MassIVE MSV000089736

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Integration of Proteomics, Phosphoproteomics and Kinomics Enables the Discovery of Anticancer Drugs for Pancreatic Cancer

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Description

Here we performed phosphoproteomic, kinome examination of surgical specimens and patient-derived cancer cell lines.Kinomics and phosphoproteomics identified changes in the activity of a number of identical protein kinases in PDAC tumors and tissue culture cells. This allowed us to use these kinases as small molecular inhibitor targets for successful in vitro PDAC cell eradication. [doi:10.25345/C5PK07573] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: pancreatic cancer, proteomics, primary cell culture, drug discovery

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Principal Investigators:
(in alphabetical order) 		Algirdas Kaupinis, Proteomics Centre Institute of Biochemistry Vilnius University, Lithuania
Submitting User: 1021458
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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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