CXCL10 expression and prognostic significance in stage II and III colorectal cancer

CXC Chemokine Ligand 10 (CXCL10), an interferon-inducible protein, has been demonstrated to inhibit the proliferation and metastasis in many tumors. In this study, we focus on the expression of CXCL10 in stage II and III colorectal cancer (CRC) and its correlation with metastasis. Real-time reverse-transcription polymerase chain reaction (real-time RT-PCR) and RT-PCR were performed in 36 snap-frozen CRC tissues with recurrence and 28 CRC tissues without recurrence to examine CXCL10 expression. For further examination in mRNA level, three CRC-metastasis-derived cell lines (SW620, Lovo, Colo205) and three primary-CRC-derived ones (SW480, Caco-2, HCT116) were also subjected to real-time RT-PCR. Analysis showed that CXCL10 down-regulated in CRC with recurrence both in tissues and cells (P < 005). Immunohistochemistry was also performed in 118 paraffin-embedded specimens. CRC were scored as strong and low CXCL10 expressers (-/+ and ++/+++, respectively). The correlation between clinicopathological or molecular variables and survival was analyzed. Lowly expressed CXCL10 mRNA were detected in snap-frozen tissues with recurrence (P < 0.05) and in cell lines derived from CRC metastases (SW620, Lovo, Colo205). No significant correlation was found between CXCL10 level detected by immunostaining and tumor location, size, histological type, lymphvascular invasion, perineural invasion or TNM stage. However, patients with lower levels of CXCL10 expression showed the poorer prognosis [low expression 70% (57/81) versus strong expression 27% (10/37); P < 0.05]. Kaplan-Meier curves comparing different CXCL10 expression levels with survival showed highly significant separation (P < 0.05, log-rank test). The Cox proportional hazards regression model also showed that low CXCL10 expression was an independent adverse prognosticator in stage II and III CRC (P < 0.05). We concluded that detection of CXCL10, as a prognostic marker for stage II and III CRC patients, may contribute to predicting clinical outcome.