
==== Front
Biochem Biophys Rep
Biochem Biophys Rep
Biochemistry and Biophysics Reports
2405-5808
Elsevier

S2405-5808(24)00180-8
10.1016/j.bbrep.2024.101816
101816
Research Article
Advancements in Chronic Myeloid Leukemia detection: Development and evaluation of a novel QCM aptasensor for use in clinical practice
Domsicova Michaela michaela.domsicova@savba.sk
a
Kurekova Simona b
Babelova Andrea c
Jakic Kristina c
Oravcova Iveta d
Nemethova Veronika ef
Razga Filip ef
Breier Albert ag
Gal Miroslav miroslav.gal@stuba.sk
h⁎
Poturnayova Alexandra alexandra.poturnayova@savba.sk
a⁎⁎
a Centre of Biosciences, Institute of Molecular Physiology and Genetics, Slovak Academy of Sciences, Dúbravská cesta 9, 840 05, Bratislava, Slovakia
b Department of Biology, Faculty of Medicine and Dentistry, Palacky University, Hněvotínska 3, 775 15, Olomouc, Czech Republic
c Biomedical Research Center, Department of Nanobiology, Cancer Research Institute, Slovak Academy of Sciences, Dúbravská cesta 9, 845 05, Bratislava, Slovakia
d National Cancer Institute, Department of Oncohematology, Klenová 1, 833 10, Bratislava, Slovakia
e Faculty of Medicine Comenius University in Bratislava, Špitálska 24, 813 72, Bratislava, Slovakia
f Selecta Biotech SE, Istrijská 6094/20, 841 07, Bratislava, Slovakia
g Institute of Biochemistry and Microbiology, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia
h Department of Inorganic Chemistry, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Radlinského 9, 81237, Bratislava, Slovakia
⁎ Corresponding author. miroslav.gal@stuba.sk
⁎⁎ Corresponding author. alexandra.poturnayova@savba.sk
23 8 2024
9 2024
23 8 2024
39 10181612 4 2024
19 8 2024
21 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Oncological diseases represent a significant global health challenge, with high mortality rates. Early detection is crucial for effective treatment, and aptamers, which demonstrate superior specificity and stability compared to antibodies, offer a promising avenue for diagnostic advancement. This study presents the design, development and evaluation of a quartz crystal microbalance (QCM) sensor functionalized with the T2-KK1B10 aptamer for the sensitive and specific detection of Chronic Myeloid Leukemia (CML) K562 cells. The research focuses on optimizing the biorecognition layer by adjusting the aptamer conditions, demonstrating the sensor's ability to detect these CML cells with high specificity and sensitivity. The aptamer-modified QCM sensor operates on the principle of mass change detection upon binding of target cells. By employing the Langmuir isotherm model, the performance of the sensor was optimized for the capture of CML cells from biological samples with LOD of 263 K562 cells. The sensor was also successfully regenerated multiple times without sensitivity loss. Validation of the sensor's performance was conducted under controlled laboratory settings, followed by extensive testing utilizing human lyophilized plasma and clinical samples from patients. The sensor exhibited high sensitivity and specificity in the detection of CML cells within clinical specimens, thereby illustrating its potential for practical clinical deployment. This research presents a novel approach to the early diagnosis of CML, facilitating timely intervention and enhanced patient outcomes. The developed aptasensor demonstrates potential for broader application in cancer diagnostics and personalized medicine.

Highlights

• Development of a QCM aptasensor for detecting K562 cells associated with Chronic Myeloid Leukemia.

• Optimization of the aptasensor's biorecognition layer for enhanced sensitivity and specificity.

• Validation of sensor performance using synthetic human plasma and clinical patient samples.

• Demonstrated clinical potential of the aptasensor for early and accurate CML detection.

Keywords

QCM aptasensor
Chronic Myeloid Leukemia
K562 cells
Biorecognition layer optimization
Clinical application
Human plasma
==== Body
pmc1 Introduction

Oncological diseases belong consistently to the most serious diagnoses with high mortality rates among the human population. Early diagnosis enables effective treatment at the state when cancer disease is not fully developed, as the survival rate of patients is only slowly improving in recent years. Therefore, it is essential to continually search for new diagnostic methods that offer high sensitivity and specificity for the detection of cancer cells [1].

Identifying biomarkers for diseases is an important objective for early diagnosis. Biomarkers are biomolecules present in human cells, tissues, or body fluids and are found in samples of cancer and/or pre-cancerous patients [2].

The diagnosis of diseases often relies on the use of antibodies to quantitatively identify or locate specific biomarkers. Antibody-based diagnostic methods are the most commonly used in clinical practice. However, their higher cost, lower stability, limited target range, and sometimes lower specificity make them less attractive [3].

Recently, there has been significant interest in aptamers. They are synthetic oligonucleotides with both single- and double-stranded areas that fold into a well-defined 3D structure, exhibiting high specificity and affinity for their target molecules. Aptamers can bind a wide range of molecules, with different molecular mass, which may be dissolved in medium or attached on surface of whole cells and tissues [4]. Their high specificity, affinity, and stability, coupled with the potential for simple modification and storage, render them advantageous for application in novel diagnostic methods. Especially DNA aptamers exhibit higher stability and easier handling compared to RNA aptamers [5].

Although traditional cancer diagnostics such as biopsies, tissue analysis, and imaging techniques offer valuable insights, they often have some limitations [6]. In contrast, aptamer-based diagnostics show promise by offering minimally invasive, highly sensitive, and specific detection methods for early and accurate cancer diagnosis [7].

The use of aptamers can aid in the early diagnosis of oncological diseases. Specifically, aptamers selected for sensitive interaction with biomarkers located on the surface of cells specific to oncological diseases can be employed. These synthetic DNA molecules can specifically target cancer biomarkers with high affinity, outperforming antibodies in key areas. Aptamers can be easily modified, reducing production costs, and expanding their target range. Additionally, their stability at diverse temperatures and lack of immunogenicity further solidifies their potential for non-invasive, point-of-care cancer detection, paving the way for personalized medicine advancements [8,9].

The interaction between aptamers and target biomolecules can be effectively measured using the quartz crystal microbalance (QCM), which allows for direct monitoring of the interaction over time using an aptasensor. QCM acts like a microscopic scale, precisely measuring mass changes on its surface. This unique ability shines in cancer cell detection, as binding of cancer cells to specific aptamers, tailor-made DNA molecules, alters the QCM's resonance frequency. This label-free, real-time detection offers high sensitivity and specificity, opening avenues for early on site cancer diagnosis and treatment efficiency monitoring, which may provide data for personalized approaches [9].

One of the clinical challenges is the detection of Minimal Residual Disease (MRD), involving the identification of small numbers of CML cells remaining after treatment. Accurate MRD detection is crucial for predicting relapse and guiding therapy, but current methods often lack the necessary sensitivity [10]. It is important to improve the specificity of these methods to ensure reliable MRD detection by distinguishing CML cells from other blood cells, limiting false positives and unnecessary interventions [11]. QCM aptasensors show potential in addressing these challenges.

The quintessence of our study was to engineer an innovative aptasensor, through the strategic immobilization of the T2-KK1B10 aptamer onto the gold electrode surface of a QCM sensor, thereby facilitating the selective detection of CML K562 cells within biological samples [12]. Our methodology is based on the adsorption phenomena of K562 cells onto the aptamer-functionalized sensor surface, postulating that this interaction adheres to the theoretical framework of the Langmuir isotherm model. The Langmuir isotherm provides a valuable framework for interpreting our data, as it can model specific, saturable binding interactions like the interaction between aptamer and target cells [13]. The culmination of our efforts was the optimization of the aptasensor, which demonstrated exemplary performance in the analysis of clinical specimens from patients diagnosed with CML. This work provides a promising approach for the rapid and sensitive detection of CML disease and lays the foundation for the use of aptasensor technology in clinical diagnostics.

The present study introduces a novel QCM aptasensor based on aptamer T2-KK1B10 for the sensitive and specific detection of CML K562 cells. By combining the specificity of aptamers with the sensitivity and real-time monitoring capabilities of QCM, we have developed a promising diagnostic tool for early-stage CML detection. Our findings contribute significantly to the field by providing a promising tool for early disease diagnosis and monitoring and demonstrating the potential of aptamer-based sensors for clinical applications.

2 Material and methods

2.1 Reagents

Ultrapure water with a resistivity of 18.2 MΩ cm at 25 °C (Simplicity 185, Merck Millipore) and chemicals with the highest available purity were used to prepare the solutions: neutravidin (Thermo Fisher Scientific), human lyophilized plasma (Helena BioSciences), hydrogen peroxide 30 %, ethanol 96 %, ammonia 26 %, acetone, methanol (Centralchem), sodium dodecyl sulfate (SDS), for PBS (pH 7.4): sodium hydrogen phosphate dihydrate (Na2HPO4·2H2O 8 mM), potassium dihydrogen phosphate (KH2PO4 2 mM), sodium chloride (NaCl 150 mM), potassium chloride (KCl 3 mM) and tablets for the preparation of PBStb (Sigma).

In this work, aptamer T2-KK1B10 was used with following sequence: [5′-TTT TTT TTT TAC AGC AGA TCA GTC TAT CTT CTC CTG ATG GGT TCC TAT TTA TAG GTG AAG CTG T-3']. It was isolated against CML K562 cells, without a more precise determination of the binding site [12]. The aptamer sequence was modified at the 5′ end with a thiol group or biotin in order to facilitate strong binding to the gold surface of the sensor [14,15].

Aptamer was synthesized by Thermo Fisher Scientific in lyophilized form and dissolved in TE buffer (10 mM Tris, 1 mM EDTA) [16], 100 μM aliquots were stored in a freezer at −20 °C. For experiments, the aptamer was dissolved in Dulbecco's Phosphate Buffered Saline with magnesium chloride and calcium chloride (D'PBS, Biosera) [12] to a concentration of 0.5 μM. 1-Dodecanethiol (DDT, Sigma) diluted in D'PBS was used to fill the vacancies on the gold surface [17].

2.2 Cell culture and patient sample preparation

K562 (human chronic myelogenous leukemia), MOLT-4 (CRL-1582, human T lymphoblast cell line), BV173 (precursor for CML), HL-60 (promyelocytic AML cell line), JURKAT (ALL T lymphoblast), Kasumi-1 (AML myeloblast), MOLM-7 (CML), THP-1 (acute monocytic leukemia monocyte) were cultured in RPMI 1640 medium (Biosera) supplemented with 10 % fetal bovine serum and 1 % penicillin-streptomycin (Sigma) in an incubator at 37 °C and 5 % CO2, diluted to ⅕ every third day [[18], [19], [20]]. For each experiment, a freshly prepared cell solution was used, washed from the medium, and the cells were diluted in sterile PBS at a concentration of 50 - 5 × 10⁶ cells per milliliter. This was achieved using the Burker's chamber method with trypan blue staining.

Clinical peripheral blood samples from patients diagnosed with CML (National Cancer Institute, Slovakia) were prepared by the isolation of mononuclear cells through gradient centrifugation using Ficoll-Paque (Sigma). The fresh blood sample was diluted 1:1 with PBS and carefully pipetted onto the Ficoll-Paque solution in a 2:1 ratio, in order to prevent penetration of the blood into the Ficoll solution. The layered blood sample was subjected to centrifugation for a period of 35 min at a speed of 400 g without the application of the brake. Subsequently, a gradient was established, comprising the blood plasma in the upper layer, a layer of isolated mononuclear cells in the centre, and the Ficoll solution and erythrocytes at the bottom of the tube. The cells were then extracted from the ring and diluted in PBS before being subjected to centrifugation [21]. The washing step was repeated two times. Following the washing procedure, the isolated cells were suspended in freezing solution and stored at −80 °C. Prior to utilisation in the experiment, the cell sample was thawed in a water bath at 37 °C and stabilized in culture medium for approximately 1 h in an incubator at 37 °C. Following stabilization, the sample was centrifuged at 330g for 10 min and washed with PBS [22]. After dilution in PBS, the cells were counted using a Burker cell counter and diluted to the desired number for direct use on the sensor.

The clinical sample was prepared by isolating mononuclear cells from fresh peripheral blood of patients diagnosed with CML (National Cancer Institute, Slovakia) using density gradient centrifugation over Ficoll-Paque (Sigma). Before experiments, cell/patient samples were counted using Burker chamber, centrifuged and resuspended in D'PBS or human plasma.

2.3 Aptasensor design

The sensor (8 MHz, Total Frequency Control Ltd.) was chemically cleaned with basic piranha (peroxide: ammonia: water = 1 : 1: 5) at a temperature of 70 °C for 25 min in three repetitions. Subsequently, the sensor was rinsed and stored in 96 % ethanol. Just before the surface modification, the sensor was ultrasonically cleaned successively in a solution of acetone, methanol, and ethanol for 5 min and dried with nitrogen gas.

The cleaned sensor was inserted into a flow cell connected to the QCM circuit. Using a syringe pump, a sample flowed into the flow cell, which was monitored directly in time. To form a sensitive aptamer layer, two procedures were applied. During the first procedure the samples were placed into the flow cell and respective layer-forming agents were used in the following order: water, neutravidin, buffer, biotin-labeled aptamer, and buffer with culture medium elements (B*).

In the case of the second type of procedure an aptasensor was prepared by placing a cleaned crystal in an incubation cell, where the surface of the gold electrode came into contact with a solution of thiol-labeled aptamer and DDT at room temperature overnight. After incubation, the sensor was washed, gently dried and mounted in a flow cell. The performance of aptamers prepared by both methods was then compared. The procedures used were adopted from the work of Poturnayová et al. [23].

2.4 Quartz crystal microbalance

RQCM (Maxtek, Inficon) consists of an AT-cut quartz crystal with gold electrodes on the surface and is used to study interaction affinity reactions of sample and surface-immobilized layer. When an alternating voltage is applied through the electrodes, due to the piezoelectric effect, an acoustic wave propagates from the surface into the liquid. The consequence of the viscous forces causing friction between the surrounding fluid and the layer immobilized on the surface is a decrease in the resonance frequency depending on the weight attached to the surface according to the equation derived for the liquid environment from Sauerbrey equation for vacuum measurements Δf=−f03/2ρLηLπμqρq [24].

To accurately quantify these interactions, a flow system was employed, leveraging the robust interaction between neutravidin and the biotin-labeled aptamer [25]. This dynamic setup enabled the direct observation of binding events over time, thereby providing valuable kinetic information. To optimize the experimental conditions, a variety of parameters were investigated, including buffer composition, aptamer pretreatment and concentration. The resulting optimized protocol was then applied to experiments utilizing an aptasensor prepared by chemisorption of a thiol-labeled aptamer on the gold electrode surface. A comparative analysis of the two aptamer immobilization methods (biotin-neutravidin and thiol-gold) was conducted to determine the most stable and sensitive configuration for the aptasensor.

It is crucial to consider the influence of experimental conditions on aptamer structure and function.

The 3D structure of the aptamer is dependent on specific conditions, including a suitable ionic environment. The presence of ions in the solution stabilizes this structure. To ensure optimal conditions for the flow system reaction environment, it is necessary to optimize the ion content of the washing solution [26]. However, it is important to ensure that the composition of the washing solution does not affect the interaction of cells with the aptamer. To evaluate a suitable composition, it is necessary to test the robustness of the binding of the aptamer to the neutravidin layer on the surface of the sensor, its stability, and the interaction with the K562 cell sample.

2.5 Confocal microscopy

Each cell line was exposed to 0.5 μM of FAM-labeled T2-KK1B10 aptamer and incubated at 37 °C and 5 % CO2 for 60 min. After incubation, the cells were washed with buffer to remove extracellular T2-KK1B10 aptamer, and fresh medium without Phenol Red was added. The cell membranes were stained with WGA Texas Red membrane stain (Invitrogen) and visualized at 595/615. The FAM-labeled T2-KK1B10 aptamer was visualized using a Leica TCS SP8 AOBS confocal microscope (Leica Microsystems, Wetzlar, Germany) at 493/517 nm. The visualizations were obtained with magnification of 63 × using an oil immersed objective.

The Langmuir isotherm model was used to fit the data points in SigmaPlot.

3 Results and discussion

3.1 Optimization of experimental conditions

To design the aptasensor correctly, the first step is to optimize the conditions for creating a stable, properly oriented, and sensitive biological recognition layer [27]. This involves selecting the appropriate composition of the washing solution, aptamer treatment, and concentration to ensure fast and gentle preparation of the aptasensor.

To form a sensitive recognition layer for the aptasensor in the flow, we used the T2-KK1B10 aptamer, which binds to K562 cells, derived from a patient with chronic myeloid leukemia [12]. In Fig. 1 the changes in resonance frequencies during optimization experiments are plotted. In addition, the confocal images of the direct interaction of K562 cells and the T2-KK1B10 aptamer in buffers with different ion content are also shown to visualize respective interactions.Fig. 1 Resonance frequency changes (Δfs) in optimization experiments. A - Aptamer Biotin-T2-KK1B10 binds neutravidin (125 μg/ml) in a washing solution with varying compositions. B - Changes in frequency after detection of 50 × 103 K562 cells by aptamer with different composition of washing solution. C - Binding of an aptamer prepared with and without temperature shock. D - Binding of an aptamer of different concentration to neutravidin. E − Confocal visualization of the interaction of K562 cells and the T2-KK1B10 aptamer in buffers with different ion content. Red dye (WGA Texas Red) visualizes cell membrane and green dye visualizes FAM-modified T2-KK1B10 aptamer. The physical size of each map is 92 × 92 μm.

Fig. 1

Fig. 1A and B clearly demonstrates that D'PBS provided the most sensitive and stable response for both cell and aptamer response. Based on this observation D'PBS was used in all following experiments as a washing solution. These findings are in accordance with previous studies that have isolated the T2-KK1B10 aptamer [12]. In this study, the same D'PBS solution was employed as the binding solution. It is established that utilizing the binding solution as the washing solution yields optimal results for the folding of the 3D structure of the aptamer [28]. This choice was further confirmed through direct visualization using a confocal microscope (Fig. 1E), as the most intense interaction between the aptamer and cells was observed in the D’PBS solution.

Ensuring sensor sensitivity and stability entails the second optimization factor which involves thermal pretreatment of the aptamer. To achieve the correct folding of the 3D structure, subjecting the DNA strand to a temperature shock may be necessary. The aptamer solution should be exposed to a temperature of 90–95 °C for 3 min and then allowed to cool down to room temperature [29]. The aptamer that underwent this treatment exhibited better stability and sensitivity in cell detection compared to the untreated aptamer (Fig. 1C). The impact of temperature treatment on the stability of the three-dimensional structures of the aptamer, and thus on the sensitivity of the aptamer, has also been demonstrated for the detection of thrombin [30].

Subsequently, the third important factor in optimizing the preparation of the aptasensor was studied. In this step, the concentration of the aptamer was optimized to create a stable monolayer and saturate the surface of the sensor covered with neutravidin in the shortest possible time. An optimum aptamer concentration of 0.5 μM was determined because it produced the most stable and compact layer without significant washing out of unbound molecules and with sufficiently rapid deposition of aptamer molecules on the surface (Fig. 1D). Following these optimization procedures, a stable aptasensor was created in the QCM flow system by forming a strong biological bond between neutravidin and a biotin-labeled aptamer or by incubating a thiol-labeled aptamer on the gold surface of an electrode for the detection of the CML cell line K562 from a sample.

3.2 Detection of CML cells in the sample

In addition to the previous series of optimization steps for the preparation of the biorecognition layer, it is important to keep in mind when constructing a functional biosensor that the monolayer of the aptamer must be appropriately oriented on the surface of the gold substrate. Fig. 2 shows the changes in resonance frequency (Δfs) of the aptasensor over time. This includes the formation of a sensitive recognition layer, recognition of K562 cells, and repeated detection after surface regeneration.Fig. 2 A - Changes in resonance frequency Δfs of the aptasensor over time during the formation of a sensitive recognition layer. The frequency decreases during binding events on the surface after the addition of neutravidin (125 μg/ml) and aptamer (0.5 μM). Individual additions are indicated by arrows. B - Resonance frequency changes after addition of K562 cells (50, 5 × 103, 10 × 103) to the surface of an aptasensor with a sensitive recognition layer formed by incubating a thiol-labeled aptamer on a gold surface. C - Frequency changes caused by the addition of 50 × 103 K562 cells before and after surface regeneration with 1 % SDS regenerating agent. Addition of cells after surface regeneration is shown by arrows. R indicates steps of washing with a buffer, adding 1 % SDS and washing.

Fig. 2

As can be seen in Fig. 2, the gold electrode surface is saturated with neutravidin molecules from an aqueous solution with a concentration of 125 μg/ml. After washing away the unbound molecules with water, a chemisorbed monolayer is formed, which reacts with the biotin-labeled DNA sequence of the aptamer. The change in frequency is equivalent to the weight bound on the gold surface [31].

Once the frequency has stabilized, it is necessary to change the reaction medium from water to a wash solution with an appropriate ion content to support the correct folding of the aptamer's 3D structure and enable it to bind effectively. This is observed as a frequency deviation in the QCM recording. After stabilization of frequency changes, the biotin-labeled aptamer binds to neutravidin molecules in a D’PBS solution with a concentration of 0.5 μM, utilizing the high affinity of biotin to neutravidin [32]. Then another washing procedure is applied with subsequent frequency stabilization indicating the end of binding events. The remaining sensor's free sites are blocked for non-specific reactions by a solution containing trace elements of the culture medium in which K562 cells are grown (B*). A decrease in frequency indicates that the medium components bind to the free surface of the sensor between the aptamer molecules.

Finally, the prepared aptasensor is ready to detect the presence of K562 cells in the sample. After applying the optimized experimental conditions for creating a functional aptasensor in the flow system, we used these conditions on the aptasensor that was prepared by directly incubating the thiol-labeled aptamer on the gold surface of the sensor.

Afterwards the sensitivity and stability of both aptasensors were tested and compared by adding different amounts of the cells (Fig. 2B). After adding the first, lowest amount, the sensor was washed and the second, higher number of K562 cells was added. This step was repeated several times. The cells were added for the same duration of 40 min to enable comparison.

The ability of aptasensor to re-detect CML cells following regeneration of the sensitive surface demonstrates its stability and clinical potential. The study of Xue et al. demonstrated the aptasensors' capacity for facile regeneration of the surface, whereby the electrochemical aptasensor was regenerated using high temperature, thereby retaining high stability even after five cycles of surface regeneration [33]. The SPR aptasensor was successfully regenerated five times using 0.5 % SDS, with the sensitivity remaining almost constant [34]. Furthermore, the regeneration of the QCM aptasensor for the detection of bacterial cells using a 20 mmol/L NaOH solution containing 1.0 % SDS has been previously documented [35]. Sensor regeneration can be successfully reproduced multiple (at least four) times for aptasensors created using both flow-through and incubation approaches. The efficiency of an aptasensor to detect K562 cells of the same amount, following ideal surface regeneration, ranged from 80 to 110 % (Fig. 2C). This statement confirms that it is possible to use a single sensor for multiple sample analyses without a significant loss of recognition ability.

To confirm the specificity of the aptamer towards K562 cells, it was necessary to exclude the possibility of non-specific interactions, which were monitored by QCM. Given that the T2-KK1B10 aptamer was isolated specifically for the K562 CML cell line, cell lines of other types of CML and leukemia were considered as negative controls with significantly lower anticipated interaction values. A comparison of the interaction between the aptasensor and the non-specific CML cell line BV-173 by QCM revealed a partial interaction of 27.5 %, thereby confirming the specificity of the aptasensor for K562. The examination of interactions with other leukemia type cell lines, including MOLT-4 and JURKAT (ALL) and HL-60, KASUMI (AML), THP-1, and healthy lymphocytes, revealed even lower interactions, with a value of 19.1 % (see Supplementary Fig. S1). This is in accordance with confocal microscopy results (Supplementary Fig. S2).

Since the T2-KK1B10 aptamer is specific for a cell type and not for a particular surface marker, it is assumed that it can also capture to some extent cells that have some similarity to the K562 line [36,37]. The detection of oncological cells using QCM is dependent on the presence of a specific aptamer in the recognition layer bound to the sensor surface and the provision of suitable conditions. In the absence of the aptamer, there was no interaction with the K562 cell line in either the D'PBS environment or the human plasma environment. This highlights the importance of aptamer selection and suitable conditions for successful detection.

3.3 Calibration curves and limit of detection

The limit of detection (LOD) represents a critical attribute of a high-quality and sensitive biosensor, serving as a benchmark for its analytical performance. This parameter is pivotal in assessing the suitability of a biosensor for clinical applications, as it quantifies the lowest concentration that can be detected with statistical significance, distinguishing high-performing devices from those inadequate for precise diagnostic purposes. We plotted the calibration curves from the dependence of the resonance frequency changes, Δfs on the different number of K562 cells added and determined the LOD of our aptasensor (Fig. 3).Fig. 3 Calibration dependencies of the frequency change from cell number using biotin-labeled (A) and thiol-labeled (C) aptamer. Limits of detection from the linear region of the calibration curves for biotin (B) and thiol (D) labeled aptamer.

Fig. 3

A calibration curve was constructed by recording the frequency changes at least three times for each addition of cells, showing the relationship between the frequency change and the number of K562 cells added to the flow system (Fig. 3A and C). Based on the literature data the LOD was calculated from the linear part of the calibration curves [38].

As shown in Fig. 3, the frequency change remains linear at lower cell amounts. However, at higher amounts, the dependence becomes saturated and loses its linearity. For clinical purposes such as early diagnosis, the focus is primarily on the performance of the sensor in the detection of lower cell numbers in the sample [39].

After evaluating the performance of aptasensors constructed through flow-through and incubation methodologies, it is evident that the incubation-based system, which uses thiol-labeled aptamers attached to a gold electrode surface, shows superior sensitivity. This system can distinguish significantly lower cell counts (see Fig. 3). In the context of the thiol-T2-KK1B10 aptasensor, a reduction in frequency was observed at cell concentrations as low as several tens of cells per milliliter. However, for the biotin-T2-KK1B10 aptasensor, this reduction was only noticeable at cell concentrations in the thousands per milliliter. The comparison of LOD values supports these findings. The LOD for thiol-T2-KK1B10 is 263 cells, while for biotin-T2-KK1B10, it is 4153 cells (as shown in Fig. 3B and D). The linear range of more sensitive, thiol-aptamer modified sensor is 0.5 × 102 - 5 × 105 where the correlation coefficient fits 0.01 level of significance for two tailed test. The QCM aptasensor we developed demonstrates excellent performance in the detection of K562 cells, as shown in Table 1, compared to other types of sensors used in previous studies. It is worth noting that according to our observation aptasensors produced through the incubation process exhibit remarkable stability, maintaining their sensitivity for several days of storage. This characteristic gives them the ability to be deployed quickly, allowing for rapid assessments as needed in clinical practice.Table 1 Various sensors for detecting K562 cells and their LODs.

Table 1Detection method and sensor	Linear range [K562/ml]	LOD [K562/ml]	Reference	
thiol QCM aptasensor designed in this work	0.5 × 102 - 5 × 105	263	this work	
electrochemical sensor: reduced graphene oxide + Ag nanoclusters quantum dots	–	<1 × 103	[48]	
electrochemical sensor: concanavalin A on gold amplified by AuNPs	1 × 102 - 1 × 107	73	[49]	
electrochemical aptasensor: Au nanoflower decorated graphene–hemin composite	–	10	[50]	
electrochemical aptacytosensor: aptamer + biotin conjugated concanavalin A	1 × 102 - 1 × 107	79	[51]	
electrochemical aptasensor: polystyrene microspheres + quantum dots	0.1 × 102 - 1 × 107	3	[52]	
electrochemical sensor: collagen/peptide probe on a glassy carbon plate	0.27 × 102 - 2 × 103	8	[53]	
electrochemical sensor: aptamer concatamer-CdTe quantum dots probe	1 × 102 - 1 × 107	60	[54]	
electrochemiluminescence device: aptamer-ZnO@carbon quantum dots	–	46	[55]	

Table 1 presents a comprehensive comparison of various sensors for detecting K562 cells, focusing on their respective detection limits, linear range, and design. Although our aptasensor demonstrated a slightly higher limit of detection (LOD) compared to other methods, it could detect interactions at a threshold as low as 50 cells. Electrochemical sensors have been highlighted for their lower limit of detection (LOD); however, they exhibit certain limitations that our Quartz Crystal Microbalance (QCM) aptasensor effectively addresses by providing a simpler, more direct detection method, reducing the need for intricate sample handling, and eliminating the requirement for specialized chemicals or complicated sensor preparation procedures. This represents a significant advancement, given the skepticism surrounding the LODs of other methods, which may stem from inconsistencies in sample preparation, such as dilution effects. Our QCM aptasensor is notable for its rapid response, ease of fabrication and operation, and the elimination of sample modification or elaborate preparation of the sensing layer. Furthermore, the incorporation of Gold Nanoparticles (AuNPs) facilitates signal enhancement, indicating a promising avenue for further improving the sensor's performance.

3.4 Langmuir isotherm model

To ensure that the adsorption of K562 cells on the solid surface of a gold sensor covered with a layer of aptamer, either modified with biotin or with thiol, is not influenced by uncertain internal processes in the flow cell, the measured data were processed using an isotherm model (Fig. 4).Fig. 4 Fig. 4: Adsorption of K562 cells on the solid surface of a gold sensor covered with a layer of aptamer A - modified with biotin, B - modified with thiol. Nonlinear fit according to the Langmuir Isotherm model.

Fig. 4

In this model, the changes of measured frequency responses Δfs in the dependence on the number of cells were plotted and subsequently fitted by nonlinear model (Fig. 4) using equation B=BM×(cc+K). Here, B represents the number of adsorbed cells, Bm represents the maximum number of adsorbed cells when c (number of cells) approaches infinity, and K represents the median concentration that fulfills cell adsorption where B equals half of Bm. The Langmuir adsorption isotherm is commonly used to depict the equilibrium between an adsorbate and adsorbent system, where the adsorption of the adsorbate is confined to a single molecular layer. This model is generally applicable for describing the sorption process when various types of bonds (ionic, covalent, or van der Waals) are established between the adsorbent and adsorbate, and the adsorbate's binding sites become successively occupied by the adsorbate [40].

In our measurements this model assumes that the adsorbed cells do not bind the next layer of cells, resulting in a single layer of adsorption. Once the surface is occupied, no further interactions occur. The process behavior is only controlled by the isotherm without the influence of internal processes in the flow cell [41,42]. In this case, the limiting process is the adsorption of cells on the aptasensor surface either modified by biotin or thiol. Therefore, the change in frequency is linearly and clearly dependent on the number of adsorbed cells and not on other internal processes in the flow cell. The correlation between the number of adsorbed cells and the number of added (suspended) cells at low numbers is due to the abundance of availability of binding sites for individual cells. At higher numbers of cells added, the aptasensor surface quickly saturates, resulting in a deviation from linearity as the cells do not have an excess of binding sites available. The observed trends in our data suggest agreement with the Langmuir model's principles, indicating a well-defined, monolayer binding process on the sensor surface.

3.5 Clinical testing

The potential of aptamers for use in testing clinical samples has already been demonstrated by several published papers. It has been shown that very low concentrations of SARS-CoV-2 disease-associated proteins can be rapidly detected by an aptamer-based biosensor from nasal swab, urine and saliva samples with LOD of 10 fM [43]. The detection of mannose-capped lipoarabinomannan, a molecule produced by Mycobacterium tuberculosis, serves as a biomarker for tuberculosis disease. Aptamer immunohistochemistry demonstrated a 36 % higher detection efficiency than the antibody-based method [44]. An aptamer, designated LC-18, with high affinity for lung cancer tissue and circulating tumour cells in blood, was employed to construct an aptasensor for the detection of cancer-related proteins in blood plasma samples. The detection limit of the aptasensor was found to be 2.3 ng/mL [45].

To validate the clinical feasibility of the aptasensor, its performance must be validated under conditions that closely mimic the human physiological environment. Human plasma is a more accurate surrogate for the blood environment than D’PBS [46]. Washing the sensor's surface with D’PBS solution is crucial in stabilizing the aptamer structure, preserving its integrity, and ensuring its ability to recognize cells in a diluted plasma solution. The response of the aptasensor to the introduction of K562 cells suspended in human plasma was carefully monitored. Its detection efficiency was compared to the calibration data obtained under optimal conditions provided by D’PBS (referenced in Table 1).

The evaluation of a stable aptasensor with clinical patient samples marks a critical transition from laboratory settings to actual clinical application. The correlation between the K562 cell line and Chronic Myeloid Leukemia (CML) supports the use of an aptasensor, particularly one that includes the T2-KK1B10 aptamer, for detecting CML cells in clinical patient specimens [47]. Samples from patients diagnosed with CML were analyzed using the aptasensor configured with the thiol-labeled aptamer, which has increased sensitivity and stability. Subsequently, we compared the effectiveness of detecting K562 cells suspended in plasma and detecting CML cells in clinical samples of four diagnosed patients to the detection of the K562 cell line in D’PBS.

The detection efficiency remained very high, an average of 97 ± 18 % for plasma and 96 ± 9 % for patient samples when compared to ideal laboratory conditions, respectively. Our findings present promising results for a novel QCM biosensor that utilizes the T2-KK1B10 aptamer to effectively identify CML cells, even under conditions that mimic real-world scenarios. The biosensor's sensitivity remains intact when exposed to human plasma and actual patient samples, making it a valuable tool for real-world applications. Furthermore, the sensor was able to detect the presence of CML with as few as 500 cells per milliliter. This sensitivity approaches the LOD for thiol aptasensor in laboratory conditions. These results underscore the significant potential of our approach in clinical practice. The high sensitivity and effectiveness of the aptasensor in realistic settings render it a promising tool for earlier and more accurate diagnosis of CML. This advancement holds the potential to significantly improve patient outcomes and revolutionize the management of this challenging disease.

CRediT authorship contribution statement

Michaela Domsicova: Writing – original draft, Visualization, Validation, Investigation, Formal analysis. Simona Kurekova: Writing – review & editing, Investigation. Andrea Babelova: Writing – review & editing, Resources. Kristina Jakic: Writing – review & editing, Resources. Iveta Oravcova: Resources. Veronika Nemethova: Writing – review & editing, Funding acquisition. Filip Razga: Writing – review & editing, Funding acquisition. Albert Breier: Writing – review & editing, Formal analysis. Miroslav Gal: Writing – review & editing, Funding acquisition. Alexandra Poturnayova: Supervision, Project administration, Methodology, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Filip Razga reports a relationship with Selecta Biotech SE that includes: board membership, employment, and equity or stocks. Veronika Nemethova reports a relationship with Selecta Biotech SE that includes: board membership, employment, and equity or stocks. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the Supplementary data to this article:Multimedia component 1

Multimedia component 1

figs1 figs1

figs2 figs2

Acknowledgements

This work was supported by the 10.13039/501100006109 Science Grant Agency VEGA [grant numbers 2/0160/21 , 1/0069/20 , and 1/0157/24 ] and The 10.13039/501100005357 Slovak Research and Development Agency [grant number 19-0070 ].

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbrep.2024.101816.
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