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Down-regulation of tumor suppressor in lung cancer 1 (TSLC1) expression correlates with poor prognosis in patients with colon cancer

Overview of attention for article published in Journal of Molecular Histology, August 2012
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Title
Down-regulation of tumor suppressor in lung cancer 1 (TSLC1) expression correlates with poor prognosis in patients with colon cancer
Published in
Journal of Molecular Histology, August 2012
DOI 10.1007/s10735-012-9438-7
Pubmed ID
Authors

Jinfeng Zhang, Jinfeng Ning, Jingshu Geng, Binbin Cui, Xinshu Dong

Abstract

Tumor suppressor in lung cancer 1 (TSLC1), a novel tumor suppressor gene, has been reported to be frequently inactivated in a variety of human malignant tumors. The aim of this study was to detect TSLC1 expression in human colon cancer and to analyze its association with prognosis of patients with colon cancer. Using quantitative real-time PCR and Western blot analysis, we found significantly decreased expression of TSLC1 in primary colon tumor tissues (n = 30) compared with adjacent normal tissues. Immunohistochemistry analysis also found decreased TSLC1 expression in 41.3 % (33/80) colon tumor tissues. In clinicopathological analysis, loss of TSLC1 expression significantly correlated with female gender and lymph node metastasis of colon cancer patients (P < 0.05). In addition, decreased expression of TSLC1 in tumors was found to be closely associated with a poor prognosis (P = 0.037, log-rank test), and multivariate analysis showed that lower TSLC1 protein expression was an independent prognostic factor for colon cancer patients. Our study suggests that down-regulated expression of TSLC1 may play an important role in the progression of colon cancer and TSLC1 expression may serve as a useful marker for the prognostic evaluation of patients with colon cancer.

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Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 33%
Researcher 1 17%
Student > Postgraduate 1 17%
Other 1 17%
Unknown 1 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 50%
Neuroscience 1 17%
Medicine and Dentistry 1 17%
Unknown 1 17%