2.1.

Materials

Formalin-fixed paraffin-embedded slides of cell lines (SK-BR-3, BT-474, T-47D, MDA-MB-231, MDA-MB-468, and MCF-7) were purchased from AMS Biotechnology (Europe) Ltd., Switzerland. Specifications for cell preparation can be found at the AMS Biotechnology’s website. Phosphate-buffered saline (PBS) $10\times$ and Tween20 were purchased from Sigma. PBS $1\times$ was obtained by diluting the concentrated PBS stock in deionized water. For immunostaining, the primary antibodies rabbit antihuman c-erbB-2 oncoprotein primary antibody (HER2, code: A0485) and mouse antihuman cytokeratin (CK, code M3515) were purchased from Agilent Technology (Switzerland) and diluted from the stock in PBS supplemented with Tween 0.05% (PBST 0.05%) to get a final concentration $2.4\mu \mathrm{g}/\mathrm{mL}$ (for HER2) and CK $1.72\mu \mathrm{g}/\mathrm{mL}$ (for CK). Secondary antibodies Alexa Fluor 594 goat antirabbit IgG (H+L, code: A-11037) and Alexa Fluor 647 goat antimouse IgG (code: A-21236) were purchased from Thermo Fisher Scientific (Switzerland) and diluted in PBST 0.05% to get the final concentration of $\text{50\hspace{0.17em}\hspace{0.17em}}\mu \mathrm{g}/\mathrm{mL}$.

2.2.

Fabrication of the Microfluidic Chip

The structure and fabrication of the chip were reported previously.^7,10,14 First, a 4-in. silicon wafer with a $2.5\text{-}\mu \mathrm{m}$ wet-oxide layer was taken, on which $5\text{-}\mu \mathrm{m}$ AZ9260 photoresist was spun, exposed with the channel mask, and developed to form the channels. The oxide underneath was etched by reactive ion etching (601E; Alcatel, France). The resist was stripped, and an additional lithography was realized by spinning $5\text{-}\mu \mathrm{m}$ AZ9260 photoresist (MicroChemicals GmbH, Germany) and exposing the latter to a second mask. After the lithography, the front side was etched in two steps by deep reactive ion etching (DRIE; 601E, Alcatel, France) to form channels and vertical access holes with different depths. First, the wafer was etched to a depth of $100\mu \mathrm{m}$ and the resist was stripped. Thereafter, the channels were etched via the patterned hard mask realized in the first step. The etch depth varied between 50 and $200\mu \mathrm{m}$, depending on the design. Subsequently, the silicon wafer was bonded to a $2\text{-}\mu \mathrm{m}$ parylene-C-coated Pyrex wafer using a low-stress parylene-C bonding procedure. After bonding, additional lithography of the glass/silicon-bonded stack was done on the silicon side using a $8\text{-}\mu \mathrm{m}$-thick AZ9260 resist. Then, one more step of DRIE was performed from the backside until the access holes were reached, a process used at the same time to generate notches for o-ring incorporation. Subsequently, the resist was stripped and oxygen plasma was applied to clean the device. Fabrication was finalized by dicing the glass/silicon micromachined structures into their final shapes [Fig. 1(a)].

Fig. 1

Microfluidic chip for immunostaining: (a) three-dimensional schematics of both sides of the chip, with a zoom on the feed-though holes passing from one side of the chip to the other; scale bar: 1 mm and (b) picture of the experimental setup, with the location of the constitutive elements.

2.3.

Immunofluorescence Staining

Cell slides were deparaffinized in three Histoclear II solutions (National Diagnostics) for 5 min each. Then, they were transferred to gradual ethanol series of 100%, 95%, 70%, and 40%, for 2 min each. Finally, they were put 40 min at 95°C in Target Retrieval Solution Citrate pH 6 (Dako, cose S169984), and then stored in PBS $1\times$ until the staining process. Next, they were stained using the microfluidic tissue processor. For the staining, the chip was mechanically clamped to the sample slide together with a soft (polydimethylsiloxane) o-ring that constitutes the walls of the $100\text{-}\mu \mathrm{m}$-height chamber above the slide. The microfluidic tissue processor was connected to external syringes and pumps via the unique inlet and used to deliver specific antibodies and buffer solutions homogeneously onto the surface of the cell pellet via the tree-like microfluidic channels [Fig. 1(b)]. An automatic syringe pump system delivered the following solutions: PBST 0.05% (flow rate $10\mu \mathrm{L}/\mathrm{s}$ for 12 s), HER2 and CK primary antibody cocktail (flow rate $10\mu \mathrm{L}/\mathrm{s}$ for 12 s then $0.01\mu \mathrm{L}/\mathrm{s}$ for 2 min), PBS $1\times$ wash (flow rate $10\mu \mathrm{L}/\mathrm{s}$ for 30 s), AF594 and AF647 secondary antibody cocktail (flow rate $12\mu \mathrm{L}/\mathrm{s}$ during 5 s then $0.01\mu \mathrm{L}/\mathrm{s}$ for 2 min), PBS $1\times$ wash (flow rate $10\mu \mathrm{L}/\mathrm{s}$ for 30 s), and distilled water (DIW, flow rate $10\mu \mathrm{L}/\mathrm{s}$ during 30 s). After these automatic reagent flushing steps, the slide was removed from the setup and cleaned again in DIW before receiving SlowFade™ Gold Antifade mountant (Life Technologies) containing 4′, 6-diamidino-2-phenylindole (DAPI). The slide was coverslipped and stored in the fridge before imaging. All other slides in the batch were treated in the same manner. The incubation time and the volume of primary and secondary antibodies’ solution were optimized in our previous studies.^7,10

2.4.

Image Acquisition

The whole microscope slide was scanned tile by tile (10% overlap) using the microscope Axio Imager M2m (Zeiss, Germany) with a $20\times$ objective (Plan-Apochromat, numerical aperture = 0.8) in $2\times 2$ binning mode. The exposure time was first adjusted using an HER2+ slide that received primary Abs to reach 80% of the highest nonsaturated exposure. This exposure time and light intensity were kept constant for all slides. In each position, emissions of three fluorophores AF594, AF647, and DAPI, corresponding to HER2, CK, and DAPI signals, respectively, under adaptive excitation lights were recorded and merged into an image. Images were represented by three colors (blue, green, and red), corresponding to the DAPI, CK, and HER2 signals, respectively. After scanning, tiles were stitched using the Axiovision software.

3.1.

Ultrafast and Automated Optical Detection of Biomarkers: Microfluidic Staining and Fluorescence-Based Cell Segmentation

To test the opportunity to characterize clinical controls at the cell level with a rapid and robust procedure, we applied a protocol of immunofluorescence staining to breast cancer cell lines with the microfluidic tissue processor and, subsequently, analyzed the fluorescence images with an automatic processing algorithm. We have chosen to characterize both HER2+ (SK-BR-3 and BT-474) and HER2− (T-47D, MDA-MB-231, MDA-MB-468, and MCF-7) cell lines to find robust parameters for quantification that could be used as clinical controls when staining patient tissues. Based on previous results reporting the importance of both HER2 and CK assessment for potential breast cancer diagnostics,¹⁰ we stained and quantified both biomarkers.

The on-chip protocol was very simple and fast: delivery of the primary Ab cocktail (rabbit antihuman HER2 IgG and mouse antihuman CK IgG) for 12 s; incubation for 2 min, washing for 30 s, delivery of the secondary Ab cocktail (goat antirabbit IgG tagged with A596 and goat antimouse IgG tagged with A647) for 12 s, incubation for 2 min, and washing for 1 min. The entire protocol, including slide removal and coverslip mounting, takes only 5 min. The result of this procedure is shown in Fig. 2. The membrane staining of HER2 is sharp and visible for HER2+ cell lines, as well as the CK in the cytoplasm, whereas only the latter is visible in HER2− cell lines. This is expected because, according to previous research,^7,10 microfluidic immunofluorescence imposes a fast, well-controlled staining that limits nonspecific adsorption of antibodies.

Fig. 2

Immunofluorescence staining and cell segmentation. False-color fluorescence images of biomarkers in the case of an HER2+ cell line (SK-BR-3, a) and an HER2− cell line (T-47D, b) with the segmented version after image processing, in which the white lines define the region of a specific cell. Scale bars: $20\mu \mathrm{m}$.

To analyze the biomarker expression at the cell level, we developed an algorithm to segment the cells in the images. The procedure are as follows:

Examples of the result of this procedure are shown in Fig. 2.

The regions in which the image is partitioned by this algorithm define a cell in the majority of cases, but for those that correspond to the background or to only a part of a cell, we excluded them from all subsequent analysis using robust filtering methods:

3.2.

Quantitative Biomarker Analysis of Breast Cancer Cell Lines

We performed on-chip staining, fluorescence imaging, and image processing on four cases of HER2+ cell lines and four cases of HER2− cell lines. Among the two biomarkers, none of them defines a clear separation between HER+ and HER2− status, and their distributions partially overlap [Fig. 3(a)]. We also plotted the cell-by-cell status in the HER2 versus CK scatter plot [Fig. 3(b)]. We observe that the cells belonging to a particular cell line cluster together in the biomarker expression plot, as expected. Moreover, duplicates of HER2+ cell lines (SK-BR-3 and BT-474) are also close to each other. This indicates that the experimental and analytical procedure reliably quantifies the expression of the biomarkers despite the potential technical variations of the staining and the imaging steps (e.g., excitation light intensity, washing efficiency, and temperature) between a slide and another, which can explain the small differences between duplicates of the same cell line. Furthermore, we observe that HER2+ and HER2− cell lines likely cluster apart following a straight line with positive slope. This can provide a robust method to distinguish between positive and negative cases.

Fig. 3

Biomarker status in breast cancer cell lines: (a) box-plot of CK and HER2 expression for several cell lines and (b) HER2 expression versus CK expression for several cell lines.

To test a potential diagnostic criterion to split HER2+ and HER2− cells using a simple straight line in the biomarker-expression scatter plot, we calculated the number of true negatives (TN), true positives (TP), false negatives (FN), and false positives (FP) from the scatter plot for all the possible straight lines with positive slope. These quantities are defined as: true (resp. false) positives all the HER2+ (resp. HER2−) cells lying above the line and true (resp. false) negatives all the HER2− (resp. HER2+) cells lying below the line. We subsequently calculated the sensitivity ($\mathrm{Se}=\frac{\mathrm{TP}}{\mathrm{TP}+\mathrm{FN}}$), the specificity ($\mathrm{Sp}=\frac{\mathrm{TN}}{\mathrm{TN}+\mathrm{FP}}$), and the informedness ($\mathrm{In}=\mathrm{Se}+\mathrm{Sp}-1$) of the test [Fig. 4(a)], which are major clinically relevant parameters used in the field of diagnostics.¹⁵ We observe that sensitivity and specificity are mainly mutally exclusive [Fig. 4(a) left and middle] as expected,¹⁵ but there is a region within which any straight line splits the positive and the negative populations of cells in a very reliable fashion with In $>99\%$ [Fig. 4(a) right]. This could, therefore, provide an effective and robust diagnostic criterion for HER2-type breast carcinoma, using HER2+ and HER2− cell lines as control samples to set the threshold line [Fig. 4(b)].

Fig. 4

Diagnostics analysis based on biomarker expression. (a) Sensitivity, specificity, and informedness of a potential diagnostic test that uses a straight line to split HER2+ and HER2− cells, as a function of its slope and intercept in the HER2-/CK-expression scatter plot. (b) HER2-/CK-expression scatter plot. Any straight line included in the gray-shaded region provides informedness $>99\%$.

Beyond the information on the biomarker expression, we explored the possibility to use the cell size as another indicator of the cancer status (Fig. 5) and found that the performance in the discrimination of cells is much less effective (i.e., lower informedness), which confirms the similarity in size of HER2+ and HER2− cancer cells identifiable in cancer tissues.^4,10

Fig. 5

Diagnostics analysis based on biomarker expression and cell size. (a) and (b) Sensitivity, specificity, and informedness of a potential diagnostic test as in Fig. 4, but using the cell size as variable together with one of the two biomarkers.

Finally, to quantitatively compare to what was observed previously on tissue samples at a tile level,¹⁰ we computed the average cell HER2/CK ratio of the different samples and showed it together with the HER2 signal of the same samples (Fig. 6). When using the HER2 signal alone [Fig. 6(a)], the 95% confidence intervals of HER2− and HER2+ samples overlap, which show the indistinguishability of the two types. Whereas, when adjusting for CK expression at single-cell level [Fig. 6(b)], the two types are much more separated.

Fig. 6

HER2 signal versus HER2/CK ratio. (a) Cell-based HER2 signal, average and 95% confidence interval for the positive and negative cell lines. (b) Cell-based HER2/CK, average and 95% confidence interval for the positive and negative cell lines.