# Design of an electrochemical biosensor based on reduced graphene oxide conjugated with a pyrene-carbohydrate for the subfemtomolar detection of the cancer biomarker AMF/PGI

Jia Guo, Hafsa Korri-Youssoufi, Laurent Salmon

► To cite this version:

Jia Guo, Hafsa Korri-Youssoufi, Laurent Salmon. Design of an electrochemical biosensor based on reduced graphene oxide conjugated with a pyrene-carbohydrate for the subfemtomolar detection of the cancer biomarker AMF/PGI. Electrochimica Acta, 2025, 543, pp.147587. 10.1016/j.electacta.2025.147587. hal-05403605

HAL Id: hal-05403605

https://hal.science/hal-05403605v1

Submitted on 8 Dec 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

# Design of an electrochemical biosensor based on reduced graphene oxide conjugated with a pyrene-carbohydrate for the subfemtomolar detection of the cancer biomarker AMF/PGI

<figure><img src="image_3.png" /></figure>

Check for
updates

Jia Guo ID, Hafsa Korri-Youssoufi ID, Laurent Salmon ID

Université Paris-Saclay, CNRS, Institut de Chimie Moléculaire et des Matériaux d'Orsay (ICMMO), 17 Avenue des Sciences, 91400 Orsay, France

## ARTICLE INFO

**Keywords:**

Cancer

Biomarker

Biosensor

SPCE

rGO

Pyrene

## ABSTRACT

Phosphoglucose isomerase (PGI) is a multifunctional protein involved in glucose metabolism that also functions extracellularly as a cytokine known as autocrine motility factor (AMF), promoting tumor cell migration, metastasis, and angiogenesis. Elevated levels of AMF/PGI in serum and urine are associated with cancer progression, making it a potential biomarker for early diagnosis and monitoring. However, current methods for the detection of AMF/PGI are limited by their complexity and insufficient sensitivity. In this work, we have developed a novel carbohydrate-based electrochemical biosensor using D-fructose 6-phosphate (F6P), one of the two substrates of PGI, as a biorecognition element for ultrasensitive AMF/PGI detection. The biosensor was constructed using an assembly of reduced graphene oxide (rGO) conjugated with a rationally designed, pyrene-based spacer that was covalently bonded to F6P and immobilized on a screen-printed carbon electrode (SPCE). The rGO/pyrene-F6P nanocomposites were synthesized through a chemical process and fully characterized using contact angle measurements, atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS) and electrochemical techniques including cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). These techniques were used to demonstrate the nanocomposite's attachment to proteins. Using rabbit muscle PGI as a model of AMF, the biosensor exhibited high specificity and ultra-low limits of detection of 0.94 fM in Tris buffer and 0.79 fM in human plasma. This platform is a significant advancement in sugar-based electrochemical biosensing for protein biomarkers. Its modular design allows for the detection of other clinically relevant protein biomarkers by replacing F6P with alternative biorecognition elements.

## 1. Introduction

Pathological biomarkers play a critical role in modern medicine for the diagnosis, prognosis, and monitoring of a wide range of diseases. These biomarkers can often reveal the presence of underlying pathologies at an early stage, even before clinical symptoms appear. Early detection is especially critical in cancer, as timely diagnosis can significantly improve treatment outcomes and survival rates. Once metastases appear, the chances of recovery are greatly reduced [1].

Cancer biomarkers are specific molecules associated with tumor development and can be found in various body fluids, including blood, plasma, saliva and urine. The development of non-invasive, cost-effective detection techniques has enabled the identification of thousands of potential cancer biomarkers in body fluids, such as proteins, cytokines,

hormones, microRNA, and circulating DNA [2]. Several classical cancer biomarkers are already in clinical use, with varying degree of success, including alpha-fetoprotein [3], carcinoembryonic antigen [4], carbohydrate antigen 19-9 [5], carbohydrate antigen 125 [6], and prostate-specific antigen (PSA) [7]. In recent years, considerable research efforts have focused on identifying novel cancer biomarkers with improved diagnostic potential. Among these, phosphoglucose isomerase (PGI) has gained increasing interest [8,9].

In fact, PGI is a multifunctional enzyme that is primarily known for its intracellular role in glycolysis, catalyzing the reversible interconversion of D-glucose 6-phosphate (G6P) and D-fructose 6-phosphate (F6P). Remarkably, PGI also performs critical extracellular functions. Notably, it acts as a cytokine known as autocrine motility factor (AMF), which promotes tumor cell migration, angiogenesis, and metastasis

<footnote>* Corresponding authors.</footnote>

<footnote>E-mail addresses: hafsa.korri-youssoufi@universite-paris-saclay.fr (H. Korri-Youssoufi), laurent.salmon@universite-paris-saclay.fr (L. Salmon).</footnote>
[10]. PGI is expressed in all cells ubiquitously, whereas secretion of the protein has never been found from normal cells to date, but only from tumor cells, embryonic cells, and activated T-cells [11]. Indeed, elevated levels of AMF/PGI have been found in the serum and/or urine of patients in several types of cancer, making it a promising biomarker of cancer progression [12].

Given the importance of time in anticancer therapy, the development of an analytical tool that allows the fast, sensitive, and specific quantification of PGI in human fluids would greatly improve patient prognosis. Conventional analytical methods for PGI detection and quantification, such as enzymatic, colorimetric, and immunological assays, are often time-consuming, complex and difficult to adapt to point-of-care applications [13–15]. Biosensor technology is the clear choice for rapid, cost-effective detection of cancer biomarkers [16,17].

In our previous work, we developed an electrochemical affinity biosensor designed for sensitive and selective quantification of AMF/PGI. It used commercial rabbit muscle phosphoglucose isomerase (RmPGI) in phosphate buffer as a protein model. Indeed, RmPGI has been demonstrated to have AMF activity and displays 93% homology with human AMF/PGI [18–20]. Furthermore, it exhibits 100% homology with the residues at the active site (see the sequence alignment in Supp. Info. SIO). The recognition element was D-fructose 6-phosphate, one of the two natural substrates of the PGI, which was covalently linked via a stable oxime bond to a spacer on a gold electrode surface. The resulting Au/F6P biosensor exhibited high sensitivity, with a limit of detection of 6.6 fM in phosphate buffer (PBS) and 113 fM in human plasma. The detection range of the biosensor was found to be from 10 fM to 500 nM in PBS [8]. In a subsequent report, we presented a dendritic electrochemical biosensor that had been modified with N-(5-phosphate-D-arabinoyl)-2-amino ethanamine (5PAED), a PGI inhibitor, to serve as the recognition element. The PAMAM G2/5PAED biosensor demonstrated a limit of detection of 43 fM and a detection range from 1 pM to 1 µM in HEPES buffer [9].

Despite these encouraging results, gold electrodes are not a viable long-term solution due to their inherent limitations. The fabrication process often involves the use of sophisticated equipment for the coating of gold on a substrate [21]. Furthermore, the construction of biosensors on a gold surface generally involves a series of surface modification steps for the covalent attachment of the bioreceptor via a molecular spacer. These limitations hinder the scalability and reproducibility of biosensor fabrication. Conversely, carbon-based electrodes, particularly those incorporating graphene, offer a number of advantages. Graphene is a highly versatile material that is both cost-effective and possesses exceptional electrical conductivity. It can be easily deposited on screen-printed carbon electrodes (SPCE), making it a suitable choice for a variety of applications [22]. Notably, graphene enables non-covalent π-π stacking interactions with aromatic anchors, such as pyrene, to which a bioreceptor can be grafted. This approach preserves the electronic properties of graphene, enabling efficient bioreceptor immobilization on the basal plane of graphene. This approach provides a high surface-to-volume ratio for the immobilized bioreceptor. Additionally, the synthesis of the pyrene-bioreceptor can be rationalized by modeling the spacer length to obtain a high level of both affinity and sensitivity. Finally, the preparation of nanocomposites using pyrene-bioreceptor conjugates enables the formation of stable, conductive inks that are well-suited for flexible, miniaturized, and large-scale biosensor production.

In this study, we present the design, synthesis, and evaluation of a novel carbohydrate-based electrochemical biosensor for ultrasensitive detection of AMF/PGI, using RmPGI as the model protein [23]. The specific recognition element is F6P, the substrate that yielded the lowest limit of detection [8]. F6P was covalently “ click ed” to a modified pyrene molecule bearing an alkyl spacer, functionalized by an oxyamine group. The resulting pyrene-F6P conjugate was then non-covalently bound to reduced graphene oxide (rGO) via strong π-π stacking interactions to form a nanocomposite. The nanocomposite was then deposited onto a

screen-printed carbon electrode (SPCE) by drop casting. The resulting SPCE/rGO/pyrene-F6P biosensor was characterized by contact angle measurements, FT-IR spectroscopy, X-ray photoelectron spectroscopy (XPS), and electrochemical methods, including cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Our research demonstrates the rapid, efficient, and reliable detection of RmPGI in Tris buffer and human plasma at femtomolar concentrations by the SPCE/rGO/pyrene-F6P biosensor. This biosensor exhibits exceptional stability over time, making it a valuable tool for analytical chemistry. The platform is a versatile tool for developing next-generation carbohydrate-based biosensors that can detect a broad range of protein biomarkers by simply exchanging the sugar bioreceptor.

## 2. Experimental section

### 2.1. Materials and reagents

Boc-amino-oxyacetic acid was purchased from BLD Pharmatech. Sodium borohydride was purchased from TCI and ethylenediamine from Thermo Scientific. 1-Pyrenecarboxylic acid and N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) were purchased from Fluochem. D-Fructose 6-phosphate (F6P), graphene oxide (GO), titanium(IV) isopropoxide, rabbit muscle phosphoglucose isomerase (RmPGI, 358 U·mg protein⁻¹), and *Saccharomyces cerevisiae* glucose-6-phosphate dehydrogenase (G6PDH, 237 U·mg protein⁻¹) were purchased from Sigma-Aldrich. Screen-printed carbon electrodes (SPCE) were purchased from Metrohm (DropSens DRP-C110). Phosphate buffered saline (PBS, pH 7.4, 10 mM Na₂HPO₄, 1.8 mM KH₂PO₄, 2.7 mM KCl, 137 mM NaCl) and Tris buffer (pH 8.0, 50 mM) were prepared with double distilled water, filtered on 0.22 µm membranes, and stored at 4°C before use. Human blood plasma samples were purchased from Sigma-Aldrich. Organic solvents were obtained from Carlo Erba. Methanol, CH₂Cl₂ and THF were dried by refluxing with, respectively, Mg/I₂, CaH₂, and Na/benzophenone, then distilled and used immediately. DMF was dried on 4 Å molecular sieves and distilled under reduced pressure. Chloroform was stored on alumine in the dark, and filtered before use. Chromatography was performed using silica gel (70–200 µm, Merck) at atmospheric pressure and flash-chromatography using silica gel (35–70 µm, Merck) under N₂ pressure. Unless otherwise mentioned, organic solutions were dried over Na₂SO₄ and filtered. The preconcentration of solutions was performed under reduced pressure at temperatures < 40°C using a rotary evaporator. All air- and moisture-sensitive reactions were performed under an atmosphere of argon. Analytical thin-layer chromatography (TLC) was performed using Silica Gel 60 F254 pre-coated aluminum plates (E. Merck). Spots were visualized by treatment with 5% ethanolic H₂SO₄ followed by heating and/or by absorbance of UV light at 254 nm. Optical rotations were measured at 25°C on a Jasco DIP-370 digital polarimeter at 589 nm. NMR spectra were recorded at 298 K in CDCl₃ and CD₃OD with Bruker DRX 300 (¹H at 300.1 MHz and ¹³C at 75.5 MHz) spectrometers using SpinWorks 4.2.10.0 software. Chemical shifts are reported in ppm (δ) and coupling constants in Hz (Jᵢⱼ). ¹H NMR spectra were referenced to internal residual chloroform (δ 7.26) and CD₂HOD (δ 3.31) for solutions in CDCl₃ and CD₃OD, respectively. ¹³C NMR spectra were referenced to solvent for solutions in CDCl₃ (δ 77.0) and CD₃OD (δ 49.1). Infrared spectra were recorded with an FTIR Bruker IFS-66 spectrometer. Low-resolution mass spectrometry (MS) and high-resolution mass spectrometry (HRMS) analyses were performed by electrospray with positive (ESI+) or negative (ESI-) ionization mode on a Bruker MicrOTOF-Q (2009). ¹H and ¹³C NMR, and HR-MS spectra are reported in the Supp. Info. SII section.

XPS analyses were performed on the samples using a K-Alpha spectrometer (Thermo-Fisher) equipped with a monochromatic Al Kα X-ray source (hν = 1486.6 eV). The measurements were performed with a spot size of 400 µm. The hemispherical analyzer was operated in CAE (Constant Analyzer Energy) mode, with a pass energy of 200 eV and a step size of 1 eV for survey spectra, and a pass energy of 50 eV and a step
size of 0.1 eV for high resolution spectra. The total acquisition time was 11 min 45 s, and 100 scans were accumulated for each measurement. The spectra were processed using the Thermo-Fisher software, with a Shirley-type background subtraction applied for data analysis. The binding energy scale was calibrated using the C1s peak of adventitious carbon at 284.8 eV. FT-IR spectra were performed with Bruker IFS66 spectrometer equipped with MCT and DSTG detectors and an Attenuated Total Reflectance (ATR) crystal of Germanium. AFM images were acquired using a Bruker Dimension Icon system operated in standard tapping mode. A NanoWorld Pointprobe® NCH (TESPA) monolithic silicon cantilever (NanoAndMore) was used, with a nominal resonance frequency of 284 kHz and a spring constant of 30 N/m. Contact angle measurements were made using a Malvern Panalytical goniometer controlled by the "Drop Shape Analyses" software. Surface hydrophilicity was determined by the Young-Laplace method. All measurements were made at 20°C using 3 µL water droplets.

### 2.1.1. $N^1$-(pyren-1-ylmethyl)ethane-1,2-diamine (1)

Compound 1 was synthesized as described [24]. FT-IR $ν$ 3276 (NH₂), 3038-2825 (CH, CH₂, CHarom), 1592 (NH), 1454 (C=C), 900-600 (CHarom) cm⁻¹; ¹H NMR (300 MHz, CDCl₃) δ 8.42 (d, 1H, *J* = 9.3 Hz, Harom), 8.22-8.14 (m, 4H, Harom), 8.07-8.00 (m, 4H, Harom), 4.53 (s, 2H, pyrene-CH₂), 2.89 (s, 4H, CH₂-CH₂-NH₂), 1.60 (br s, 3H, NH and NH₂) ppm; ¹³C NMR (75.5 MHz, CDCl₃) δ 134.0, 131.3, 130.9, 130.7, 129.1 (5s, 7Carom), 127.6, 127.5, 127.1, 127.0, 125.9, 125.1, 125.0, 124.7, 123.2 (9s, 9CHarom), 52.5 (pyrene-CH₂), 51.8 (CH₂CH₂NH₂), 41.9 (CH₂CH₂NH₂) ppm; HR-MS (ESI⁺) *m/z*: Calcd for C₁₉H₁₉N₂ [M+H]⁺ 275.1548, Found 275.1532; HR-MS (ESI⁺) *m/z*: Calcd for C₁₉H₁₈N₂Na [M+Na]⁺ 297.1368, Found 297.1353.

### 2.1.2. tert-Butyl (2-oxo-2-((2-((pyren-1-ylmethyl)amino)ethyl)amino)ethoxy)carbamate (2)

$N^1$-(Pyren-1-ylmethyl)ethane-1,2-diamine (1, 1.5 mmol), (Boc-aminooxy)acetic acid (1.5 mmol) and N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC) were placed in a dry 250 mL flask under an argon atmosphere. Anhydrous DMF (10 mL) was added by syringe and the mixture stirred for 24 h. The reaction mixture was then diluted with ethyl acetate (50 mL) and washed with 10% v/v dilute acetic acid (3 × 30 mL). The pH was then adjusted to 10.0 using a saturated sodium bicarbonate solution. The organic phase was dried over sodium sulfate and concentrated in vacuo to give compound 2 in 52% yield. Compound 2 was not fully characterized at this point, because of its partial deprotection to the next product 3. Rf = 0.36 (silica gel, CHCl₃/MeOH 98/2); HR-MS (ESI⁺) *m/z*: Calcd for C₂₆H₃₀N₃O₄ [M+H]⁺ 448.2231, Found 448.2212; HR-MS (ESI⁺) *m/z*: Calcd for C₂₆H₂₉N₃O₄Na [M+Na]⁺ 470.2050, Found 470.2036.

### 2.1.3. 2-(Aminooxy)-N-(2-((pyren-1-ylmethyl)amino)ethyl)acetamide (3)

Deprotection of the Boc-aminooxy group of compound 2 (0.25 mmol) was carried out using an excess of TFA (5.0 mmol, 20 equiv.) in dry dichloromethane (2.5 mL), with stirring at room temperature for 2 h. A concentrated solution of NaOH (1 M) was then added to the reaction mixture to adjust the pH to around 12. The product was extracted in chloroform (3×5 mL), and the chloroform layer was separated and dried over anhydrous Na₂SO₄. The solvent was removed under reduced pressure, affording compound 3 in 98% yield. Rf = 0.10 (silica gel, CHCl₃/MeOH 98/2); FT-IR $ν$ 3324 (NH), 2931 (CH₂, CHarom), 1659 (C=O), 1542 (NH, C=C), 1268 (C-N), 1043 (C=O) cm⁻¹; ¹H NMR (300 MHz, CD₃OD) δ 8.43 (d, 1H, *J* = 9.3 Hz, Harom), 8.26-8.19 (m, 4H, Harom), 8.10-8.01 (m, 4H, Harom), 4.54 (s, 2H, CH₂O), 4.09 (s, 2H, pyrene-CH₂), 3.52 (t, 2H, *J* = 6.3 Hz, CH₂NHCO), 2.97 (t, *J* = 6.3 Hz, 2H, CH₂CH₂NHCO) ppm; ¹³C NMR (75.5 MHz, CD₃OD) δ 170.4 (s, C=O) 131.4, 130.6, 129.8, 129.3, 127.4, 125.9, 125.6, 125.4, 124.2, 123.3, 123.2, 123.1, 122.9, 121.2 (1s, 16 Carom & CHarom), 72.6 (CH₂O), 48.7 (pyrene-CH₂), 38.9 (pyrene-CH₂NHCH₂), 36.6 (CH₂NHCO) ppm; HR-MS (ESI⁺) *m/z*: Calcd for C₂₁H₂₂N₃O₂ [M+H]⁺ 348.1707, Found 348.1699;

HR-MS (ESI⁺) *m/z*: Calcd for C₂₁H₂₁N₃O₂Na [M+Na]⁺ 370.1526, Found 370.1518.

### 2.1.4. ((2R,3R,4R)-3,4-Dihydroxy-5-(hydroxymethyl)-5-((2-oxo-2-((2-((pyren-1-ylmethyl)amino)ethyl)amino)ethoxy)amino)tetrahydrofuran-2-yl)methyl phosphate (4)

A solution of D-fructose 6-phosphate (F6P, sodium salt, 1 mg/mL) in acetate buffer (100 mM, pH 4.6) and a solution of 3 (2 mg/mL) in methanol were prepared. The two solutions were mixed in a molar ratio 3/F6P = 1/4 and stirred at room temperature for 36 h. The reaction mixture was then concentrated under vacuum and the resulting solid mixture was washed with methanol. Since F6P is insoluble in methanol, this step effectively allowed the product to get extracted from the excess F6P. Finally, the product was recrystallized in methanol to give compound 4 in 62% yield. FTIR $ν$ 3278 (NH₂) 2985-2917 (CH, CH₂, CHarom), 1652 (C=O), 1541 (C=C), 1230 (P=O), 1074 (C-O, P-O-C); ¹³C NMR (75.5 MHz, CD₃OD) δ 169.7 (C=O), 131.0, 128.9, 127.9, 127.6, 127.4, 127.2, 126.2, 125.3, 125.2, 124.8, 124.5, 124.3, 122.4 (13s, 16 Carom), 101.6 (C2'), 80.4 (C5'), 75.6 (C4'), 74.7 (C3'), 73.8 (CH₂ONH), 64.3 (C6'), 62.9 (C1'), 49.3 (pyrene-CH₂), 47.3 (pyrene-CH₂NHCH₂), 37.7 (CH₂NHCO) ppm; HR-MS (ESI-) *m/z*: Calcd for C₂₇H₃₁N₃O₁₀P [M+H]⁻ 588.1753, Found 588.1742.

## 2.2. Construction of the SPCE/rGO/pyrene-F6P biosensor

### 2.2.1. Preparation of reduced graphene oxide (rGO)

Graphene oxide (GO, 10 mg) was ground to a fine dark red powder and dispersed in 20 mL DMF (0.5 mg/mL) under ultrasound for 1 h. The solution was centrifuged at 4300 rpm for 20 min to remove undissolved GO, and the supernatant was collected. The collected solution was heated in an oil bath at 160°C for 8 h, during which the color of the dispersion changed from light brown to black, indicating the conversion of GO to rGO. The solution was then centrifuged at 10,000 rpm for 1 h, and the resulting pellet collected. The product was washed with distilled water (2×60 mL), acetone (2×60 mL), then centrifugated (10,000 rpm, 30 min) to isolate the solid. The solid obtained was dried in an oven at 45°C for 72 h to give a black powder. FT-IR $ν$ 3240 (OH), 1730 (C=O), 1562 (C=C), 1230 (C-O-C, C-OH); XPS C1s 284.6 eV (C-C, C=C) 92.3%, O1s 532.0 eV (C-O) 7.1% (cf. Supp. Info. SI2, Fig. S1).

### 2.2.2. Preparation of rGO/pyrene-F6P adduct (5)

rGO (1 mg/mL, 1 mL) was mixed with the pyrene-F6P compound 4 (4 mg/mL, 1 mL) in MeOH. The resulting solution was exposed to ultrasound for 5 h, stirred overnight to create a dark suspension, and then centrifugated at 500 rpm for 5 min. After centrifugation, the supernatant containing the rGO/pyrene-F6P adduct 5 in methanol was carefully collected by pipetting. Preliminary tests indicated that the 1/4 ratio exhibited optimal electrochemical performance with regard to protein detection (see Fig. S2, Fig. S3 and Table S1 in Supp. Info. SI3 for complete optimization data and characterization).

### 2.2.3. Preparation of SPCE/rGO/pyrene-F6P biosensor (6)

Prior to the experiment, the screen-printed carbon electrode (SPCE) was pre-cleaned with ethanol and water, then the silver reference electrode part of the SPCE was treated with sodium hypochlorite to obtain Ag/AgCl. Next, the SPCE was activated by performing cyclic voltammetry (CV) in a 10 mM sulfuric acid solution, with a potential window ranging from -0.5 to 2 V at a scan rate of 0.05 V/s for 10 cycles. The activated SPCE was then rinsed with water and dried at room temperature. The resulting SPCE electrode was used directly for subsequent electrochemical studies. The methanolic solution containing rGO/pyrene-F6P 5 was drop-casted in three aliquots (2 µL each, total 6 µL) to the surface of the working electrode, allowing brief solvent evaporation (~30 sec) between each application. Drying in an oven at 40°C for 2 h produced the biolayer SPCE/rGO/pyrene-F6P biosensor (6). After drying, the electrode surface was gently rinsed with a PBS solution (pH =
7.4) to remove loosely grafted pyrene-F6P composite, followed by careful drying using compressed argon. To avoid non-specific interactions, the electrode was then immersed in a solution of bovine serum albumin (BSA 0.25 µM in PBS containing 0.05% Tween 20) for 10 min at 20°C. At the end of incubation, the electrode was carefully washed several times with a PBS solution containing 0.01% Tween 20, ensuring optimal preparation of the SPCE/rGO/pyrene-F6P biosensor 6 for subsequent measurements.

## 2.3. Electrochemical measurements

Electrochemical characterization was performed utilizing a Metrohm Autolab PGSTAT12 potentiostat controlled with Nova software 1.10 (Metrohm AG, Switzerland). Biosensor formation employed screen-printed carbon electrodes (SPCEs) from Metrohm Dropsens (Astorias, Spain). Cyclic voltammetry (CV) analyses were conducted in Tris buffer with 5 mM $[Fe(CN)_6]^{4-}/[Fe(CN)_6]^{3-}$, scanning the potential between +600 mV and -600 mV vs screen-printed Ag/AgCl reference electrode at a scan rate of 100 mV.s$^{-1}$. Electrochemical impedance spectroscopy (EIS) was conducted in a Tris buffer with 5 mM $[Fe(CN)_6]^{4-}/[Fe(CN)_6]^{3-}$ species at an open circuit potential and with potential of 10 mV using a frequency range from 100 kHz to 0.1 Hz.

## 2.4. Protein detection in Tris buffer and human plasma

As previously reported [8], commercially available RmPGI has been used as a protein model for AMF due to its high homology (93%) with human AMF [19,20], particularly with regards to the active site amino acids for which 100% homology is observed (see the sequence alignment of RmPGI and human AMF/PGI in the Supp. Info. file). In addition, RmPGI has been shown to induce tumor cell motility and therefore to have AMF activity [18,19]. Concerning protein detection in Tris buffer, RmPGI was detected and quantified in a range of concentrations from 10 fM to 100 nM. All protein solutions were prepared in 50 mM Tris buffer at the optimum pH of 8.0 for enzymatic activities [25,26]. A volume of 50 µL of protein solution at the desired concentration was deposited on the surface of the biosensor and incubated for 1 h at room temperature. The biosensor was then successively washed with a solution of PBS (pH = 7.4) containing 0.1% Tween 20. Protein detection in human plasma was carried out in the same way as in Tris buffer, using RmPGI in a concentration range from 10 fM to 100 nM. Human plasma (purchased from Sigma-Aldrich) was used diluted in Tris buffer (5-fold) and unfiltered.

## 2.5. Data processing and statistical analysis

To estimate the limit of detection and the sensitivity of the biosensor, a calibration curve was constructed using impedance spectroscopy measurements, as EIS provides higher sensitivity for monitoring interfacial changes and charge-transfer resistance variations induced by biomolecular binding, compared with voltammetric techniques. The electrochemical response was expressed as the normalized charge transfer variation, ΔRct/Rct₀, obtained on four independent electrodes. The limit of detection (LOD) is defined as the lowest analyte concentration that can be distinguished from the blank with acceptable uncertainty, although it may not be possible to quantify it under the described experimental conditions. This limit can be estimated using different analytical approaches. The most common method uses the calibration line y = a + bx. In this case, the limit of detection (xLOD) is calculated according to the equation below, where sₐ is the standard deviation of the blank. This standard deviation is determined from several measurements performed on the bare biosensor prior to the detection experiments.

$$x_{LOD} = \frac{a + 3s_{a}}{b}$$

# 3. Results and discussion

## 3.1. Construction of the SPCE/rGO/pyrene-F6P biosensor

The synthesis followed for the overall construction of the SPCE/rGO/pyrene-F6P biosensor is depicted on Fig. 1 where F6P was first ' click ed' to a modified pyrene molecule bearing a spacer functionalized by an oxyamine group (Fig. 1A). Subsequently, the pyrene-F6P conjugate was bound to reduced graphene oxide (rGO). Following a purification step, the suspension was subsequently deposited on a SPCE, resulting in the new SPCE/rGO/pyrene-F6P biosensor (Fig. 1B).

The first step consisted in introducing a protected oxyamine group onto a functionalized pyrene molecule by coupling $N^{1-}(1-pyrenylmethyl)-1,2-ethanediamine$ (1) [24] with (Boc-aminooxy)acetic acid in the presence of the coupling agent EDC in anhydrous DMF, to give tert-butyl $(2-oxo-2-((2-((pyren-1-ylmethyl)amino)ethyl)amino)ethoxy)carbamate$ (2) in 52% yield. NMR spectroscopic analysis was complicated by the fact that part of 2 is deprotected to product 3 during the analytical process. Complete deprotection of the Boc-aminooxy group by treatment of 2 with trifluoroacetic acid (TFA) in dry methylene chloride gave pure 2-(aminooxy)-N-(2-((pyren-1-ylmethyl)amino)ethyl)acetamide (3) in 98% yield. The pyrene-F6P conjugate (4) was then obtained by a condensation reaction of 3 with D-fructose 6-phosphate in methanol and acetate buffer. Following recrystallization in methanol, most of F6P in excess was removed to give 4 in 62% yield. Structures of compounds 1-4 were fully characterized by FT-IR, NMR and HR-MS spectroscopies (see Experimental part and Supp. Info. SI1 section).

The rGO/pyrene-F6P nanocomposite (5) was obtained by mixing the pyrene-F6P conjugate (4) and rGO in a methanolic solution using ultrasonication and centrifugation. The SPCE/rGO/pyrene-F6P biosensor (6) was obtained by depositing the methanolic solution containing the rGO/pyrene-F6P nanocomposite (5) on the SPCE working electrode using the drop-casting method, and treated with a BSA solution to block the surface against non-specific interactions.

## 3.2. Characterization of biosensor and confirmation of RmPGI interaction

Once construction of the SPCE/rGO/pyrene-F6P biosensor was complete, surface modification was monitored using several analytical techniques to ensure appropriate functionalization and biosensor efficiency. We used contact angle measurements to monitor the balance of hydrophobicity and hydrophilicity associated with sugar grafting. We used FT-IR and XPS spectroscopy to determine the molecular structure obtained after biosensor grafting and protein attachment. These methods were also employed to analyze protein attachment to the surface.

The contact angle measurements (Fig. 2a-d) show that the SPCE electrode initially exhibited a contact angle of 112 ± 1° (Fig. 2a), indicating a highly hydrophobic surface. Subsequent to the deposition of the rGO/pyrene-F6P 5 on the SPCE working electrode, a significant decrease in the contact angle was observed, reaching 58 ± 1° (Fig. 2b). This finding indicates a remarkably hydrophilic surface, a consequence of the carbohydrate modification of the electrode. Furthermore, it validates the effective grafting of rGO/pyrene-F6P onto the surface. The interaction of BSA and RmPGI proteins results in a change in the contact angle, which shifts from 51 ± 1° (Fig. 2c) to 46 ± 1° (Fig. 2d). The alterations exhibited divergent chemical behavior, attributable to the chemical properties inherent in both proteins and the manner in which they interact with the surface. The attachment of BSA to the pinhole surface and the formation of a complex between RmPGI and the surface are noteworthy phenomena in this regard.

FT-IR spectroscopy confirms the successful attachment of the rGO/pyrene-F6P 5 on the SPCE surface (Fig. 2 e,f). Bands corresponding to stretching vibrations of pyrene alkyl chains at 2971 and 2850 cm$^{-1}$ and
<figure><img src="image_4.png" /><figcaption>**Fig 1.** A) Synthesis of the pyrene-F6P conjugate (4): (a) Boc-NHOCH₂COOH, EDC, DMF, 24 h, rt, 52%; (b) TFA, CH₂Cl₂, 2 h, rt, 98%; (c) F6P, acetate buffer pH 4.6, MeOH, 36 h, rt, 62%. B) Construction of the SPCE/rGO/pyrene-F6P biosensor: ① nanocomposite formation (activated rGO, MeOH, 5 h, rt); ② drop-casting of nanocomposite (5) on SPCE (2 h, 40°C); ③ blocking with BSA; ④ deposition of RmPGI onto the electrode; ⑤ electrochemical detection of RmPGI protein interactions.</figcaption></figure>

amide vibration bands at 1722, 1577 and 1231 cm⁻¹ were observed. The formation of a stable covalent bond between F6P and the amine group of the pyrene derivative was observed in the presence of a band corresponding to the C=N-OH bond at 3217 cm⁻¹ (Fig. 2f). More conclusive evidence for the grafting of biosensor onto the electrode surface is provided by the results of the XPS analysis of biosensor 6 (Fig. 2g-k). First, the presence of sugar-like functional groups on the surface is indicated by an increase in the intensity of the peaks associated with the C-O and C-N (~286.5 eV) bonds and the C=O (~288.0 eV) bonds, as shown in Fig. 2h. Furthermore, the presence of phosphorus-containing F6P is confirmed by the peaks associated with P-O bonds (~133.0 eV), as shown in Fig. 2i. The detection of 0.02% phosphorus content (Supp. Info. SI4, Table S2) also provides evidence of F6P grafting to the electrode surface.

XPS analysis also verifies the interaction of BSA and RmPGI with the surface (Fig. 2j,k). In the high-resolution C1s spectra (Fig. 2j), a clear decrease in the intensity of the sp² carbon signal (~284.5 eV) occurred after incubation with RmPGI. This was accompanied by a notable increase in the peak centered around 286.2 eV, which corresponds to the sp³ carbon signal. This shift in spectral signature is consistent with the presence of a protein layer on the surface. In contrast, samples incubated with BSA showed no significant spectral variation, supporting the hypothesis that RmPGI was specifically immobilized through molecular recognition with the F6P-modified interface, while BSA exhibited minimal non-specific adsorption. The N1s spectra further support this interpretation by revealing an obvious change following RmPGI exposure (Fig. 2k). The RmPGI-incubated surface exhibited a characteristic doublet at 399.5 eV and 401.3 eV, which is a typical of proteinaceous nitrogen environments, indicating substantial protein binding. The nitrogen content exhibited an increase from 1.3% to 3.5% (Supp. Info. SI4, Table S3), indicating a substantial and localized enrichment of nitrogen-containing species. This finding serves to further substantiate the presence of adsorbed protein. This compositional alteration also exhibits a strong correlation with the AFM outcomes, which exhibited significant topographical and mechanical contrast following RmPGI binding. The obtained results confirm the selective immobilization of RmPGI over the minimal background adsorption of BSA, thereby validating the

biosensor's surface design.

The AFM findings further corroborate the XPS analysis, providing more conclusive evidence for the formation of the biosensor and the specific interaction of the RmPGI protein with the functionalized electrode surface. In the present study, Atomic Force Microscopy (AFM) was performed in tapping mode. This method was employed to evaluate the surface morphology and nanoscale interactions of a functionalized surface before and after exposure to BSA and RmPGI (Fig. 3). The topographic image of the rGO/pyrene-F6P surface revealed a moderately rough texture, with features reaching up to 80 nm in height. The observed morphology, which is characterized by an entangled fibrous structure, is consistent with a surface that is covered by a pyrene-functionalized layer. This layer may be embedding or bridging the rGO nanosheets, thereby obscuring the nanosheet structure of rGO. The pyrene units have the potential to form a thin, disordered organic layer on top of the rGO sheets. This contributes to a fibrillar or mesh-like appearance in topographic imaging. This phenomenon has also been previously demonstrated in the case of rGO associated with pyrene modified with peptide, described as organogel [27]. Another study lends support to the notion that this fibrillar structure is related to the chirality of rGO induced by anchored molecules [28]. Furthermore, the phase image exhibited relatively uniform contrast, suggesting the presence of homogeneous mechanical and adhesive properties across the surface. This homogeneity lends support to the hypothesis that the surface is uniformly coated with the rGO-pyrene composite, providing a suitable foundation for subsequent protein immobilization. After incubating with the BSA protein, the topography remained largely unchanged. The phase image displayed a uniform contrast, similar to that of the rGO/pyrene-F6P surface. This suggests that the BSA did not adsorb onto the biolayer due to a lack of affinity, instead attaching specifically to pinhole carbon surface.

Conversely, exposure to the RmPGI protein, which was predicted to interact with the surface via F6P, resulted in significant alterations. The topographic image revealed the formation of localized structures, some reaching heights of up to ~150 nm, which suggests the development of adsorbed protein domains or clusters. It is important to note that the phase image reveals distinct regions with altered contrast, ranging from
<figure><img src="image_5.png" /><figcaption>**Fig 2.** Characterization of the biosensor – Contact-angle measurements of the surface of a modified electrode when in contact with a H₂O droplet (3 µL): (a) initial state of SPCE; (b) after F6P grafting (SPCE/rGO/pyrene-F6P biosensor 6); (c) after BSA treatment (SPCE/rGO/pyrene-F6P/BSA); (d) after incubation with RmPGI. FT-IR spectroscopy of the surface modified with: (e) SPCE/rGO (black), SPCE/rGO/compound 3 adduct (blue), pyrene alone (purple), the circle indicates alkyl bands, the dotted lines indicate amide bands; (f) SPCE/rGO/compound 3 adduct (blue) and after grafting of F6P (SPCE/rGO/pyrene-F6P biosensor 6, orange), the circle indicates O–H bands of hydroxyl and phosphate groups, the dotted lines indicate P–O and P=O bands. XPS results of the surface modified with compound 3 (SPCE/rGO/pyrene, blue), after F6P grafting (SPCE/rGO/pyrene-F6P biosensor 6, orange), after exposure to BSA (SPCE/rGO/pyrene-F6P/BSA, green), and after exposure to RmPGI (SPCE/rGO/pyrene-F6P/BSA/RmPGI, pink); (g) surveys XPS spectra; (h) C1s peaks with and without F6P grafting; (i) P2p peaks; (j) C1s peaks after biosensor construction and protein interactions; (k) N1s peaks after biosensor construction and protein interactions.</figcaption></figure>

light to dark areas. This indicates spatial variation in the surface's me-
chanical or adhesive properties at the nanoscale. These variations in the
phase signal are generally associated with disparities in the viscoelas-
ticity, stiffness, or adhesion forces between the AFM tip and the mate-
rial. In this case, the observed contrast is due to the protein's successful
interaction, which alters the local surface properties compared to the
rGO-F6P surface. The phase image shows the loss of the original fila-
mentous texture of the rGO/pyrene, as well as the appearance of
smoother or more diffuse zones, which further supports the presence of a
protein coating. This phase contrast strongly indicates heterogeneous
surface composition, confirming that protein binding occurred selec-
tively, altering the mechanical response detected by the AFM tip. The
topographical and phase data provide complementary evidence for the
specific and stable immobilization of the RmPGI protein onto the func-
tionalized surface.

3.3. *Electrochemical characterization*

The electrochemical properties of the F6P biosensor were thoroughly
examined using both electrochemical impedance spectroscopy (EIS,
Fig. 4a) and cyclic voltammetry (CV, Fig. 4b). The measurements were
performed by evaluating the electron and charge transfer properties of
the redox probe [Fe(CN)₆]⁴⁻/[Fe(CN)₆]³⁻ from solution to the surface
of the various steps of biosensor construction: SPCE/rGO/pyrene-F6P
and SPCE/rGO/pyrene-F6P/BSA. EIS measurements provide detailed
information about the charge transfer kinetics across the biosensor layer
and electrode. These measurements provide valuable insight into

surface modification and complex formation. The impedance spectra were best fitted with a series-connected dual RC equivalent circuit. The two time constants are highlighted by distinct maxima in the Bode-phase spectra (see Supp. Info. SI5, Table S4, Table S5, and Fig. S4), and the low χ² values confirm the quality of the fit. This model reflects the two interfacial processes: electrode/graphene–pyrene nanocomposite and the F6P bioreceptor/solution interface, consistent with previous reports [29].

After depositing the biosensor rGO/pyrene-F6P on SPCE, EIS mea-
surement shows a significant decrease in impedance compared to SPCE
(Fig. 4a). This behavior underscores the enhanced electrical properties
of the nanocomposite. BSA treatment results in a slight modification of
the impedance, indicating that BSA is attached to the remaining pinhole
carbon surface. The Nyquist plots of rGO/pyrene-F6P/SPCE and rGO/
pyrene-F6P/BSA/SPCE show two distinct semicircles demonstrating
two interfacial electrical property behaviors. The fitting data with the
equivalent circuit confirms the experimental data. The first semicircle,
located in the high-frequency region, likely corresponds to the charge-
transfer resistance (Rct) at the electrode interface. It shows a signifi-
cant decrease compared to the bare electrode. The rGO/pyrene-F6P
nanocomposite structure enhances the conductivity of the modified
surface, thereby improving electron transfer kinetics to the electrode.
Meanwhile, the appearance of the second semicircle in the low-
frequency region indicates the extra impedance provided by the
immobilized F6P carbohydrate layer at the electrode-solution interface.
The negatively charged phosphate group of F6P repels the negatively
charged redox marker [Fe(CN)₆]³⁻/Fe²⁺, which contributes to this
<figure><img src="image_6.png" /><figcaption>**Fig 3.** AFM tapping mode images of bare electrode SPCE (first column), rGO/Py-F6P-modified surface (second column), rGO/Py-F6P after incubation with BSA protein (third column), and rGO/Py-F6P surface after incubation with BSA and RmPGI binding protein (fourth column): (A) topography images, (B) phase images, and (C) roughness analysis are shown for each surface (for each AFM measurement, two different areas of the same sample were analyzed. As the results were similar, only one representative set is shown).</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Fig 4.** Surface analysis of different modification steps (black: SPCE bare, orange: SPCE/rGO/pyrene-F6P, green: surface blocked with BSA): (a) surface impedance analysis (Nyquist diagrams) obtained in a frequency range from 100 kHz to 0.1 Hz, (b) surface analysis by cyclic voltammetry during 3 cycles at 50 mV/s in a Tris buffer with 5 mM $[Fe(CN)_6]^{4-}/[Fe(CN)_6]^{3-}$.</figcaption></figure>

secondary impedance feature.

After BSA treatment, which blocks non-specific binding sites, both semicircles in the Nyquist plot slightly enlarge. This is because the BSA protein insulating layer on the pinholes forms a physical barrier that hinders the transfer of electrons and charges of the redox marker. This result confirms the AFM observations in which BSA was attached to the

remaining non-modified carbon electrode pinhole, thereby preventing non-specific interactions of the biosensor. The fitting data are listed in the supplemental information (Supp. Info. SI6, Table S6 and S7), and highlight the electrical parameters of the various steps in biosensor construction. Fitting the experimental data to the equivalent circuit shows that both capacitances are replaced by a constant phase element,
which confirms the inhomogeneous structure of the nanocomposite observed in AFM.

Cyclic voltammetric measurements were performed after the biosensor was constructed, and the results obtained are consistent with those obtained by EIS measurements. As shown in Fig. 4b (black), the bare SPCE electrode exhibits low peak currents and a large peak-to-peak separation (ΔEp). These characteristics are indicative of relatively slow electron transfer kinetics at the unmodified carbon surface. Upon modification with the rGO/pyrene-F6P layer (Fig. 4b, orange), both the

anodic and cathodic peak currents increase significantly and ΔEp nar-
rows, indicating improved electron transfer kinetics due to the high
conductivity of rGO and the favorable π-π interactions provided by
pyrene. These changes are consistent with the decrease in Rct observed
in EIS measurements. After BSA treatment (Fig. 4b, green), the peak
currents decrease slightly, while the ΔEp remains largely unchanged.
This indicates that the BSA protein layer acts as a physical barrier
through pinholes only, without significantly altering the electrode sur-
face itself. Thus, the CV results overall reinforce the conclusions drawn

<figure><img src="image_8.png" /><figcaption>Fig 5. (a) Nyquist plots of the RmPGI biosensor response after protein interaction with different concentrations of RmPGI in Tris buffer, from bottom to top: ■ black: biosensor alone, ● red: 10 fM, ▲ light green: 100 fM, ▼blue: 1 pM, ◆ light blue: 10 pM, ◁ pink: 100 pM, ▶ yellow: 1 nM, ● brown: 10 nM, ★ dark green: 100 nM; the symbols are the experimental data and the solid lines are the fitted curves using the equivalent circuit model shown in the inset; (b) calibration curves obtained from the EIS data of the SPCE/rGO/pyrene-F6P (blue) and SPCE/pyrene-F6P (orange) biosensors as a function of RmPGI concentrations in Tris buffer (logarithmic scale); (c) Histogram of ΔRct₂/Rct₀ values obtained from EIS analyses at RmPGI concentrations of 100 fM, 100 pM and 100 nM: SPCE/rGO/pyrene-F6P biosensor (blue) and SPCE/rGO/pyrene-D-fructose biosensor (orange); (d) Histogram of ΔRct₂/Rct₀ values obtained from EIS analyses for the SPCE/rGO/pyrene-F6P biosensor for RmPGI (blue) and HSA (green) at concentrations of 100 fM, 100 pM and 100 nM; (e) study of the stability of the biosensor following variation in the oxidation and reduction currents of the biosensor response over time: oxidation peak at E = 0.24 V (black), reduction peak at E = 0.02 V (red); (f) study of the stability of the biosensor following variation in Rct of the biosensor response over time: Rct₁ (orange), Rct₂ (blue); (g) calibration curve obtained from EIS data of the SPCE/rGO/pyrene-F6P biosensor as a function of RmPGI concentration in Tris buffer (the error bars represent the standard deviation of three independent measurements, and the inset shows the calibration curve as a function of protein concentration in logarithmic scale); (h) Nyquist plots of the RmPGI biosensor response after protein interaction as a function of RmPGI in human plasma (the same comments and color code are used as in Fig. 5a); (i) calibration curve obtained from EIS data of the SPCE/rGO/pyrene-F6P biosensor as a function of RmPGI concentration in human plasma. All measurements were performed with four replicates in freshly prepared biosensors, and the standard deviation is indicated in each Figure.</figcaption></figure>
from the EIS and AFM analyses, validating the stepwise surface modification process and its impact on the interfacial charge transfer behavior.

### 3.4. Biosensing performance evaluation

#### 3.4.1. Evaluation of the SPCE/rGO/pyrene-F6P biosensor toward RmPGI and its sensing mechanism

We analyzed the interaction between F6P and the protein by EIS in a $[Fe(CN)_6]^{4-}/[Fe(CN)_6]^{3-}$ solution (Fig. 5a). Nyquist plots revealed an increase in impedance after the formation of the F6P-protein complex at different RmPGI protein concentrations in a Tris buffer solution. The impedance increases after protein attachment, indicating a change in the sensing layer's permeability when a large protein attaches to its surface. This alters the interfacial properties, thereby affecting the charge transfer resistance. Various studies have demonstrated that this behavior occurs when the bioreceptor forms a complex with the protein on the surface. This reduces the permeation of redox markers at the electrode-carbon interface, which prevents electronic and ionic transfer [30]. This behavior is enhanced by a dense carbohydrate surface. A lower carbohydrate density results in a smaller change in the response signal, which affects the biosensor's sensitivity. This behavior was observed during the optimization of nanocomposite formation, as well as during the investigation of the effect of the rGO:pyrene-F6P ratio. The optimization step shows that increasing the rGO/pyrene-F6P ratio in the composite from 1/1 to 1/4 makes the biosensor more sensitive (See Supp. Info. SI4). However, increasing the ratio to 1/6 results in decreased sensitivity, likely due to excessive surface crowding or steric hindrance interfering with efficient protein binding. This demonstrates that the optimized density of F6P carbohydrate receptors results in protein attachment without disrupting interactions between proteins and bioreceptors.

To emphasize the importance of rGO in the sensing system, a control device for comparative experiments was formed by drop-casting pyrene-F6P onto an SPCE. A comparative analysis of EIS data analysis between the SPCE/rGO/pyrene-F6P and SPCE/pyrene-F6P biosensors (Fig. 5b) clearly demonstrates the critical role of rGO in enabling concentration-dependent PGI detection (see data in Supp. Info. SI6, Table S8 and Fig. S5). The SPCE/pyrene-F6P control sensor exhibited minimal variation in charge transfer values ($\Delta R_{ct}/R_{ct_0}$) across three orders of magnitude of PGI concentration (100 fM, 100 pM, and 100 nM). However, the rGO-incorporated biosensor exhibited a significant increase in $\Delta R_{ct}/R_{ct_0}$ that correlated with elevated PGI levels. This striking contrast confirms the essential role of the reduced graphene oxide layer in converting PGI binding events into measurable electrochemical signals. This is likely due to the layer's increased ability to transfer charges and its larger surface area. These factors facilitate efficient interaction between the pyrene-F6P recognition layer and target proteins.

The SPCE/pyrene-F6P sensor's concentration-independent response confirms that the observed detection capability originates specifically from the synergistic effect of rGO and pyrene-F6P, rather than from the F6P modification alone. These results conclusively demonstrate that rGO is essential to this biosensing architecture for achieving sensitive PGI determination.

#### 3.4.2. Sensing properties mechanism

To evaluate the effect of RmPGI concentration on electrical parameters, the EIS data obtained after the interaction of the protein were well-fitted with the previously described series-connected dual RC equivalent circuit model (Fig. 5a, inset). As previously presented, the first $R_{ct_1}$ component describes the charge transfer process at the electrode interface. The second $R_{ct_2}$ component accounts for the impedance characteristics of the interface F6P-modified biolayer interface. EIS data following protein interaction showed a slight decrease in $R_{ct_1}$ and a significant increase in $R_{ct_2}$ as the protein concentration increased (see electrical parameters in Supp. Info. SI6, Table S9). Unlike BSA's non-

specific blocking effect, which increases both semicircles uniformly, the specific binding of the target protein (PGI) demonstrates a distinct impedance modulation pattern. This pattern is characterized by a slight reduction in the diameter of the first semicircle and a significant increase in the diameter of the second semicircle. When the concentration of RmPGI rises from 10 fM to 100 nM, we observe a decrease in $R_{ct_1}$ from 94.9 Ω to 44.3 Ω and an increase in $R_{ct_2}$ from 169.9 Ω to 346.3 Ω. As shown in Fig. 5c, 5d and 5e, control experiments were performed to highlight that these variations in $R_{ct_1}$ and $R_{ct_2}$ are related to the specific RmPGI binding rather than non-specific surface modifications or alterations (see data in Supp. Info. SI6, Table S7 and Fig. S6). The variation in the two interfacial properties following interaction with the protein is explained by the strong interactions occurring at the SPCE-modified electrode and the rGO-pyrene. The large modification of $R_{ct_2}$ is related to the large modification of this interfacial layer, as RmPGI proteins are attached to F6P on the surface. It also confirms the biosensor's ability to recognize molecules selectively through its distinct, dual-parameter impedance signatures. This differential response provides compelling evidence of the specific interaction mechanism between PGI and the F6P-modified surface.

#### 3.4.3. Specificity study of the biosensor

The specificity of RmPGI for the SPCE/rGO/pyrene-F6P biosensor was confirmed through the study of various biosensors in which the D-fructose 6-phosphate (F6P) recognition element had been substituted with D-fructose, a carbohydrate that does not bind to the RmPGI protein. The SPCE/rGO/pyrene-D-fructose biosensor was designed and incubated in RmPGI solutions of varying concentrations, under the same conditions as the SPCE/rGO/pyrene-F6P biosensor. Following the washing steps, EIS analyses were performed, and $R_{ct_2}$ was measured by fitting the data. The $\Delta R_{ct_2}/R_{ct_0}$ values obtained demonstrate that the fructose-based biosensor exhibit a non-significant response to RmPGI in comparison to the SPCE/rGO/pyrene-F6P biosensor when equivalent RmPGI concentrations are analyzed (Fig. 5c, see data in Supp. Info. SI6, Table S10). A low detectable response was observed at various concentrations of PGI, ranging from 100 fM to 100 nM. However, the SPCE/rGO/pyrene-F6P biosensor demonstrated a distinct and specific response at substantially lower concentrations. The results underscore the absence of interaction of D-fructose with the protein.

To further evaluate the selectivity of the biosensor, the major plasma protein human serum albumin (HSA) was also tested. The SPCE/rGO/pyrene-F6P biosensor was incubated with HSA solutions at concentrations equivalent to those used for RmPGI (100 fM, 100 pM, and 100 nM). After washing, EIS measurements were performed under identical conditions. The resulting $\Delta R_{ct_2}/R_{ct_0}$ values indicated that HSA produced no significant changes to the signal across the tested concentration range (Fig. 5d, see data in Supp. Info. SI6, Table S11). These findings are consistent with those obtained using D-fructose. They confirm that the biosensor SPCE/rGO/pyrene-F6P exhibits high specificity for RmPGI, with negligible interference from abundant plasma proteins such as HSA.

#### 3.4.4. Biosensor stability and reproducibility

The stability of the SPCE/rGO/pyrene-F6P biosensor was investigated using CV and EIS in a $[Fe(CN)_6]^{4-}/[Fe(CN)_6]^{3-}$ solution. As part of the study, the electrodes were incubated in PBS at pH 7.4 for 24 h and seven analyses were performed. The response of the biosensor was monitored by measuring the oxidation and reduction peaks of the redox signal (Fig. 5e) and the EIS signal (Fig. 5f and Supp. Info. SI6, Fig. S6) over time. The peak current and $R_{ct}$ values obtained indicate that the surface remained stable over time. Furthermore, the stability of the rGO/pyrene-F6P suspension was tested by storing it at 4°C for a period of three months (see Fig. S7 in Supp. Info. SI6). The biosensor response remained constant throughout this period, indicating the successful formation of the nanocomposite assembly through sonication and centrifugation. The reproducibility of the SPCE/rGO/pyrene-F6P
biosensor was investigated by carrying out four separate measurements on freshly prepared biosensors. A relative standard deviation of 4% was observed.

### 3.4.5. Biosensor's analytical performance

To demonstrate the biosensor's sensitivity towards RmPGI, the effect of protein concentration on the impedance response was evaluated. A calibration curve was constructed using the normalized charge transfer variation (ΔRct₂/Rct₀), averaged from four independent assays (Fig. 5g). The impedance data obtained from the four independent biosensors can be found in the supplementary information (SI6, Table S9). Each data point on the calibration curve represents the mean of the four assays, and the error bars show the standard deviation. The calibration curve shows the relationship between ΔRct₂/Rct₀ and RmPGI concentration. It exhibits a strong linear correlation (R² = 0.98) with the logarithmic scale of the RmPGI concentration over the range of 10 fM to 100 nM. The regression equation is: ΔRct₂/Rct₀ = 0.13log[RmPGI] + 2.18. As described in Section 2.5, the limit of detection (LOD) was calculated from the slope of the calibration curve and the standard deviation of the blank response obtained from four repeated measurements using only the biosensor. Using a signal-to-noise ratio of 3, the LOD was calculated to be 0.94 ± 0.04 fM.

### 3.4.6. Detection in human plasma

The same procedure described in Tris buffer was used for the detection in human plasma. Human plasma was diluted five-fold in Tris buffer and supplemented with various concentrations of RmPGI ranging from 10 fM to 100 nM. The resulting Nyquist plots were consistent with those observed in Tris buffer (Fig. 5h). A calibration curve was obtained by measuring the mean value of ΔRct₂/Rct₀ of four independent biosensors as a function of protein concentration (Fig. 5i) and include SD for each concentration. Lower Rct values were obtained in human plasma than in Tris buffer, most likely due to the change in medium. ΔRct₂/Rct₀ displays a strong linear correlation with the logarithmic scale of RmPGI concentration ranging from 10 fM to 100 nM (R² = 0.99). The regression equation is ΔRct₂/Rct₀ = 0.082 log[RmPGI] + 1.38. The calculated limit of detection is 0.79 ± 0.04 fM (Fig. 5i, inset and in Supp. Info. SI7, Table S12).

### 3.5. Sensing performance comparison

The detection of cancer biomarkers in human tissues and biological fluids is a critical area of research that has been extensively reviewed in the literature [31–33]. Biosensors developed for the detection of clinically relevant cancer biomarkers are primarily immunosensors [6–35]. When compared to most reported cancer detection sensors, our biosensor demonstrates superior performance in terms of limit of detection (LOD) and dynamic range, while maintaining a cost-effective design (Table 1). This enhancement not only improves the practical value of the sensor but also underscores its potential for integration into the clinical diagnostic process. The quantification of autocrine motility factor (AMF) has been achieved through the implementation of several established methodologies, including enzymatic assays [15], colorimetric methods [14], and immunological techniques [13]. These conventional approaches generally operate within the pM to nM concentration range, which is significantly higher than the femtomolar detection range achieved by our SPCE/rGO/pyrene-F6P biosensor. This is particularly noteworthy when compared to our previously reported F6P biosensor based on a gold electrode with a limit of detection of 6.6 fM [8]. The novel SPCE/rGO/pyrene-F6P biosensor features further optimization of sensing performance, including a sub-femtomolar limit of detection (0.79 ± 0.04 fM) and improved sensitivity, reproducibility and stability over the time. These advances enable our biosensor to achieve exceptional accuracy and reliability in detecting ultra-low levels of AMF, which is critical for early cancer detection.

In addition, the majority of carbohydrate-based electrochemical biosensors documented in the literature for detecting sugar-binding proteins utilize lectin recognition [52,53]. In this context, the F6P electrochemical biosensor is noteworthy because it is one of a very limited number of non-lectin-based biosensors with outstanding sugar binding performance. In comparison with conventional lectin-based sensors, our biosensor exhibits enhanced selectivity and sensitivity. These performances are linked, on the one hand, to the rGO properties and, on the other, to the use of a 'pyrene' anchor onto which the chosen bioreceptor, in this case F6P, is covalently grafted. This biosensor design leverages the robust π-π stacking interactions between the rGO and the pyrene anchor. This ensures exceptional electrical properties are preserved and an extensive active surface area is attained with a substantial

<table><caption>**Table 1**

Comparison of the sensing performances for the electrochemical detection of selected cancer biomarkers in clinical useª.</caption><thead><tr><th>Biomarker</th><th>Cancer Type</th><th>Detection Method</th><th>Linear Range</th><th>LOD (pg mL<sup>-1</sup>)</th><th>LOD (fM)</th><th>Materials Used/ Epitope Linked</th><th>Ref.</th></tr></thead><tbody><tr><td>AFP</td><td>several</td><td>ECL</td><td>0.14 fM–14 pM</td><td>0.001</td><td>0.014</td><td>AuNP/Ab2-DNA-hemin</td><td>[36]</td></tr><tr><td>AMF</td><td>several</td><td>EIS-SWV</td><td>10 fM–100 nM</td><td>0.84</td><td>6.6</td><td>Au/PEG-F6P</td><td>[8]</td></tr><tr><td><strong>AMF</strong></td><td><strong>several</strong></td><td><strong>EIS</strong></td><td><strong>10 fM–100 nM</strong></td><td><strong>0.05</strong></td><td><strong>0.79</strong></td><td><strong>SPCE/rGO/pyrene-F6P</strong></td><td><strong>this work</strong></td></tr><tr><td>BRAF</td><td>colorectal</td><td>AMP</td><td>0.05–20 ng/μL</td><td>10<sup>5</sup></td><td>-</td><td>C/MB/Biotin-dUTP/SPP</td><td>[37]</td></tr><tr><td>BRCA1</td><td>Breast, pancreas</td><td>EIS</td><td>50 fM–1.0 nM</td><td>-</td><td>1.72</td><td>AuNP/PEG-ssDNA</td><td>[38,39]</td></tr><tr><td>BRCA2</td><td>Breast, pancreas</td><td>ECL</td><td>1 fM–1.0 nM</td><td>-</td><td>0.18</td><td>CdTe@CdS QD</td><td>[40]</td></tr><tr><td>CA-125</td><td>Ovary, Lung</td><td>DPV</td><td>0.1–300.0 U/mL</td><td>1.85·10<sup>5</sup></td><td>-</td><td>NMC/Aptamer</td><td>[6]</td></tr><tr><td>CA19-9</td><td>Gastroint. tract</td><td>BEI</td><td>10.0–120.0 U/mL</td><td>6.25·10<sup>6</sup></td><td>-</td><td>EDC-NHS/Antigen CA19-9</td><td>[5]</td></tr><tr><td>CEA</td><td>several</td><td>ECL</td><td>0.0003–10 ng/mL</td><td>0.06</td><td>-</td><td>CdSe-CdS-QD</td><td>[41]</td></tr><tr><td>CEA</td><td>several</td><td>ECL</td><td>0.005–0.35 pg/mL</td><td>0.02</td><td>-</td><td>Ru(bpy)<sub>2</sub>-GN/Ab1-QD</td><td>[42]</td></tr><tr><td>EGFR</td><td>several</td><td>CV/DPV</td><td>0.05 to 200 ng/mL</td><td>5</td><td>-</td><td>AuNP/graphene/aptamer</td><td>[43]</td></tr><tr><td>NOX2</td><td>several</td><td>SWV</td><td>0.1–200 nM</td><td>63000</td><td>1·10<sup>6</sup></td><td>Au/NOX2-Aptamer</td><td>[44]</td></tr><tr><td>ErbB2</td><td>Breast</td><td>EIS</td><td>1.0 fM–500 nM</td><td>-</td><td>1.0</td><td>ZnOnF/anti-ErbB2</td><td>[45]</td></tr><tr><td>HER2</td><td>Breast</td><td>CV/DPV</td><td>1.0 nM–1.0 mM</td><td>0.44</td><td>-</td><td>C/AuNP/PEDOT/PEG/peptide</td><td>[46]</td></tr><tr><td>KRAS</td><td>several</td><td>CV</td><td>0.5–12 ng/μL</td><td>0.58·10<sup>6</sup></td><td>-</td><td>SPCE/EDC-NHS/ssDNA</td><td>[47]</td></tr><tr><td>p53</td><td>several</td><td>CV</td><td>2.2 pM–5.6 nM</td><td>120</td><td>2200</td><td>AuNW/ODN-AuNP-Strep</td><td>[48]</td></tr><tr><td>PD-L1</td><td>Breast</td><td>CV</td><td>0.001–100 ng/mL</td><td>0.143</td><td>-</td><td>CNT/PEI/AuNP/aptamer</td><td>[49]</td></tr><tr><td>PSA</td><td>Prostate</td><td>DPV</td><td>-</td><td>6</td><td>-</td><td>AuPD/Ab1</td><td>[50]</td></tr><tr><td>PSA</td><td>Prostate</td><td>ECL</td><td>0.001–50 ng/mL</td><td>0.6</td><td>-</td><td>CNT-Chitosan-AuNP/Ab1</td><td>[51]</td></tr><tr><td>TP53</td><td>Breast</td><td>AMP</td><td>0.01–0.1 μM</td><td>-</td><td>2900</td><td>SPCE/rGO/CMC-Strep-HPR</td><td>[30]</td></tr></tbody></table>

<footnote>ª AFP: Alpha-fetoprotein, AMF: Autocrine Motility Factor, AMP: Amperometry, BRCA: breast cancer, C: Carbon electrode, CEA: Carcinoembryonic antigen, BEI: bioelectrochemical impedance, CNT: Carbon nanotube, CV: cyclic voltammetry, DPV: differential pulse voltammetry, ECL: Electrochemiluminescence, EIS: electrochemical impedance spectroscopy, GN: Graphene-Nafion, HRP: Horseradish Peroxidase, LOD: limit of detection, MB: Magnetic Beads, nF: nanofibers, NP: nanoparticles, PEDOT: poly(3,4-ethylenedioxythiophene, PD: paper disk, PEG: PolyEthylene Glycol, PSA: Prostate Specific Antigen, QD: Quantum dots, rGO, reduced Graphene Oxide, SPCE: Screen-Printed Carbon Electrode, SPP: Streptavidin-Peroxidase Polymer, Strep: streptavidin, SWV: square wave voltammetry.</footnote>
quantity of deposited bioreceptor. Notably, the biosensor's performance is attained through a direct detection mechanism, thereby obviating the necessity for signal amplification steps. This feature simplifies the operating protocol and enhances its applicability to complex biological matrices, such as plasma, without compromising performance. Our work offers a highly sensitive, cost-effective, and practical solution for the detection of cancer biomarkers. The biosensor's innovative design allows for expedited development of this type of diagnostic tool for pathological biomarkers. The process involves grafting a fully characterized pyrene-bioreceptor conjugate onto an rGO support, facilitating the creation of the biosensor.

## 4. Conclusions

This study proposes an electrochemical biosensing platform for the quantification of rabbit muscle phosphoglucose isomerase (RmPGI), a model protein for the autocrine motility factor (AMF). It uses a screen-printed carbon electrode (SPCE) modified with reduced graphene oxide (rGO)/pyrene-functionalized D-fructose-6-phosphate (F6P). The biosensor demonstrated a limit of detection of 0.94 ± 0.04 fM in Tris buffer and 0.79 ± 0.04 fM in human plasma, with a linear response spanning six orders of magnitude (10 fM-100 nM). The biosensor exhibited a high degree of specificity for RmPGI, which was confirmed by control experiments employing n-fructose as the recognition element and HSA as a non-specific protein. This represents an advancement in the field of carbohydrate-based biosensors, introducing a novel architecture that involves the immobilization of pyrene-F6P affinity elements on rGO through strong π-π stacked interactions. It provides a cost-effective and adaptable solution for cancer biomarker detection in complex biological matrices, underscoring its promise for early cancer detection in clinical diagnostics. The biosensor could be used to detect other glycoprotein biomarkers by selecting the appropriate carbohydrate bioreceptor.

## Notes

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### CRediT authorship contribution statement

**Jia Guo:** Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation. **Hafsa Korri-Youssoufi:** Writing – review & editing, Supervision, Investigation, Data curation, Conceptualization. **Laurent Salmon:** Writing – review & editing, Writing – original draft, Visualization, Data curation, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgements

Jia Guo carried out this work as part of its PhD at the University of Paris-Saclay and thanks the Chinese Scientific Council for its financial support. The authors would like to thank Jean-Pierre Baltaze for helping with the NMR analyses, Tania Inceoglu and Hélène Maisonneuve for the MS data, Guillaume Dubourdieu for AFM measurements and Diana Dragoe for the XPS measurements.

### Supplementary materials

Supplementary material associated with this article can be found, in

the online version, at doi:10.1016/j.electacta.2025.147587.

### Data availability

Data will be made available on request.

### References

[1] M.F. Ullah, M. Aatif, The footprints of cancer development: cancer biomarkers, Cancer Treat. Rev. 35 (2009) 193–200, https://doi.org/10.1016/j.ctrv.2008.10.004.

[2] Y. Zhou, L. Tao, J. Qiu, J. Xu, X. Yang, Y. Zhang, X. Tian, X. Guan, X. Cen, Y. Zhao, Tumor biomarkers for diagnosis, prognosis and targeted therapy, Signal. Transduct. Target. Ther. 9 (2024) 1–86, https://doi.org/10.1038/s41392-024-01823-2.

[3] C.-W. Shan, Z. Chen, G.-C. Han, X.-Z. Feng, H.-B. Kraatz, Electrochemical immunobiosensors for the detection of the tumor marker alpha-fetoprotein: a review, Talanta 271 (2024) 125638, https://doi.org/10.1016/j.talanta.2024.125638.

[4] C. Bao, L. Deng, F. Huang, M. Yang, X. Li, Signal amplification strategies in photoelectrochemical sensing of carcinoembryonic antigen, Biosens. Bioelectron. 262 (2024) 116543, https://doi.org/10.1016/j.bios.2024.116543.

[5] H.-C. Huang, X.-Z. Wen, H. Xue, R.-S. Chen, J.-F. Ji, L. Xu, Phosphoglucose isomerase gene expression as a prognostic biomarker of gastric cancer, Chin. J. Cancer Res. Chung-Kuo Yen Cheng Yen Chiu 31 (2019) 771–784, https://doi.org/10.21147/j.issn.1000-9604.2019.05.07.

[6] Z. Liu, Q. Huang, Y. Yan, J. Yao, F. Zhong, S. Xie, M. Zhang, H. Zhang, M. Jin, L. Shui, A multi-unit integrated electrochemical biosensor array for synergistic signal enhancing carbohydrate antigen 125 detection, Sens. Actuators. B Chem. 393 (2023) 134224, https://doi.org/10.1016/j.snb.2023.134224.

[7] J.E. Oesterling, Prostate specific antigen: a critical assessment of the most useful tumor marker for adenocarcinoma of the prostate, J. Urol. 145 (1991) 907–923, https://doi.org/10.1016/s0022-5347(17)38491-4.

[8] M. Devillers, L. Ahmad, H. Korri-Youssoufi, L. Salmon, Carbohydrate-based electrochemical biosensor for detection of a cancer biomarker in human plasma, Biosens. Bioelectron. 96 (2017) 178–185, https://doi.org/10.1016/j.bios.2017.04.031.

[9] L. Ahmad, L. Salmon, H. Korri-Youssoufi, Electrochemical detection of the human cancer biomarker 'autocrine motility factor-phosphoglucose isomerase' based on a biosensor formed with a monosaccharidic inhibitor, Sens. Actuators. B Chem. (2019) 126933, https://doi.org/10.1016/j.snb.2019.126933.

[10] L.A. Liotta, R. Mandler, G. Murano, D.A. Katz, R.K. Gordon, P.K. Chiang, E. Schiffmann, Tumor cell autocrine motility factor, Proc. Natl. Acad. Sci. U. S. A. 83 (1986) 3302–3306, https://doi.org/10.1073/pnas.83.10.3302.

[11] Y. Niinaka, S. Paku, A. Haga, H. Watanabe, A. Raz, Expression and secretion of neuroleukin/phosphohexose isomerase/maturity factor as autocrine motility factor by tumor cells, Cancer Res. 58 (1998) 2667–2674. https://pubmed.ncbi.nlm.nih.gov/9635595/.

[12] M. Baumann, A. Kappl, T. Lang, K. Brand, W. Siegfried, E. Paterok, The diagnostic validity of the serum tumor marker phosphohexose isomerase (PHI) in patients with gastrointestinal, kidney, and breast cancer, Cancer Invest. 8 (1990) 351–356, https://doi.org/10.3109/07357909009012053.

[13] L. Dai, L.-J. Zhu, D.-H. Zheng, Y.-Q. Mo, X.-N. Wei, J.-H. Su, F. Pessler, B.-Y. Zhang, Elevated serum glucose-6-phosphate isomerase correlates with histological disease activity and clinical improvement after initiation of therapy in patients with rheumatoid arthritis, J. Rheumatol. 37 (2010) 2452–2461, https://doi.org/10.3899/jrheum.100157.

[14] O. Bodansky, Serum phosphohexose isomerase in cancer. II, as an index of tumor growth in metastatic carcinoma of the breast, Cancer 7 (1954) 1200–1226. https://www.ncbi.nlm.nih.gov/pubmed/13209520.

[15] R.W. Gracy, B.E. Tilley, Phosphoglucose isomerase of human erythrocytes and cardiac tissue, Methods Enzymol. (1975) 392–400, https://doi.org/10.1016/S0076-6879(75)41086-2.

[16] H. Khan, M.R. Shah, J. Barek, M.I. Malik, Cancer biomarkers and their biosensors: a comprehensive review, TrAC Trends Anal. Chem. 158 (2023) 116813, https://doi.org/10.1016/j.trac.2022.116813.

[17] F. Achi, A.M. Attar, A. Ait Lahcen, Electrochemical nanobiosensors for the detection of cancer biomarkers in real samples: trends and challenges, TrAC Trends Anal. Chem. 170 (2024) 117423, https://doi.org/10.1016/j.trac.2023.117423.

[18] H. Watanabe, K. Takehana, M. Date, T. Shinozaki, A. Raz, Tumor cell autocrine motility factor is the neuroleukin/phosphohexose isomerase polypeptide, Cancer Res. 56 (1996) 2960–2963. https://pubmed.ncbi.nlm.nih.gov/8674049/.

[19] A. Lagana, T. Duchaine, A. Raz, L. DesGroseillers, I.R. Nabi, Expression of autocrine motility factor/phosphohexose isomerase in Cos7 cells, Biochem. Biophys. Res. Commun. 273 (2000) 213–218, https://doi.org/10.1006/bbrc.2000.2904.

[20] A. Lagana, J.G. Goetz, N.Y.Y. Altschuler, I.R. Nabi, pH-specific sequestration of phosphoglucose isomerase/autocrine motility factor by fibronectin and heparan sulphate, J. Cell Sci. 118 (2005) 4175–4185, https://doi.org/10.1242/jcs.02538.

[21] M. Zamani, C.M. Klapperich, A.L. Furst, Recent advances in gold electrode fabrication for low-resource setting biosensing, Lab. Chip. 23 (2020) 1410–1419, https://doi.org/10.1039/d2lc00552b (n.d.).

[22] H. Beitollahi, S.Z. Mohammadi, M. Safaei, S. Tajik, Applications of electrochemical sensors and biosensors based on modified screen-printed electrodes: a review, Anal. Methods 12 (2020) 1547–1560, https://doi.org/10.1039/C9AY02598G.
[23] Y.-J. Sun, C.-C. Chou, W.-S. Chen, R.-T. Wu, M. Meng, C.-D. Hsiao, The crystal structure of a multifunctional protein: phosphoglucose isomerase/autocrine motility factor/neuroleukin, Proc. Natl. Acad. Sci. 96 (1999) 5412–5417, https://doi.org/10.1073/pnas.96.10.5412.

[24] R. Kumar, A. Srivastava, Anion binding-induced white light emission using a water-tolerant fluorescent molecular tweezer, Chem. – Eur. J. 22 (2016) 3224–3229, https://doi.org/10.1002/chem.201504269.

[25] E.A. Noltmann, Isolation of crystalline phosphoglucose isomerase from rabbit muscle, J. Biol. Chem. 239 (1964) 1545–1550. https://www.ncbi.nlm.nih.gov/pubmed/14189891.

[26] J.E.D. Dyson, E.A. Noltmann, The effect of pH and temperature on the kinetic parameters of phosphoglucose isomerase, J. Biol. Chem. 243 (1968) 1401–1414. http://www.jbc.org/content/243/7/1401.

[27] B. Adhikari, J. Nanda, A. Banerjee, Pyrene-containing peptide-based fluorescent organogels: inclusion of graphene into the organogel, Chem. – Eur. J. 17 (2011) 11488–11496, https://doi.org/10.1002/chem.201101360.

[28] B. Zhao, S. Yang, J. Deng, K. Pan, Chiral graphene hybrid materials: structures, properties, and Chiral applications, Adv. Sci. 8 (2021) 2003681, https://doi.org/10.1002/ads.202003681.

[29] B.T.T. Nguyen, A.E.K. Peh, C.Y.L. Chee, K. Fink, V.T.K. Chow, M.M.L. Ng, C.-S. Toh, Electrochemical impedance spectroscopy characterization of nanoporous alumina dengue virus biosensor, Bioelectrochemistry. 88 (2012) 15–21, https://doi.org/10.1016/j.bioelechem.2012.04.006.

[30] B. Esteban-Fernández de Ávila, E. Araque, S. Campuzano, M. Pedrero, B. Dalkiran, R. Barderas, R. Villalonga, E. Kiliç, J.M. Pingarrón, Dual functional graphene derivative-based electrochemical platforms for detection of the TP53 gene with single nucleotide polymorphism selectivity in biological samples, Anal. Chem. 87 (2015) 2290–2298, https://doi.org/10.1021/ac504032d.

[31] B.V. Chikkaveeraiah, A.A. Bhirde, N.Y. Morgan, H.S. Eden, X. Chen, Electrochemical immunosensors for detection of cancer protein biomarkers, ACS. Nano 6 (2012) 6546–6561, https://doi.org/10.1021/nn3023969.

[32] M. Yang, X. Yi, J. Wang, F. Zhou, Electroanalytical and surface plasmon resonance sensors for detection of breast cancer and Alzheimer's disease biomarkers in cells and body fluids, Analyst 139 (2014) 1814–1825, https://doi.org/10.1039/c3an02065g.

[33] K. Ondraskova, R. Sebuyoya, L. Moranova, J. Holcakova, P. Vonka, R. Hrstka, M. Bartosik, Electrochemical biosensors for analysis of DNA point mutations in cancer research, Anal. Bioanal. Chem. 415 (2023) 1065–1085, https://doi.org/10.1007/s00216-022-04388-7.

[34] L. Guo, S. Chao, P. Huang, X. Lv, Q. Song, C. Wu, Y. Pei, Z. Pei, A universal photochemical method to prepare carbohydrate sensors based on perfluorophenylazide modified polydopamine for study of carbohydrate-lectin interactions by QCM biosensor, Polymers. 11 (2019) 1023, https://doi.org/10.3390/polym11061023.

[35] J.W. Chamberlain, K. Maurer, J. Cooper, W.J. Lyon, D.L. Danley, D.M. Ratner, Microelectrode array biosensor for studying carbohydrate-mediated interactions, Biosens. Bioelectron. 34 (2012) 253–260, https://doi.org/10.1016/j.bios.2012.02.017.

[36] D. Lin, J. Wu, F. Yan, S. Deng, H. Ju, Ultrasensitive immunoassay of protein biomarker based on electrochemiluminescent quenching of quantum dots by Hemin bio-bar-coded nanoparticle tags, Anal. Chem. 83 (2011) 5214–5221, https://doi.org/10.1021/ac200398x.

[37] L. Moranova, J. Strmiskova, K. Ondraskova, M. Bardelcik, M. Cwik, I. Kiss, R. Hrstka, M. Bartosik, Electrochemical detection of BRAF V600E mutation in a liquid biopsy format: LAMPing the way to an improved diagnostics and treatment, Adv. Mater. Technol. 10 (2025) 2401404, https://doi.org/10.1002/admt.202401404.

[38] W. Wang, X. Fan, S. Xu, J.J. Davis, X. Luo, Low fouling label-free DNA sensor based on polyethylene glycols decorated with gold nanoparticles for the detection of breast cancer biomarkers, Biosens. Bioelectron. 71 (2015) 51–56, https://doi.org/10.1016/j.bios.2015.04.018.

[39] D. Wang, W. Hu, Y. Xiong, Y. Xu, C. Ming Li, Multifunctionalized reduced graphene oxide-doped polypyrrole/pyrrolepropylic acid nanocomposite impedimetric immunosensor to ultra-sensitively detect small molecular aflatoxin B1, Biosens. Bioelectron. 63 (2015) 185–189, https://doi.org/10.1016/j.bios.2014.06.070.

[40] Q. Cai, H. Li, B. Wang, G. Jie, A spatial-potential-resolved electrochemiluminescence biosensor for simultaneous detection of BRCA1 and BRCA2 based on a novel self-luminescent metal–organic framework, Chem. Eng. J. 476 (2023) 146799, https://doi.org/10.1016/j.cej.2023.146799.

[41] G.-F. Jie, P. Liu, S.-S. Zhang, Highly enhanced electrochemiluminescence of novel gold/silica/CdSe-CdS nanostructures for ultrasensitive immunoassay of protein tumor marker, Chem. Commun. Camb. Engl. 46 (2010) 1323–1325, https://doi.org/10.1039/b919186k.

[42] T. Hao, Z. Guo, S. Du, L. Shi, Ultrasensitive detection of carcinoembryonic antigen based on electrochemiluminescence quenching of Ru(bpy)32+ by quantum dots, Sens. Actuators. B Chem. (2012) 803–809, https://doi.org/10.1016/j.snb.2012.05.074, 171–172.

[43] Y. Wang, S. Sun, J. Luo, Y. Xiong, T. Ming, J. Liu, Y. Ma, S. Yan, Y. Yang, Z. Yang, J. Reboud, H. Yin, J.M. Cooper, X. Cai, Low sample volume origami-paper-based graphene-modified aptasensors for label-free electrochemical detection of cancer biomarker-EGFR, Microsyst. Nanoeng. 6 (2020) 1–9, https://doi.org/10.1038/s41378-020-02146-2.

[44] M. Quansah, L. Fetter, A. Fineran, H.V. Colling, K. Silver, T.J. Rowland, A. J. Bonham, Rapid and quantitative detection of lung cancer biomarker ENOX2 using a novel aptamer in an electrochemical DNA-based (E-DNA) biosensor, Biosensors 13 (2023) 675, https://doi.org/10.3390/bios13070675.

[45] M.A. Ali, K. Mondal, C. Singh, B.D. Malhotra, A. Sharma, Anti-epidermal growth factor receptor conjugated mesoporous zinc oxide nanofibers for breast cancer diagnostics, Nanoscale 7 (2015) 7234–7245, https://doi.org/10.1039/C5NR00194C.

[46] X. Yang, P. Chen, X. Zhang, H. Zhou, Z. Song, W. Yang, X. Luo, An electrochemical biosensor for HER2 detection in complex biological media based on two antifouling materials of designed recognizing peptide and PEG, Anal. Chim. Acta 1252 (2023) 341075, https://doi.org/10.1016/j.aca.2023.341075.

[47] B. Attoye, M.J. Baker, F. Thomson, C. Pou, D.K. Corrigan, Optimisation of an electrochemical DNA sensor for measuring KRAS G12D and G13D point mutations in different tumour types, Biosensors 11 (2021) 42, https://doi.org/10.3390/bios11020042.

[48] J. Wang, X. Zhu, Q. Tu, Q. Guo, C.S. Zarui, J. Momand, X.Z. Sun, F. Zhou, Capture of p53 by electrodes modified with consensus DNA duplexes and amplified voltammetric detection using ferrocene-capped gold nanoparticle/streptavidin conjugates, Anal. Chem. 80 (2008) 769–774, https://doi.org/10.1021/ac0714112.

[49] Y. Zhang, S. Chen, J. Ma, X. Zhou, X. Sun, H. Jing, M. Lin, C. Zhou, Enzyme-catalyzed electrochemical aptasensor for ultrasensitive detection of soluble PD-L1 in breast cancer based on decorated covalent organic frameworks and carbon nanotubes, Anal. Chim. Acta 1282 (2023) 341927, https://doi.org/10.1016/j.aca.2023.341927.

[50] C.K. Tang, A. Vaze, J.F. Rusling, Paper-based electrochemical immunoassay for rapid, inexpensive cancer biomarker protein detection, Anal. Methods 6 (2014) 8878–8881, https://doi.org/10.1039/C4AY01962H.

[51] M. Zhang, W. Dai, M. Yan, S. Ge, J. Yu, X. Song, W. Xu, Ultrasensitive electrochemiluminescence immunosensor using PtAg@carbon nanocrystals composites as labels and carbon nanotubes-chitosan/gold nanoparticles as enhancer, Analyst 137 (2012) 2112–2118, https://doi.org/10.1039/c2an35186b.

[52] C. Huang, Y. Chen, G. Jin, A one-step immunoassay for carbohydrate antigen 19-9 by biosensor based on imaging ellipsometry, Ann. Biomed. Eng. 39 (2011) 185–192, https://doi.org/10.1007/s10439-010-0174-4.

[53] L. Zhang, Y. Wang, Q. Tian, Y. Liu, J. Li, Multienzyme decorated polysaccharide amplified electrogenerated chemiluminescence biosensor for cytosensing and cell surface carbohydrate profiling, Biosens. Bioelectron. 89 (2017) 1013–1019, https://doi.org/10.1016/j.bios.2016.10.040.