Li, XiaokangSoler Aznar, MariaBelushkin, AlexanderYesilköy, FilizAltug, Hatice2018-02-272018-02-272018-02-272018-02-2310.1117/12.2289721https://infoscience.epfl.ch/handle/20.500.14299/145055Cell signaling activities play a critical role in physiological and disease processes. The analysis of the tumor microenvironment or the immune system activation is nowadays providing valuable insights towards disease understanding and novel therapies development. Due to the various dynamic profiles, it is essential to implement a continuous monitoring methodology for accurate analysis. The current fluorescent and colorimetric approaches hinder such applications due to their multiple time-consuming steps, molecular labeling, and the ‘snapshot’ endpoint readouts. Photonics technology, and especially nanoplasmonic biosensors offer a unique opportunity to implement lab-on-a-chip systems that provide highly sensitive and label-free analysis of cell signaling events in real time. Here, we will present a microfluidics-integrated nanoplasmonic biosensor for long-term and real-time monitoring of cell secretion activity. The biosensor consists of a gold nanohole array supporting extraordinary optical transmission (EOT), which has been optimized to enable ultra-sensitive and high-throughput biomolecular detection. The nanobiosensor is integrated with a specifically designed microfluidic system that provides well-controlled cell culture conditions for long-term monitoring. We achieved an outstanding sensitivity for the detection of vascular endothelial growth factor (VEGF) directly secreted from microfluidic-cultured cancer cells. We demonstrated real-time monitoring for over 10 hours, preserving good cell viability. The multiplexing capability of our nanobiosensor could enable simultaneous analysis of different cell types and molecules-of-interest. Thus, our innovative approach of probing live cells can be a powerful tool to evaluate cellular activities for diagnostics and novel therapy development.Optofluidic nanoplasmonic biosensor for label-free live cell analysis in real timetext::conference output::conference proceedings::conference paper