Cyfra21-1 aptamer, screening method and application thereof
By using structure-guided mutagenesis and bioinformatics tools, CYFRA21-1 aptamers were successfully screened, solving the problems of low screening efficiency and high cost in traditional methods. This enabled efficient and low-cost CYFRA21-1 detection, which is suitable for early cancer screening and disease monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- UNIV OF SHANGHAI FOR SCI & TECH
- Filing Date
- 2026-02-11
- Publication Date
- 2026-05-29
AI Technical Summary
Existing technologies struggle to efficiently screen CYFRA21-1 aptamers with good affinity and specificity. Traditional methods are labor-intensive, costly, and limited in sequence diversity. Furthermore, they are inefficient when there is a lack of known aptamers as references.
The structure of CYFRA21-1 was predicted using alphafold3. The aptamer of the HIV-1 REV peptide was selected as a template, and an aptamer library was constructed by structure-guided directed mutagenesis. Bioinformatics tools such as AptaNet, DeepNAP, HDOCK, HADDOCK, and ZDOCK were used for pre-screening. The affinity and specificity of the aptamers were verified using the AuNPs method.
The CYFRA21-1 aptamer with good affinity and specificity was successfully screened, realizing a rapid and low-cost detection method suitable for early cancer screening and disease monitoring.
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Figure CN122104714A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of biomedical technology, and in particular relates to a CYFRA21-1 aptamer, its screening method, and its application. Background Technology
[0002] Cancer is one of the most serious threats to human health, with persistently high morbidity and mortality rates. Besides factors related to current clinical treatments, low early diagnosis rates and inadequate monitoring during disease progression are also significant factors contributing to low patient survival rates. Cytokeratin 19 fragment (CYFRA21-1), as a tumor marker, has important clinical value in the early screening, disease monitoring, and prognostic assessment of various cancers, including lung cancer, bladder cancer, colorectal cancer, and esophageal cancer. Therefore, establishing accurate and efficient CYFRA21-1 detection methods is crucial for improving the cancer diagnosis and treatment system.
[0003] Currently, clinical detection of CYFRA21-1 mainly relies on enzyme-linked immunosorbent assay (ELISA) / enzyme-linked chemiluminescence immunoassay (ELISA), which suffers from limitations such as high cost and cumbersome preparation methods for the key recognition element (antibody). In recent years, nucleic acid aptamers, as a novel recognition element, have shown great potential in the field of biosensing detection due to their combination of the high affinity and specificity of antibodies with the advantages of easy preparation and low cost. However, no aptamers for recognizing CYFRA21-1 have been reported to date.
[0004] Traditional aptamer screening methods utilize SELEX technology, which begins with an initial random library followed by repeated binding, separation, elution, and amplification steps. Finally, the enriched library is sequenced and analyzed in detail to determine the aptamer sequences. However, this screening method is labor-intensive, time-consuming, and costly. Furthermore, the limited sequence diversity of the initial library leads to insufficient exploration of the sequence space. Amplification bias in PCR amplification can also cause the loss of excellent sequences, affecting the final screening results. In recent years, with the rapid development of bioinformatics, virtual screening tools such as prediction, visualization, and energy assessment of molecular interactions have been increasingly applied to aptamer screening, significantly reducing experimental trial-and-error costs and improving screening efficiency. However, most existing studies are based on known aptamer sequences, using aptamer sequence mutation and screening to improve affinity. This strategy is clearly unsuitable for targets lacking known aptamers, such as CYFRA21-1. Therefore, how to construct effective aptamer libraries in the absence of known aptamers as references is a pressing problem to be solved in current virtual aptamer screening processes. Summary of the Invention
[0005] To address the aforementioned technical problems, this invention proposes a CYFRA21-1 aptamer, its screening method, and its applications. The CYFRA21-1 aptamer provided by this invention has good affinity and specificity and can be used as a recognition element in the fields of CYFRA21-1 detection and cancer screening.
[0006] To achieve the above objectives, the present invention provides a CYFRA21-1 aptamer, the nucleotide sequence of which is shown in SEQ ID NO.3.
[0007] The present invention also provides a method for screening the CYFRA21-1 aptamer, comprising the following steps: 1) Predict the structure of CYFRA21-1 using alphafold3; 2) Based on the structure of CYFRA21-1 obtained in step 1), the aptamer of the HIV-1 REV peptide in the PDB database was selected as the template aptamer; 3) Construct an apter library based on the template apter described in step 2); 4) Predict the binding probability and affinity between the sequence and CYFRA21-1 using AptaNet and DeepNAP programs respectively, and pre-screen the aptamer library obtained in step 3). 5) Use HDOCK to perform molecular docking of the pre-screened sequences obtained in step 4) with CYFRA21-1. Filter the top 100 sequences according to the docking scores, and then use HADDOCK and ZDOCK to perform molecular docking of the top 100 HDOCK sequences with CYFRA21-1. 6) Calculate the Z total score of the top 100 sequences in step 5) with CYFRA21-1's HDOCK, HADDOCK, and ZDOCK, and obtain the top 10 sequences; 7) Analyze the interaction forces and the number of interaction sites of the top 10 sequences obtained in step 6) using MOE and LigPLOT; 8) Perform molecular docking of the top 100 sequences obtained in step 5) with the HIV-1 REV peptide, calculate the total Z-scores of HDOCK, HADDOCK, and ZDOCK of the top 100 sequences with the HIV-1 REV peptide, and compare the total Z-scores of the top 10 sequences obtained in step 6) with the HIV-1 REV peptide. 9) Verify the affinity and specificity of the aptamer sequence selected in step 7) using the AuNPs method to obtain the CYFRA21-1 aptamer.
[0008] Preferably, the PDB database number of the HIV-1 REV peptide in step 2) is 1ULL.
[0009] Preferably, step 3) of constructing the aptamer library specifically involves: performing a traversal mutation on the loop region of the template aptamer using a base mutation program; then predicting the secondary structure of the obtained sequence using the RNAfold program and removing sequences with altered secondary structures; predicting the tertiary structure of the obtained sequence using RNAComposer; performing molecular docking between the obtained sequence and CYFRA21-1 using HDOCK; screening the top 10 candidate sequences based on docking scores; analyzing the docking posture and interaction sites using MOE and LigPlot to select preferred sequences; and finally, performing a traversal mutation on the stem region of the preferred sequences using a base mutation program to filter out sequences with altered secondary structures, thereby obtaining the aptamer library.
[0010] More preferably, the ring region of the template adapter is 6G, 7A, 28A, 29A, and 30A.
[0011] Further preferably, the stem region of the preferred sequence is 9U, 10C, 11G, 12U, 13A, 20U, 21A, 22C, 25G, and 26A.
[0012] The present invention also provides the application of the CYFRA21-1 aptamer in the preparation of products for early cancer screening, disease monitoring and prognostic assessment.
[0013] Preferably, the cancer includes one or more of lung cancer, ovarian cancer, bladder cancer, colorectal cancer, and esophageal cancer.
[0014] The present invention also provides the application of the CYFRA21-1 aptamer in screening cancer biomarkers.
[0015] Preferably, the cancer marker is CYFRA21-1.
[0016] Compared with the prior art, the present invention has the following advantages and technical effects: This invention provides a CYFRA21-1 aptamer, its screening method, and its applications. The provided CYFRA21-1 aptamer exhibits good affinity and specificity, and can be used as a novel recognition element for the detection of CYFRA21-1. The CYFRA21-1 aptamer provided by this invention can be easily obtained through currently mature chemical synthesis methods, filling a gap in CYFRA21-1 aptamer availability. This invention also innovatively proposes a structure-guided directed mutation screening method. Through template selection, directed creation of aptamer libraries, pre-screening, and screening, aptamers for CYFRA21-1 are successfully screened even in the absence of existing aptamers as references. The affinity and specificity of the aptamers are verified using AuNPs. Compared to traditional methods, the screening method of this invention quickly identifies potential aptamer structures by selecting a template, and constructs an aptamer library by directed mutation of the template under the guidance of the binding mode between the template and its target. Then, various bioinformatics tools are used to gradually narrow down the range of candidate aptamer sequences. The proposed screening method and its application are expected to provide a reference for the research and development of aptamers, especially for targets for which aptamers have not yet been reported. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a schematic diagram of the structure of CYFRA21-1; Figure 2 For Z total Interaction analysis diagram of the top ten sequences with CYFRA21-1, where a is the interaction force analysis and b is the number of sites contributing to the interaction analysis; Figure 3 The Z-scores for the top ten sequences are for CYFRA21-1 and for the HIV-1 REV peptide. Figure 4 The mass spectra of aptamers M2.96 and M2.963 are shown, where a is aptamer M2.96 and b is aptamer M2.963. Figure 5The figures show the aggregation state and affinity fitting results of AuNPs under different CYFRA21-1 concentrations. In the figures, a represents the aggregation state of AuNPs under different CYFRA21-1 concentrations of aptamer M2.96, b represents the aggregation state of AuNPs under different CYFRA21-1 concentrations of aptamer M2.963, c represents the affinity fitting result of aptamer M2.96, and d represents the affinity fitting result of aptamer M2.963. R1, R2, and R3 in the figures represent three replicates. Figure 6 This is a specificity test diagram for aptamer M2.96. Detailed Implementation
[0019] Various exemplary embodiments of the present invention are now described in detail. This detailed description should not be considered as a limitation of the invention, but rather as a more detailed description of certain aspects, features, and embodiments of the invention. It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. The specification and embodiments of this invention are merely exemplary.
[0020] The materials and instruments used in this invention are tetrachloroauric acid (HAuCl4, Sinopharm, catalog number 10010711), sodium citrate dihydrate (Sigma, catalog number V900095), sodium chloride (Greagent, catalog number G81793J), CYFRA21-1 (Shanghai Lingchao, catalog number L2C00802), CEA (Shanghai Lingchao, catalog number L2C01001), 10×PBS (Thermo Fisher Scientific, catalog number AM9625), DEPC water (Sangon Biotech, catalog number B501005), and a multi-functional plate reader (Shanghai Bai'aojie Biotechnology Co., Ltd., equipment model: Synergy H1).
[0021] Example 1 I. Screening for CYFRA21-1 aptamers.
[0022] 1. Predicting the structure of CYFRA21-1 using Alphafold3: The results are as follows Figure 1 As shown, CYFRA21-1 exhibits an α-helical structure.
[0023] 2. Using the aptamer of HIV-1 REV peptide (PDB:1ULL) in the PDB database as the template aptamer, and named it M0, its nucleotide sequence is shown in SEQ ID NO.1.
[0024] SEQ ID NO. 1: GGCUGGACUCGUACUUCGGUACUGGAGAAACAGCC.
[0025] The PDB database contained 141 protein-aptamer pairs. Considering that the binding of aptamers to target proteins is highly dependent on the conformational fit between them, complexes with target protein structures primarily consisting of α-helices were screened to provide a reference for subsequent aptamer template design. Following the above screening criteria, two suitable complexes were obtained, with PDB numbers 1ULL and 6CF2. Further investigation revealed that their aptamer sequences were completely identical; the target protein in 1ULL.pdb was part of 6CF2.pdb, and the main binding regions of the aptamer in 6CF2.pdb were all contained within 1ULL.pdb. Therefore, the target protein (HIV-1 REV peptide) in 1ULL.pdb was compared with CYFRA21-1. The alignment results showed a root mean square deviation (RMSD) of 1.702 Å, indicating good overlap between the two. Therefore, the aptamer in 1ULL.pdb was selected as the template aptamer.
[0026] 3. Constructing an adapter library: (1) The loop regions (6G, 7A, 28A, 29A, 30A) of the template aptamer were mutated in a traversal manner to obtain 1024 sequences. Then, the secondary structure of the 1024 sequences was predicted using the RNAfold server (http: / / rna.tbi.univie.ac.at / cgi-bin / RNAWebSuite / RNAfold.cgi). Sequences whose secondary structure was changed after mutation were removed, and finally 257 one-round mutation sequences were obtained, which were named M1.1~M1.257.
[0027] (2) The tertiary structures of RNA were generated in batches using the RNAComposer server (https: / / rnacomposer.cs.put.poznan.pl / ). Subsequently, the energy of the resulting mutant sequences and the structure of CYFRA21-1 was minimized using MOE.
[0028] (3) Molecular docking of M1.1~M1.257 after step (2) with CYFRA21-1 was performed using the HDOCK online website (http: / / hdock.phys.hust.edu.cn / ). The top 10 sequences were sorted by docking score. The docking conformation and interaction sites were analyzed using MOE to determine that the M1.44 sequence was the preferred sequence for a first-round mutation, and its nucleotide sequence is shown in SEQ ID NO.2.
[0029] SEQ ID NO. 2: GGCUGACCUCGUACUUCGGUACUGGAGAUGCAGCC.
[0030] (4) The stem region (9U, 10C, 11G, 12U, 13A, 20U, 21A, 22C, 25G, 26A) of the M1.44 sequence was subjected to traversal mutations to obtain 1,048,576 sequences. As in step (1), sequences with changes in secondary structure were filtered out, and 1,154 sequences were obtained as aptamer libraries, named M2.1~M2.1154.
[0031] 4. The AptaNet interaction model (https: / / github.com / nedaemami / AptaNet) was used to predict the binding probability between the obtained sequences and CYFRA21-1. AptaNet was used to predict the binding probability, and sequences with a binding probability greater than 0.5 were classified as "positive". Sequences predicted as "positive" were selected and their affinity (Kd) with CYFRA21-1 was predicted using the DeepNAP model (https: / / github.com / StructuralBiologyLabIISERTirupati / DeePNAPWebsite). The smaller the Kd, the higher the affinity. Since the second round of mutations was performed based on M1.44, the Kd of M1.44 was used as a threshold to filter out sequences with Kd less than that of M1.44, totaling 527 sequences.
[0032] 5. Following steps (2) and (3) in step 3, perform HDOCK docking on the 527 sequences and sort them based on the docking scores to select the top 100 sequences. To avoid bias from a single docking tool, HADDOCK and ZDOCK were then used to simulate docking on the resulting 100 sequences.
[0033] Considering that different docking methods have their own independent scoring systems, to improve the accuracy and reliability of the evaluation, the three docking results of these 100 sequences were standardized. The standardization method used was the Z-test: Z = (E - Ē) / δ, where E is the docking score, Ē is the mean of the docking scores of these 100 sequences and CYFRA21-1, and δ represents the standard deviation. It is important to note that under the HDOCK and HADDOCK scoring systems, a more negative docking score indicates higher affinity. However, under the ZDOCK scoring system, a higher docking score indicates better affinity. To eliminate this difference, the docking scores obtained from ZDOCK were uniformly negative. The total Z-score for each sequence is the sum of the Z-values obtained from the three docking results. total =Z HOCK +Z HADDOCK +Z ZDOCK Among them, Z HOCK Z HADDOCK and Z ZDOCKThese represent the Z-values of the docking results for HDOCK, HADDOCK, and ZDOCK, respectively. (Press Z...) total The values are sorted from smallest to largest, and the top 10 are selected as the TOP10 sequence.
[0034] 6. To further screen the candidate TOP10 sequences for aptamers with the best CYFRA21-1 binding potential, the HDOCK docking conformation and interaction modes (such as hydrogen bonding, van der Waals forces, electrostatic interactions, hydrophobic interactions, and π-π stacking interactions) of the TOP10 sequences with CYFRA21-1 were analyzed using MOE and LigPLOT software systems. Based on this, the number of sites contributing to the interaction was further quantified and statistically analyzed, including the number of nucleotides involved in binding at the aptamer end and the number of amino acid residues involved in binding at the CYFRA21-1 end.
[0035] like Figure 2 As shown in Figure b, M2.96 (SEQ ID NO.3) ranks first in both the number of key nucleotides at the aptamer end and the number of key amino acid residues at the target end, followed by M2.963 (SEQ ID NO.4). Furthermore, compared to other candidate sequences, the binding of both sequences to CYFRA21-1 is primarily through hydrogen bonds, van der Waals forces, and hydrophobic interactions, with electrostatic interactions also playing a role. Figure 2 (a) These forces are generally considered to be key forces mediating the specific recognition of aptamers and targets. Therefore, M2.96 and M2.963 were subsequently selected for experimental verification, and their nucleotide sequences are shown in SEQ ID NO.3 and SEQ ID NO.4, respectively.
[0036] SEQ ID NO. 3: GGCUGACCUCAGUCUUCGGACUUGGAGAUGCAGCC.
[0037] SEQ ID NO. 4: GGCUGACCGCAGCCUUCGGGCUUGGCGAUGCAGCC.
[0038] 7. To assess the targeting specificity of the top 10 sequences, the corresponding Z-score was calculated by docking with the template protein (i.e., the HIV-1 REV peptide) and compared with the Z-score obtained from docking with CYFRA21-1. Figure 3As shown, the top 10 sequences obtained had relatively lower Z-scores. For example, the Z-score for M2.963 and CYFRA21-1 was -5.37, while the Z-score for M2.963 and HIV-1 Rev peptide was -3.50. This indicates that although the designed method uses the aptamer of HIV-1 Rev peptide as the original template, after structure-guided directed mutagenesis, the resulting aptamers can selectively distinguish between CYFRA21-1 and HIV-1 Rev peptide.
[0039] II. The selected aptamers were prepared using the phosphate amide ester method.
[0040] M2.96 and M2.963 were synthesized by Sangon Biotech (Shanghai) Co., Ltd., and their nucleotide sequences are shown in SEQ ID NO.3 and SEQ ID NO.4, respectively.
[0041] The quality of the synthesized RNA aptamers was verified using a linear quadrupole ion trap (LTQ) liquid chromatography-mass spectrometry (LC-MS / MS). The results are as follows: Figure 4 a and Figure 4 As shown in Figure b, the mass spectrum displays only one sharp and symmetrical main peak, with no obvious impurity peaks. Furthermore, the deviation between the measured main peak mass and the theoretical molecular weight shown in the mass spectrum is ≤ ±0.3%, further verifying the successful synthesis of the M2.96 and M2.963 aptamers.
[0042] III. Verification of the binding performance of the CYFRA21-1 aptamer.
[0043] The affinity and specificity of the obtained aptamers for CYFRA21-1 were verified using an AuNP aggregation / dispersion strategy, and the specific steps are as follows: 1. Synthesis of AuNPs: AuNPs were synthesized using the classic sodium citrate reduction method. 4.1 mL of HAuCl4 (1%) was diluted to 100 mL with ultrapure water and boiled for 30 min. Then, 10 mL of 38.8 mM sodium citrate solution was rapidly added. The solution was observed to gradually change from pale yellow to black, and when it turned wine red, the heating device was removed. Stirring continued until cooled to room temperature. The resulting solution was filtered through a 0.22 μm filter membrane to remove aggregated particles. The resulting AuNPs solution was transferred to a brown glass bottle and stored at 4°C protected from light.
[0044] 2. Affinity test: The aptamer powder was dissolved in DEPC water to a concentration of 100 μM. Before the experiment, the aptamer solution was annealed, i.e., incubated at 90 °C for 10 min to fully open the interchain structure, and then slowly cooled to form a specific secondary structure.
[0045] In a 96-well plate, 5 μL of aptamer solution (6 μM) and 80 μL of AuNPs solution were incubated at room temperature for 1 h. Then, 5 μL of CYFRA21-1 at different concentrations were added, and incubation was continued at room temperature for 30 min. Subsequently, 10 μL of NaCl solution (250 mM) was added, and incubation was continued for 30 min. The absorbance at 520 nm and 620 nm was read using a microplate reader, and the aggregation ratio (Ag) was calculated. 620 / A 520 The data was analyzed using Origin software.
[0046] like Figure 5 a and Figure 5 As shown in Figure b, with increasing CYFRA21-1 concentration, AuNPs gradually changed from red to dark purple. This is because as the concentration of CYFRA21-1 in the system increases, more aptamers bind to it, resulting in fewer aptamers on the surface of AuNPs, thus reducing the protective ability against AuNPs. Figure 5 c and Figure 5 As shown in d, by the aggregation ratio of AuNPs (A 620 / A 520 Nonlinear fitting was performed between M2.96 and the concentration of CYFRA21-1, and the calculated affinity was found to be optimal (Kd = 7.39 ng / mL), followed by M2.963 (Kd = 11.12 ng / mL). Therefore, M2.96 was determined to be the final CYFRA21-1 aptamer selected.
[0047] 3. Specificity test: The aptamer with the best affinity (M2.96) was selected for specificity experiments. The aggregation ratio of 40 ng / mL CYFRA21-1 and CEA was determined according to the method in step 2, while the control group was replaced with an equal volume of PBS.
[0048] The results are as follows Figure 6 As shown, a significant increase in aggregation ratio was only observed in the presence of CYFRA21-1. The signal response to CEA was similar to that of the blank control group, indicating that M2.96 has good specificity and can distinguish CYFRA21-1 from other non-target proteins.
[0049] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.
Claims
1. A CYFRA21-1 aptamer, characterized in that, The nucleotide sequence of the CYFRA21-1 aptamer is shown in SEQ ID NO.
3.
2. The screening method for CYFRA21-1 aptamers as described in claim 1, characterized in that, Includes the following steps: 1) Predict the structure of CYFRA21-1 using alphafold3; 2) Based on the structure of CYFRA21-1 obtained in step 1), the aptamer of the HIV-1 REV peptide in the PDB database was selected as the template aptamer; 3) Construct an apter library based on the template apter described in step 2); 4) Predict the binding probability and affinity between the sequence and CYFRA21-1 using AptaNet and DeepNAP programs respectively, and pre-screen the aptamer library obtained in step 3). 5) Use HDOCK to perform molecular docking of the pre-screened sequences obtained in step 4) with CYFRA21-1. Filter the top 100 sequences according to the docking scores, and then use HADDOCK and ZDOCK to perform molecular docking of the top 100 HDOCK sequences with CYFRA21-1. 6) Calculate the Z total score of the top 100 sequences in step 5) with CYFRA21-1's HDOCK, HADDOCK, and ZDOCK, and obtain the top 10 sequences; 7) Analyze the interaction forces and the number of interaction sites of the top 10 sequences obtained in step 6) using MOE and LigPLOT; 8) Perform molecular docking of the top 100 sequences obtained in step 5) with the HIV-1 REV peptide, calculate the total Z-scores of HDOCK, HADDOCK, and ZDOCK of the top 100 sequences with the HIV-1 REV peptide, and compare the total Z-scores of the top 10 sequences obtained in step 6) with the HIV-1 REV peptide. 9) Verify the affinity and specificity of the aptamer sequence selected in step 7) using the AuNPs method to obtain the CYFRA21-1 aptamer.
3. The screening method according to claim 2, characterized in that, The HIV-1 REV peptide mentioned in step 2) has a PDB database number of 1ULL.
4. The screening method according to claim 2, characterized in that, Step 3) involves constructing the aptamer library as follows: The loop region of the template aptamer is subjected to traversal mutations using a base mutation program; the secondary structure of the obtained sequence is predicted using the RNAfold program, and sequences with altered secondary structures are removed; the tertiary structure of the obtained sequence is predicted using RNAComposer; the obtained sequence is molecularly docked with CYFRA21-1 using HDOCK, and the top 10 candidate sequences with the highest docking scores are selected; MOE and LigPlot are used to analyze the docking posture and interaction sites, and preferred sequences are selected; the stem region of the preferred sequences is subjected to traversal mutations using a base mutation program, and sequences with altered secondary structures are filtered out to obtain the aptamer library.
5. The screening method according to claim 4, characterized in that, The ring regions of the template adapter are 6G, 7A, 28A, 29A, and 30A.
6. The screening method according to claim 4, characterized in that, The preferred sequences have stem regions of 9U, 10C, 11G, 12U, 13A, 20U, 21A, 22C, 25G, and 26A.
7. The use of the CYFRA21-1 aptamer as described in claim 1 in the preparation of products for early cancer screening, disease monitoring, and prognostic assessment.
8. The application according to claim 7, characterized in that, The cancers mentioned include one or more of the following: lung cancer, ovarian cancer, bladder cancer, colorectal cancer, and esophageal cancer.
9. The application of the CYFRA21-1 aptamer as described in claim 1 in the detection of cancer biomarkers.
10. The application according to claim 9, characterized in that, The cancer biomarker is CYFRA21-1.