Dataset Information

Bioinformatics Analysis of Global Proteomic and Phosphoproteomic Data Sets Revealed Activation of NEK2 and AURKA in Cancers.

ABSTRACT: Tumor heterogeneity attributes substantial challenges in determining the treatment regimen. Along with the conventional treatment, such as chemotherapy and radiotherapy, targeted therapy has greater impact in cancer management. Owing to the recent advancements in proteomics, we aimed to mine and re-interrogate the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data sets which contain deep scale, mass spectrometry (MS)-based proteomic and phosphoproteomic data sets conducted on human tumor samples. Quantitative proteomic and phosphoproteomic data sets of tumor samples were explored and downloaded from the CPTAC database for six different cancers types (breast cancer, clear cell renal cell carcinoma (CCRCC), colon cancer, lung adenocarcinoma (LUAD), ovarian cancer, and uterine corpus endometrial carcinoma (UCEC)). We identified 880 phosphopeptide signatures for differentially regulated phosphorylation sites across five cancer types (breast cancer, colon cancer, LUAD, ovarian cancer, and UCEC). We identified the cell cycle to be aberrantly activated across these cancers. The correlation of proteomic and phosphoproteomic data sets identified changes in the phosphorylation of 12 kinases with unchanged expression levels. We further investigated phosphopeptide signature across five cancer types which led to the prediction of aurora kinase A (AURKA) and kinases-serine/threonine-protein kinase Nek2 (NEK2) as the most activated kinases targets. The drug designed for these kinases could be repurposed for treatment across cancer types.

SUBMITTER: Deb B

PROVIDER: S-EPMC7072708 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Bioinformatics Analysis of Global Proteomic and Phosphoproteomic Data Sets Revealed Activation of NEK2 and AURKA in Cancers.

Deb Barnali B Sengupta Pratyay P Sambath Janani J Kumar Prashant P

Biomolecules 20200204 2

Tumor heterogeneity attributes substantial challenges in determining the treatment regimen. Along with the conventional treatment, such as chemotherapy and radiotherapy, targeted therapy has greater impact in cancer management. Owing to the recent advancements in proteomics, we aimed to mine and re-interrogate the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data sets which contain deep scale, mass spectrometry (MS)-based proteomic and phosphoproteomic data sets conducted on human tumor ...[more]

PMID: 32033228

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Project description:Protein glycosylation plays fundamental roles in many cellular processes, and previous reports have shown dysregulation to be associated with several human diseases, including diabetes, cancer, and neurodegenerative disorders. Despite the vital role of glycosylation for proper protein function, the analysis of glycoproteins has been lagged behind to other protein modifications. In this study, we describe the reanalysis of global proteomic data from breast cancer xenograft tissues using recently developed software package GPQuest 2.0, revealing a large number of previously unidentified N-linked glycopeptides. More importantly, we found that using immobilized metal affinity chromatography (IMAC) technology for the enrichment of phosphopeptides had coenriched a substantial number of sialoglycopeptides, allowing for a large-scale analysis of sialoglycopeptides in conjunction with the analysis of phosphopeptides. Collectively, combined tandem mass spectrometry (MS/MS) analyses of global proteomic and phosphoproteomic data sets resulted in the identification of 6 724 N-linked glycopeptides from 617 glycoproteins derived from two breast cancer xenograft tissues. Next, we utilized GPQuest 2.0 for the reanalysis of global and phosphoproteomic data generated from 108 human breast cancer tissues that were previously analyzed by Clinical Proteomic Analysis Consortium (CPTAC). Reanalysis of the CPTAC data set resulted in the identification of 2 683 glycopeptides from the global proteomic data set and 4 554 glycopeptides from phosphoproteomic data set, respectively. Together, 11 292 N-linked glycopeptides corresponding to 1 731 N-linked glycosites from 883 human glycoproteins were identified from the two data sets. This analysis revealed an extensive number of glycopeptides hidden in the global and enriched in IMAC-based phosphopeptide-enriched proteomic data, information which would have remained unknown from the original study otherwise. The reanalysis described herein can be readily applied to identify glycopeptides from already existing data sets, providing insight into many important facets of protein glycosylation in different biological, physiological, and pathological processes.

Project description:Understanding molecular mechanisms underlying plant salinity tolerance provides valuable knowledgebase for effective crop improvement through genetic engineering. Current proteomic technologies, which support reliable and high-throughput analyses, have been broadly used for exploring sophisticated molecular networks in plants. In the current study, we compared phosphoproteomic and proteomic changes in roots of different soybean seedlings of a salt-tolerant cultivar (Wenfeng07) and a salt-sensitive cultivar (Union85140) induced by salt stress. The root samples of Wenfeng07 and Union85140 at three-trifoliate stage were collected at 0 h, 0.5 h, 1 h, 4 h, 12 h, 24 h, and 48 h after been treated with 150 mm NaCl. LC-MS/MS based phosphoproteomic analysis of these samples identified a total of 2692 phosphoproteins and 5509 phosphorylation sites. Of these, 2344 phosphoproteins containing 3744 phosphorylation sites were quantitatively analyzed. Our results showed that 1163 phosphorylation sites were differentially phosphorylated in the two compared cultivars. Among them, 10 MYB/MYB transcription factor like proteins were identified with fluctuating phosphorylation modifications at different time points, indicating that their crucial roles in regulating flavonol accumulation might be mediated by phosphorylated modifications. In addition, the protein expression profiles of these two cultivars were compared using LC MS/MS based shotgun proteomic analysis, and expression pattern of all the 89 differentially expressed proteins were independently confirmed by qRT-PCR. Interestingly, the enzymes involved in chalcone metabolic pathway exhibited positive correlations with salt tolerance. We confirmed the functional relevance of chalcone synthase, chalcone isomerase, and cytochrome P450 monooxygenase genes using soybean composites and Arabidopsis thaliana mutants, and found that their salt tolerance were positively regulated by chalcone synthase, but was negatively regulated by chalcone isomerase and cytochrome P450 monooxygenase. A novel salt tolerance pathway involving chalcone metabolism, mostly mediated by phosphorylated MYB transcription factors, was proposed based on our findings. (The mass spectrometry raw data are available via ProteomeXchange with identifier PXD002856).

Dataset Information

Bioinformatics Analysis of Global Proteomic and Phosphoproteomic Data Sets Revealed Activation of NEK2 and AURKA in Cancers.

Publications

Bioinformatics Analysis of Global Proteomic and Phosphoproteomic Data Sets Revealed Activation of NEK2 and AURKA in Cancers.

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