SiNW-based Biosensors for Profiling Biomarkers in Breast Tumor Tissues

Breast cancer is the most common life-threatening malignancy in women of most developed countries today, with approximately 200,000 new cases diagnosed every year. About 30% of these cases progress to metastatic disease and death. Considering that one-third of these cancer deaths could be decreased if detected and treated early, new strategies for early breast cancer detection are needed to improve the efficacy of current diagnostics. The sensitive analysis of proteins such as breast cancer biomarkers has become the focus of intensive research due to its relevance to tumor diagnosis. However, the state-of-the-art diagnostic tools still lack the level of resolution needed for the detection of biomarkers at the very early stage of the disease, when treatments have more probability of success, and when protein concentration in tumor tissue is still very low. Nanotechnologies have shown great potential for the development of high-sensitive, portable devices for clinical applications. In particular, SiNWs with their unique properties such as the high surface-to-volume ratio and size, combined with the specificity of immune-sensing, are natural candidates for the fabrication of nanosensors. Thanks to their compatibility with conventional CMOS technology, SiNWs have been incorporated in standard FETs. In biosensing, SiNW-FETs have been shown a promising method for the label-free detection of trace amounts of biomolecules. However, detection of Antigen using Antibody immobilized SiNW-FETs is limited by ionic screening effects that reduce the sensor responsiveness and limit their applicability in tumor tissue. Here, we propose novel SiNW-based biosensing strategies with the aim of overcoming current sensitivity limitations of conventional SiNW-FET biosensors for the detection of breast cancer biomarkers in real human samples. Specifically, we address this goal by investigating two different approaches of biosensing. In the first method, we push the sensitivity of SiNW-FETs to their limits by proposing an alternative way of doing sensing in dry conditions. We show that in-air electrical measurements of Ab-Ag binding have the big advantage of increased Debye screening length in non-bulk solutions, and enable highly sensitive and specific measurements in breast tumor extract. Then, we present a completely novel biosensing paradigm that shows, for the first time, the use of memristive effects in fabricated SiNWs for biodetection purposes. This novel detection method has been named Voltage Gap (VoG)-biosensing as it is based on the changes of the VoG parameter, observed in the hysteretic characteristic of memristive devices, as a function of biomolecules. In this research, we demonstrate the use of the memristive-based VoG effect in Schottky Barrier SiNWs for the high-resolution sensing of ionic and biological species both in ideal buffer solutions and in tumor tissue extracts. Moreover, we propose an original theory enabling the physical interpretation and prediction of the mechanisms underlying the VoG-biosensing method in memristive devices. Finally, we demonstrate the potential of our system for future integration in a multi-panel VoG-biosensing platform. We fabricated a PDMS microfluidics enabling selective and high-quality functionalization of the NWs. We also realized a CMOS readout circuit for multiplexed VoG acquisition. The simulations demonstrate the feasibility of the approach and the potential for the integration of the reader with a portable and automated biosensing platform. Microfluidics and VoG reader will enable fast, concurrent detection ofmultiple angiogenic and inflammatory ligands in tumor tissue. This will highly improve the level of knowledge of the cancer disease by capturing the heterogeneity and the complexity of the tumor microenvironment, thus leading to novel opportunities in breast cancer diagnosis.

De Micheli, Giovanni
Carrara, Sandro
Lausanne, EPFL
Other identifiers:
urn: urn:nbn:ch:bel-epfl-thesis7013-7

 Record created 2016-05-18, last modified 2018-05-01

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