Correlation between Cancerous Exosomes and Protein Markers Based on Surface-Enhanced Raman Spectroscopy (SERS) and Principal Component Analysis (PCA).
Hyunku ShinHyesun JeongJaena ParkSunghoi HongYeonho ChoiPublished in: ACS sensors (2018)
Exosomes, which are nanovesicles secreted by cells, are promising biomarkers for cancer diagnosis and prognosis, based on their specific surface protein compositions. Here, we demonstrate the correlation of nonsmall cell lung cancer (NSCLC) cell-derived exosomes and potential protein markers by unique Raman scattering profiles and principal component analysis (PCA) for cancer diagnosis. On the basis of surface enhanced Raman scattering (SERS) signals of exosomes from normal and NSCLC cells, we extracted Raman patterns of cancerous exosomes by PCA and clarified specific patterns as unique peaks through quantitative analysis with ratiometric mixtures of cancerous and normal exosomes. The unique peaks correlated well with cancerous exosome ratio ( R2 > 90%) as the unique Raman band of NSCLC exosome. To examine the origin of the unique peaks, we compared these unique peaks with characteristic Raman bands of several exosomal protein markers (CD9, CD81, EpCAM, and EGFR). EGFR had 1.97-fold similarity in Raman profiles than other markers, and it showed dominant expression against the cancerous exosomes in an immunoblotting result. We expect that these results will contribute to studies on exosomal surface protein markers for diagnosis of cancers.
Keyphrases
- raman spectroscopy
- mesenchymal stem cells
- small cell lung cancer
- stem cells
- binding protein
- induced apoptosis
- epidermal growth factor receptor
- label free
- gold nanoparticles
- amino acid
- sensitive detection
- papillary thyroid
- tyrosine kinase
- squamous cell carcinoma
- cell therapy
- bone marrow
- cell proliferation
- cell cycle arrest
- small molecule
- single cell
- signaling pathway
- hydrogen peroxide
- nitric oxide
- endoplasmic reticulum stress
- childhood cancer
- fluorescent probe
- ionic liquid
- cell death
- human health
- energy transfer
- monte carlo