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GPnotebook: A pan-cancer glycoproteomic database and toolkit for analysis of protein glycosylation changes associated with cancer phenotypes

Zhang, H.; Hu, Y.

2024-04-19 bioinformatics
10.1101/2024.04.18.589619 bioRxiv
Show abstract

Protein glycosylation plays a pivotal role in various biological processes, and the analysis of intact glycopeptides (IGPs) has emerged as a powerful approach for characterizing alterations in protein glycosylation associated with diseases. Despite the critical insights gained from IGP analysis, there is an evident scarcity of intact glycopeptide database and specialized tools for a comprehensive glycoproteomic examination. In response to this deficiency, we have developed a Python package, "GPnotebook," which consolidates the intact glycopeptides identified from different cancer types by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and includes analytical tools for an in-depth characterization of glycopeptides. GPnotebook facilitates an array of functions including statistical profiling, differential expression analysis, glycosylation subtype categorization, investigation of glycosylation-phosphorylation interplay, survival analysis, and glycosylation enzyme assessment. We have deployed GPnotebook in a study of Pancreatic Ductal Adenocarcinoma (PDAC), thereby validating its application and demonstrating its capabilities. Our findings suggest that IGPs hold significant promise as cancer-specific changes and subtype differentiation. Consequently, GPnotebook stands out as a valuable resource for cancer researchers delving into the nuances of protein glycosylation and its correlation with cancer phenotypes. HILIGHTSO_LISimplified and unified access to pan-cancer glycoproteomic database including 90,795 intact glycopeptides. C_LIO_LIDeveloped a glycoproteomic analysis toolkit for systematic glycoproteomic data analysis C_LIO_LIApplied the toolkit for identification of glycosylation changes associated with cancer phenotypes in pancreatic cancer. C_LI

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