Dual-lncrna photoelectrochemical biosensor based on hcr signal amplification and preparation method and application thereof

Abstract

This invention discloses a dual lncRNA photoelectrochemical biosensor based on HCR signal amplification, its preparation method, and its applications. The sensor comprises a magnetic bead-nucleic acid complex, SnS2 quantum dot-modified hairpin probes, a dual-channel photoelectrode system, and a magnetic separation-chemical cleavage combined separation system. The magnetic bead-nucleic acid complex is formed by the biotin-streptavidin binding of streptavidin magnetic beads and hairpin probes H1 and H2. The SnS2 quantum dot-modified hairpin probes are prepared by reacting H3 and H4 with EDC / NHS-activated SnS2 quantum dots. The dual-channel photoelectrode system includes two configurations: Cu2S-Cu2O / ITO and Cu2O-Cu2S / ITO. The magnetic separation-chemical cleavage combined separation system utilizes TCEP to selectively cleave the disulfide bonds in H1 to achieve spatial separation of the dual-target products. This sensor can be used to detect lncRNAs HOTAIR and MALAT1, and combined with machine learning models for early lung cancer diagnosis, exhibiting advantages such as high sensitivity, strong specificity, and good stability.

Description

Technical Field

[0001] This invention belongs to the field of biosensing technology, specifically relating to a dual-target photoelectrochemical (PEC) sensor based on hybridization chain reaction (HCR) signal amplification, magnetic bead separation technology and quantum dot quenching effect, for the simultaneous detection of long non-coding RNA (lncRNA) HOTAIR and MALAT1, and the application of this sensor in the early diagnosis of lung cancer. Background Technology

[0002] Long non-coding RNAs (lncRNAs) are a class of non-coding RNA molecules longer than 200 nucleotides that play important regulatory roles in the occurrence, development, and metastasis of tumors. Among them, HOTAIR (HOX transcriptional antisense RNA) and MALAT1 (lung adenocarcinoma metastasis-associated transcript 1) are two lncRNA biomarkers closely related to lung cancer and have been proven to be potential diagnostic biomarkers for non-small cell lung cancer (NSCLC).

[0003] Currently, the detection of HOTAIR and MALAT1 mainly employs a single biomarker detection strategy, but this approach suffers from limitations such as high false positive rates and insufficient specificity. Studies have shown that combined detection of dual lncRNA targets can effectively overcome the limitations of single biomarker detection and improve diagnostic accuracy. Therefore, establishing a combined detection method for HOTAIR and MALAT1 is of great significance for the early diagnosis of lung cancer.

[0004] Among existing technologies, photoelectrochemical biosensors have attracted widespread attention due to their advantages such as high sensitivity, low background signal, and simple equipment. Hybridization chain reaction (HCR), as an enzyme-free isothermal nucleic acid amplification technique, forms long-chain DNA polymers through alternating hybridization of hairpin probes, enabling efficient signal amplification. Magnetic separation technology has also been applied in the field of biosensing for the enrichment and separation of targets.

[0005] However, the existing technologies mainly have the following problems: (1) Limited detection throughput: Traditional PEC sensors are mostly single-target detection, making it difficult to achieve simultaneous detection of multiple targets; (2) Single separation strategy: Existing magnetic-assisted enrichment technology is mainly used for single-target detection or simple dual-signal ratio detection, lacking a magnetic separation-chemical cut-off synergistic strategy that can achieve complete separation of dual targets; (3) Single signal quenching mechanism: There is a lack of efficient signal quenching materials to achieve a sensitive "signal-off" detection mode; (4) Single heterostructure: Existing Cu2O-Cu2S materials are mainly used for photocatalysis, and their directional configuration design has not been explored in the field of biosensing.

[0006] Therefore, developing a photoelectrochemical sensor capable of dual-target joint detection with high sensitivity and specificity is of significant clinical value for the early diagnosis of lung cancer. Summary of the Invention

[0007] The technical problem to be solved by this invention is to overcome the technical defects of existing technologies, such as difficulty in dual-target detection and separation, single signal amplification strategy, and insufficient detection sensitivity, and to provide a dual lncRNA photoelectrochemical biosensor based on HCR signal amplification to achieve highly sensitive and highly specific joint detection of lncRNAs HOTAIR and MALAT1.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A dual lncRNA photoelectrochemical biosensor based on HCR signal amplification, the sensor comprising a magnetic bead-nucleic acid complex, a SnS2 quantum dot-modified hairpin probe, a dual-channel photoelectrode system, and a magnetic separation-chemical cleavage combined separation system; The magnetic bead-nucleic acid complex includes streptavidin magnetic beads and hairpin probes H1 and H2 immobilized thereon via biotin-streptavidin binding, wherein H1 is a biotin-modified disulfide-labeled hairpin probe and H2 is a biotin-modified hairpin probe. The SnS2 quantum dot-modified hairpin probes include H3-SnS2 and H4-SnS2, wherein H3-SnS2 and H4-SnS2 are prepared by reacting hairpin probes H3 and H4 with SnS2 quantum dots activated by EDC / NHS. The dual-channel photoelectrode system includes a Cu2S-Cu2O / ITO electrode and a Cu2O-Cu2S / ITO electrode, wherein the Cu2S-Cu2O / ITO electrode includes a Cu2S layer on the outer layer, and the Cu2O-Cu2S / ITO electrode includes a Cu2O layer on the outer layer and a magnetic tape attached to the back of the electrode. The magnetic separation-chemical cleavage combined separation system includes a TCEP processing unit and a magnetic separation unit. The TCEP processing unit selectively cleaves the disulfide bonds in H1, releasing the HCR product induced by HOTAIR into the supernatant. The magnetic separation unit separates the supernatant from the magnetic beads that retain the HCR product induced by MALAT1, thereby achieving spatial separation of the dual-target products.

[0009] Preferably, in the Cu2S-Cu2O / ITO electrode, the Cu2S layer is located on the outer layer and is bonded to HCR products containing HOTAIR, and in the Cu2O-Cu2S / ITO electrode, the Cu2O layer is located on the outer layer and has magnetic tape attached to its back side and is bonded to magnetic beads containing MALAT1.

[0010] Preferably, the SnS2 quantum dots are prepared by hydrothermal reaction of SnCl4·5H2O and L-cysteine.

[0011] This invention also provides a method for preparing the above-mentioned dual lncRNA photoelectrochemical biosensor, the method comprising the following steps: (1) Hydrothermal synthesis of SnS2 quantum dots: 6.0 mmol / L SnCl4·5H2O and 20 mmol / L L-cysteine ​​were dissolved in ultrapure water, reacted at 180 °C for 6 h, purified by centrifugation and dialyzed to obtain SnS2 quantum dots; (2) Preparation of streptavidin magnetic beads: Fe3O4 nanoparticles were synthesized by solvothermal method, coated with SiO2 shell by TEOS, modified with APTES amino group, and streptavidin was fixed by crosslinking with glutaraldehyde. (3) Preparation of Cu2O-Cu2S nanomaterials and construction of dual-channel photoelectrodes: Cu2O nanomaterials were prepared by liquid-phase reduction method, and Cu2O-Cu2S nanomaterials were formed by Na2S solution treatment. They were then transferred to the surface of ITO electrode to form two configurations: Cu2S-Cu2O / ITO and Cu2O-Cu2S / ITO. (4) Preparation of SnS2 quantum dot modified hairpin probes: H3-SnS2 and H4-SnS2 were prepared by activating the carboxyl groups on the surface of SnS2 quantum dots with EDC / NHS and reacting them with hairpin probes H3 and H4. (5) Perform HCR amplification reaction: Incubate streptavidin magnetic beads with biotin-modified hairpins H1 and H2 to form a magnetic bead-nucleic acid complex. Add target lncRNA for hybridization reaction. After magnetic separation and washing, resuspend to obtain solution A. Add H3-SnS2 and H4-SnS2 to solution A, shake at 37 ℃ for 90 min for HCR amplification. After magnetic separation and washing, resuspend to obtain solution B. (6) Constructing a dual-target detection system: Add TCEP solution to solution B, and after TCEP treatment for 30 min, perform magnetic separation. Transfer the supernatant to the Cu2S-Cu2O / ITO electrode and fix the magnetic beads on the back of the Cu2O-Cu2S / ITO electrode for detection.

[0012] Preferably, in step (3), the Cu2O-Cu2S nanomaterials are prepared by liquid phase interface reaction method: Cu2O nanomaterials are dispersed in toluene, deionized water and Na2S·9H2O solution are quickly added, and the mixture is stirred gently for 2 min.

[0013] Preferably, in step (5), the HCR amplification reaction takes 90 min.

[0014] Preferably, in step (6), the TCEP treatment time is 30 min and the TCEP concentration is 50 mM.

[0015] The present invention also provides the application of the above-mentioned dual lncRNA photoelectrochemical biosensor in the detection of lncRNAs HOTAIR and MALAT1.

[0016] Preferably, the linear range of the detection is 10² amol / L to 10 7 The detection limits were 38 amol / L and 35 amol / L, respectively.

[0017] The present invention also provides the application of the above-mentioned dual lncRNA photoelectrochemical biosensor in the early diagnosis of lung cancer, including: extracting extracellular vesicles from the sample to be tested and lysing them; using the sensor to detect the content of lncRNA HOTAIR and MALAT1 in the lysate; and inputting the detection results and the subject's epidemiological information into a machine learning model based on artificial neural networks to predict the risk of lung cancer.

[0018] Preferably, the machine learning model uses the detection results of lncRNA HOTAIR and MALAT1, as well as age and smoking history as input variables, and outputs a prediction result of lung cancer or non-lung cancer. The model accuracy is 96% and the AUC value is 0.955.

[0019] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention combines magnetic bead separation technology with chemically selective cleavage, utilizing the specific cleavage effect of TCEP on disulfide bonds to achieve spatial separation of dual-target HCR products. Through the disulfide bond design in the H1 probe, HOTAIR-induced HCR products are released into the supernatant after TCEP treatment, while MALAT1-induced HCR products remain on the magnetic bead surface. This achieves complete separation and detection of dual targets in a single reaction system, avoiding signal cross-interference and overcoming the limitations of traditional multi-target detection requiring multiple separations or complex microfluidic devices.

[0020] 2. This invention uses SnS2 quantum dots as the HCR signal amplification carrier while leveraging their broad-spectrum absorption characteristics to achieve photocurrent quenching of the Cu2O-Cu2S heterojunction photoelectrode. SnS2 quantum dots form long-chain DNA polymers through the HCR reaction. The accumulation of a large number of quantum dots generates significant steric hindrance and electron transfer obstruction. Simultaneously, the light absorption of the quantum dots competes with the light trapping of the photoelectrode, resulting in a dual quenching mechanism that significantly improves detection sensitivity.

[0021] 3. This invention constructs two different photoelectrode configurations by controlling the assembly method of the Cu2O-Cu2S heterojunction on the ITO electrode: Cu2S-Cu2O / ITO (outer Cu2S) and Cu2O-Cu2S / ITO (outer Cu2O). This directional configuration design not only optimizes the photoelectric conversion efficiency of the photoelectrode, but more importantly, achieves compatibility with the magnetic separation system. The Cu2O-Cu2S / ITO electrode can directly adsorb magnetic beads via the magnetic tape on the back, simplifying the operation process and improving the integration of detection. 4. This invention combines dual-target PEC detection results with epidemiological information to construct a machine learning evaluation model based on artificial neural networks. The multi-parameter model achieves an accuracy of 96% and an AUC value of 0.955, significantly outperforming the single-parameter model and other machine learning models, providing a new technical approach for the early diagnosis of lung cancer. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the detection principle of the dual-target photoelectrochemical sensor based on HCR signal amplification and SnS2 quantum dots of the present invention. Figure 2 The figures show the HRTEM and XRD patterns of SnS2 quantum dots. In the figures, (A) is the HRTEM pattern of SnS2 QDs; and (B) is the XRD pattern of SnS2 QDs. Figure 3 The FT-IR spectrum of SnS2 quantum dots; Figure 4 The FT-IR spectrum of SA-MB is shown below. Figure 5 The image shows SEM images of Cu2O-Cu2S nanomaterials. In the image, (A) Cu2O-Cu2S; (B) Cu2S-Cu2O. Figure 6 XRD pattern of Cu2O-Cu2S nanomaterials; Figure 7 The figures show the PEC response of a dual-target photoelectrochemical sensor. In the figure, (A) is the PEC response of HOTAIR; and (B) is the PEC response of MALAT1. Figure 8 The figures show the EIS response diagrams of dual-target photoelectrochemical sensors. In the figure, (A) is the EIS response diagram of HOTAIR; and (B) is the EIS response diagram of MALAT1. Figure 9 The image shows the PAGE verification of the HCR reaction triggered by lncRNA HOTAIR and MALAT1. In the image, (A) is the PAGE of lncRNA HOTAIR; (B) is the PAGE of lncRNA MALAT1. Figure 10The figure shows the optimized HCR reaction time. In the figure, (A) is the HCR reaction time of HOTAIR; and (B) is the HCR reaction time of MALAT1. Figure 11 The diagram shows the optimized disulfide bond breaking time. Figure 12 The figure shows the standard curve for lncRNA HOTAIR detection. In the figure, (A) is the PEC response; and (B) is the standard curve. Figure 13 The figure shows the standard curve for the detection of lncRNA MALAT1. In the figure, (A) is the PEC response; and (B) is the standard curve. Figure 14 The graph shows the selectivity evaluation of the dual-target photoelectrochemical sensor. In the graph, (A) is the selectivity of lncRNA HOTAIR; and (B) is the selectivity of lncRNA MALAT1. Figure 15 The figure shows the stability evaluation of the dual-target photoelectrochemical sensor. In the figure, (A) is the stability of lncRNA HOTAIR; and (B) is the stability of lncRNA MALAT1. Figure 16 The figure shows the reproducibility evaluation of the dual-target photoelectrochemical sensor. In the figure, (A) is the reproducibility of lncRNA HOTAIR; and (B) is the reproducibility of lncRNA MALAT1. Figure 17 The graph shows the correlation analysis between the PEC method and the RT-qPCR method. In the graph, (A) HOTAIR bar chart; (B) HOTAIR correlation analysis; (C) MALAT1 bar chart; (D) MALAT1 correlation analysis. Figure 18 The image shows the detection results of lncRNAs HOTAIR and MALAT1 in plasma sEVs of lung cancer patients and healthy controls. In the image, (A) HOTAIR box plot; (B) HOTAIR heatmap; (C) MALAT1 box plot; (D) MALAT1 heatmap. Figure 19 The diagram shows the diagnostic efficacy evaluation based on machine learning models. In the diagram, (A) comparison of multiple machine learning models; (B) confusion matrix diagram: (a) HOTAIR and MALAT1 concentrations and epidemiological information, (b) HOTAIR concentrations and epidemiological information, (c) MALAT1 concentrations and epidemiological information, (d) epidemiological information, (e) HOTAIR and MALAT1 concentrations; (C) ROC curve. Detailed Implementation

[0023] The technical solution of the present invention will be described in detail below with reference to specific embodiments, but the scope of protection of the present invention is not limited to these embodiments.

[0024] Example 1: Preparation and characterization of SnS2 quantum dots: SnS2 quantum dots were synthesized by a hydrothermal method: 6.0 mmol / L SnCl4·5H2O and 20 mmol / L L-cysteine ​​were dissolved in 25 mL of ultrapure water to form a transparent precursor solution; the mixture was transferred to a 50 mL polytetrafluoroethylene-lined stainless steel autoclave and heated at 180 °C for 6 h; after the reaction was completed, the mixture was centrifuged at 12000 rpm for 15 min at 4 °C, and the yellow supernatant was collected to remove reactant residues. The supernatant was then dialyzed using a dialysis bag (molecular weight cutoff: 3000 Da) to finally obtain SnS2 quantum dots.

[0025] HRTEM observations revealed that the average particle size of SnS2 quantum dots was approximately 3 nm, with lattice fringes of 0.305 nm and 0.32 nm corresponding to the (101) and (006) crystal planes of SnS2, respectively (see [link to HRTEM observation]). Figure 2 The XRD pattern is consistent with the JCPDS PDF#21-1231 standard card. In the FT-IR spectrum, 3000-3600 cm⁻¹ -1 The broad absorption band at 1630 cm⁻¹ is attributed to the NH stretching vibration of the amino group in the L-cysteine ​​ligand. -1 The strong absorption peak at 400-800 cm⁻¹ corresponds to the C=O stretching vibration of the amide bond. -1 The characteristic peak at that location corresponds to the stretching vibration of the Sn-S bond (see [reference]). Figure 3 This confirms the successful preparation of SnS2 quantum dots.

[0026] Example 2: Preparation and characterization of streptavidin magnetic beads (SA-MB): Weigh 1.7840 g of ferric chloride hexahydrate (FeCl3·6H2O) and dissolve it in 60 mL of ethylene glycol. Stir magnetically until completely dissolved, yielding a pale yellow, clear solution. Add 4.5 g of anhydrous sodium acetate (NaAc) and continue stirring for 30 min. Transfer the solution to a 100 mL polytetrafluoroethylene-lined high-pressure reactor and react at 200 °C for 8 h. After the reaction is complete, allow it to cool naturally. Collect the black solid product by magnetic separation, wash three times each with Milli-Q water and anhydrous ethanol, and dry under vacuum.

[0027] Take 0.05 g of the above powder and ultrasonically disperse it in a mixed solution of 35 mL anhydrous ethanol and 6 mL water. Add diluted ammonia to adjust the pH to 9.0, then add 0.2 mL of tetraethyl orthosilicate (TEOS). Stir vigorously for 10 h to complete the silica coating. Wash and collect the product after the reaction is complete.

[0028] To perform surface amino functionalization, the product was ultrasonically dispersed in 34 mL of anhydrous ethanol, the pH was adjusted to 9.0, and 0.1 mL of TEOS and 1.7 mL of 3-aminopropyltriethoxysilane (APTES) were added sequentially. The mixture was stirred vigorously for 8 h. After the reaction was completed, the product was magnetically separated and washed, and finally dispersed in 25 mL of PBS to prepare a 2 mg / mL dispersion.

[0029] Four mg of aminated Fe3O4@SiO2 nanoparticles were dispersed in 2 mL of Tris-HCl buffer (10 mmol / L, pH 7.4), and 200 μL of 2.5% (v / v) glutaraldehyde (GLD) solution was added. The mixture was incubated at room temperature with shaking for 2 h. After centrifugation and washing, the nanoparticles were dispersed in 1 mL of Tris-HCl buffer, and 50 μL of SA solution (1 mg / mL) was added. The mixture was incubated at 4 °C for 1 h. After washing, the nanoparticles were dispersed in 2 mL of Tris-HCl buffer to obtain SA-MB.

[0030] FT-IR spectral verification (see) Figure 4 Compared to pure Fe3O4, SA-MB exhibits higher activity at 1000-1200 cm⁻¹. -1 and 800 cm -1 The presence of characteristic peaks for Si-O-Si and Si-O in the vicinity confirms the successful coating of the SiO2 shell; 3000-3600 cm⁻¹ -1 and 1630cm -1 The absorption band at that location confirms the successful modification of SA.

[0031] Example 3: Preparation and characterization of Cu2O-Cu2S nanomaterials: Weigh 40 mL of ethylene glycol (EG) into a 100 mL round-bottom flask, add 0.3025 g of PVP, and stir for 30 min until completely dissolved. Add 5 mL of EG solution containing 1.25 mmol / L NaCl, then add 5 mL of Cu(NO3)2·3H2O solution (10 mmol / L), and react for 4 h to obtain Cu2O nanomaterials.

[0032] Take 1 mL of Cu₂O nanomaterials dispersed in anhydrous ethanol into a 10 mL beaker, add 2 mL of toluene, and vortex to mix thoroughly. Quickly add 8 mL of deionized water, then add Na₂S·9H₂O solution, and stir gently for 2 min to obtain Cu₂O-Cu₂S nanomaterials.

[0033] SEM characterization shows (see...) Figure 5 The Cu₂O-Cu₂S nanomaterials exhibit a spherical morphology, a rough surface, and good dispersibility. XRD patterns (see [reference needed]). Figure 6In the study, pure Cu2O showed (111), (200) and (220) crystal plane diffraction peaks at 36.5°, 42.4° and 61.5°; Cu2O-Cu2S composite material showed characteristic peaks of Cu2S (451) and (184) crystal plane at 35.3° and 38.4°, confirming the successful modification of Cu2S.

[0034] Example 4: Construction and feasibility verification of a dual-target photoelectrochemical sensor: (1) Preparation of SnS2 quantum dot modified hairpin probes: 60 μL of PBS solution containing 20 mmol / L EDC and 10 mmol / L NHS was mixed with 30 μL of SnS2 quantum dots and reacted at 37 °C for 2 h to activate the carboxyl groups. 12 μL of hairpin H3 or H4 with a concentration of 10 μmol / L was added respectively, and the reaction was continued at 37 °C for 2 h to obtain H3-SnS2 and H4-SnS2, which were stored at 4 °C for later use.

[0035] (2) Preparation of magnetic bead-nucleic acid complex: 100 μL of SA-MB (2 mg / mL) was placed in a low-adsorption centrifuge tube and washed three times with 10 mmol / L PBS buffer. 20 μL of biotin-modified hairpin H1 solution (10 μmol / L) and 20 μL of biotin-modified hairpin H2 solution (10 μmol / L) were added, and the mixture was incubated at 37 °C with shaking for 30 min. After magnetic separation and washing, the MB-H1 / H2 complex was obtained.

[0036] (3) Target recognition and HCR amplification: MB-H1 / H2 was resuspended in a 200 μL reaction system, and 20 μL lncRNA HOTAIR (10 pM), 20 μL lncRNA MALAT1 (10 pM), and 160 μL DNA hybridization buffer were added. The mixture was incubated at 37 °C with shaking for 90 min. After magnetic separation and washing, the mixture was resuspended in 200 μL PBS to obtain solution A. 100 μL of solution A was taken, and 100 μL H3-SnS2, 100 μL H4-SnS2, and 100 μL DNA hybridization buffer were added. The mixture was incubated at 37 °C with shaking for 90 min to perform HCR amplification. After magnetic separation and washing, the mixture was resuspended in 100 μL PBS to obtain solution B.

[0037] (4) Magnetic separation-chemical cleavage and dual-channel detection: Add 40 μL of 50 mM TCEP solution to solution B and shake at 37 °C for 30 min. After magnetic separation, collect the supernatant and precipitate. Transfer the supernatant to the surface of the Cu2S-Cu2O / ITO electrode, react at room temperature for 1 h, and then store at 4 °C overnight (HOTAIR detection channel); fix the precipitate to the surface of the Cu2O-Cu2S / ITO electrode with magnetic tape and react at room temperature for 60 min (MALAT1 detection channel). Place the prepared electrode in Tris-HCl buffer (0.1 mol / L, pH 7.4) containing 0.1 mol / L AA for PEC testing with a bias voltage of -0.1 V.

[0038] (5) Feasibility verification: PEC response results show (see Figure 7 The initial photocurrent values ​​of bare electrodes Cu2S-Cu2O / ITO and Cu2O-Cu2S / ITO were -42.3 μA and -38.6 μA, respectively; the photocurrent values ​​of blank samples (without target) dropped to -40.7 μA and -36.1 μA, indicating that the introduction of hairpin probes and magnetic beads increased the steric hindrance; in the presence of a target, HCR amplification loaded with SnS2 quantum dots significantly reduced the photocurrent, confirming the feasibility of the sensor.

[0039] EIS verification (see) Figure 8 The results showed that the electron transfer resistance increased significantly in the presence of the target, consistent with the steric hindrance effect of HCR products and SnS2 quantum dots.

[0040] PAGE verification (see PAGE verification) Figure 9 The results showed that high molecular weight continuous diffuse bands appeared only when the target was present, confirming the target dependence of the HCR reaction.

[0041] Example 5: Optimization of detection conditions: (1) Optimization of HCR reaction time: The effect of HCR reaction time (0-120 min) on PEC response was investigated. The results showed that as the reaction time was extended to 90 min, the photocurrent gradually decreased and tended to stabilize (see Figure 10 Therefore, 90 minutes was chosen as the optimal HCR reaction time.

[0042] (2) Optimization of disulfide bond breaking time: The effect of TCEP treatment time (0-60 min) on PEC response was investigated; the results showed that the photocurrent decreasing trend weakened after 30 min (see Figure 11 Therefore, 30 min was chosen as the optimal disulfide bond breaking time.

[0043] Example 6, Standard Curve and Detection Limit: Under optimal conditions, different concentrations of lncRNAs HOTAIR and MALAT1 were detected: HOTAIR assay: Concentration range 10² amol / L to 10 7 amol / L, the linear regression equation is I(μA) = 5.27lgCHOTAIR - 48.29, R² = 0.998 (see [reference]). Figure 12 The detection limit was 38 amol / L (S / N=3).

[0044] MALAT1 detection: Concentration range 10² amol / L to 10 7 amol / L, the linear regression equation is I(μA) = 3.77lgCMALAT1 - 39.18, R² = 0.992 (see...) Figure 13 The detection limit is 35 amol / L (S / N=3).

[0045] Example 7, Methodological Evaluation: (1) Selectivity: The effects of potential interfering agents such as lncRNA HULC, MEG3, miRNA-let7a, and miRNA-486 were investigated. The results showed (see [link to study]). Figure 14 When the interfering object is present alone, the photocurrent value is not significantly different from that of the blank; when the target is present alone or in combination, the photocurrent is significantly reduced, indicating that the sensor has good selectivity.

[0046] (2) Stability: After the sensor was stored at 4 °C for 7, 14 and 21 days, the HOTAIR detection signal retention rates were 96.4%, 95.8% and 95.3%, respectively; the MALAT1 detection signal retention rates were 97.7%, 98.2% and 98.0%, respectively (see Figure 15 This indicates good stability.

[0047] (3) Reproducibility: The RSDs of 10 pM HOTAIR and MALAT1 were 2.09% and 4.39% respectively for 5 independent electrodes from the same batch (see Figure 16 This indicates good reproducibility.

[0048] (4) Spike recovery rate: When different concentrations of standard were added to the human plasma sEVs lysate, the average recovery rate of HOTAIR was 98.0%-103.0%, and the average recovery rate of MALAT1 was 98.9%-104.4% (see Table 1 and Table 2), which met the requirements for biological sample detection.

[0049] Table 1. Detection of HOTAIR lncRNA in human plasma sEVs lysate samples (n=3) 36.64 <![CDATA[1×10 2 ]]> <![CDATA[1.32×10 2 ±4]]> 3.0 98.0 36.64 <![CDATA[1×10 4 ]]> <![CDATA[1.02×10 4 ±297]]> 2.9 101.3 36.64 <![CDATA[5×10 6 ]]> <![CDATA[5.15×10 6 ±2×10 5 ]]> 3.9 103.0 Table 2. Detection of MALAT1 lncRNA in human plasma sEVs lysate samples (n=3) 14.00 <![CDATA[1×10 2 ]]> <![CDATA[1.18×10 2 ±3]]> 2.5 104.4 14.00 <![CDATA[1×10 4 ]]> <![CDATA[1.00×10 4 ±338]]> 3.4 100.1 14.00 <![CDATA[5×10 6 ]]> <![CDATA[4.94×10 6 ±4×10 5 ]]> 8.0 98.9 Example 8, Analysis of actual samples: (1) Methodological comparison: The PEC method of this invention and RT-qPCR were used to detect the same batch of human plasma sEVs lysates. The results showed that the two methods had good consistency (see Figure 17 Correlation analysis (A, C) showed that r = 0.999 for HOTAIR (P < 0.001) and r = 0.997 for MALAT1 (P < 0.05) (see A, C). Figure 17 B, D).

[0050] (2) Clinical sample analysis: Plasma sEVs lysates from 40 lung cancer patients and 40 healthy controls were analyzed. Results showed (see...) Figure 18 The PEC response values ​​of HOTAIR and MALAT1 in the lung cancer group were significantly higher than those in the healthy control group (t=10.54 and 7.61, P<0.001), and the heatmap showed that the two targets were significantly heterogeneous between the lung cancer group and the healthy control group.

[0051] (3) Machine Learning-Assisted Evaluation: An evaluation model based on ANN was constructed, with input variables including HOTAIR and MALAT1 detection results and epidemiological information. Multi-model comparisons showed (see...) Figure 19 A) The ANN model achieved an accuracy of 96%, sensitivity of 91%, and specificity of 100%, outperforming the DT, SVM, LR, and RF models; the multi-parameter ANN model (dual target + epidemiological information) had the highest accuracy (96%), with an AUC value of 0.955 (95% CI: 0.950-0.970) (see [reference]). Figure 19 C) is significantly better than the single-parameter model.

[0052] In summary, this invention provides a dual lncRNA photoelectrochemical biosensor based on HCR signal amplification, its fabrication method, and its applications. This sensor achieves dual-target separation through magnetic bead-mediated HCR signal amplification and TCEP selective cleavage. It utilizes SnS2 quantum dots to quench the photocurrent signal of the Cu2O-Cu2S heterojunction photoelectrode, enabling highly sensitive joint detection of lncRNAs HOTAIR and MALAT1. Compared with existing technologies, this invention represents a significant technological advancement in detection throughput, separation strategy, signal amplification mechanism, and heterostructure design, providing a new technological platform for the early diagnosis of lung cancer.

Claims

1. A dual-lncRNA optoelectrochemical biosensor based on HCR signal amplification, characterized in that: The sensor includes a magnetic bead-nucleic acid complex, a SnS2 quantum dot-modified hairpin probe, a dual-channel photoelectrode system, and a magnetic separation-chemical cutting combined separation system. The magnetic bead-nucleic acid complex includes streptavidin magnetic beads and hairpin probes H1 and H2 immobilized thereon via biotin-streptavidin binding, wherein H1 is a biotin-modified disulfide-labeled hairpin probe and H2 is a biotin-modified hairpin probe. The SnS2 quantum dot-modified hairpin probes include H3-SnS2 and H4-SnS2, wherein H3-SnS2 and H4-SnS2 are prepared by reacting hairpin probes H3 and H4 with SnS2 quantum dots activated by EDC / NHS. The dual-channel photoelectrode system includes a Cu2S-Cu2O / ITO electrode and a Cu2O-Cu2S / ITO electrode, wherein the Cu2S-Cu2O / ITO electrode includes a Cu2S layer on the outer layer, and the Cu2O-Cu2S / ITO electrode includes a Cu2O layer on the outer layer and a magnetic tape attached to the back of the electrode. The magnetic separation-chemical cleavage combined separation system includes a TCEP processing unit and a magnetic separation unit. The TCEP processing unit selectively cleaves the disulfide bonds in H1, releasing the HCR product induced by HOTAIR into the supernatant. The magnetic separation unit separates the supernatant from the magnetic beads that retain the HCR product induced by MALAT1, thereby achieving spatial separation of the dual-target products.

2. The dual-lncRNA photoelectrochemical biosensor based on HCR signal amplification according to claim 1, characterized in that: In the Cu2S-Cu2O / ITO electrode, the Cu2S layer is located on the outer layer and is bonded to HCR products containing HOTAIR. In the Cu2O-Cu2S / ITO electrode, the Cu2O layer is located on the outer layer and is covered with magnetic tape on the back and bonded to magnetic beads containing MALAT1.

3. The dual lncRNA photoelectrochemical biosensor based on HCR signal amplification according to claim 1, characterized in that: The SnS2 quantum dots were prepared by hydrothermal reaction of SnCl4·5H2O and L-cysteine.

4. A method for preparing a dual lncRNA photoelectrochemical biosensor according to any one of claims 1 to 3, characterized in that, The method includes the following steps: (1) Hydrothermal synthesis of SnS2 quantum dots: 6.0 mmol / L SnCl4·5H2O and 20 mmol / L L-cysteine ​​were dissolved in ultrapure water, reacted at 180 °C for 6 h, purified by centrifugation and dialyzed to obtain SnS2 quantum dots; (2) Preparation of streptavidin magnetic beads: Fe3O4 nanoparticles were synthesized by solvothermal method, coated with SiO2 shell by TEOS, modified with APTES amino group, and streptavidin was fixed by crosslinking with glutaraldehyde. (3) Preparation of Cu2O-Cu2S nanomaterials and construction of dual-channel photoelectrodes: Cu2O nanomaterials were prepared by liquid-phase reduction method, and Cu2O-Cu2S nanomaterials were formed by Na2S solution treatment. They were then transferred to the surface of ITO electrode to form two configurations: Cu2S-Cu2O / ITO and Cu2O-Cu2S / ITO. (4) Preparation of SnS2 quantum dot modified hairpin probes: H3-SnS2 and H4-SnS2 were prepared by activating the carboxyl groups on the surface of SnS2 quantum dots with EDC / NHS and reacting them with hairpin probes H3 and H4. (5) Perform HCR amplification reaction: Incubate streptavidin magnetic beads with biotin-modified hairpins H1 and H2 to form a magnetic bead-nucleic acid complex. Add target lncRNA for hybridization reaction. After magnetic separation and washing, resuspend to obtain solution A. Add H3-SnS2 and H4-SnS2 to solution A, shake at 37 ℃ for 90 min for HCR amplification. After magnetic separation and washing, resuspend to obtain solution B. (6) Constructing a dual-target detection system: Add TCEP solution to solution B, and after TCEP treatment for 30 min, perform magnetic separation. Transfer the supernatant to the Cu2S-Cu2O / ITO electrode and fix the magnetic beads on the back of the Cu2O-Cu2S / ITO electrode for detection.

5. The preparation method according to claim 4, characterized in that: In step (3), the Cu2O-Cu2S nanomaterials are prepared by liquid-phase interface reaction method: Cu2O nanomaterials are dispersed in toluene, deionized water and Na2S·9H2O solution are quickly added, and the mixture is stirred gently for 2 min; in step (5), the HCR amplification reaction time is 90 min; in step (6), the TCEP treatment time is 30 min, and the TCEP concentration is 50 mM.

6. The application of the dual lncRNA photoelectrochemical biosensor according to any one of claims 1 to 3 in the detection of lncRNAs HOTAIR and MALAT1.

7. The application of the dual lncRNA photoelectrochemical biosensor according to any one of claims 1 to 3 in the early diagnosis of lung cancer, characterized in that, include: Extracellular vesicles were extracted from the sample to be tested and lysed. The sensor was used to detect the levels of lncRNA HOTAIR and MALAT1 in the lysate; The test results and the subjects' epidemiological information were input into a machine learning model based on artificial neural networks to predict lung cancer risk.

8. The application according to claim 7, characterized in that: The machine learning model uses the detection results of lncRNA HOTAIR and MALAT1, as well as age and smoking history as input variables, and outputs a prediction result of lung cancer or non-lung cancer.

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