Proteomic dataset for altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells

Sheta, Razan; Roux‐Dalvai, Florence; Woo, Christina M.; Fournier, Frédéric; Bourassa, Sylvie; Bertozzi, Carolyn R.; Droit, Arnaud; Bachvarov, Dimcho

doi:10.1016/j.dib.2016.05.060

Cited by 6 publications

(40 citation statements)

References 20 publications

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“…Protein concentration from the three fractions was measured by bicinchonic acid assay (Pierce). Western blots were performed as described in [13]. Affinity purification via copper-catalyzed azide-alkyne cycloaddition (CuAAC) with a biotin–alkyne probe was next performed as previously shown ([19,20]; see also [13]).…”

Section: Methodsmentioning

confidence: 99%

“…Streptavidin-agarose resin was added, and the resulting mixture was incubated for 12 h at 24 °C with rotation. Beads were pelleted by centrifugation, and the supernatant containing uncaptured proteins was separated as described in [13]. The beads were then washed, reduced and alkylated, followed by on-bead trypsin digestion as shown in [13].…”

Section: Methodsmentioning

confidence: 99%

“…Spectra were searched against a human proteins database (Uniprot Complete Proteome – taxonomy Homo sapiens – 69165 sequences) using the Andromeda module of MaxQuant software v. 1.5.2.8 [11,21], as shown in [13]. For protein validation, a maximum false discovery rate of 1% at peptide and protein level was used based on a target/decoy search.…”

Section: Methodsmentioning

confidence: 99%

“…For protein validation, a maximum false discovery rate of 1% at peptide and protein level was used based on a target/decoy search. MaxQuant was also applied for Label Free Quantification (LFQ), as described in [13]. …”

Section: Methodsmentioning

confidence: 99%

“…O- and N-glycoprotein prediction analysis using the NetOGlyc 4.0 and the NetNGlyc 1.0 servers was performed, as described in [13]. Gene ontology (GO) enrichment analysis was performed using AmiGO (http://amigo.geneontology.org), as shown in [13].…”

Section: Methodsmentioning

confidence: 99%

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A metabolic labeling approach for glycoproteomic analysis reveals altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells

Sheta

Woo

Roux‐Dalvai³

et al. 2016

Journal of Proteomics

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Epithelial ovarian cancer (EOC) is a disease responsible for more deaths among women in the Western world than all other gynecologic malignancies. There is urgent need for new therapeutic targets and a better understanding of EOC initiation and progression. We have previously identified the polypeptide N-acetylgalactosaminyltransferase 3 (GALNT3) gene, a member of the GalNAc-transferases (GalNAc-Ts) gene family, as hypomethylated and overexpressed in high-grade serous EOC tumors, compared to low malignant potential EOC tumors and normal ovarian tissues. This data also suggested for a role of GALNT3 in aberrant EOC glycosylation, possibly implicated in disease progression. To evaluate differential glycosylation in EOC caused by modulations in GALNT3 expression, we used a metabolic labeling strategy for enrichment and mass spectrometry-based characterization of glycoproteins following GALNT3 gene knockdown (KD) in A2780s EOC cells. A total of 589 differentially expressed glycoproteins were identified upon GALNT3 KD. Most identified proteins were involved in mechanisms of cellular metabolic functions, post-translational modifications, and some have been reported to be implicated in EOC etiology. The GALNT3-dependent glycoproteins identified by this metabolic labeling approach support the oncogenic role of GALNT3 in EOC dissemination and may be pursued as novel EOC biomarkers and/or therapeutic targets. Biological significance: Knowledge of the O-glycoproteome has been relatively elusive, and the functions of the individual polypeptide GalNAc-Ts have been poorly characterized. Alterations in GalNAc-Ts expression were shown to provide huge variability in the O-glycoproteome in various pathologies, including cancer. The application of a chemical biology approach for the metabolic labeling and subsequent characterization of O-glycoproteins in EOC using the Ac4GalNAz metabolite has provided a strategy allowing for proteomic discovery of GalNAc-Ts specific functions. Our study supports an essential role of one of the GalNAc-Ts — GALNT3, in EOC dissemination, including its implication in modulating PTMs and EOC metabolism. Our approach validates the use of the applied metabolic strategy to identify important functions of GalNAc-Ts in normal and pathological conditions.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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A metabolic labeling approach for glycoproteomic analysis reveals altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells

Sheta

Woo

Roux‐Dalvai³

et al. 2016

Journal of Proteomics

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A seven‐DNA methylation signature as a novel prognostic biomarker in breast cancer

Tao

Luo

Jing

et al. 2019

J of Cellular Biochemistry

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Background Breast cancer (BC) is a common malignant tumor and its incidence and mortality rates are ranked first among female cancers. So far, there has been no effective biomarkers for BC prognosis. Methods The DNA methylation data of BC was downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and Functional ANnoTation of The Mammalian Genome databases. The RNA‐Seq data and clinical information of patients were downloaded from TCGA. R packages edgeR and minfi were used for differentially methylated genes (DMGs) screening. Then, the DMGs were collected for gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis by the online tool database for annotation, visualization and integrated discovery (DAVID) and Reactome. Cox regression analysis was used to screen candidate differentially methylated sites (DMSs) for BC prognosis. Logrank test was used to explore the correlation between DMSs and survival time. Correlation analysis was used to investigate the correlation between DNA methylation and gene expression. Results We identified 276 DMGs which contained 1454 DMSs in those three datasets. Also, six DMGs that contained seven DMSs were identified by Cox regression analysis. Interestingly, their expression levels were negatively correlated with the DNA methylation level and not affected by age, subtypes, or tumor stages. Conclusions We proposed that these seven differentially DNA methylation sites can be used as a novel prognostic biomarker for BC area under curve (AUC) = 0.74), which may facilitate research and benefit the clinical treatment of BC.

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Advancements in High-Throughput Omics-Technologies for Understanding the Biology of Neglected and Underutilized Crops

Choudhary

Riyazuddin

Maurya

et al. 2021

Neglected and Underutilized Crops - Towards Nutritional Security and Sustainability

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Proteomic dataset for altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells

Cited by 6 publications

References 20 publications

A metabolic labeling approach for glycoproteomic analysis reveals altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells

A metabolic labeling approach for glycoproteomic analysis reveals altered glycoprotein expression upon GALNT3 knockdown in ovarian cancer cells

A seven‐DNA methylation signature as a novel prognostic biomarker in breast cancer

Advancements in High-Throughput Omics-Technologies for Understanding the Biology of Neglected and Underutilized Crops

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