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An ultra-sensitive biosensor to investigate Random Telegraph Noise in human breast cancer cells
* 1, 2 , 2 , 2
1  Department of Computer Science, Centre for Accountable, Responsible and Transparent AI (ART-AI), University of Bath, Bath, United Kingdom
2  Department of Electronic and Electrical Engineering, Centre for Biosensors, Bioelectronics and Biodevices (C3Bio), University of Bath, Bath, United Kingdom (registering DOI)

Breast cancer is a leading cause of death in women worldwide and yet its pathophysiology is poorly understood. Although single-cell studies have highlighted the contribution of membrane depolarisation to the proliferation of breast cancer, dynamic signalling at a network level has not been extensively researched. It is urgent therefore to decode the intercellular signalling patterns linked to metastasis, particularly at a cell cohort level. This paper introduces a novel strategy for conducting such recordings on highly metastatic MDA-MB-231 cells, via an ultra-low noise biosensor based on a large electrode area which maximises the Helmholtz double-layer capacitance. The extracellular sensitivity of our biosensor allows, for the first time, the detection of pA level Random Telegraph Signal (RTS) noise superimposed with an omnipresent 1/f noise. The RTS noise is validated and modelled using a Markov chain. The analysis of slow cooperative potentials across the large area electrode suggests the involvement of cohort calcium signalling, and the 1/f noise analysis suggests a strong contribution of resting membrane noise. Overall, this work shows the potential of the new recording platform and statistical analysis for better understanding and predicting the underlying signalling mechanisms of metastatic breast cancer cells. In future, this platform could highlight the effects of compounds, or drugs, on the underlying activity of cancer cell cohorts in a clinical setting.

Keywords: RTS noise; 1/f noise; breast cancer; multi-electrode arrays; extracellular sensing