International Journal of Cancer and Oncology
Discovery and Identification of Serum Potential Biomarkers for Colorectal Cancer Using TMT Quantitative Proteomics
- 1General Surgery Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
- 2State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China
- #Authors contributed equally to this work
M. Li, General Surgery Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China, Tel/Fax: 8610-85231323; E-mail: email@example.com
J. Ji, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing 100871, China, Tel/Fax: 8610 62755470; E-mail: firstname.lastname@example.org
Li, M., et al. Discovery and Identification of Serum Potential Biomarkers for Colorectal Cancer Using TMT Quantitative Proteomics. (2017) Int J Cancer Oncol 4(2): 1- 7.
© 2017 Li, M. This is an Open access article distributed under the terms of Creative Commons Attribution 4.0 International License.
KeywordsColorectal cancer, TMT labeling quantitative proteomics, Differentially expressed protein, Biomarker
Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. Nevertheless, the exact mechanism of CRC occurrence remains unclear, and it is lack of biomarkers for early detection. In this study, we employed a TMT-based quantitative proteomic approach to analyze the proteomic changes in the sera collected from early-staged colorectal cancer patient and healthy volunteers. Among the 282 proteins identified, a total of 76 proteins were found differentially expressed in the patients. Bioinformatics analysis revealed that the differentially expressed proteins were related to focal adhesion and p53 signaling pathway. The differential expression of S-adenosylmethionine synthase (MAT2A) and ATP-binding cassette sub-family B member 9 (ABCB9) was further confirmed by using ELISA analysis. The receiver operation characteristic curve of the diagnostic model was 0.908 for MAT2A, and 0.980 for ABCB9. In conclusion, MAT2A and ABCB9 may be potential protein biomarkers of CRC. Our research may shed light on the early diagnosis of CRC.