Analysis of the expression of cancer-associated fibroblast- and EMT-related proteins in submucosal invasive colorectal cancer

J Cancer. 2018 Jun 23;9(15):2702-2712. doi: 10.7150/jca.25646. eCollection 2018.

Abstract

Objective: Recent studies have shown that cancer-associated fibroblasts (CAFs) and the epithelial-mesenchymal transition (EMT) play important roles in the progression and metastasis of CRC. Although prediction of lymph node metastasis in submucosal invasive colorectal cancer (SiCRC) is important, the relationships of CAF and EMT with lymph node metastasis of SiCRC have not yet been examined. Here, we aimed to analyze the expression patterns of CAF- and EMT-related proteins in SiCRC. Materials and Methods: The expression of CAF-related markers, including α-smooth muscle actin, CD10, podoplanin, fibroblast specific protein 1, and adipocyte enhancer-binding protein 1, and EMT-related proteins [zinc finger protein SNAI2 (ZEB1) and twist-related protein 1 (TWIST1) in SiCRC with (n = 29) or without (n = 80) lymph node metastasis was examined by immunohistochemistry. We examined the expression patterns of biomarkers using hierarchical cluster analysis. Consequently, four subgroups were established based on the expression patterns of CAF- and EMT-related markers, and the associations of these subgroups with clinicopathological variables. Results: In multivariate analysis, subgroup 2, which was characterized by high expression of all markers, was correlated with lymph node metastasis (p < 0.01). Next, we examined the associations of individual biomarkers with lymph node metastasis. Multivariate analysis showed that moderately differentiated adenocarcinoma was significantly associated with lymph node metastasis (p < 0.05). Conclusions: Our findings showed that expression patterns of CAF markers and EMT-related proteins may allow for stratification of patients into risk categories for lymph node metastasis in SiCRC.

Keywords: cancer-associated fibroblast; colorectal cancer; epithelial-mesenchymal transition; hierarchical cluster analysis; submucosal colorectal cancer.