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A quantum dot-based microfluidic multi-window platform for quantifying the biomarkers of breast cancer cells† Seyong Kwon,a Minseok S. Kim,b Eun Sook Lee,c Jang Sihn Sohnd and Je-Kyun Park*a Conventional molecular profiling methods using immunochemical assays have limits in terms of multiplexity and the quantification of biomarkers in investigation of cancer cells. In this paper, we demonstrate a
Received 27th October 2013, Accepted 11th February 2014
quantum dot (QD)-based microfluidic multiple biomarker quantification (QD-MMBQ) method that enables labeling of more than eight proteins immunochemically on cell blocks within 1 h, in a quantitative manner.
DOI: 10.1039/c3ib40224j
An internal reference, b-actin, was used as a loading control to compensate for differences in not only the cell number but also in staining quality among specimens. Furthermore, the microfluidic blocking method
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exhibited less nonspecific binding of QDs than the conventional static blocking method.
Insight, innovation, integration Immunochemical assay using an antibody-based molecular detection technology can provide information on both cellular morphology and the quantities of molecules within cells (immunocytochemistry) or tissues (immunohistochemistry). In this field, multiplexed protein quantification remains difficult using conventional methods. Here, we demonstrate a new analytical concept that integrates a microfluidic multiplexing platform and a QD double-staining method. The microfluidic double-staining method enabled accurate quantification by normalization of biomarker levels to that of b-actin as an internal reference. This novel molecular profiling method will accelerate cancer cell studies and the development of diagnostic tools for personalized medicine.
Introduction The development of an accurate, quantitative molecular profiling technology for cellular materials remains a challenge for investigation of cell physiology, drug responses, and fatal diseases such as various types of cancer.1 In particular, a molecular profiling-based personalized cancer diagnosis system is desirable because a considerable number of cancer patients do not benefit from existing therapeutics, including molecular-targeted drugs.2–5 Indeed, breast cancer has a high recurrence rate due to its heterogeneity.6,7 Thus, there is a need for tailored treatment strategies for breast cancer.
a
Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea. E-mail: [email protected]; Tel: +82-42-350-4315 b Samsung Advanced Institute of Technology, 97 Samsung 2-ro, Giheung-gu, Yongin-si, Gyeonggi-do 446-712, Republic of Korea c Research Institute and Hospital, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do 410-769, Republic of Korea d Department of Pathology, College of Medicine, Konyang University, 158 Gwanjeodong-ro, Seo-gu, Daejeon 302-718, Republic of Korea † Electronic supplementary information (ESI) available: Fig. S1 and S2. See DOI: 10.1039/c3ib40224j
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Understanding the complex molecular mechanisms of individual cancer cells requires molecular detection of multiple proteins at the single-cell level. Among the existing molecular detection technologies (e.g., polymerase-chain reaction, western blotting, mass spectrometry, and enzyme-linked immunosorbent assay), only immunocytochemistry (ICC) or immunohistochemistry (IHC) can provide information on both morphology and the quantity of molecules, which is not possible with other techniques that involve destruction of cellular structures. Quantum dot (QD) nanoparticles enable multiplexed protein detection in immunochemical assays due to their superior optical properties, such as brightness, narrow emission peak, photobleaching resistance, large Stokes shift, and simultaneous excitation of multiple fluorescence colors.8–11 In recent reports, however, the number of proteins that can be analyzed using multiplexed QD-immunochemical assay techniques has been limited to four or five.12–14 To increase the number of proteins in QD multiplexing methods, several approaches have been attempted; to date, all were unsuccessful or inefficient. For example, for the multiplexed use of primary antibodies (Abs), QDs were directly conjugated to primary Abs. This makes the multiplexed assay process easier and faster. Nevertheless, this
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method has disadvantages in its preparation process. Due to the harsh conditions of Ab conjugation to QDs, it consumes a considerable amount of Abs and time that is not efficient for the use of large numbers of biomarkers. A sequential QD multiplexing method is more flexible to overcome these problems and could be used to identify a number of proteins by labeling with different Abs from the same species. However, this method requires multiple blocking steps between sequential reactions. Due to the processing time required per reaction, this also requires more than 3 h using conventional methods; thus labeling large numbers of proteins is laborious and time-consuming. Moreover, recent multiplexed QD-based IHC studies showed that the sequential QD multiplexing method caused distorted results.15–17 Previously, we reported a microfluidic immunochemical assay platform that enabled simultaneous detection of multiple proteins by dividing a cell block or tissue section into several isolated areas by means of reversible bonding of a PDMS microfluidic layer with multiple parallel channels on the cell or tissue slide directly.18,19 A multiple-channel layout can be used with simultaneous incubation of multiple Abs on the sample slide. Although this method can be used to increase the maximum multiplexing number in immunochemical assays, protein quantification was difficult due to the lack of a robust quantification method. In this report, we developed an accurate QD-based microfluidic multiple biomarker quantification (QD-MMBQ) method that facilitated determination of the levels of proteins of interest at the single-cell level. For the accurate quantitative analysis of several proteins in the same biological specimen, we exploited the normalization concept using a microfluidic immunochemical assay platform by co-labeling the loading control (LC) protein with a different target protein in each microchannel. Expression levels of eight proteins in various cell lines were compared by co-labeling a different target protein and the same LC in each microchannel. Our microfluidic method represents a flexible and rapid multiplexed QD-immunochemical assay technique, facilitating analysis of the data and more accurate quantification of biomarkers.
Results and discussion Crosstalk of QD-conjugated secondary Abs As noted above, crosstalk of QD-conjugated secondary Abs is regarded as a key technical problem in QD-multiplexed immunostaining. Prior to the development of microchannel QD-multiplexing methods, validation of several QD-multiplexing techniques was performed to avoid nonspecific binding of QD particles. A formalin-fixed paraffin-embedded cell block was used to address QD multiplexing problems systematically. The breast cancer cell line SK-BR-3 strongly expresses HER2 in the membrane and Ki-67 in the nucleus. To investigate the staining tendency of a sequential method, a single primary Ab species and different-color-QD-conjugated secondary Abs (QD525-conjugated anti-rabbit Ab and QD605-conjugated anti-rabbit Ab) were used to sequentially label HER2 (rabbit) and Ki-67 (rabbit). Primary Abs from different species and different-color-QD-conjugated secondary
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Fig. 1 Staining of HER2 with QD525, and Ki-67 with QD605 on SK-BR-3 cell-block sections. (A) HER2 was labeled with a rabbit anti-HER2 Ab and QD525-conjugated goat anti-rabbit Ab. (B) Ki-67 was labeled with a rabbit anti-Ki-67 Ab and QD605-conjugated goat anti-rabbit Ab. (C–E) HER2 and Ki-67 were stained in the order, rabbit anti-HER2, QD525-conjugated goat anti-rabbit, rabbit anti-Ki-67, and QD605-conjugated goat anti-rabbit Abs. The fluorescence image obtained using a long-pass fluorescence filter (C) to receive the total QD525 and QD605, and the individual QD525 (D) and QD605 (E) fluorescence signals; the latter were obtained using a band-pass fluorescence filter. (F–H) HER2 and Ki-67 were stained in the order, rabbit anti-Ki-67, QD605-conjugated goat anti-rabbit, rabbit antiHER2, and QD525-conjugated goat anti-rabbit Abs. The total fluorescence image obtained using a long-pass fluorescence filter (F), and individual QD525 (G) and QD605 (H) fluorescence signals. (I–K) HER2 and Ki-67 were labeled using a cocktail method with a mixture of mouse anti-HER2 and rabbit anti-Ki-67 Abs, and a mixture of QD525-conjugated goat antimouse and QD605-conjugated goat anti-rabbit Abs. The total fluorescence image obtained using a long-pass fluorescence filter (I), and individual QD525 (J) and QD605 (K) fluorescence signals.
Abs (QD525-conjugated anti-mouse Ab and QD605-conjugated anti-rabbit Ab) were also used to label HER2 (mouse) and Ki-67 (rabbit) using a cocktail method (a mixture of primary Abs produced by different species), which is widely used for QD-based detection of two or three biomarkers. Control data were obtained by QD staining for each protein separately. Typical sequential and cocktail staining results are shown in Fig. 1. Notably, the sequential QD staining results showed that the last-in-sequence QD-conjugated secondary Abs bound not only to the final primary Abs but also to previous primary Abs despite the blocking process that is supposed to prevent such unintended binding. This was demonstrated by changing the multiplexing order and observing the localization of the QD-conjugated secondary Abs (Fig. 1). Increasing the incubation time of the QD-conjugated secondary Abs so that the binding sites of the primary Abs were fully occupied for 2 h, had no effect on this phenomenon (see ESI,† Fig. S1). This problem is critical because unintended QD labeling of primary Abs will result in both IHC and ICC being compromised by inaccurate protein localization information and incorrect measurements of protein quantities (Fig. 1E and G). This hinders the study of cell and protein functions, such as protein translocalization, using IHC or ICC. Using a cocktail method, multiple QD conjugates were labelled on the desired proteins (Fig. 1J and K). HER2 proteins (cell membrane) were labelled specifically with QD525, and Ki-67 proteins (nucleus) with QD605. The same staining tendencies were also observed with microfluidic staining (data not shown).
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Although the cocktail method has benefits in QD multiplexing, such as high selectivity due to use of primary Abs that originate from different species, the QD multiplexing number is limited to three or four due to the number of commercially available Ab-producing species (mouse, rabbit, rat, goat, etc.).
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Microfluidic biomarker screening For the accurate quantitative analysis of large numbers of proteins in the same biological specimen, we exploited the normalization concept using a microfluidic immunochemical assay platform by co-labeling the LC with a different target protein in each microchannel (Fig. 2). Since the cocktail method is useful for multiplexing of small numbers of proteins with QDs, such as by reducing the total process time and involving high selectivity, we applied a cocktail method to develop our QD-MMBQ technique. Blocking is important in QD-based immunochemical assay to control nonspecific binding of QDs. To investigate the efficiency of the blocking process in association with microfluidics, two cell-block sections were treated with blocking solution; one was incubated statically (conventional method), while the other was incubated with flow. After blocking for 30 min, the sections were incubated with QD605–secondary Ab conjugates for 1 h. The flow-based blocking section showed a significant decrease in the nonspecific binding of QDs at a flow rate of 6 mL h 1 (Fig. 3A). Furthermore, the data indicate that the conventional static incubation method cannot
Fig. 2 Schematic of the QD-based microfluidic multiple biomarker quantification (QD-MMBQ) method. In step 1, the reference marker Ab and each biomarker Ab, originating from different species, were reacted with the cell-block section within the microchannel. Here, the reference marker stained the cytoplasm, while each biomarker stained the nuclear region. In step 2, two types of QDs conjugated with the various secondary Abs (goat anti-rabbit Ab and goat anti-mouse Ab) were reacted with the cell-block section on the microchannel. Inset a and b in each step indicate the area of the circle in each microchannel.
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Fig. 3 Result of QD-secondary Ab incubation with blocking solution under flow and static conditions. (A) MCF-7-cell-block sections were incubated with blocking solution under microfluidic flow for 30 min at a flow rate of 6 mL h 1 (left), or static incubation for 30 (center) or 60 (right) min. After the blocking process, the QD605-conjugated anti-rabbit goat Ab was added and incubated for 30 or 60 min. (B) Results of QD-secondary Ab incubation after the flow-based blocking at various flow rates.
block completely the nonspecific binding of QD–secondary Ab conjugates. A longer incubation period had little effect on blocking. In contrast, the flow-based blocking process was efficient and could be used to control the blocking time by varying the flow rate (Fig. 3B). This is due to the effective deposition of BSA on the section surface by the continuous flow within the microchannels. The brightness of a QD can be regarded as a weakness in any immunochemical assay if nonspecific binding cannot be controlled. Therefore, efficient, controllable blocking is an advantage of microfluidic immunochemical assay over conventional immunochemical assay techniques. The left panel in Fig. 4A shows our immunostaining system platform. The sample slide was covered with a microfluidic device and specialized metal frames were used to hold the device in the desired place on the sample. The center panel of Fig. 4A shows a dark-field image of microfluidic channels placed and held on the sample. After the flow-based blocking process, the selected rabbit Abs were injected into each inlet mixed with mouse b-actin, which is used as a LC. b-actin has been known as a stable LC for breast cancer cells.20 After incubation of the Ab mixtures under continuous flow conditions, unbound Abs were washed away with Tris-buffered saline containing Tween (TBS-T). Then, a mixture of QD605-conjugated anti-rabbit Ab and QD525-conjugated anti-mouse Ab was injected into each inlet, followed by a further incubation to finish the QD labeling. All samples were mounted with QD mounting medium (Invitrogen). Due to the microfluidic immunostaining, the shape of the channel was visible on the sample (Fig. 4A, right panel). Consequently, red QD-labeling of the eight proteins can be seen in the form of stripes on the cell-block surface: no non-specific binding was observed (Fig. 4B and C). Note that more proteins can be multiplexed as the
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Fig. 4 The fluorescence image of an MCF-7-cell-block section, multiplex-stained using the QD-MMBQ system. (A) The microfluidic device is integrated with the cell-block section using an integration system (left). Multi-microchannels are placed on the cell-block section (center). After the immunoreactions, the multi-microchannels are detached from the cell-block section (right). (B) The cell-block section was labeled with eight Abs using a microfluidic immunostaining system. (C) Magnified images of Ab-labeled areas. Each image indicates the upper biomarker area in (B). Both the QD525 and QD605 signals are shown in the upper images and those of each biomarker with QD605 in the lower images.
number of microchannels increases.19 Moreover, this method requires only 1 h for incubation of nine Abs (including a reference marker). A recent report indicated that 46 h is required to label four proteins with QDs.14 Since our method takes less time than conventional QD-based IHC, it reduces the total process time markedly. This is due to the parallel microfluidic multiplexing and efficient protein–Ab reactions in multiple microchannels resulting from the enhanced mass transfer of Abs to the surface proteins of the biospecimen.18 Recently, Ciftlik et al. reported that Ab incubation and highReynolds-number flow in a microchannel can reduce Ab incubation times to 5 min.21 Because the QD-MMBQ method can be used readily in microfluidics-based immunochemical assay, it is possible to reduce the total processing time further than those described here by changing the material of the microchannel or the device geometry. Additionally, to enhance the multiplexity of the method, repeated Ab staining is possible, using, for example, the Ab de-staining method reported by Zrazhevskiy et al.22
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antibody selection for multiplexed assay development. In addition, because the emission peaks of the QDs were sufficiently separated, no spectral deconvolution was necessary for plotting of the protein expression profiles, which was important in previous quantitative QD-immunochemical assay studies.12,13 Furthermore, our method allows use of QDs of only two colors, and no adjustment of fluorescence intensities is required. These characteristics enable more accurate quantitative comparisons of multiple biomarkers. Red or far-red QDs are brighter than other QDs.23 The QD-MMBQ method labels all target biomarkers with the same QDs such as red QDs. Thus, our method is easier, more accurate, and more sensitive than previous multiplexed QD detection techniques. Note that although a cell-block section comprises homogeneous cells and it is regarded as a uniformly dispersed cell layer, the signal of a particular QD-labelled protein from randomly selected areas can differ considerably before LC normalization. This is due to variation in cell numbers and cell volume difference in a confined area (Fig. 5). The variation in cell number and volume in a cell-block section may be limited, but a significant signal difference arises due to the high sensitivity of QDs. However, QD signal variation was reduced by normalization of protein expression to that of the LC at the same location. Thus the immunochemical normalizing approach can compensate for the cell number and volume variation, guaranteeing a more accurate single-cell level quantification of protein expression in ICC (Fig. 4B). Specifically, a microfluidic immunochemical assay uses the microchannels as individual Ab-incubation chambers, and each protein is stained for in only a small region of the cell-block section. Therefore, microfluidic immunochemical assays would result in quantification errors if protein expression was measured without a LC in each channel due to the small number of sampling locations. Therefore, LC
Protein quantification using multi-windows and LC High flexibility is one of the strongpoints of the QD-MMBQ method. As previously stated, a cocktail method, which does not allow unintended reactions of QD–Ab conjugates, facilitates exploitation of Abs produced by different species to enhance multiplexing efficiency and avoid inappropriate QD binding. Nevertheless, more Ab producing species are needed to allow labeling of more proteins. Until now, since few animal species have been developed to produce Abs, the use of existing QD-IHC methods in pathology is problematic. In contrast, our QD-MMBQ method requires only two Abs from different animal species. All of the anti-protein-target Abs can be produced from the same species; only the LC Ab needs to be come from a distinct species. Accordingly, only two QD-conjugated reagents are required. Therefore, our method ensures high flexibility of
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Fig. 5 Fluorescence intensity of QD-labeled mTOR and b-actin. The SK-BR-2 cell-block section was stained with anti-mTOR Ab-QD605 and anti-b-actin Ab-QD525. (A) Fluorescence QD-stained images of randomly selected areas of a cell-block section. To emphasize the effect of LC normalization, sampling was performed from locations with different cell densities. Scale bar, 50 mm. (B) Fluorescence intensities of QD525 and QD605 in randomly selected areas of cell-block sections. mTOR*, the mTOR signal normalized to that of b-actin.
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normalization ensures the accuracy of protein quantification by microfluidic immunochemical assays.
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Comparison of protein expression levels between cell lines Furthermore, we were able to quantitate and compare the expression of various proteins in not only one cell-block section but also among cell-block sections. Eight proteins in SK-BR-3, MCF-7, and HCC-70 cells were compared quantitatively. As shown in Fig. 6, we compared the expression of the eight proteins with and without normalization. Importantly, without normalization, the ER expression of SK-BR-3 and MCF-7 cells was similar, although SK-BR-3 cells are ER-negative and MCF-7 cells ER-positive.24 In comparison, the normalized ER signal of SK-BR-3 and MCF-7 cells showed a considerable difference, being identified as negative and positive, respectively (Fig. 6B). Also, SK-BR-3 cells are PR-negative and MCF-7 cells are PR-positive.25 However, the PR expression levels of these cell lines become distinct after normalization. Thus we confirmed that normalized protein expression signals are more credible than non-normalized signals comparing previous proteomic studies of breast cancer cell lines.24,25 This is due to the overall elevation of protein expression in MCF-7 cells with normalization. Note that there is significant variation in the protein staining quality between tissues or cell sections with IHC or ICC due to the complex steps involved in sample preparation and staining steps (e.g., gel loading, fixation, paraffin embedding, microtome sectioning, deparaffinization, re-hydration, antigen retrieval process, etc.).26–31 Likewise, proteins in the MCF-7 cell-block section were generally stained more lightly than those in other sections; comparison of protein expression among different sections accurately is difficult without a calibration process. This is a critical issue in all kinds of immunochemical assays because conventional immunochemical assay is associated with technical difficulties in calibrating differences in staining among specimens. The b-actin-based normalization strategy compensates for differences in not only
Fig. 6 Protein expression by MCF-7, HCC-70, and SK-BR-3 cells. (A) Eight target proteins and b-actin were labeled with QDs on MCF-7, HCC-70, and SK-BR-3 cell blocks. QD605 was used to visualize the expression of each protein, while the QD525 intensity represented the reference marker signal. The lower images show the gray signal of biomarker expression (QD605). (B) Fluorescence intensity is expressed as arbitrary units (a.u.) of the QD605 signal (left panel) and the QD605 divided by QD525 signal (right panel) intensities for each strip (generated by the microchannels). In this way, the expression levels of the eight proteins were quantitated at the single-cell level (right panel).
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cell number but also in staining quality among specimens which is not possible using conventional methods. Multiple biomarker quantification in tissues Due to the use of micro-sized channels, a limited biomarker staining area can be problematic considering the unexpectedly distributed cancer cells in tissues. For this reason, determination of the region where tumor cells are populated in high density is critical to achieve successive biomarker screening using the QD-MMBQ method. To address this issue, we mounted a bundle of multiple channels over a densely populated cancer cell area which was determined by hematoxylin and eosin staining. Fig. 7A shows a staining result of eight biomarkers on a breast cancer tissue. Like the cell specimen staining using our method, biomarkers were labeled with QD605 and b-actin was attached with QD525. QDs were stained correctly at each location as shown in right images of Fig. 7A. Using our b-actinbased normalization strategy, eight biomarkers were quantified using spectroscopy (Fig. 7B). Although we demonstrated our method using clinical samples, tissue heterogeneity could be a problem using our biomarker multiplexing system, which uses tissue dimensions of about 400 mm 5000 mm for each biomarker, separately. This would not be adequate for the cases such as rare cell discovery using IHC.17 Our system could be effective for use in multiplexed biomarker screening of less heterogeneous cancer tissues. We previously demonstrated that for cases in which breast cancer
Fig. 7 Quantitative analysis of eight proteins on a breast cancer tissue section. (A) Eight target proteins and b-actin were labeled with QDs on a breast cancer tissue. QD605 was used to visualize the expression of each protein, while the QD525 intensity represented the reference marker signal. (B) The fluorescence intensity in arbitrary units (a.u.) of each area was compared quantitatively using the b-actin signal. (C) The values of coefficient of variation (CV) were compared between the b-actin normalized signal and the original signal of QD605. The b-actin normalized signal tends to be less variable than that was not normalized.
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tissues were analyzed, the parallel biomarker multiplexing approach showed strong consensus with conventional wholesection analysis.18 Also, because our system can be readily applied to various clinical specimens, assay accuracy can be improved by combining our system with a tissue microarray consisting of small replicate specimens. On the other hand, the use of an appropriate LC for the particular cancer can be a better solution to improve our quantification system in tissues. Notably, even when a tissue consisted of heterogeneous cells, normalized biomarker intensity showed less variance over the signal acquisition areas than biomarker intensity which was not normalized (Fig. 7C). This shows that the b-actin-based normalization concept has a possibility to be used for the accurate biomarker quantification of tissue samples.
Materials and methods Preparation of specimens A formalin-fixed paraffin-embedded breast cancer cell block was used for the demonstration of our protein quantification system. Breast cell lines, including MCF-7, SK-BR-3, and HCC70 cells, were purchased from the American Type Culture Collection (ATCC; Manassas, VA). MCF-7 and HCC-70 cells were cultured in RPMI-1640. SK-BR-3 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 100 IU mL 1 penicillin, and 100 mg mL 1 streptomycin. All cells were maintained at 37 1C and 5% CO2. For the fabrication of engineered tissues, after trypsinization, harvested cells were centrifuged. Formalin fixation, agar suspension, and paraffin embedding was accomplished to make cell blocks. Paraffin embedded blocks were then sectioned at 4 mm, the sections were mounted and baked onto positively charged glass slides. These samples were dried for 1 h at room temperature followed by 1 h in an incubator at 60 1C. Human breast cancer tissue samples were obtained from the Konyang University Hospital (Daejeon, Korea), with the corresponding written consents given by the patients or their relatives. This study was approved by the Institutional Review Board (IRB) at the Konyang University Hospital and the Korea Advanced Institute of Science and Technology (KAIST). Human tissue samples were fixed in 4% neutral-buffered formalin, Bouin’s fixative, acetic formalin alcohol (AFA), or 4% or 10% unbuffered formalin; 4 h in PreFer (Anatech, Battle Creek, MI) or Pen-Fix (Richard Allen Scientific; Kalamazoo, MI); or 48 h in 4% neutral-buffered formalin. After the paraffin embedding process, tumor specimens were sectioned into 4 mm and dried for 1 h at room temperature, followed by 1 h in a convection incubator at 60 1C. Immunocytochemical staining For the investigation of the multiplexed staining tendency of the sequential method, rabbit anti-human epidermal growth factor receptor 2 (HER2) antibody (Ab) (1 : 500, Dako, Denmark), rabbit anti-Ki-67 Ab (1 : 200, Novus Biologicals), and QD605conjugated goat anti-rabbit Ab (1 : 250, Invitrogen, Carlsbad, CA)
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and QD525-conjugated goat anti-rabbit Ab (1 : 100, Invitrogen) were used in sequential multiplexing. Cell blocks were deparaffinized in xylene and hydrated through a graded series of ethanol (70%, 80%, 95%, and 100% ethanol). The microwave antigen-retrieval technique was conducted in target retrieval solution, pH 9 (Dako), for 20 min at 750 W. The slide surface was blocked using blocking solution (2% bovine serum albumin with 5% goat serum in 1 phosphate buffered saline) or commercially available blocking solution (Zymed, San Francisco, CA) for 30 min at room temperature, the slides were incubated with primary Ab at room temperature for 30 min or 1 h. After washing with 1 Tris buffered saline-Tween (TBS-T; 0.1% Tween 20), QD-conjugated secondary Ab was applied to the slides at room temperature for 30 min or 2 h. Using this protocol, SK-BR-3 cells were labeled with rabbit antiHER2 Ab-QD525-conjugated goat anti-rabbit Ab and rabbit anti-Ki-67 Ab-QD605-conjugated goat anti-rabbit Ab. One slide was labeled with anti-HER2–QD525 first, the other was labeled with anti-Ki-67–QD605 first. For the demonstration of the cocktail method, mouse antiHER2 Ab (1 : 500, Dako) and rabbit anti-Ki-67 (1 : 200, Dako) were mixed prior to incubation. The Ab mixture was incubated on the SK-BR-3 cell-block section at room temperature for 30 min. After the washing step with TBS-T, QD605-conjugated goat anti-rabbit Ab (1 : 250, Invitrogen) and QD525-conjugated goat anti-mouse Ab (1 : 100, Invitrogen) were mixed and the QD-labeled Ab mixture was applied to the slides at room temperature for 30 min. Fabrication of a microfluidic device A conventional soft lithography technique was conducted to fabricate the devices. To make a mold of the microchannels, SU-8 3025 was spincoated on a bare silicon wafer to make rectangular reaction channels. The wafer was exposed to ultraviolet light with a mask and subsequently developed using an SU-8 developer. Then, the microfluidic device was fabricated by using a poly(dimethylsiloxane) (PDMS; Sylgard 184; Dow Corning, MA) replica molding process.18,19 Microfluidic immunochemical staining Estrogen receptor (ER) Ab (Ventana, Tucson, AZ), progesterone receptor (PR) Ab (Ventana), HER2 Ab (1 : 1000, Dako), human growth factor receptor 3 (HER3) Ab (1 : 50, Abcam, Cambridge, MA) were used at 1 concentrations or ready-to-use concentrations. Ki-67 (1 : 200, Dako) Ab, the mammalian target of rapamycin (mTOR) Ab (Abcam), transforming growth factor alpha (TGF-a) Ab (1 : 50, Abcam), and betacellulin (BTC) Ab (1 : 100, Proteintech Group, USA) were also used at 1 ready-to-use concentrations. All these antibodies were produced from rabbits, 2.5 mL of each biomarker was mixed with 2.5 mL of b-actin Ab (1 : 1000, Abcam), produced from mice prior to channel injection. To apply the QD-MMBQ to tissue models, SK-BR-3, MCF-7, and HCC-70 breast cancer cell-block sections were deparaffinized. After antigen retrieval treatment, a microfluidic device was mounted on the cell block slide, and the microfluidic channel layer was pressuresealed to prevent leakage between the channels formed on the sample slide. The mounted PDMS layer provided multiple isolated areas on the specimen. Then, the deparaffinized cell blocks were blocked with a blocking solution containing bovine
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serum albumin (BSA) and goat serum in phosphate-buffered saline (PBS; pH 7.4). 5 mL of each mixture was injected to each inlet, and withdrawal pumping from the outlet was accomplished to incubate biomarkers at a flow rate of 80 mL h 1 for 30 min. All inlets were washed with TBS-T after the incubation. Then, QD605-conjugated goat anti-rabbit Ab (1 : 250, Invitrogen) and QD525-conjugated goat anti-mouse Ab (1 : 100, Invitrogen) were mixed and 5 mL of the mixture was injected into every inlet. QD mixtures were incubated at a flow rate of 80 mL h 1 for 30 min. Prior to tissue staining, device alignment to the specific region of tissue section is required to collect protein signals from the region where the cancer cells are densely populated due to the morphological heterogeneity of breast cancer tissues. The alignment process was described in our previous report.18 Briefly, one of the tissue sections was stained with hematoxylin and eosin. After the determination of the region where tumor cells are populated in high density, the device was aligned to that region by comparing adjacent tissue sections to the hematoxylin and eosin stained one. All remaining processes for multiplexed QD staining were the same as above. Quantification of proteins For biomarker quantification, optical spectroscopy was performed using a fluorescence microscope (IX72; Olympus) with a spectrometer (QE65000; Ocean Optics) and a charge-coupled device. To determine the staining intensity of each protein, the fluorescence signal was collected from each strip individually. As mentioned above, we used two QDs (QD525 and QD605) with emission peaks of 525 nm for the reference marker and 605 nm for the target proteins. After elimination of autofluorescence, the QD605 signal was normalized to that of QD525 (see ESI,† Fig. S2).
Conclusions We have demonstrated a microfluidic multiple biomarker quantification method using QD nanoparticles and microfluidics. Particularly, we verified the QD sequential staining method staining-sequence problem using cell-block sections. The QD labeling method based on sequential staining induces unintended binding of QD–secondary-Ab conjugates, making qualitative and quantitative analyses problematic. In addition, our novel method can quantify simultaneously more than eight proteins in the same biological specimen. Expression levels of eight proteins in various cell lines were compared by co-labeling each target protein and the same LC in each microchannel. Our microfluidic method provides the most flexible multiplexed QD-immunochemical assay technique, allowing facile data analysis and more accurate biomarker quantification. LC-based quantification also shows the effect of cell number and staining quality variation among specimens. We also showed a possibility of using this system in multiple biomarker quantification of breast cancer tissues. Furthermore, microfluidic blocking is superior and controllable compared to the conventional static method. Based on its applicability in breast tissue from cancer patients, this facile method for quantification of multiple biomarkers will contribute to realization of the use of multiplexed QD-immunochemical assay in many fields.
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Acknowledgements This research was supported by a National Leading Research Laboratory Program (NRF-2013R1A2A1A05006378), a Nano/Bio Science and Technology Program (NRF-2005-2001291), and a Converging Research Center Program (2011K000864) through the National Research Foundation of Korea funded by the Ministry of Science, ICT and Future Planning. The authors also acknowledge a Cooperative Research Program for Agriculture Science and Technology Development (Grant PJ009842) supported by the Rural Development Administration of Korea.
Notes and references 1 D. K. Nomura, M. M. Dix and B. F. Cravatt, Nat. Rev. Cancer, 2010, 10, 630–638. 2 N. Turner, M. B. Lambros, H. M. Horlings, A. Pearson, R. Sharpe, R. Natrajan, F. C. Geyer, M. van Kouwenhove, B. Kreike and A. Mackay, Oncogene, 2010, 29, 2013–2023. 3 P. Zrazhevskiy and X. Gao, Nano Today, 2009, 4, 414–428. 4 B. Weigelt, A. Mackay, R. A’hern, R. Natrajan, D. S. Tan, M. Dowsett, A. Ashworth and J. S. Reis-Filho, Lancet Oncol., 2010, 11, 339–349. 5 M. C. Cheang, D. Voduc, C. Bajdik, S. Leung, S. McKinney, S. K. Chia, C. M. Perou and T. O. Nielsen, Clin. Cancer Res., 2008, 14, 1368–1376. ´s, L. Prudkin, C. Aura, 6 M. Scaltriti, P. J. Eichhorn, J. Corte ´nez, S. Chandarlapaty, V. Serra, A. Prat and Y. H. J. Jime Ibrahim, Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 3761–3766. 7 S. Zhang, W.-C. Huang, P. Li, H. Guo, S.-B. Poh, S. W. Brady, Y. Xiong, L.-M. Tseng, S.-H. Li and Z. Ding, Nat. Med., 2011, 17, 461–469. 8 U. Resch-Genger, M. Grabolle, S. Cavaliere-Jaricot, R. Nitschke and T. Nann, Nat. Methods, 2008, 5, 763–775. 9 I. L. Medintz, H. T. Uyeda, E. R. Goldman and H. Mattoussi, Nat. Mater., 2005, 4, 435–446. 10 X. Gao, Y. Cui, R. M. Levenson, L. W. Chung and S. Nie, Nat. Biotechnol., 2004, 22, 969–976. 11 X. Michalet, F. Pinaud, L. Bentolila, J. Tsay, S. Doose, J. Li, G. Sundaresan, A. Wu, S. Gambhir and S. Weiss, Science, 2005, 307, 538–544. 12 Y. Xing, Q. Chaudry, C. Shen, K. Y. Kong, H. E. Zhau, L. W. Chung, J. A. Petros, R. M. O’Regan, M. V. Yezhelyev and J. W. Simons, Nat. Protoc., 2007, 2, 1152–1165. 13 M. V. Yezhelyev, A. Al-Hajj, C. Morris, A. I. Marcus, T. Liu, M. Lewis, C. Cohen, P. Zrazhevskiy, J. W. Simons and A. Rogatko, Adv. Mater., 2007, 19, 3146–3151. 14 J. Liu, S. K. Lau, V. A. Varma, R. A. Moffitt, M. Caldwell, T. Liu, A. N. Young, J. A. Petros, A. O. Osunkoya and T. Krogstad, ACS Nano, 2010, 4, 2755–2765. 15 E. Sweeney, T. H. Ward, N. Gray, C. Womack, G. Jayson, A. Hughes, C. Dive and R. Byers, Biochem. Biophys. Res. Commun., 2008, 374, 181–186. 16 D. Huang, X. Peng, L. Su, D. Wang, F. R. Khuri and D. M. Shin, Nano Res., 2010, 3, 61–68.
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17 J. Liu, S. K. Lau, V. A. Varma, B. A. Kairdolf and S. Nie, Anal. Chem., 2010, 82, 6237–6243. 18 M. S. Kim, T. Kim, S.-Y. Kong, S. Kwon, C. Y. Bae, J. Choi, C. H. Kim, E. S. Lee and J.-K. Park, PLoS One, 2010, 5, e10441. 19 M. S. Kim, S. Kwon, T. Kim, E. S. Lee and J.-K. Park, Biomaterials, 2011, 32, 1396–1403. 20 J. B. de Kok, R. W. Roelofs, B. A. Giesendorf, J. L. Pennings, E. T. Waas, T. Feuth, D. W. Swinkels and P. N. Span, Lab. Invest., 2004, 85, 154–159. 21 A. T. Ciftlik, H.-A. Lehr and M. A. Gijs, Proc. Natl. Acad. Sci. U. S. A., 2013, 110, 5363–5368. 22 P. Zrazhevskiy and X. Gao, Nat. Commun., 2013, 4, 1619. 23 P. K. Chattopadhyay, D. A. Price, T. F. Harper, M. R. Betts, J. Yu, E. Gostick, S. P. Perfetto, P. Goepfert, R. A. Koup and S. C. De Rosa, Nat. Med., 2006, 12, 972–977.
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24 J. Kao, K. Salari, M. Bocanegra, Y.-L. Choi, L. Girard, J. Gandhi, K. A. Kwei, T. Hernandez-Boussard, P. Wang and A. F. Gazdar, PLoS One, 2009, 4, e6146. 25 P. A. Kenny, G. Y. Lee, C. A. Myers, R. M. Neve, J. R. Semeiks, P. T. Spellman, K. Lorenz, E. H. Lee, M. H. Barcellos-Hoff and O. W. Petersen, Mol. Oncol., 2007, 1, 84–96. 26 L. C. Tong, N. Nelson, J. Tsourigiannis and A. M. Mulligan, Am. J. Surg. Pathol., 2011, 35, 545–552. 27 I. Z. Yildiz-Aktas, D. J. Dabbs and R. Bhargava, Mod. Pathol., 2012, 25, 1098–1105. 28 P. Maxwell and W. McCluggage, J. Clin. Pathol., 2000, 53, 929–932. 29 T. J. O’Leary, Appl. Immunohistochem. Mol. Morphol., 2001, 9, 3–8. 30 T. Seidal, A. J. Balaton and H. Battifora, Am. J. Surg. Pathol., 2001, 25, 1204–1207. 31 C. R. Taylor, Hum. Pathol., 1994, 25, 2–11.
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A quantum dot-based microfluidic multi-window platform for quantifying the biomarkers of breast cancer cells† Seyong Kwon,a Minseok S. Kim,b Eun Sook Lee,c Jang Sihn Sohnd and Je-Kyun Park*a Conventional molecular profiling methods using immunochemical assays have limits in terms of multiplexity and the quantification of biomarkers in investigation of cancer cells. In this paper, we demonstrate a
Received 27th October 2013, Accepted 11th February 2014
quantum dot (QD)-based microfluidic multiple biomarker quantification (QD-MMBQ) method that enables labeling of more than eight proteins immunochemically on cell blocks within 1 h, in a quantitative manner.
DOI: 10.1039/c3ib40224j
An internal reference, b-actin, was used as a loading control to compensate for differences in not only the cell number but also in staining quality among specimens. Furthermore, the microfluidic blocking method
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exhibited less nonspecific binding of QDs than the conventional static blocking method.
Insight, innovation, integration Immunochemical assay using an antibody-based molecular detection technology can provide information on both cellular morphology and the quantities of molecules within cells (immunocytochemistry) or tissues (immunohistochemistry). In this field, multiplexed protein quantification remains difficult using conventional methods. Here, we demonstrate a new analytical concept that integrates a microfluidic multiplexing platform and a QD double-staining method. The microfluidic double-staining method enabled accurate quantification by normalization of biomarker levels to that of b-actin as an internal reference. This novel molecular profiling method will accelerate cancer cell studies and the development of diagnostic tools for personalized medicine.
Introduction The development of an accurate, quantitative molecular profiling technology for cellular materials remains a challenge for investigation of cell physiology, drug responses, and fatal diseases such as various types of cancer.1 In particular, a molecular profiling-based personalized cancer diagnosis system is desirable because a considerable number of cancer patients do not benefit from existing therapeutics, including molecular-targeted drugs.2–5 Indeed, breast cancer has a high recurrence rate due to its heterogeneity.6,7 Thus, there is a need for tailored treatment strategies for breast cancer.
a
Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea. E-mail: [email protected]; Tel: +82-42-350-4315 b Samsung Advanced Institute of Technology, 97 Samsung 2-ro, Giheung-gu, Yongin-si, Gyeonggi-do 446-712, Republic of Korea c Research Institute and Hospital, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang-si, Gyeonggi-do 410-769, Republic of Korea d Department of Pathology, College of Medicine, Konyang University, 158 Gwanjeodong-ro, Seo-gu, Daejeon 302-718, Republic of Korea † Electronic supplementary information (ESI) available: Fig. S1 and S2. See DOI: 10.1039/c3ib40224j
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Understanding the complex molecular mechanisms of individual cancer cells requires molecular detection of multiple proteins at the single-cell level. Among the existing molecular detection technologies (e.g., polymerase-chain reaction, western blotting, mass spectrometry, and enzyme-linked immunosorbent assay), only immunocytochemistry (ICC) or immunohistochemistry (IHC) can provide information on both morphology and the quantity of molecules, which is not possible with other techniques that involve destruction of cellular structures. Quantum dot (QD) nanoparticles enable multiplexed protein detection in immunochemical assays due to their superior optical properties, such as brightness, narrow emission peak, photobleaching resistance, large Stokes shift, and simultaneous excitation of multiple fluorescence colors.8–11 In recent reports, however, the number of proteins that can be analyzed using multiplexed QD-immunochemical assay techniques has been limited to four or five.12–14 To increase the number of proteins in QD multiplexing methods, several approaches have been attempted; to date, all were unsuccessful or inefficient. For example, for the multiplexed use of primary antibodies (Abs), QDs were directly conjugated to primary Abs. This makes the multiplexed assay process easier and faster. Nevertheless, this
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method has disadvantages in its preparation process. Due to the harsh conditions of Ab conjugation to QDs, it consumes a considerable amount of Abs and time that is not efficient for the use of large numbers of biomarkers. A sequential QD multiplexing method is more flexible to overcome these problems and could be used to identify a number of proteins by labeling with different Abs from the same species. However, this method requires multiple blocking steps between sequential reactions. Due to the processing time required per reaction, this also requires more than 3 h using conventional methods; thus labeling large numbers of proteins is laborious and time-consuming. Moreover, recent multiplexed QD-based IHC studies showed that the sequential QD multiplexing method caused distorted results.15–17 Previously, we reported a microfluidic immunochemical assay platform that enabled simultaneous detection of multiple proteins by dividing a cell block or tissue section into several isolated areas by means of reversible bonding of a PDMS microfluidic layer with multiple parallel channels on the cell or tissue slide directly.18,19 A multiple-channel layout can be used with simultaneous incubation of multiple Abs on the sample slide. Although this method can be used to increase the maximum multiplexing number in immunochemical assays, protein quantification was difficult due to the lack of a robust quantification method. In this report, we developed an accurate QD-based microfluidic multiple biomarker quantification (QD-MMBQ) method that facilitated determination of the levels of proteins of interest at the single-cell level. For the accurate quantitative analysis of several proteins in the same biological specimen, we exploited the normalization concept using a microfluidic immunochemical assay platform by co-labeling the loading control (LC) protein with a different target protein in each microchannel. Expression levels of eight proteins in various cell lines were compared by co-labeling a different target protein and the same LC in each microchannel. Our microfluidic method represents a flexible and rapid multiplexed QD-immunochemical assay technique, facilitating analysis of the data and more accurate quantification of biomarkers.
Results and discussion Crosstalk of QD-conjugated secondary Abs As noted above, crosstalk of QD-conjugated secondary Abs is regarded as a key technical problem in QD-multiplexed immunostaining. Prior to the development of microchannel QD-multiplexing methods, validation of several QD-multiplexing techniques was performed to avoid nonspecific binding of QD particles. A formalin-fixed paraffin-embedded cell block was used to address QD multiplexing problems systematically. The breast cancer cell line SK-BR-3 strongly expresses HER2 in the membrane and Ki-67 in the nucleus. To investigate the staining tendency of a sequential method, a single primary Ab species and different-color-QD-conjugated secondary Abs (QD525-conjugated anti-rabbit Ab and QD605-conjugated anti-rabbit Ab) were used to sequentially label HER2 (rabbit) and Ki-67 (rabbit). Primary Abs from different species and different-color-QD-conjugated secondary
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Fig. 1 Staining of HER2 with QD525, and Ki-67 with QD605 on SK-BR-3 cell-block sections. (A) HER2 was labeled with a rabbit anti-HER2 Ab and QD525-conjugated goat anti-rabbit Ab. (B) Ki-67 was labeled with a rabbit anti-Ki-67 Ab and QD605-conjugated goat anti-rabbit Ab. (C–E) HER2 and Ki-67 were stained in the order, rabbit anti-HER2, QD525-conjugated goat anti-rabbit, rabbit anti-Ki-67, and QD605-conjugated goat anti-rabbit Abs. The fluorescence image obtained using a long-pass fluorescence filter (C) to receive the total QD525 and QD605, and the individual QD525 (D) and QD605 (E) fluorescence signals; the latter were obtained using a band-pass fluorescence filter. (F–H) HER2 and Ki-67 were stained in the order, rabbit anti-Ki-67, QD605-conjugated goat anti-rabbit, rabbit antiHER2, and QD525-conjugated goat anti-rabbit Abs. The total fluorescence image obtained using a long-pass fluorescence filter (F), and individual QD525 (G) and QD605 (H) fluorescence signals. (I–K) HER2 and Ki-67 were labeled using a cocktail method with a mixture of mouse anti-HER2 and rabbit anti-Ki-67 Abs, and a mixture of QD525-conjugated goat antimouse and QD605-conjugated goat anti-rabbit Abs. The total fluorescence image obtained using a long-pass fluorescence filter (I), and individual QD525 (J) and QD605 (K) fluorescence signals.
Abs (QD525-conjugated anti-mouse Ab and QD605-conjugated anti-rabbit Ab) were also used to label HER2 (mouse) and Ki-67 (rabbit) using a cocktail method (a mixture of primary Abs produced by different species), which is widely used for QD-based detection of two or three biomarkers. Control data were obtained by QD staining for each protein separately. Typical sequential and cocktail staining results are shown in Fig. 1. Notably, the sequential QD staining results showed that the last-in-sequence QD-conjugated secondary Abs bound not only to the final primary Abs but also to previous primary Abs despite the blocking process that is supposed to prevent such unintended binding. This was demonstrated by changing the multiplexing order and observing the localization of the QD-conjugated secondary Abs (Fig. 1). Increasing the incubation time of the QD-conjugated secondary Abs so that the binding sites of the primary Abs were fully occupied for 2 h, had no effect on this phenomenon (see ESI,† Fig. S1). This problem is critical because unintended QD labeling of primary Abs will result in both IHC and ICC being compromised by inaccurate protein localization information and incorrect measurements of protein quantities (Fig. 1E and G). This hinders the study of cell and protein functions, such as protein translocalization, using IHC or ICC. Using a cocktail method, multiple QD conjugates were labelled on the desired proteins (Fig. 1J and K). HER2 proteins (cell membrane) were labelled specifically with QD525, and Ki-67 proteins (nucleus) with QD605. The same staining tendencies were also observed with microfluidic staining (data not shown).
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Although the cocktail method has benefits in QD multiplexing, such as high selectivity due to use of primary Abs that originate from different species, the QD multiplexing number is limited to three or four due to the number of commercially available Ab-producing species (mouse, rabbit, rat, goat, etc.).
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Microfluidic biomarker screening For the accurate quantitative analysis of large numbers of proteins in the same biological specimen, we exploited the normalization concept using a microfluidic immunochemical assay platform by co-labeling the LC with a different target protein in each microchannel (Fig. 2). Since the cocktail method is useful for multiplexing of small numbers of proteins with QDs, such as by reducing the total process time and involving high selectivity, we applied a cocktail method to develop our QD-MMBQ technique. Blocking is important in QD-based immunochemical assay to control nonspecific binding of QDs. To investigate the efficiency of the blocking process in association with microfluidics, two cell-block sections were treated with blocking solution; one was incubated statically (conventional method), while the other was incubated with flow. After blocking for 30 min, the sections were incubated with QD605–secondary Ab conjugates for 1 h. The flow-based blocking section showed a significant decrease in the nonspecific binding of QDs at a flow rate of 6 mL h 1 (Fig. 3A). Furthermore, the data indicate that the conventional static incubation method cannot
Fig. 2 Schematic of the QD-based microfluidic multiple biomarker quantification (QD-MMBQ) method. In step 1, the reference marker Ab and each biomarker Ab, originating from different species, were reacted with the cell-block section within the microchannel. Here, the reference marker stained the cytoplasm, while each biomarker stained the nuclear region. In step 2, two types of QDs conjugated with the various secondary Abs (goat anti-rabbit Ab and goat anti-mouse Ab) were reacted with the cell-block section on the microchannel. Inset a and b in each step indicate the area of the circle in each microchannel.
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Fig. 3 Result of QD-secondary Ab incubation with blocking solution under flow and static conditions. (A) MCF-7-cell-block sections were incubated with blocking solution under microfluidic flow for 30 min at a flow rate of 6 mL h 1 (left), or static incubation for 30 (center) or 60 (right) min. After the blocking process, the QD605-conjugated anti-rabbit goat Ab was added and incubated for 30 or 60 min. (B) Results of QD-secondary Ab incubation after the flow-based blocking at various flow rates.
block completely the nonspecific binding of QD–secondary Ab conjugates. A longer incubation period had little effect on blocking. In contrast, the flow-based blocking process was efficient and could be used to control the blocking time by varying the flow rate (Fig. 3B). This is due to the effective deposition of BSA on the section surface by the continuous flow within the microchannels. The brightness of a QD can be regarded as a weakness in any immunochemical assay if nonspecific binding cannot be controlled. Therefore, efficient, controllable blocking is an advantage of microfluidic immunochemical assay over conventional immunochemical assay techniques. The left panel in Fig. 4A shows our immunostaining system platform. The sample slide was covered with a microfluidic device and specialized metal frames were used to hold the device in the desired place on the sample. The center panel of Fig. 4A shows a dark-field image of microfluidic channels placed and held on the sample. After the flow-based blocking process, the selected rabbit Abs were injected into each inlet mixed with mouse b-actin, which is used as a LC. b-actin has been known as a stable LC for breast cancer cells.20 After incubation of the Ab mixtures under continuous flow conditions, unbound Abs were washed away with Tris-buffered saline containing Tween (TBS-T). Then, a mixture of QD605-conjugated anti-rabbit Ab and QD525-conjugated anti-mouse Ab was injected into each inlet, followed by a further incubation to finish the QD labeling. All samples were mounted with QD mounting medium (Invitrogen). Due to the microfluidic immunostaining, the shape of the channel was visible on the sample (Fig. 4A, right panel). Consequently, red QD-labeling of the eight proteins can be seen in the form of stripes on the cell-block surface: no non-specific binding was observed (Fig. 4B and C). Note that more proteins can be multiplexed as the
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Fig. 4 The fluorescence image of an MCF-7-cell-block section, multiplex-stained using the QD-MMBQ system. (A) The microfluidic device is integrated with the cell-block section using an integration system (left). Multi-microchannels are placed on the cell-block section (center). After the immunoreactions, the multi-microchannels are detached from the cell-block section (right). (B) The cell-block section was labeled with eight Abs using a microfluidic immunostaining system. (C) Magnified images of Ab-labeled areas. Each image indicates the upper biomarker area in (B). Both the QD525 and QD605 signals are shown in the upper images and those of each biomarker with QD605 in the lower images.
number of microchannels increases.19 Moreover, this method requires only 1 h for incubation of nine Abs (including a reference marker). A recent report indicated that 46 h is required to label four proteins with QDs.14 Since our method takes less time than conventional QD-based IHC, it reduces the total process time markedly. This is due to the parallel microfluidic multiplexing and efficient protein–Ab reactions in multiple microchannels resulting from the enhanced mass transfer of Abs to the surface proteins of the biospecimen.18 Recently, Ciftlik et al. reported that Ab incubation and highReynolds-number flow in a microchannel can reduce Ab incubation times to 5 min.21 Because the QD-MMBQ method can be used readily in microfluidics-based immunochemical assay, it is possible to reduce the total processing time further than those described here by changing the material of the microchannel or the device geometry. Additionally, to enhance the multiplexity of the method, repeated Ab staining is possible, using, for example, the Ab de-staining method reported by Zrazhevskiy et al.22
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antibody selection for multiplexed assay development. In addition, because the emission peaks of the QDs were sufficiently separated, no spectral deconvolution was necessary for plotting of the protein expression profiles, which was important in previous quantitative QD-immunochemical assay studies.12,13 Furthermore, our method allows use of QDs of only two colors, and no adjustment of fluorescence intensities is required. These characteristics enable more accurate quantitative comparisons of multiple biomarkers. Red or far-red QDs are brighter than other QDs.23 The QD-MMBQ method labels all target biomarkers with the same QDs such as red QDs. Thus, our method is easier, more accurate, and more sensitive than previous multiplexed QD detection techniques. Note that although a cell-block section comprises homogeneous cells and it is regarded as a uniformly dispersed cell layer, the signal of a particular QD-labelled protein from randomly selected areas can differ considerably before LC normalization. This is due to variation in cell numbers and cell volume difference in a confined area (Fig. 5). The variation in cell number and volume in a cell-block section may be limited, but a significant signal difference arises due to the high sensitivity of QDs. However, QD signal variation was reduced by normalization of protein expression to that of the LC at the same location. Thus the immunochemical normalizing approach can compensate for the cell number and volume variation, guaranteeing a more accurate single-cell level quantification of protein expression in ICC (Fig. 4B). Specifically, a microfluidic immunochemical assay uses the microchannels as individual Ab-incubation chambers, and each protein is stained for in only a small region of the cell-block section. Therefore, microfluidic immunochemical assays would result in quantification errors if protein expression was measured without a LC in each channel due to the small number of sampling locations. Therefore, LC
Protein quantification using multi-windows and LC High flexibility is one of the strongpoints of the QD-MMBQ method. As previously stated, a cocktail method, which does not allow unintended reactions of QD–Ab conjugates, facilitates exploitation of Abs produced by different species to enhance multiplexing efficiency and avoid inappropriate QD binding. Nevertheless, more Ab producing species are needed to allow labeling of more proteins. Until now, since few animal species have been developed to produce Abs, the use of existing QD-IHC methods in pathology is problematic. In contrast, our QD-MMBQ method requires only two Abs from different animal species. All of the anti-protein-target Abs can be produced from the same species; only the LC Ab needs to be come from a distinct species. Accordingly, only two QD-conjugated reagents are required. Therefore, our method ensures high flexibility of
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Fig. 5 Fluorescence intensity of QD-labeled mTOR and b-actin. The SK-BR-2 cell-block section was stained with anti-mTOR Ab-QD605 and anti-b-actin Ab-QD525. (A) Fluorescence QD-stained images of randomly selected areas of a cell-block section. To emphasize the effect of LC normalization, sampling was performed from locations with different cell densities. Scale bar, 50 mm. (B) Fluorescence intensities of QD525 and QD605 in randomly selected areas of cell-block sections. mTOR*, the mTOR signal normalized to that of b-actin.
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normalization ensures the accuracy of protein quantification by microfluidic immunochemical assays.
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Comparison of protein expression levels between cell lines Furthermore, we were able to quantitate and compare the expression of various proteins in not only one cell-block section but also among cell-block sections. Eight proteins in SK-BR-3, MCF-7, and HCC-70 cells were compared quantitatively. As shown in Fig. 6, we compared the expression of the eight proteins with and without normalization. Importantly, without normalization, the ER expression of SK-BR-3 and MCF-7 cells was similar, although SK-BR-3 cells are ER-negative and MCF-7 cells ER-positive.24 In comparison, the normalized ER signal of SK-BR-3 and MCF-7 cells showed a considerable difference, being identified as negative and positive, respectively (Fig. 6B). Also, SK-BR-3 cells are PR-negative and MCF-7 cells are PR-positive.25 However, the PR expression levels of these cell lines become distinct after normalization. Thus we confirmed that normalized protein expression signals are more credible than non-normalized signals comparing previous proteomic studies of breast cancer cell lines.24,25 This is due to the overall elevation of protein expression in MCF-7 cells with normalization. Note that there is significant variation in the protein staining quality between tissues or cell sections with IHC or ICC due to the complex steps involved in sample preparation and staining steps (e.g., gel loading, fixation, paraffin embedding, microtome sectioning, deparaffinization, re-hydration, antigen retrieval process, etc.).26–31 Likewise, proteins in the MCF-7 cell-block section were generally stained more lightly than those in other sections; comparison of protein expression among different sections accurately is difficult without a calibration process. This is a critical issue in all kinds of immunochemical assays because conventional immunochemical assay is associated with technical difficulties in calibrating differences in staining among specimens. The b-actin-based normalization strategy compensates for differences in not only
Fig. 6 Protein expression by MCF-7, HCC-70, and SK-BR-3 cells. (A) Eight target proteins and b-actin were labeled with QDs on MCF-7, HCC-70, and SK-BR-3 cell blocks. QD605 was used to visualize the expression of each protein, while the QD525 intensity represented the reference marker signal. The lower images show the gray signal of biomarker expression (QD605). (B) Fluorescence intensity is expressed as arbitrary units (a.u.) of the QD605 signal (left panel) and the QD605 divided by QD525 signal (right panel) intensities for each strip (generated by the microchannels). In this way, the expression levels of the eight proteins were quantitated at the single-cell level (right panel).
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cell number but also in staining quality among specimens which is not possible using conventional methods. Multiple biomarker quantification in tissues Due to the use of micro-sized channels, a limited biomarker staining area can be problematic considering the unexpectedly distributed cancer cells in tissues. For this reason, determination of the region where tumor cells are populated in high density is critical to achieve successive biomarker screening using the QD-MMBQ method. To address this issue, we mounted a bundle of multiple channels over a densely populated cancer cell area which was determined by hematoxylin and eosin staining. Fig. 7A shows a staining result of eight biomarkers on a breast cancer tissue. Like the cell specimen staining using our method, biomarkers were labeled with QD605 and b-actin was attached with QD525. QDs were stained correctly at each location as shown in right images of Fig. 7A. Using our b-actinbased normalization strategy, eight biomarkers were quantified using spectroscopy (Fig. 7B). Although we demonstrated our method using clinical samples, tissue heterogeneity could be a problem using our biomarker multiplexing system, which uses tissue dimensions of about 400 mm 5000 mm for each biomarker, separately. This would not be adequate for the cases such as rare cell discovery using IHC.17 Our system could be effective for use in multiplexed biomarker screening of less heterogeneous cancer tissues. We previously demonstrated that for cases in which breast cancer
Fig. 7 Quantitative analysis of eight proteins on a breast cancer tissue section. (A) Eight target proteins and b-actin were labeled with QDs on a breast cancer tissue. QD605 was used to visualize the expression of each protein, while the QD525 intensity represented the reference marker signal. (B) The fluorescence intensity in arbitrary units (a.u.) of each area was compared quantitatively using the b-actin signal. (C) The values of coefficient of variation (CV) were compared between the b-actin normalized signal and the original signal of QD605. The b-actin normalized signal tends to be less variable than that was not normalized.
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tissues were analyzed, the parallel biomarker multiplexing approach showed strong consensus with conventional wholesection analysis.18 Also, because our system can be readily applied to various clinical specimens, assay accuracy can be improved by combining our system with a tissue microarray consisting of small replicate specimens. On the other hand, the use of an appropriate LC for the particular cancer can be a better solution to improve our quantification system in tissues. Notably, even when a tissue consisted of heterogeneous cells, normalized biomarker intensity showed less variance over the signal acquisition areas than biomarker intensity which was not normalized (Fig. 7C). This shows that the b-actin-based normalization concept has a possibility to be used for the accurate biomarker quantification of tissue samples.
Materials and methods Preparation of specimens A formalin-fixed paraffin-embedded breast cancer cell block was used for the demonstration of our protein quantification system. Breast cell lines, including MCF-7, SK-BR-3, and HCC70 cells, were purchased from the American Type Culture Collection (ATCC; Manassas, VA). MCF-7 and HCC-70 cells were cultured in RPMI-1640. SK-BR-3 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 100 IU mL 1 penicillin, and 100 mg mL 1 streptomycin. All cells were maintained at 37 1C and 5% CO2. For the fabrication of engineered tissues, after trypsinization, harvested cells were centrifuged. Formalin fixation, agar suspension, and paraffin embedding was accomplished to make cell blocks. Paraffin embedded blocks were then sectioned at 4 mm, the sections were mounted and baked onto positively charged glass slides. These samples were dried for 1 h at room temperature followed by 1 h in an incubator at 60 1C. Human breast cancer tissue samples were obtained from the Konyang University Hospital (Daejeon, Korea), with the corresponding written consents given by the patients or their relatives. This study was approved by the Institutional Review Board (IRB) at the Konyang University Hospital and the Korea Advanced Institute of Science and Technology (KAIST). Human tissue samples were fixed in 4% neutral-buffered formalin, Bouin’s fixative, acetic formalin alcohol (AFA), or 4% or 10% unbuffered formalin; 4 h in PreFer (Anatech, Battle Creek, MI) or Pen-Fix (Richard Allen Scientific; Kalamazoo, MI); or 48 h in 4% neutral-buffered formalin. After the paraffin embedding process, tumor specimens were sectioned into 4 mm and dried for 1 h at room temperature, followed by 1 h in a convection incubator at 60 1C. Immunocytochemical staining For the investigation of the multiplexed staining tendency of the sequential method, rabbit anti-human epidermal growth factor receptor 2 (HER2) antibody (Ab) (1 : 500, Dako, Denmark), rabbit anti-Ki-67 Ab (1 : 200, Novus Biologicals), and QD605conjugated goat anti-rabbit Ab (1 : 250, Invitrogen, Carlsbad, CA)
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and QD525-conjugated goat anti-rabbit Ab (1 : 100, Invitrogen) were used in sequential multiplexing. Cell blocks were deparaffinized in xylene and hydrated through a graded series of ethanol (70%, 80%, 95%, and 100% ethanol). The microwave antigen-retrieval technique was conducted in target retrieval solution, pH 9 (Dako), for 20 min at 750 W. The slide surface was blocked using blocking solution (2% bovine serum albumin with 5% goat serum in 1 phosphate buffered saline) or commercially available blocking solution (Zymed, San Francisco, CA) for 30 min at room temperature, the slides were incubated with primary Ab at room temperature for 30 min or 1 h. After washing with 1 Tris buffered saline-Tween (TBS-T; 0.1% Tween 20), QD-conjugated secondary Ab was applied to the slides at room temperature for 30 min or 2 h. Using this protocol, SK-BR-3 cells were labeled with rabbit antiHER2 Ab-QD525-conjugated goat anti-rabbit Ab and rabbit anti-Ki-67 Ab-QD605-conjugated goat anti-rabbit Ab. One slide was labeled with anti-HER2–QD525 first, the other was labeled with anti-Ki-67–QD605 first. For the demonstration of the cocktail method, mouse antiHER2 Ab (1 : 500, Dako) and rabbit anti-Ki-67 (1 : 200, Dako) were mixed prior to incubation. The Ab mixture was incubated on the SK-BR-3 cell-block section at room temperature for 30 min. After the washing step with TBS-T, QD605-conjugated goat anti-rabbit Ab (1 : 250, Invitrogen) and QD525-conjugated goat anti-mouse Ab (1 : 100, Invitrogen) were mixed and the QD-labeled Ab mixture was applied to the slides at room temperature for 30 min. Fabrication of a microfluidic device A conventional soft lithography technique was conducted to fabricate the devices. To make a mold of the microchannels, SU-8 3025 was spincoated on a bare silicon wafer to make rectangular reaction channels. The wafer was exposed to ultraviolet light with a mask and subsequently developed using an SU-8 developer. Then, the microfluidic device was fabricated by using a poly(dimethylsiloxane) (PDMS; Sylgard 184; Dow Corning, MA) replica molding process.18,19 Microfluidic immunochemical staining Estrogen receptor (ER) Ab (Ventana, Tucson, AZ), progesterone receptor (PR) Ab (Ventana), HER2 Ab (1 : 1000, Dako), human growth factor receptor 3 (HER3) Ab (1 : 50, Abcam, Cambridge, MA) were used at 1 concentrations or ready-to-use concentrations. Ki-67 (1 : 200, Dako) Ab, the mammalian target of rapamycin (mTOR) Ab (Abcam), transforming growth factor alpha (TGF-a) Ab (1 : 50, Abcam), and betacellulin (BTC) Ab (1 : 100, Proteintech Group, USA) were also used at 1 ready-to-use concentrations. All these antibodies were produced from rabbits, 2.5 mL of each biomarker was mixed with 2.5 mL of b-actin Ab (1 : 1000, Abcam), produced from mice prior to channel injection. To apply the QD-MMBQ to tissue models, SK-BR-3, MCF-7, and HCC-70 breast cancer cell-block sections were deparaffinized. After antigen retrieval treatment, a microfluidic device was mounted on the cell block slide, and the microfluidic channel layer was pressuresealed to prevent leakage between the channels formed on the sample slide. The mounted PDMS layer provided multiple isolated areas on the specimen. Then, the deparaffinized cell blocks were blocked with a blocking solution containing bovine
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serum albumin (BSA) and goat serum in phosphate-buffered saline (PBS; pH 7.4). 5 mL of each mixture was injected to each inlet, and withdrawal pumping from the outlet was accomplished to incubate biomarkers at a flow rate of 80 mL h 1 for 30 min. All inlets were washed with TBS-T after the incubation. Then, QD605-conjugated goat anti-rabbit Ab (1 : 250, Invitrogen) and QD525-conjugated goat anti-mouse Ab (1 : 100, Invitrogen) were mixed and 5 mL of the mixture was injected into every inlet. QD mixtures were incubated at a flow rate of 80 mL h 1 for 30 min. Prior to tissue staining, device alignment to the specific region of tissue section is required to collect protein signals from the region where the cancer cells are densely populated due to the morphological heterogeneity of breast cancer tissues. The alignment process was described in our previous report.18 Briefly, one of the tissue sections was stained with hematoxylin and eosin. After the determination of the region where tumor cells are populated in high density, the device was aligned to that region by comparing adjacent tissue sections to the hematoxylin and eosin stained one. All remaining processes for multiplexed QD staining were the same as above. Quantification of proteins For biomarker quantification, optical spectroscopy was performed using a fluorescence microscope (IX72; Olympus) with a spectrometer (QE65000; Ocean Optics) and a charge-coupled device. To determine the staining intensity of each protein, the fluorescence signal was collected from each strip individually. As mentioned above, we used two QDs (QD525 and QD605) with emission peaks of 525 nm for the reference marker and 605 nm for the target proteins. After elimination of autofluorescence, the QD605 signal was normalized to that of QD525 (see ESI,† Fig. S2).
Conclusions We have demonstrated a microfluidic multiple biomarker quantification method using QD nanoparticles and microfluidics. Particularly, we verified the QD sequential staining method staining-sequence problem using cell-block sections. The QD labeling method based on sequential staining induces unintended binding of QD–secondary-Ab conjugates, making qualitative and quantitative analyses problematic. In addition, our novel method can quantify simultaneously more than eight proteins in the same biological specimen. Expression levels of eight proteins in various cell lines were compared by co-labeling each target protein and the same LC in each microchannel. Our microfluidic method provides the most flexible multiplexed QD-immunochemical assay technique, allowing facile data analysis and more accurate biomarker quantification. LC-based quantification also shows the effect of cell number and staining quality variation among specimens. We also showed a possibility of using this system in multiple biomarker quantification of breast cancer tissues. Furthermore, microfluidic blocking is superior and controllable compared to the conventional static method. Based on its applicability in breast tissue from cancer patients, this facile method for quantification of multiple biomarkers will contribute to realization of the use of multiplexed QD-immunochemical assay in many fields.
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Acknowledgements This research was supported by a National Leading Research Laboratory Program (NRF-2013R1A2A1A05006378), a Nano/Bio Science and Technology Program (NRF-2005-2001291), and a Converging Research Center Program (2011K000864) through the National Research Foundation of Korea funded by the Ministry of Science, ICT and Future Planning. The authors also acknowledge a Cooperative Research Program for Agriculture Science and Technology Development (Grant PJ009842) supported by the Rural Development Administration of Korea.
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