Microenvironmental markers are correlated with lymph node metastasis in invasive submucosal colorectal cancer.

AIMS

Recent studies have shown that the microenvironment can include cancer cells and cancer-associated fibroblasts (CAFs), and that both play important roles in the progression and metastasis of CRC. Here, we aimed to analyse the expression patterns of cancer cell- and CAF-related proteins in submucosal invasive colorectal cancer (SiCRC) and whether such markers are correlated with lymph node metastasis (LNM).

METHODS AND RESULTS

Quantitative analysis was conducted for Ki-67, p53, β-catenin and matrix metalloproteinase-7 (MMP7) to assess cancer cell markers. In addition, we examined CAF markers, including smooth muscle alpha-actin (α-SMA), CD10, podoplanin, fibroblast-specific protein 1 (FSP-1), platelet-derived growth factor receptor (PDGFR)-α, PDGFR-β, adipocyte enhancer-binding protein 1 (AEBP1), fibroblast-associated protein 1 (FAP-1), zinc finger E-box binding homeobox 1 (ZEB1) and TWIST-related protein 1 (TWIST1). In both cases, we conducted digital pathology with Aperio software. We also examined the expression patterns of biomarkers using hierarchical cluster analysis. Two subgroups were established based on the expression patterns of cancer cell- and CAF- related markers, and the associations of these subgroups with clinicopathological variables. In multivariate analysis, subgroup 2, which was characterised by high expression of Ki-67, p53, FAP-1, platelet-derived growth factor receptor (PDGFR)-α, PDGFR-β and TWIST1, was correlated with LNM (P < 0.01). Next, we examined the associations of individual biomarkers with LNM. Multivariate analysis showed that high expression levels of Ki-67 and FAP-1 were significantly associated with LNM (P < 0.05).

CONCLUSIONS

Our findings showed that expression patterns of cancer cell- and CAF-related proteins may allow for stratification of patients into risk categories for LNM in SiCRC. In addition, Ki-67- and FAP-1-expressing microenvironmental cells might be helpful for identification of correlations with LNM in SiCRC.