Application of biomarkers in predicting restenosis after carotid endarterectomy

Abstract

The application provides application of a biomarker in prediction of restenosis after carotid endarterectomy, and belongs to the field of biotechnology. It is found for the first time that the expression level of CCL-8 in perivascular adipose tissue can be used for prediction of restenosis after carotid endarterectomy, and the expression level of CCL-8 in the perivascular adipose tissue has good efficiency in prediction of restenosis after carotid endarterectomy, which is verified by real clinical samples collected by the application.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of biotechnology, and particularly relates to application of a biomarker in predicting restenosis after carotid endarterectomy. BACKGROUND

[0002] Carotid atherosclerosis is one of the main causes of ischemic stroke, and 15% to 20% of patients with 50% or more severe carotid stenosis will develop ischemic stroke or transient ischemic attack. Carotid endarterectomy (CEA) is an effective method for preventing the occurrence of ischemic stroke. However, 8% to 30% of patients experience restenosis after CEA, and there is currently a lack of biomarkers that can effectively predict restenosis. SUMMARY

[0003] In view of this, in order to make up for the shortcomings of the prior art, the present application is proposed.

[0004] The first aspect of the present application provides the use of a reagent for detecting the expression level of CCL-8 in perivascular adipose tissue in a test sample in the preparation of a product for predicting restenosis after carotid endarterectomy.

[0005] In the present application, the perivascular adipose tissue (PVAT) is defined as adipose tissue within an equal distance from the lumen diameter of the blood vessel. This definition is applicable to any artery with a lumen diameter < 2 cm, while for arteries with a lumen diameter > 2 cm, PVAT is conventionally defined as adipose tissue within a range of 2 cm from the outer wall of the blood vessel.

[0006] In some embodiments, the PVAT is carotid PVAT. The carotid lumen diameter is generally < 8 mm, so the carotid PVAT can be defined as adipose tissue within an equal distance from the lumen diameter around the carotid artery.

[0007] In some embodiments, the PVAT is the PVAT removed during carotid endarterectomy.

[0008] In the present application, the CCL-8 includes wild type, mutant or fragment thereof. This term encompasses full-length, unprocessed CCL-8, as well as any form of CCL-8 derived by processing in the cell. This term encompasses naturally occurring variants of CCL-8, e.g. splice variants or allelic variants. This term encompasses, for example, the CCL-8 gene, human CCL-8, as well as CCL-8 from any other vertebrate source, including mammals such as primates and rodents (e.g. mice and rats). As a preferred embodiment, in the present application, the CCL-8 is human CCL-8 gene or its encoded protein, Gene ID: 6355.

[0009] In the present application, "expression level" refers to the amount, accumulation or rate of CCL-8 molecules or genome. The expression level can be represented, for example, by the amount or synthesis rate of messenger RNA (mRNA) encoded by the gene, the amount or synthesis rate of polypeptide or protein encoded by the gene, or the amount or synthesis rate of biological molecules accumulated in the cell or biological fluid. The term "expression level" refers to the absolute amount of molecules in the sample or the relative amount of molecules determined under steady state or non-steady state conditions.

[0010] In the present application, the expression level of CCL-8 in the perivascular adipose tissue refers to the expression level of CCL-8 in the specific tissue of perivascular adipose tissue.

[0011] In some embodiments, if the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested is higher than the threshold value, the sample to be tested has a high risk of restenosis after carotid endarterectomy, and if the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested is lower than the threshold value, the sample to be tested has a low risk of restenosis after carotid endarterectomy.

[0012] In the present application, the threshold value is an exemplary threshold value.

[0013] In some embodiments, the threshold value is 2.56 pg / mL.

[0014] In some embodiments, the reagent is selected from an oligonucleotide probe specifically recognizing the CCL-8 gene, a primer specifically amplifying the CCL-8 gene or a binding agent specifically binding to the protein encoded by the CCL-8 gene.

[0015] In the present application, the term "probe" refers to a molecule that is capable of binding to a particular sequence or subsequence or other portion of another molecule. Unless otherwise indicated, the term "probe" generally refers to a polynucleotide probe that is capable of binding to another polynucleotide (often referred to as a "target polynucleotide") by complementary base pairing. Depending on the stringency of the hybridization conditions, the probe can bind to a target polynucleotide that lacks perfect sequence complementarity to the probe. The probe can be directly or indirectly labeled. Hybridization formats include, but are not limited to, solution phase, solid phase, mixed phase, or in situ hybridization assays.

[0016] In the present application, the term "primer" refers to an oligonucleotide that is capable of specifically annealing to a site on a RNA or DNA region adjacent to a target sequence and serving as a point of initiation of synthesis of DNA under suitable conditions in which synthesis of a primer extension product is induced. PCR reactions typically employ a pair of amplification primers, also referred to as a "primer pair," including an "upstream" or "forward" primer and a "downstream" or "reverse" primer, which define a region of RNA or DNA to be amplified.

[0017] In the present application, the term "amplification" refers to a process for replicating a portion of a nucleic acid using, for example, any of a variety of primer extension reactions. Exemplary primer extension reactions include, but are not limited to, PCR. Unless otherwise specified, "amplification" refers to single replication, or arithmetic, logarithmic, or exponential amplification.

[0018] In the present application, the term "binding agent" refers to a substance that is capable of binding to all or a portion of a protein molecule. Binding agents can be, for example, receptors for the protein, lectins that bind the protein, antibodies directed against the protein, and in some cases, binding agents can be bispecific dual binding agents, such as bispecific antibody formats.

[0019] In some embodiments, the reagent further comprises a detectable label.

[0020] In some embodiments, the label is any composition capable of being detected by an apparatus or method, including but not limited to spectroscopic, photochemical, biochemical, immunochemical, electrical, optical, chemical detection apparatus, or any other suitable apparatus. In some embodiments, the label can be detected visually without the aid of an apparatus.

[0021] In some embodiments, the detectable label includes, but is not limited to, DNA barcodes, radioisotopes, nucleotide chromophores, enzymes, substrates, fluorescent molecules, chemiluminescent moieties, magnetic particles, bioluminescent moieties.

[0022] In the present application, radioisotopes include, but are not limited to 3 H, 14 C, 35 S, 125 I, 131I. Enzymes include, but are not limited to, horseradish peroxidase, beta-galactosidase, luciferase, alkaline phosphatase, acetylcholinesterase. Fluorescent molecules include, but are not limited to, FITC, rhodamine, lanthanide phosphors.

[0023] The products of the present application can be provided in any form, including but not limited to a chip, a kit, a test paper, or a nucleic acid membrane strip.

[0024] In the present application, the term "chip" is also referred to as "array", which refers to a solid support comprising linked nucleic acid or peptide probes. The array typically comprises a plurality of different nucleic acid or peptide probes linked to the surface of a substrate at different known locations. These arrays, also referred to as "microarrays", can typically be produced using mechanical synthesis methods or light-directed synthesis methods, which incorporate a combination of photolithographic methods and solid-phase synthesis methods. The array can comprise a flat surface, or can be nucleic acids or peptides on beads, gels, polymeric surfaces, fibers such as optical fibers, glass, or any other suitable substrate. The array can be packaged in a manner that allows for use in a fully functional device.

[0025] In some embodiments, the chip comprises a gene chip, a protein chip.

[0026] In some embodiments, the gene chip comprises oligonucleotide probes that specifically recognize CCL-8 gene for detecting the transcription level of CCL-8 gene.

[0027] In some embodiments, the protein chip comprises binding agents that specifically bind to the protein encoded by CCL-8 gene.

[0028] In the present application, the term "nucleic acid membrane strip" comprises a substrate and oligonucleotide probes immobilized on the substrate; the substrate can be any substrate suitable for immobilizing oligonucleotide probes, such as nylon membrane, nitrocellulose membrane, polypropylene membrane, glass sheet, silica gel wafer, microscale magnetic beads, etc.

[0029] In the present application, the term "kit" refers to any delivery system for delivering materials, including kits for research and clinical applications.

[0030] In some embodiments, the kit comprises a gene detection kit, a protein detection kit.

[0031] In some embodiments, the gene detection kit comprises reagents for detecting the transcription level of CCL-8 gene.

[0032] In some embodiments, the gene detection kit comprises, but is not limited to, a qPCR kit.

[0033] In some embodiments, the protein detection kit comprises reagents for detecting CCL-8 protein expression level.

[0034] In some embodiments, the protein detection kit comprises, but is not limited to, Abseq protein detection kit, immunoblot detection kit, immunochromatographic detection kit, flow cytometry kit, immunohistochemistry detection kit, ELISA kit, electrochemiluminescence detection kit.

[0035] In some embodiments, the kit further comprises reagents for lysing PVAT.

[0036] In some embodiments, the reagents for lysing PVAT comprise reagents for lysing fat.

[0037] In some embodiments, the kit further comprises, but is not limited to, containers, instructions for use, positive controls, negative controls, buffers, solvents, preservatives, or protein stabilizers. Components of a kit can be packaged in an aqueous medium or in a lyophilized form. Suitable containers for the kit generally include at least one vial, test tube, flask, bottle, syringe or other container, into which a component can be placed, and preferably, suitably aliquoted. Where there is more than one component in the kit, the kit can also contain a second, third or other additional containers into which separate components can be separately placed. Yet, different combinations of components can be contained in one vial. The kit of the present application will also typically include a container into which the reagents can be contained, sealed for commercial sale. Such container can include a molded or blown plastic container, into which the desired vials can be retained.

[0038] In other embodiments, the products of the present application comprise, but are not limited to, computer systems, apparatus, devices, readable storage media, program products.

[0039] The computer systems, apparatus, devices, readable storage media, program products comprise a processing unit, which obtains a prediction result of restenosis after carotid endarterectomy according to the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested. If the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested is higher than the threshold value, the risk of restenosis after carotid endarterectomy of the sample to be tested is high. If the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested is lower than the threshold value, the risk of restenosis after carotid endarterectomy of the sample to be tested is low.

[0040] In the present application, the computer system, device, apparatus, readable storage medium are a method for distinguishing different components, elements, parts, portions or assemblies of different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions. Those skilled in the art of the technical field to which the present application pertains are familiar that the present application can be implemented as a computer system, device, apparatus, readable storage medium, program product. Therefore, the present application can be embodied in the form of a complete hardware, a complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. In addition, in some specific embodiments, the present application can also be implemented in the form of a computer program product in one or more computer readable media, which contains computer readable program code.

[0041] In other embodiments, the product of the present application comprises a prediction model. The CCL-8 expression level data in the perivascular adipose tissue of the sample to be tested can be input into the prediction model, which predicts the risk of restenosis after carotid endarterectomy of the sample to be tested based on the CCL-8 expression level data in the perivascular adipose tissue of the sample to be tested.

[0042] In some embodiments, the model is constructed using machine learning methods, and the algorithms used include but are not limited to: support vector machine, linear discriminant analysis, recursive feature elimination, logistic regression, classification and regression tree (CART), least absolute shrinkage and selection operator (LARS), random forest, multiple additive regression tree (MART), and other machine learning algorithms or combinations thereof.

[0043] The second aspect of the present application provides a product for predicting restenosis after carotid endarterectomy, which comprises a reagent for lysing the perivascular adipose tissue of the sample to be tested and a reagent for detecting the expression level of CCL-8 in the lysed perivascular adipose tissue of the sample to be tested.

[0044] In some embodiments, the reagent for lysing the perivascular adipose tissue of the sample to be tested comprises a reagent for lysing adipose tissue.

[0045] The reagent for detecting the expression level of CCL-8 in the lysed perivascular adipose tissue of the sample to be tested is explained in the first aspect of the present application. In general, the reagent for detecting the expression level of CCL-8 in the lysed perivascular adipose tissue of the sample to be tested includes but is not limited to an oligonucleotide probe that specifically recognizes the CCL-8 gene, a primer that specifically amplifies the CCL-8 gene, or a binding agent that specifically binds to the protein encoded by the CCL-8 gene.

[0046] In some embodiments, the reagent for detecting the expression level of CCL-8 in the perivascular adipose tissue of the lysed sample of the test sample further comprises a detectable label.

[0047] In some embodiments, the detectable label comprises, but is not limited to, a DNA barcode, a radioisotope, a nucleotide chromophore, an enzyme, a substrate, a fluorescent molecule, a chemiluminescent moiety, a magnetic particle, a bioluminescent moiety.

[0048] The products of the present application can be provided in any form, including but not limited to a kit.

[0049] In some embodiments, the kit comprises both a reagent for lysing the perivascular adipose tissue of the test sample and a reagent for detecting the expression level of CCL-8 in the lysed perivascular adipose tissue of the test sample.

[0050] In some embodiments, the kit comprises a genetic detection kit, a protein detection kit.

[0051] In some embodiments, the genetic detection kit comprises a reagent for detecting the transcription level of CCL-8 gene.

[0052] In some embodiments, the genetic detection kit comprises, but is not limited to, a qPCR kit.

[0053] In some embodiments, the protein detection kit comprises a reagent for detecting the expression level of CCL-8 protein.

[0054] In some embodiments, the protein detection kit comprises, but is not limited to, an Abseq protein detection kit, an immunoblotting detection kit, an immunochromatography detection kit, a flow cytometry analysis kit, an immunohistochemistry detection kit, an ELISA kit, an electrochemiluminescence detection kit.

[0055] In other embodiments, the products comprise a combination of kits and other forms of products.

[0056] In other embodiments, the products are a combination of a kit and a chip, the kit comprising a reagent for lysing the perivascular adipose tissue of the test sample, and the chip being used for detecting the expression level of CCL-8 in the lysed perivascular adipose tissue of the test sample.

[0057] In some embodiments, the chip comprises a genetic chip, a protein chip.

[0058] In some embodiments, the genetic chip comprises an oligonucleotide probe specifically recognizing CCL-8 gene for detecting the transcription level of CCL-8 gene.

[0059] In some embodiments, the protein chip comprises a binding agent that specifically binds to a protein encoded by the CCL-8 gene.

[0060] In some embodiments, the product is a combination of a kit and a test paper, wherein the kit comprises reagents for lysing perivascular adipose tissue of a sample to be tested, and the test paper is used to detect the expression level of CCL-8 in the lysed perivascular adipose tissue of the sample to be tested.

[0061] In some embodiments, the product is a combination of a kit and a nucleic acid strip, wherein the kit comprises reagents for lysing perivascular adipose tissue of a sample to be tested, and the nucleic acid strip is used to detect the expression level of CCL-8 in the lysed perivascular adipose tissue of the sample to be tested.

[0062] In some embodiments, the kit further comprises, but is not limited to, a container, an instruction manual, a positive control, a negative control, a buffer, a solvent, a preservative, or a protein stabilizer. The components of the kit can be packaged in an aqueous medium or in a lyophilized form. The appropriate container in the kit will generally include at least one vial, test tube, flask, bottle, syringe or other container, into which a component can be placed, and, preferably, suitably aliquoted. Where more than one component is present in the kit, the kit will also contain a second, third, or additional containers to separately hold each of the additional components. However, different combinations of components can be contained in a single vial. The kit of the present application will also typically include a container into which the reagents can be contained, sealed for commercial sale. Such container can include a molded or blown plastic container, into which the desired vials can be retained.

[0063] The third aspect of the present application provides a product for predicting restenosis after carotid endarterectomy, wherein the product comprises a processing unit, which obtains a prediction result of restenosis after carotid endarterectomy of a sample to be tested according to the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested.

[0064] In some embodiments, if the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested is higher than a threshold value, the risk of restenosis after carotid endarterectomy is high, and if the expression level of CCL-8 in the perivascular adipose tissue of the sample to be tested is lower than a threshold value, the risk of restenosis after carotid endarterectomy is low.

[0065] In some embodiments, the product of the present application comprises, but is not limited to, a computer system, device, apparatus, readable storage medium, program product.

[0066] In the present application, the computer system, device, equipment, readable storage medium, program product are used to distinguish different components, elements, parts or assemblies of different levels. If other words can achieve the same purpose, the words can be replaced by other expressions. Those skilled in the art of the technical field to which the present application belongs are familiar that the present application can be implemented as a computer system, device, equipment, readable storage medium, program product. Therefore, the present application can be embodied in the form of entirely hardware, entirely software or a combination of hardware and software. In addition, in some specific embodiments, the present application can also be implemented in the form of a computer program product in one or more computer readable storage media, which contains computer readable program code.

[0067] In other embodiments, the product of the present application comprises a prediction model. The CCL-8 expression level data in the perivascular adipose tissue of the test sample can be input into the prediction model, which predicts the risk of restenosis after carotid endarterectomy of the test sample based on the CCL-8 expression level data in the perivascular adipose tissue of the test sample.

[0068] In some embodiments, the model is constructed using machine learning methods, and the algorithms used include but are not limited to: support vector machine, linear discriminant analysis, recursive feature elimination, logistic regression, classification and regression tree (CART), least absolute shrinkage and selection operator (LARS), random forest, multiple additive regression tree (MART), and other machine learning algorithms or combinations thereof.

[0069] The present application also provides a method for predicting restenosis after carotid endarterectomy, comprising the following steps:

[0070] detecting the expression level of CCL-8 in the perivascular adipose tissue of the test sample;

[0071] predicting the risk of restenosis after carotid endarterectomy of the subject according to the detected expression level of CCL-8 in the perivascular adipose tissue of the test sample, if the expression level of CCL-8 in the perivascular adipose tissue of the test sample is higher than the threshold, the risk of restenosis after carotid endarterectomy is high, if the expression level of CCL-8 in the perivascular adipose tissue of the test sample is lower than the threshold, the risk of restenosis after carotid endarterectomy is low.

[0072] The present application has the advantages and beneficial effects:

[0073] The application provides application of a biomarker in predicting restenosis after carotid endarterectomy, and belongs to the technical field of biotechnology. BRIEF DESCRIPTION OF DRAWINGS

[0074] Figure 1 is a PVAT CCL-1 restenosis and non-restenosis group difference result graph;

[0075] Figure 2 is a PVAT CCL-5 restenosis and non-restenosis group difference result graph;

[0076] Figure 3 is a PVAT CCL-8 restenosis and non-restenosis group difference result graph;

[0077] Figure 4 is a PVAT CXCL-16 restenosis and non-restenosis group difference result graph;

[0078] Figure 5 is a PVAT EGF restenosis and non-restenosis group difference result graph;

[0079] Figure 6 is a PVAT GM-CSF restenosis and non-restenosis group difference result graph;

[0080] Figure 7 is a PVAT IFN-γ restenosis and non-restenosis group difference result graph;

[0081] Figure 8 is a PVAT IL-1β restenosis and non-restenosis group difference result graph;

[0082] Figure 9 is a PVAT IL-2 restenosis and non-restenosis group difference result graph;

[0083] Figure 10 is a PVAT IL-4 restenosis and non-restenosis group difference result graph;

[0084] Figure 11 is a PVAT IL-10 restenosis and non-restenosis group difference result graph;

[0085] Figure 12 is a PVAT IL-17 restenosis and non-restenosis group difference result graph;

[0086] Figure 13Figure 2 is a PVAT TGF-β3 restenosis versus non-restenosis group difference results plot.

[0087] Figure 14 Figure 3 is a PVAT TNF-α restenosis versus non-restenosis group difference results plot.

[0088] Figure 15 Figure 4 is a PVAT TNF-β restenosis versus non-restenosis group difference results plot.

[0089] Figure 16 Figure 5 is a PVAT CCL-8 ROC curve for predicting restenosis. DETAILED DESCRIPTION

[0090] The present application is further described in connection with the following examples, which are not intended to limit the application in any way. Any modification or equivalent arrangement made by any person skilled in the art using the teachings of the present application shall be considered to fall within the scope of the present application.

[0091] EXAMPLE

[0092] 1. Experimental materials

[0093] Quantibody Human Angiogenesis array 1000 (RayBiotech, QAH-ANG-1000)

[0094] Laser scanner (InnoScan 300 microarray scanner)

[0095] 2. Experimental methods

[0096] PVAT tissue was collected from the carotid sheath of the surgical artery during CEA surgery, and PVAT samples were lysed using a kit (Quantibody Human Angiogenesis Array 1000, RayBiotech, QAH-ANG-1000) and then centrifuged to collect the supernatant. After dilution, the PVAT sample concentration was 500 μg / mL, and a multiplex sandwich ELISA quantitative array was used to measure inflammatory protein markers, and the fluorescence signal was detected by a laser scanner with a wavelength of 532 nm. Restenosis was defined as at least 50% stenosis of the CEA surgical artery within 1 year after surgery.

[0097] Differences in PVAT inflammatory protein markers between the restenosis group and the non-restenosis group were compared using the Mann-Whitney U test, and the correlation between restenosis and PVAT attenuation was evaluated using univariate and multivariate binary logistic regression analysis, and the correlation was described using the odds ratio (OR) of the 95% confidence interval (95% CI).

[0098] 3. Experimental results

[0099] Patients with restenosis and patients without restenosis were detected for PVAT protein markers. It was observed that there were statistically significant differences in CCL-1, CCL-5, CCL-8, CXCL-16, EGF, GM-CSF, IFN-γ, IL-1β, IL-2, IL-4, IL-10, IL-17, TGF-β3, TNF-α, and TNF-β among the 15 PVAT protein markers in patients with restenosis and patients without restenosis (see Table 2). Figures 1-15 ).

[0100] Further evaluation of the predictive value of CCL-8, GM-CSF, IL-2, IL-4, TGF-β3, and TNF-α for restenosis found that CCL-8 had the strongest predictive value for restenosis (AUC 0.782) (see Table 1).

[0101] Table 1. Predictive value of PVAT protein markers for restenosis

[0102] / AUC Optimal cut-off pg / mL Sensitivity Specificity CCL-8 0.782 2.520 0.875 0.661 IFN-γ 0.672 5.505 0.938 0.411 IL-2 0.657 25.850 0.688 0.304 IL-4 0.717 16.145 0.813 0.643 TGF-β3 0.741 244.290 0.688 0.768 TNF-α 0.691 6.860 0.750 0.554

[0103] A total of 64 patients who underwent carotid endarterectomy, of which 8 patients had restenosis, were included in the modeling set to verify the predictive value of PVAT CCL-8 for restenosis. In the modeling set, the AUC of CCL-8 for predicting restenosis was 0.785, and when the cutoff value was 2.56 pg / mL (the concentration of CCL-8 in the above-mentioned lysed and diluted PVAT sample was 2.56 pg / mL), the sensitivity was 87.5% and the specificity was 70% (see Table 2). Figure 16 ).

[0104] A total of 64 patients who underwent carotid endarterectomy, of which 8 patients had restenosis, were included in the modeling set to verify the predictive value of PVAT CCL-8 for restenosis. In the modeling set, the AUC of CCL-8 for predicting restenosis was 0.785, and when the cutoff value was 2.56 pg / mL (the concentration of CCL-8 in the above-mentioned lysed and diluted PVAT sample was 2.56 pg / mL), the sensitivity was 87.5% and the specificity was 70% (see Table 2). Figure 16 .

[0105] The above description of the embodiments is only for understanding the method of the present application and its core idea. It should be noted that, for those skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications will also fall within the protection scope of the claims of the present application.

Claims

1. The application of a reagent for detecting the expression level of CCL-8 in perivascular adipose tissue of a test sample in the preparation of products for predicting restenosis after carotid endarterectomy, characterized in that, The reagent is a binding agent that specifically binds to the protein encoded by the CCL-8 gene.

2. The application according to claim 1, characterized in that, The reagent also includes a detectable marker.

3. The application according to claim 2, characterized in that, The detectable markers include radioactive isotopes, enzymes, substrates, fluorescent molecules, chemiluminescent components, magnetic particles, and bioluminescent components.

4. The application according to any one of claims 1-3, characterized in that, The products include chips, test strips, or reagent kits.

5. The application according to claim 4, characterized in that, The kit includes a reagent for lysing the perivascular adipose tissue of the sample to be tested.

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