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Isobaric tags for relative and absolute quantitation-based proteome analysis of Vietnamese colorectal carcinoma tissues


 Department of Biotechnology, School of Biotechnology, International University, Vietnam National University HCMC, Quarter 6, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam

Correspondence Address:
Thi Thu Hoai Nguyen,
School of Biotechnology, International University, Vietnam National University HCMC, Quarter 6, Linh Trung Ward, Thu Duc District, Ho Chi Minh City
Vietnam
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Source of Support: None, Conflict of Interest: None

Context: Colorectal cancer (CRC) is one of the most common malignancies and one of the leading causes of cancer death worldwide. Establishing early detection methods or markers of CRC is central to improve the survival rate of CRC patients. Nowadays, new molecular tools have been developed to acquire further knowledge on tumor progression. Aims: Comparative proteomics analysis of Vietnamese colorectal carcinoma in different stages was performed to gain an insight into the molecular events taking place in CRC and metastasis. Subjects and Methods: In this study, the comparative protein expression analysis of ten paired CRC and its corresponding noncancerous tissue samples was performed using the combination of isobaric tags for relative and absolute quantitation labeling and mass spectrometry (MS). The data obtained were further analyzed with Ingenuity Pathways Analysis (IPA) system. Results: Based on the MS/MS spectra analyzed by ProteinPilot software, 684 proteins were identified, out of which 215 were observed to be differentially expressed in at least 1 sample pair. Individual protein expression and variation have been identified for each patient. IPA system demonstrated cytoskeletal signaling as the top-ranked functional pathway network associated with the oncogenic function. Conclusions: Our study supplemented the understanding about proteome of Vietnamese CRC patients and identified statistically protein expression differences among samples assisting in finding effective biomarkers for CRC diagnostics.


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