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  • Title: Highly Sensitive Colorimetric Cancer Cell Detection Based on Dual Signal Amplification.
    Author: Yu T, Dai PP, Xu JJ, Chen HY.
    Journal: ACS Appl Mater Interfaces; 2016 Feb; 8(7):4434-41. PubMed ID: 26824724.
    Abstract:
    Facile and efficient detection of cancer cells at their preclinical stages is one of the central challenges in cancer diagnostics. A direct, rapid, highly sensitive and specific biosensor for detection of cancer biomarkers is desirable in early diagnosis and prognosis of cancer. In this work, we developed, for the first time, an easy and intuitive dispersion-dominated colorimetric strategy for cancer cell detection based on combining multi-DNA released from an aptamer scaffold with cyclic enzymatic amplification, which was triggered by aptamer DNA conformational switch and demonstrated by non-cross-linking gold nanoparticles (Au NPs) aggregation. First, five kinds of messenger DNAs (mDNAs) were aligned on the cancer cell aptamers modified on magnetic beads (MBs) to form mDNAs-Apt-MBs biocompatible nanosensors. In the presence of target cells, the aptamer would bind to the receptors on the cell membranes, and mDNAs would be released, resulting in the first amplification that one biological binding event would cause the release of multiple kinds of mDNAs simultaneously. After magnetic separation, the released mDNAs were introduced into the cyclic enzymatic amplification to cleave more single strand DNA (ssDNA) fragments. Instead of modification of Au NPs, these fragments and mDNAs could be adsorbed on the surface of Au NPs to prevent particle aggregation and ensure the stability and color of solution in high salt environments. The linear response for HL-60 cells in a concentration range from 10 to 10(4) cells was obtained with a detection limit of four cells in buffer solution. Moreover, the feasibility of the proposed strategy was demonstrated in a diluted serum sample. This dual signal amplification method can be extended to other types of cancer cells, which has potential application in point-of-care cancer diagnosis.
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