Introduction Aberrant microenvironment and endoplasmic reticulum (ER) stress are associated with solid-tumor progression. Stress proteins, like heat shock proteins and glucose-regulated proteins, are frequently overexpressed in human tumors. It has been reported that derlin-1 is involved in ER stress response. In vitro studies have demonstrated that derlin-1 participates in the retrotranslocation of misfolded proteins from ER into the cytosol. Because the roles of derlin-1 in human cancer have not yet been characterized, we investigated the expression of derlin-1 in human breast carcinoma and whether it protected cancer cells against ER stress-induced apoptosis.
Purpose: This study aimed to identify novel biological markers for the prediction of colorectal cancer liver metastasis. Experimental Design: We established two models that mimicked the interactions between colorectal tumor cells and the liver microenvironment. From these models we established subcell lines that had an enhanced ability to metastasize to the liver. Genes that related to hepatic metastasis were screened by microarray. The candidate markers were tested by immunohistochemistry, and their predictive accuracy was assessed by the cross-validation method and an independent test set. Results: Highly metastatic colon cancer cell sublines SW1116p21 and SW1116v3 were established from the tumor cell-microenvironment interaction models. Seven of the upregulated genes in the sublines were selected as candidate markers for predicting metastatic potential. A total of 245 colorectal cancer samples were divided into a training set containing 117 cases and a test set containing 128 cases. In the training set, immunohistochemical analysis showed CCL2 and SNCG expression was higher in the hepatic metastasis group than in the nonmetastasis group, and was correlated with poor survival. Logistic regression analysis revealed that CCL2 and SNCG levels in primary tumors, serum carcinoembryonic antigen level, and lymph node metastasis status were the only significant (P < 0.05) parameters for detecting liver metastasis. In leave-one-out-cross-validation, the two markers, when combined with clinicopathologic features, resulted in 90.5% sensitivity and 90.7% specificity for hepatic metastasis detection. In an independent test set, the combination achieved 87.5% sensitivity and 82% specificity for predicting the future hepatic metastasis of colorectal cancer. Conclusion: Our results suggest that these models are able to mimic the interactions between colorectal cancer cells and the liver microenvironment, and may represent a promising strategy to identify metastasis-related genes. CCL2 and SNCG, combined with clinicopathologic features, may be used as accurate predictors of liver metastasis in colorectal cancer. (Clin Cancer Res 2009;15(17):5485-93) Colorectal carcinoma is one of the major causes of cancer death worldwide (1). Liver is the most common target for metastasis in patients with this disease. It is estimated that approximately 50% of colorectal cancer patients develop liver metastases, with 15% to 25% of synchronous and 20% of heterochronous cases (2). Liver metastasis is the most critical prognostic factor for colorectal cancer. The 5-year overall survival rate of patients with hepatic metastasis is only 25% to 40%
Recent studies have demonstrated that gastric cancer stem cells (CSCs) are a rare sub-group of gastric cancer (GC) cells and have an important role in promoting the tumor growth and progression of GC. In the present study, we demonstrated that the glycolytic enzyme Enolase 1 (ENO1) was involved in the regulation of the stem cell-like characteristics of GC cells, as compared to the parental cell lines PAMC-82 and SNU16, the expression of ENO1 in spheroids markedly increased. We then observed that ENO1 could enhance stem cell-like characteristics, including self-renewal capacity, cell invasion and migration, chemoresistance, and even the tumorigenicity of GC cells. ENO1 is known as an enzyme that is involved in glycolysis, but our results showed that ENO1 could markedly promote the glycolytic activity of cells. Furthermore, inhibiting glycolysis activity using 2-deoxy-d-glucose treatment significantly reduced the stemness of GC cells. Therefore, ENO1 could improve the stemness of CSCs by enhancing the cells’ glycolysis. Subsequently, to further confirm our results, we found that the inhibition of ENO1 using AP-III-a4 (ENOblock) could reduce the stemness of GC cells to a similar extent as the knockdown of ENO1 by shRNA. Finally, increased expression of ENO1 was related to poor prognosis in GC patients. Taken together, our results demonstrated that ENO1 is a significant biomarker associated with the stemness of GC cells.
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