cells demonstrated significant alterations in amino acid and nucleotide met-abolic pathways, energy production pathways and other pathways related to cancer aggressive-ness, migration, proliferation, and drug-resistance. Joint pathway enrichment analysis unveiled unique pathways, including the antifolate resistance pathway and other important pathways that maintain cancer cells' survival, growth, and proliferation. Collectively, the results identified po-tential biomarkers for sorafenib-resistant HCC and gave insights into their role in chemotherapeutic drug resistance, cancer initiation, progression, and aggressiveness, which may contribute to better prognosis and chemotherapeutic outcomes.
Institute	Sharjah Institute for Medical Research
Last Name	Soares
First Name	Nelson
Address	University of Sharjah, Sharjah, UAE
Email	nsoares@sharjah.ac.ae
Phone	+971 65 05 7763
Submit Date	2022-08-31
Raw Data Available	Yes
Raw Data File Type(s)	d
Analysis Type Detail	LC-MS
Release Date	2022-09-16
Release Version	1

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Sample Preparation:

Sampleprep ID:	SP002365
Sampleprep Summary:	Metabolite extraction: For metabolomics, three biological replicates were used. An equal number of cells were utilized for each sample. The cells were centrifuged separately at 15000 rpm for 10 min to separate the cells and cell-free supernatants. The supernatants were dis-carded, and to each cell pellet (~3x 106), 1 mL of 0.1% formic acid in methanol was added, followed by vertexing for 2 min x 4, interrupted by 15 min incubation on ice. This is followed by sonication using a COPLEY probe-sonicator (QSONICA SONI-CATOR, USA) for 30 seconds with 30% amplifier in an ice bath. Subsequently, the cel-lular debris of each sample was collected by centrifugation at 15000 rpm for 10 min at 4°C. The supernatants were separated and dried at 37 ± 1 °C using EZ-2 Plus (Gene-Vac-Ipswich, UK). Finally, 200 µL of 0.1% formic acid in water was used to resuspend the dried samples, which were then vortexed for 2 min, filtered by a 0.45µm hydro-philic Nylon Syringe Filter and transferred to 200 μL (micro-inserts) in LC vials. The quality control (QC) sample was prepared by pooling the same volume (10 μL) of each sample, and all samples were placed in the autosampler at a temperature set at 4℃ and analyzed with UHPLC-QTOF-MS.

Sampleprep ID:

SP002365

Sampleprep Summary:

Metabolite extraction: For metabolomics, three biological replicates were used. An equal number of cells were utilized for each sample. The cells were centrifuged separately at 15000 rpm for 10 min to separate the cells and cell-free supernatants. The supernatants were dis-carded, and to each cell pellet (~3x 106), 1 mL of 0.1% formic acid in methanol was added, followed by vertexing for 2 min x 4, interrupted by 15 min incubation on ice. This is followed by sonication using a COPLEY probe-sonicator (QSONICA SONI-CATOR, USA) for 30 seconds with 30% amplifier in an ice bath. Subsequently, the cel-lular debris of each sample was collected by centrifugation at 15000 rpm for 10 min at 4°C. The supernatants were separated and dried at 37 ± 1 °C using EZ-2 Plus (Gene-Vac-Ipswich, UK). Finally, 200 µL of 0.1% formic acid in water was used to resuspend the dried samples, which were then vortexed for 2 min, filtered by a 0.45µm hydro-philic Nylon Syringe Filter and transferred to 200 μL (micro-inserts) in LC vials. The quality control (QC) sample was prepared by pooling the same volume (10 μL) of each sample, and all samples were placed in the autosampler at a temperature set at 4℃ and analyzed with UHPLC-QTOF-MS.