Zhao P

Secreted LOXL2 is a novel therapeutic target that promotes gastric cancer metastasis via the Src/FAK pathway

The purpose of this study was to investigate invasion- and metastasis-related genes in gastric cancer. To this end, we used the transwell system to select a highly invasive subcell line from minimally invasive parent cells and compared gene expression in paired cell lines with high- and low-invasive potentials. Lysyl oxidase-like 2 (LOXL2) was overexpressed in the highly invasive subcell line. Immunohistochemical analysis revealed that LOXL2 expression was markedly increased in carcinoma relative to normal epithelia, and this overexpression in primary tumor was significantly associated with depth of tumor invasion, lymph node metastasis and poorer overall survival. Moreover, LOXL2 expression was further increased in lymph node metastases compared with primary cancer tissues. RNA interference-mediated knockdown and ectopic expression of LOXL2 showed that LOXL2 promoted tumor cell invasion in vitro and increased gastric carcinoma metastasis in vivo. Subsequent mechanistic studies showed that LOXL2 could activate both the Snail/E-cadherin and Src kinase/Focal adhesion kinase (Src/FAK) pathways. However, secreted LOXL2 induced gastric tumor cell invasion and metastasis exclusively via the Src/FAK pathway. Expression correlation analysis in gastric carcinoma tissues also revealed that LOXL2 promoted invasion via the Src/FAK pathway but not the Snail/E-cadherin pathway. We then evaluated secreted LOXL2 as a target for gastric carcinoma treatment and found that an antibody against LOXL2 significantly inhibited tumor growth and metastasis. Overall, our data revealed that LOXL2 overexpression, a frequent event in gastric carcinoma progression, contributes to tumor cell invasion and metastasis, and LOXL2 may be a therapeutic target for preventing and treating metastases.

Tumor Cell-Microenvironment Interaction Models Coupled with Clinical Validation Reveal CCL2 and SNCG as Two Predictors of Colorectal Cancer Hepatic Metastasis

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 up-regulated 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)