A label-free microfluidic chip for the highly selective isolation of single and cluster CTCs from breast cancer patients

BACKGROUND: Circulating tumor cells (CTCs) existing in peripheral blood can be used to predict the prognosis and survival of cancer patients. The study was designed to detect circulating tumor cells and circulating tumor single cell genes by applying microfluidic chip technology. It was used to explore the clinical application value in breast cancer. METHODS: We have developed a size-based CTCs sorting microfluidic chip, which contains a hexagonal array and a micro-pipe channel array to isolate and confirm both single CTCs and CTCs clusters. The sorting performance of the as-fabricated chip was tested by analyzing the clinical samples collected from 129 breast cancer patients and 50 healthy persons. RESULTS: In this study, the chip can detect different immunophenotypes of CTCs in breast cancer patients. It was found that the new microfluidic device had high sensitivity (73.6%) and specificity (82.0%) in detecting CTCs. By detecting the blood samples of 129 breast cancer patients and 50 healthy blood donors, it was found that the number of CTCs was not associated with clinical factors such as age, gender, pathological type, and tumor size of breast cancer patients (P > 0.05), but was associated with TNM staging of breast cancer, with or without metastasis (P < 0.005). There was a statistically significant difference in the number of CTCs between luminal A (ER+/PR+/HER2-) and HER-2+ (ER-/PR-/HER2+) (P < 0.05). The best cut-off level distinguished by CTC between the breast cancer patients and the healthy persons was 3.5 cells/mL, with 0.845 for AUC-ROC, 0.790–0.901 for 95% CI, 73.6% for sensitivity, and 82% for specificity (P = 0.000). The combination of CTC, CEA, CA125 and CA153 can provide more effective breast cancer screening. CONCLUSIONS: The CTCs analysis method presented here doesn't rely on the specific antibody, such as anti-EpCAM, which would avoid the missed inspection caused by antibody-relied methods and offer more comprehensive biological information for clinical breast cancer diagnosis and treatment.