Research Papers:
CD133+CD54+CD44+ circulating tumor cells as a biomarker of treatment selection and liver metastasis in patients with colorectal cancer
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Abstract
Chao Fang1,2,*, Chuanwen Fan1,2,*, Cun Wang1, Qiaorong Huang3, Wentong Meng3, Yongyang Yu1, Lie Yang1, Zhihai Peng4, Jiankun Hu1, Yuan Li2, Xianming Mo3, Zongguang Zhou1,2
1Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, China
2Institute of Digestive Surgery, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
3Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
4Department of General Surgery, Shanghai First People’s Hospital, Shanghai Jiaotong University, Shanghai, China
*These authors have contributed equally to this work
Correspondence to:
Zongguang Zhou, email: [email protected]
Xianming Mo, email: [email protected]
Keywords: colorectal cancer, circulating tumor cells, CD133+CD54+CD44+ cellular subpopulation, liver metastasis, predictive biomarker
Received: February 25, 2016 Accepted: September 20, 2016 Published: October 15, 2016
ABSTRACT
Introduction: Liver is the most common site of distant metastasis in colorectal cancer (CRC). Early diagnosis and appropriate treatment selection decides overall prognosis of patients. However, current diagnostic measures were basically imaging but not functional. Circulating tumor cells (CTCs) known as hold the key to understand the biology of metastatic mechanism provide a novel and auxiliary diagnostic strategy for CRC with liver metastasis (CRC-LM).
Results: The expression of CD133+ and CD133+CD54+CD44+ cellular subpopulations were higher in the peripheral blood of CRC-LM patients when compared with those without metastasis (P<0.001). Multivariate analysis proved the association between the expression of CD133+CD44+CD54+ cellular subpopulation and the existence of CRC-LM (P<0.001). The combination of abdominal CT/MRI, CEA and the CD133+CD44+CD54+ cellular subpopulation showed increased detection and discrimination rate for liver metastasis, with a sensitivity of 88.2% and a specificity of 92.4%. Meanwhile, it also show accurate predictive value for liver metastasis (OR=2.898, 95% C.I.1.374–6.110).
Materials and Method: Flow cytometry and multivariate analysis was performed to detect the expression of cancer initiating cells the correlation between cellular subpopulations and liver metastasis in patients with CRC. The receiver operating characteristic curves combined with the area under the curve were generated to compare the predictive ability of the cellular subpopulation for liver metastasis with current CT and MRI images.
Conclusions: The identification, expression and application of CTC subpopulations will provide an ideal cellular predictive marker for CRC liver metastasis and a potential marker for further investigation.
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