Serum Chemokine CXCL7 as a Diagnostic Biomarker for Colorectal Cancer

血清趋化因子CXCL7作为结直肠癌的诊断生物标志物

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Abstract

Identification of effective biomarkers is crucial for monitoring the treatment and remission of colorectal cancer (CRC) and improving survival. It is particularly important to diagnose CRC before the tumor metastasizes (stage I-II disease) where possible, to provide the greatest opportunity for patient recovery. Here, we evaluated the clinical value of serum chemokine (C-X-C) ligand 7 (CXCL7) concentration as a biomarker for CRC diagnosis. An enzyme-linked immunosorbent assay was used to measure CXCL7 concentration in 560 serum samples from patients with CRC and controls. Logistic regression and receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic efficacy and build mathematical diagnostic models. The concentration of CXCL7 in the CRC group was significantly higher than that in the control group (P < 0.001), with an area under the ROC curve (AUC) value of 0.862 [95% confidence interval (CI): 0.831-0.890]. Further, the AUC of a regression model including the markers carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), and carbohydrate antigen 125 (CA125), along with CXCL7, was 0.933 (95% CI: 0.909-0.952). For stage I-II tumors, CXCL7 had the highest AUC (0.823, 95% CI: 0.783-0.858) among the four individual biomarkers. The AUC value for combination model analysis of samples from patients with stage I-II tumors was 0.904 (95% CI: 0.872-0.930), with a sensitivity of 82.76% and a specificity of 87.14%, and an optimal cut-off value of 2.66. AUC values for application of the regression model in subgroup analysis were 0.947 (0.917-0.968) and 0.919 (0.874-0.951) for males and females, respectively. These results suggest that CXCL7 has potential as a serum diagnostic biomarker for detection of CRC. Importantly, the combination of CXCL7, CEA, CA125, and CA19-9 may facilitate diagnosis of CRC with relatively high sensitivity and specificity. Clinical Trial Registration Number: LS2017001.

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