Nanofiber-integrated miniaturized systems: an intelligent platform for cancer diagnosis
Cancer diagnostic tools enabling screening, diagnosis, and effective disease management are essential elements to increase the survival rate of diagnosed patients. Low abundance of cancer markers present in large amounts of interferences remains the major issue. Moreover, current diagnostic technolo...
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Veröffentlicht in: | Analytical and bioanalytical chemistry 2019-07, Vol.411 (19), p.4251-4264 |
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Sprache: | eng |
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Zusammenfassung: | Cancer diagnostic tools enabling screening, diagnosis, and effective disease management are essential elements to increase the survival rate of diagnosed patients. Low abundance of cancer markers present in large amounts of interferences remains the major issue. Moreover, current diagnostic technologies are restricted to high-resourced settings only. Integrating nanofibers into miniaturized analytical systems holds a significant promise to address these challenges as demonstrated by recent publications. A large surface area, three-dimensional porous network, and diverse range of functional chemistries make nanofibers an excellent candidate as immobilization support and/or transduction elements, enabling high capture yield and ultrasensitive detection in miniaturized devices. Functional nanofibers have thus been used to isolate and detect various cancer-related biomarkers with a high degree of success in both on-chip and off-chip platforms. In fact, the chemical and functional adaptability of nanofibers has been exploited to address the technical challenges unique to each of the cancer markers in body fluids, where circulating tumor cells are prominently investigated among others (proteins, nucleic acids, and exosomes). So far, none of the work has exploited the nanofibers for cancer-derived exosomes, opening an avenue for further research effort. The trend and future prospects signal possibilities to strengthen the implementation of nanofiber-miniaturized system hybrid for a next generation of cancer diagnostic platforms both in clinical and point-of-care testing. |
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ISSN: | 1618-2642 1618-2650 |
DOI: | 10.1007/s00216-019-01589-5 |