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Correlation between mitochondrial TRAP-1 expression and lymph node metastasis in colorectal cancer
Jing-Yan Gao1, Bao-Rong Song, Jun-Jie Peng
1Department of Colorectal Cancer, Fudan University Shanghai Cancer Center, Shanghai Medical College, Fudan University, Shanghai 200032, China.
World Journal of Gastroenterology
|November 10, 2012
Summary
Mitochondrial tumor necrosis factor receptor-associated protein-1 (TRAP-1) is upregulated in colorectal cancer with lymph node metastasis. TRAP-1 overexpression predicts poor outcomes and may serve as a biomarker for colorectal cancer progression.
Area of Science:
- Oncology
- Molecular Biology
- Biochemistry
Background:
- Colorectal cancer (CRC) remains a significant health concern globally.
- Lymph node metastasis (LNM) is a critical determinant of CRC prognosis.
- Identifying novel biomarkers for LNM and prognosis in CRC is essential.
Purpose of the Study:
- To investigate the role of mitochondrial tumor necrosis factor receptor-associated protein-1 (TRAP-1) in LNM of CRC.
- To assess TRAP-1 as a potential biomarker for LNM and prognosis in Chinese CRC patients.
- To develop diagnostic and prognostic tools for CRC using quantitative real-time polymerase chain reaction (RT-PCR).
Main Methods:
- Quantitative RT-PCR analysis of mitochondrial TRAP-1 gene expression in 96 Chinese CRC samples.
- Western blotting and immunohistochemical assays to confirm TRAP-1 expression.
- Analysis of the association between TRAP-1 expression and clinicopathological parameters.
Main Results:
- TRAP-1 was significantly upregulated in CRC with LNM compared to non-LNM CRC.
- TRAP-1 overexpression strongly correlated with LNM, advanced tumor stage, increased recurrence rates, and decreased survival.
- TRAP-1 was identified as an independent prognostic factor for CRC recurrence and survival.
Conclusions:
- Mitochondrial TRAP-1 plays a role in LNM in CRC.
- TRAP-1 is a potential biomarker for LNM and a prognostic factor in CRC.
- Overexpression of TRAP-1 predicts poor outcomes in colorectal cancer patients.
