Dataset Information

Quantitative proteomics analysis reveals novel insights into mechanisms of action of Disulfiram (DSF)

ABSTRACT: The new uses of the old drugs may reduce cost and shortens the production cycle of research and development, especially that approved by FDA for important clinical conditions. Alcohol abuse Disulfiram (DSF) has been proven safe and shows the promising anti-tumor effect in may preclinical studies. However, the potential side effects of DSF on tumor remain unknown. In this study, we explored the role of DSF in cancer cells and searched for the differential expressed protein after DSF treatment in the HeLa cells. To fully understand the mechanism of action of DSF with a systems perspective, we employed a quantitative proteomics strategy to systematically identify potential targets of DSF. In total, 201 proteins were dys-regulated significantly after DSF exposure, implying that they may be potential targets of DSF. Analysis of this data on a system level revealed major changes of proteins involved in diverse biological processes, including metabolic process and response to stimulus.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

DISEASE(S): Cervix Carcinoma

SUBMITTER: peng zheng

LAB HEAD: peng zheng

PROVIDER: PXD024910 | Pride | 2021-11-27

REPOSITORIES: Pride

ACCESS DATA

Publications

Quantitative proteomics analysis reveals novel insights into mechanisms of action of disulfiram (DSF).

Zheng Peng P Liu Chenglinzi C Wu Yaoqin Y Xu Ruifeng R Chen Ying Y Hu Fan F Chen Zhuo Z Zhang Tongcun T

Proteomics. Clinical applications 20210929 1

<h4>Purpose</h4>Disulfiram (DSF) has been proven safe and shows the promising antitumor effect in preclinical studies. However, the precise mechanism of DSF on tumor is rarely reported. This study aims to fully understand the mechanism of action of DSF with a systems perspective in anticancer effects.<h4>Experimental design</h4>SILAC-based quantitative proteomics strategy was used to systematically identify differential expression proteins (DEPs) after DSF treatment in HeLa cells. Bioinformatica ...[more]

PMID: 34542231

Similar Datasets

Project description:Memory B cells play a fundamental role in host defences against viruses. This dataset aimed at understanding their maturation and stability in the context of SARS-CoV-2 infection and consist of a longitudinal single-cell and repertoire profiling of the B cell response up to six months in four severe COVID-19 patients. All four patients were recruited at Henri Mondor University Hospital (AP-HP, Paris France), between March and May 2020, and required oxygen as treatment. Clinical and biological characteristics of these patients are summarized in the Patient_information.csv file. Peripheral (CD3-CD14-CD15-CD56-CD19+IgD-) B cells were FACS-sorted (MA900, Sony) in PBS/0.08% FCS from 4 patients (S-CoV) at baseline (M0) and 6 months (M6). 5x104 to 10x105 cells were obtained for each subset and 20000 were loaded in the 10x Chromium Controller to generate single-cell gel-beads in emulsion. The scRNA-seq libraries were generated using the Chromium Next GEM Single Cell V(D)J Reagent Kit v.1.1 with Feature Barcoding (10x Genomics) according to the manufacturer’s protocol. PBMCs were initially isolated from venous blood samples via standard density gradient centrifugation and used after cryopreservation at -150°C. Cells were thawed using RPMI-1640 (Gibco) 10% FBS, washed twice and incubated with 10µg of the SARS-CoV-2 his tagged spike protein in 100µL of PBS (Gibco) 2% FBS during 20 minutes on ice. Cells were washed and resuspended in the same conditions, then fluorochrome-conjugated antibody cocktail including the 2 anti-His was added at pre-titrated concentrations for 20 min at 4°C and viable cells were identified using a LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific) incubated with conjugated antibodies used for cell sorting (CD3/CD14/CD15/CD56/CD19/IgD) as well as a panel of barcoded TotalSeqC® and homemade anti-His antibodies (see feature_reference.csv.gz files). Three distinct sorts were performed for each donor: two at the M0 time-point (M0_Sort1 and M0_Sort2) and one at the M6 time-point (M6_Sort1). His-tagged-Spike + barcoded-anti-his staining was only included in the last two sorts (M0_Sort2 and M6_Sort1). For these two sorts it should additionally be noted that 5’-transcriptomic and ADT libraries were sequenced in two separate runs (Run1 and Run2) to achieve sufficient sequencing depth for both libraries. Both runs were pooled at the Cell Ranger analysis step.

Dataset Information

Quantitative proteomics analysis reveals novel insights into mechanisms of action of Disulfiram (DSF)

Publications

Quantitative proteomics analysis reveals novel insights into mechanisms of action of disulfiram (DSF).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure