Label-free capture of breast cancer cells spiked in buffy coats using carbon nanotube antibody micro-arrays

Abstract

We demonstrate the rapid and label-free capture of breast cancer cells spiked in buffy coats using nanotube-antibody micro-arrays. Single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (EpCAM) antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester functionalization method. Following functionalization, plain buffy coat and MCF7 cell spiked buffy coats were adsorbed on to the nanotube device and electrical signatures were recorded for differences in interaction between samples. A statistical classifier for the 'liquid biopsy' was developed to create a predictive model based on dynamic time warping to classify device electrical signals that corresponded to plain (control) or spiked buffy coats (case). In training test, the device electrical signals originating from buffy versus spiked buffy samples were classified with ~100% sensitivity, ~91% specificity and ~96% accuracy. In the blinded test, the signals were classified with ~91% sensitivity, ~82% specificity and ~86% accuracy. A heatmap was generated to visually capture the relationship between electrical signatures and the sample condition. Confocal microscopic analysis of devices that were classified as spiked buffy coats based on their electrical signatures confirmed the presence of cancer cells, their attachment to the device and overexpression of EpCAM receptors. The cell numbers were counted to be ~1-17 cells per 5 µl per device suggesting single cell sensitivity in spiked buffy coats that is scalable to higher volumes using the micro-arrays.

Static micro-array isolation, dynamic time series classification, capture and enumeration of spiked breast cancer cells in blood: the nanotube–CTC chip

“…Non-specific samples such as plain blood also create such spikes in the electrical conductance versus time data, with much lower slopes. The philosophy behind this work is whether such spikes in the signals could carry meaningful information about the sample condition/interaction that could then be analyzed using microscopy of captured CTCs [23]. …”

“…This type of classification enabled us to analytically distinguish between devices that showed positive versus negative responses in an array. A kernel-based classifier employing dynamic time warping (DTW) was then used to classify the signatures that represented specific versus non-specific interactions [23]. These were classified with ~90% sensitivity and ~90% specificity in classifying devices specifically based on Her2 signatures for spiked SKBR3 (breast adenocarcinoma) cells in blood.…”

Classification of biosensor time series using dynamic time warping: applications in screening cancer cells with characteristic biomarkers

“…A digital device by which small drops of blood could be rapidly analyzed by microarrays for the detection of CTCs in the clinic would thus have great utility. 13,14 We hypothesized that a CNT device functionalized with an antibody would allow for the rapid detection of CTCs. These devices rely on the principle that each cancer cell possesses thousands of overexpressed particular target receptors, so that cooperative binding to cognate antibodies would yield characteristic spikes in the electrical signal due to free energy change.…”

“…The reduction in free energy for specific interactions is much higher than nonspecific interactions, and one can use CNT arrays to transduce the change in free energy into electrical signal. 14 From such a CNT array, a characteristic signature indicating specific interactions (CTCs present) versus a characteristic signature indicating only nonspecific interactions (CTCs not present) could be captured. Details of the nanofabrication devices used in this article have been previously discussed by Khosravi et al 14 …”

“…14 Human Buffy Coats were used from Biorepositories at the University of Louisville. The study was approved by the University of Louisville Institutional Review Board (IRB) #10.0428 and the IRB at Worcester Polytechnic Institute IRB #00007374.…”