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. 2018 Nov 19;2:26.
doi: 10.1038/s41698-018-0069-7. eCollection 2018.

Superhydrophobic Lab-On-Chip Measures Secretome Protonation State and Provides a Personalized Risk Assessment of Sporadic Tumour

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Free PMC article

Superhydrophobic Lab-On-Chip Measures Secretome Protonation State and Provides a Personalized Risk Assessment of Sporadic Tumour

N Malara et al. NPJ Precis Oncol. .
Free PMC article

Abstract

Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual's diagnosis and/or help clarify risk in healthy populations.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Super-hydrophobic chip incorporates five gold electrodes in a line for site-selective measurements of a solution (a). Individual silicon micropillars are modified to incorporate gold nano-electrodes, an intermediate layer of C4F8 and a superficial layer of the conductive PEDOT:PSS polymer, bar in the inset is 5 μm (b). Sensors are positioned from the centre (S3) to the border (S1, S5) of the device; the output of each sensor is a function of time I(t) that reaches a constant value in a characteristic time τ; the intensity of I is proportional to the externally applied voltage V (c). Convenient post-processing of a sample enables super-hydrophobicity with contact angles as large as 165° (d). SEM micrographs of the device magnified at small magnification factors (e). SEM micrograph of the device shows the gold nano-electrodes positioned on the pillar surface for localized sensing (f). Due to super-hydrophobicity, biological solutions can be manipulated and connected to an external gate during operation (g). The images were partially adapted from https://www.nature.com/articles/srep18992
Fig. 2
Fig. 2
Device response. The response of the sensor, in the analyses of a secretome made by cultures of non-haematological cells isolated by liquid biopsy of control and cancer patients, is described by the sole two parameters modulation m and time constant τ. mτ scatter plots evaluated for different values of applied voltage V and sensor position S are descriptive of the physical characteristics of the system. Sample separation is operated for high values of voltage and elevated sample numbers. In the diagrams, white label represents control subject (C, without cancer), black label represents patients (P, with cancer) and light-grey label represents intermediate category (I, suspected with cancer)
Fig. 3
Fig. 3
Data analysis of a secretome made by cultures of non-haematological cells isolated by liquid biopsy of control and cancer patients. Bar chart plots of modulation m (b) and time constant τ (c) at sensor S5 for all samples are reported as a function of V. (d) Scatter plot of each mτ pair is a point whose position varies depending on V. On varying V in the V1V5 interval, mτ doublets delineate a trajectory distinctive of measured samples. Trajectories associated to different sample types, i.e. control, patients and intermediate samples, are not intersecting. mτ scatter plot of the whole data set acquired at V5S5 is reported with (d) and without (e) identification labels. Data set into clusters (f), correctly operates assignation of C and P samples into two different groups
Fig. 4
Fig. 4
Data set of the secretome made by cultures of non-haematological cells isolated by liquid biopsy of control and cancer patients measured through the device was subjected to ANOVA analysis. Graphical ANOVA from Bonferroni post hoc test shows control C dissimilar from patients P samples with a 95% confidence interval and 5% significance level, for both time constant (a, b) modulation (c, d) measured variables. Interaction plots carried out on time constant (b) modulation (d) outputs, showing significant discrimination between C and P samples for values of potential at the gate V higher than V3. PCA analysis performed to reduce noise and extract from the whole data set combinations of voltage and sensor number, VS, in correspondence of which sample separation may be optimized (e)
Fig. 5
Fig. 5
Data clustering and sample identification. On the basis of PCA analysis, we selected the best combinations of voltage, sensor position, modulation and time constant that optimize the response of the device and maximize separation of the sample of secretome made by cultures of non-haematological cells isolated by liquid biopsy of control and cancer patients, between variables (af). For all considered configurations, data were clustered into control and patient groups with a specificity up to 100% with the exception of configuration (c), where matching the efficiency of classification is nearly 93%
Fig. 6
Fig. 6
Characterization of secretome in conditioned medium by blood-derived cultures 14 days aged. a Spectrophotometric quantification in the secretome of proteins, DNA double strands, RNA and DNA single strand. b Correlation between in vitro (conditioned medium (MC)), and in vivo tumour microenvironment (interstitial fluid phase of tumours (TM)) in the same patient, **r = 0.8; ***r = 0.9. c of the MS fragment ions by mass spectrometry. c Heatmap shows cytokines in a conditioned medium: row represents a patient and column a cytokine. Color intensity represents the levels of cytokine. Each cytokine in the data matrix is obtained through averaging two values quantified on cytokine-array membranes. The error bars are the sum of standard deviations between two values of pixel intensity for each of the patients. d Plots by repeated measures ANOVA show distributional levels of the cytokines in control and patients’ groups (p < 0.05). e Isoelectrofocusing assay on conditioned medium shows the pH value at which the net surface charge switches its sign. f Comparative levels of methylglyoxal (MG) glycation end products (MEGs) in MC assessed through immunoblotting. g Intracellular localization by immunofluorescence with antibodies against MGEs (green) and p21 (red) in breast cancer cases (reported in Data file S2). Scale bars 10 μm. h Kaplan–Meier curves show a worst prognosis for patients with secretome content high levels of MGEs
Fig. 7
Fig. 7
Schematic drawing of samples’ trace and correspondent MS profiles. The trajectory moves from control (grey) to patients (black). Intermediated samples (green) are localized at approximately the halfway point. The right-hand image shows mass spectrometry results performed on MC samples from control and patients groups. High-resolution single-ion monitoring MS, shows the pseudo molecular ion signal of G-H1, MG-H1, methionine and CEL, corresponding to, respectively, ([M+H]+), ([M−H]−), ([M+H]+) and ([M+H]+)

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