Label-free quantitative proteomics of CD133-positive liver cancer stem cells
Autor: | Wen-Lian Hsu, Wan Yu Mao, Sheng Ta Tsai, Wei Chao Chang, Chung-Hsuan Chen, Chia-Ning Shen, Chung Leung Li, Hsin Ying Han, Chih-Chiang Tsou |
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Rok vydání: | 2012 |
Předmět: |
lcsh:Cytology
Hepatocellular carcinoma Research Quantitative proteomics Liver cancer stem cells Tumor initiation Biology Bioinformatics medicine.disease Proteomics Biochemistry Proteome medicine Cancer research Label-free quantitation Annexin A3 lcsh:QH573-671 Stem cell LC-MS/MS Liver cancer Molecular Biology Annexin A1 |
Zdroj: | Proteome Science Proteome Science, Vol 10, Iss 1, p 69 (2012) |
ISSN: | 1477-5956 |
Popis: | Background CD133-positive liver cancer stem cells, which are characterized by their resistance to conventional chemotherapy and their tumor initiation ability at limited dilutions, have been recognized as a critical target in liver cancer therapeutics. In the current work, we developed a label-free quantitative method to investigate the proteome of CD133-positive liver cancer stem cells for the purpose of identifying unique biomarkers that can be utilized for targeting liver cancer stem cells. Label-free quantitation was performed in combination with ID-based Elution time Alignment by Linear regression Quantitation (IDEAL-Q) and MaxQuant. Results Initially, IDEAL-Q analysis revealed that 151 proteins were differentially expressed in the CD133-positive hepatoma cells when compared with CD133-negative cells. We then analyzed these 151 differentially expressed proteins by MaxQuant software and identified 10 significantly up-regulated proteins. The results were further validated by RT-PCR, western blot, flow cytometry or immunofluorescent staining which revealed that prominin-1, annexin A1, annexin A3, transgelin, creatine kinase B, vimentin, and EpCAM were indeed highly expressed in the CD133-positive hepatoma cells. Conclusions These findings confirmed that mass spectrometry-based label-free quantitative proteomics can be used to gain insights into liver cancer stem cells. |
Databáze: | OpenAIRE |
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