Ovarian cancer proteomics is the study of the complete set of proteins expressed in ovarian cancer cells. It aims to identify differentially expressed proteins and post-translational modifications that may contribute to the development and progression of ovarian cancer. Proteomics techniques such as mass spectrometry and 2D gel electrophoresis can be used to analyze protein expression levels and modifications in ovarian cancer tissues and cell lines. By comparing the proteomes of normal ovarian tissues with those of ovarian cancer tissues, researchers can identify potential biomarkers for early detection and new therapeutic targets for ovarian cancer treatment. Ovarian cancer proteomics is a rapidly evolving field that holds great promise for improving our understanding of the molecular mechanisms underlying ovarian cancer and developing more effective treatments for this deadly disease.
Case 1. Proteomic analysis reveals key proteins that regulate metastasis of ovarian cancer (1)
Researchers identified 8,114 proteins in the specimens of both HGSC and healthy fallopian tubes by integrating tandem mass tags (TMTs) for protein quantification, solid phase extraction of glycosite-containing peptides (SPEG), and intact glycopeptides (IGP) analysis. Of the 8,114 proteins, 5,916 were identified in both HGSC and healthy samples. Among all 8,114 proteins, researchers identified 1,690 N-glycosylated peptides and 3,202 IGPs, while among the 5,916 proteins, they detected 490 N-glycosylated peptides and 365 IGPs.
The researchers performed principal component analysis (PCA) and KEGG pathway enrichment analysis on all the IGP data. In HGSC, high-mannose type (HM-) glycosylation modification had the highest abundance and was mainly enriched in lysosomes, while sialic acid type (SA-) and fucose type (Fuc-) glycosylation modifications had relatively low abundances. The researchers found that in HGSC, some glycoproteins had no significant changes in expression levels, but the modification levels of their glycosylation sites were significantly altered.
The authors systematically described for the first time the changes in glycosylation levels in ovarian cancer, providing convincing evidence that protein glycosylation plays an important role in regulating the occurrence and development of ovarian cancer. At the same time, it also provides new potential targets and ideas for the development of early diagnosis and targeted treatment of ovarian cancer based on glycosylation modification sites.
Case 2. Comparative glycoproteomics analysis reveals differences between SKOV3 and IOSE80 cell lines (2)
This article presents a site- and structure-specific quantitative N-glycoproteomic study of the cell surface N-glycosylation of ovarian cancer SKOV3 cells, using non-cancerous ovarian epithelial cells IOSE80 as a control. The complete N-glycopeptides were enriched using the ZIC-HILIC method and isotopically labeled. The samples were analyzed online by C18 RPLC-nanoESI-MS/MS (HCD).
Based on the quantitative results of GPSeeker, the GPSeeker Quan tool was used to find the precursor ions corresponding to each ID in the primary spectrum. By selecting the three highest isotopic peaks, 4041 IDs were quantified. Among them, 1056 IDs were selected by screening for at least two identifications in three technical replicates. After further up/down-regulation screening, a total of 746 differentially expressed N-glycopeptides (DEGPs) were identified, with 421 DEGPs upregulated and 325 DEGPs downregulated.
The structure- and site-specific quantification of N-glycoproteomics using GPSeeker as the center will provide new insights for the discovery of novel biomarkers for ovarian cancer, helping to identify new clinical applications in the precise analysis of site- or structure-specific N-glycoproteins that are physiologically and pathologically relevant to ovarian cancer. The results will also contribute to the understanding of the relationship between ovarian cancer and N-glycosylation, and provide more reliable candidates for the future research on the mechanism of ovarian cancer biomarkers.
- Eckert, Mark A., et al. "Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts." Nature 569.7758 (2019): 723-728.
- Zhou, Ying, et al. "Comparative glycomics study on the surface of SKOV3 versus IOSE80 cell lines." Frontiers in Chemistry (2022): 1435.