Comparative Membrane N-Glycomics of Different Breast Cancer Cell Lines To Understand Breast Cancer Brain Metastasis.
Wenjing PengParvin MirzaeiRui ZhuShiyue ZhouYehia S MechrefPublished in: Journal of proteome research (2020)
The mechanism of brain metastatic breast cancer has gained attention because of its increased incidence rate and its low survival rate. Aberrant protein glycosylation is thought to be a contributing factor in this metastatic mechanism, in which metastatic cancer cells can pass through the blood-brain barrier (BBB). The cell membrane is the outermost layer of a cell and in direct contact with the environment and with other cells, making membrane glycans especially important in many biological processes that include mediating cell-cell adhesion, cell signaling, and interactions. Thus, membrane glycomics has attracted more interest for a variety of disease studies in recent years. To reveal the role that membrane N-glycans play in breast cancer brain metastasis, in this study, membrane enrichment was achieved by ultracentrifugation. Liquid chromatography-tandem mass spectrometry was employed to analyze enriched membrane N-glycomes from five breast cancer cell lines and one brain cancer cell line. Relative quantitative glycomic data from each cell line were compared to MDA-MB-231BR, which is the brain-seeking cell line. The higher sialylation level observed in MDA-MB-231BR suggested the importance of sialylation as it might assist with cell invasion and the penetration of the BBB. Some highly sialylated N-glycans, such as HexNAc5Hex6DeoxyHex1NeuAc3 and HexNAc6Hex7DeoxyHex1NeuAc3, exhibited higher abundances in 231BR, indicating their possible contributions to breast cancer brain metastasis as well as their potential to be indicators for the breast cancer brain metastasis.
Keyphrases
- resting state
- white matter
- functional connectivity
- single cell
- liquid chromatography tandem mass spectrometry
- small cell lung cancer
- cerebral ischemia
- cell therapy
- signaling pathway
- induced apoptosis
- cell cycle arrest
- cell adhesion
- ms ms
- climate change
- big data
- artificial intelligence
- machine learning
- brain injury
- risk assessment
- electronic health record
- genome wide
- protein protein
- tandem mass spectrometry
- case control