Previous studies used to enumerate circulating tumor cells to predict prognosis and therapeutic effect of colorectal cancer. However, increasing studies have shown that only circulating tumor cells enumeration was not enough to reflect the heterogeneous condition of tumor. In this study, we classified different metastatic-potential circulating tumor cells from colorectal cancer patients and measured FAM172A expression in circulating tumor cells to improve accuracy of clinical diagnosis and treatment of colorectal cancer. Blood samples were collected from 45 primary colorectal cancer patients. Circulating tumor cells were enriched by blood filtration using isolation by size of epithelial tumor cells, and in situ hybridization with RNA method was used to identify and discriminate subgroups of circulating tumor cells. Afterwards, FAM172A expression in individual circulating tumor cells was measured. Three circulating tumor cell subgroups (epithelial/ biophenotypic/mesenchymal circulating tumor cells) were identified using epithelial-mesenchymal transition markers. In our research, mesenchymal circulating tumor cells significantly increased along with tumor progression, development of distant metastasis, and vascular invasion. Furthermore, FAM172A expression rate in mesenchymal circulating tumor cells was significantly higher than that in epithelial circulating tumor cells, which suggested that FAM172A may correlate with malignant degree of tumor. This hypothesis was further verified by FAM172A expression in mesenchymal circulating tumor cells, which was strictly related to tumor aggressiveness factors. Mesenchymal circulating tumor cells and FAM172A detection may predict highrisk stage II colorectal cancer. Our research proved that circulating tumor cells were feasible surrogate samples to detect gene expression and could serve as a predictive biomarker for tumor evaluation.
CITATION STYLE
Cui, C. H., Chen, R. H., Zhai, D. Y., Xie, L., Qi, J., & Yu, J. L. (2017). Detection of FAM172A expressed in circulating tumor cells is a feasible method to predict high-risk subgroups of colorectal cancer. Tumor Biology, 39(6). https://doi.org/10.1177/1010428317699126
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