WO2023143326A1 - 用于预测胰腺癌发生风险的生物标志物、方法和诊断设备 - Google Patents

用于预测胰腺癌发生风险的生物标志物、方法和诊断设备 Download PDF

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WO2023143326A1
WO2023143326A1 PCT/CN2023/072981 CN2023072981W WO2023143326A1 WO 2023143326 A1 WO2023143326 A1 WO 2023143326A1 CN 2023072981 W CN2023072981 W CN 2023072981W WO 2023143326 A1 WO2023143326 A1 WO 2023143326A1
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pancreatic cancer
marker
risk
markers
cancer risk
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French (fr)
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韩达
张朝
滕小艳
马倩
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臻智达生物技术（上海）有限公司
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    • C—CHEMISTRY; METALLURGY
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    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
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    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/74—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving hormones or other non-cytokine intercellular protein regulatory factors such as growth factors, including receptors to hormones and growth factors
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    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present invention relates to the field of clinical medicine, in particular to biomarkers, methods and diagnostic equipment for predicting the risk of pancreatic cancer.
  • Pancreatic cancer is known as the king of cancers and is one of the deadliest cancers. Most pancreatic cancer patients do not have any special clinical symptoms in the early stage, so most pancreatic cancer patients miss the best treatment period. In the past few decades, no method has been found that can significantly improve the survival rate of patients. The 5-year survival rate of pancreatic cancer patients is only 5%-15%, the overall survival rate is about 6%, and only 20% of patients are diagnosed Surgical treatment is possible. Therefore, timely and effective diagnosis plays an important role in the prevention and treatment of pancreatic cancer.
  • the main diagnostic methods for pancreatic cancer are mainly imaging techniques including ultrasonography, computerized tomography (CT), and nuclear magnetic resonance, but these imaging techniques cannot meet the needs of early screening of pancreatic cancer.
  • CT computerized tomography
  • the detection of blood tumor markers only requires a small amount of blood samples, has the advantages of minimal invasiveness and safety, and is an ideal way for tumor screening and diagnosis.
  • Some tumor antigens are used as relevant indicators for the diagnosis of pancreatic cancer, among which carbohydrate antigen 199 (Carbohydrate antigen 199, CA199) is the most widely used, but the sensitivity and specificity of such markers are low, which limits its use in pancreatic cancer.
  • Applications in cancer screening and diagnosis There are currently no effective and accurate biomarkers for pancreatic cancer screening and diagnosis.
  • pancreatic cancer markers with diagnostic or combined diagnostic value and to carry out targeted drug development. Therefore, there is an urgent need in this field to develop specific markers for pancreatic cancer with high sensitivity and specificity, which can be used for early diagnosis or effective treatment of pancreatic cancer, or to evaluate the prognosis of the disease.
  • the object of the present invention is to provide a highly sensitive and specific pancreatic cancer marker and its application in clinical diagnosis and treatment.
  • a use of a pancreatic cancer risk marker gene, mRNA, cDNA, protein, or a detection reagent thereof is provided for the preparation of a diagnostic reagent or kit, and the diagnostic reagent or kit Used to determine the risk of pancreatic cancer;
  • pancreatic cancer risk markers are selected from the following group:
  • A Any marker selected from A1 to A7, or a combination thereof: (A1) ZHX2; (A2) CYYR1; (A3) GJA4; (A4) GSDME; (A5) LYNX1; (A6) RARP10; ) ZNF250.
  • pancreatic cancer risk markers further include any marker selected from the following group B, or a combination thereof: (B1) COL10A1; (B2) COL17A1; (B3) CDH3; (B4) CUZD1 ; (B5) GPT; (B6) SLC45A4; (B7) SQLE.
  • the pancreatic cancer risk marker is mRNA or cDNA.
  • pancreatic cancer risk markers further include at least two selected from A1 to A7.
  • pancreatic cancer risk markers are selected from a combination of one or more markers in A1 to A7 and one or more markers in B1 to B7.
  • the A1-A7 markers are selected from Table A:
  • the B1-B7 markers are selected from Table B:
  • pancreatic cancer risk marker combination is: (A1) ZHX2; (A2) CYYR1; (B1) COL10A1; (B2) COL17A1.
  • pancreatic cancer risk marker combination is: (A2) CYYR1; (B1) COL10A1; (B2) COL17A1.
  • pancreatic cancer risk marker combination is: (A1) ZHX2; (B1) COL10A1.
  • kits in the second aspect of the present invention, contains a detection reagent, and the detection reagent is used to detect genes, mRNA, cDNA, proteins, or combinations thereof of pancreatic cancer risk markers,
  • pancreatic cancer risk markers are selected from the following groups:
  • the detection reagent includes:
  • the genes, mRNAs, cDNAs, or proteins of any markers shown in Table A and/or Table B of the pancreatic cancer risk markers are derived from humans.
  • the subject is human.
  • the subject is a non-tumor patient or a tumor patient.
  • the tumor patient includes pancreatic cancer.
  • the genes, mRNAs, cDNAs, or proteins of the pancreatic cancer risk markers are derived from humans.
  • the detection is for an isolated sample.
  • the isolated samples include: tissue samples, cell samples, blood samples, and serum samples.
  • the detection reagent is coupled with or bears a detectable label.
  • the detectable label is selected from the group consisting of chromophores, chemiluminescent groups, fluorophores, isotopes or enzymes.
  • the antibody is a monoclonal antibody or a polyclonal antibody.
  • the diagnostic reagents include antibodies, primers, probes, sequencing libraries, nucleic acid chips (such as DNA chips) or protein chips.
  • the nucleic acid chip includes a substrate and specific oligonucleotide probes spotted on the substrate, and the specific oligonucleotide probes include any of the pancreatic A polynucleotide (mRNA or cDNA)-specific binding probe for a cancer risk marker.
  • specific oligonucleotide probes include any of the pancreatic A polynucleotide (mRNA or cDNA)-specific binding probe for a cancer risk marker.
  • the protein chip includes a substrate and specific antibodies spotted on the substrate, and the specific antibodies include specific antibodies against the pancreatic cancer risk markers.
  • the antibody is a monoclonal antibody or a polyclonal antibody.
  • the kit contains genes, mRNA, cDNA and/or proteins of pancreatic cancer risk markers as reference or quality control substances.
  • the kit further includes a label or an instruction, which indicates that the kit is used for (a) judging the risk of pancreatic cancer, and/or (b) treating pancreatic cancer Evaluate the effect of treatment.
  • the reagents include primers, probes, gRNA or combinations thereof, more preferably primer pairs or probes for PCR, qPCR, RT-PCR.
  • the detection of the pancreatic cancer risk markers can be performed by the following methods: sequencing, PCR, or a combination thereof.
  • the detection of the pancreatic cancer risk markers can be detected quantitatively.
  • a detection method comprising the steps of:
  • pancreatic cancer risk markers are selected from the following group:
  • A Any marker selected from A1 to A7, or a combination thereof: (A1) ZHX2; (A2) CYYR1; (A3) GJA4; (A4) GSDME; (A5) LYNX1; (A6) RARP10; )ZNF250;
  • pancreatic cancer risk of the detected object If the detection result of the pancreatic cancer risk of the detected object satisfies the following conditions, it will prompt that the pancreatic cancer risk of the object Adenocarcinoma at high risk of:
  • a pancreatic cancer diagnostic device comprising:
  • risk marker genes include selected from the following group:
  • A Any marker selected from A1 to A7, or a combination thereof: (A1) ZHX2; (A2) CYYR1; (A3) GJA4; (A4) GSDME; (A5) LYNX1; (A6) RARP10; )ZNF250;
  • a processing module which calculates the input marker gene according to a predetermined scoring formula to obtain a risk score; and compares the score with a cut-off value (Cut-off) to obtain a discrimination result , wherein, when the risk score is higher than the cut-off value (Cut-off), it is suggested that the subject is a pancreatic cancer patient; when the risk score is lower than the cut-off value (Cut-off) , it indicates that the subject is a non-pancreatic cancer patient; and
  • the scoring formula is:
  • the Wi is the weight value of each gene
  • the Pi is the expression level of each gene.
  • the scoring formula can be calculated manually.
  • the scoring formula can be automatically calculated by designing a computer-aided program.
  • a method for detecting the expression level of a combination of pancreatic cancer risk markers comprises the steps of:
  • step (c) performing reverse transcription on the product RNA obtained in step (b);
  • step (d) performing fluorescent quantitative PCR on the reverse transcription product obtained in step (c), so as to obtain the expression level of risk marker genes
  • the risk marker is selected from the following group:
  • A Any marker selected from A1 to A7, or a combination thereof: (A1) ZHX2; (A2) CYYR1; (A3) GJA4; (A4) GSDME; (A5) LYNX1; (A6) RARP10; ) ZNF250.
  • the method is a non-diagnostic and non-therapeutic method
  • the method is an in vitro method.
  • the upstream and downstream specific primer sequences corresponding to each gene are: SEQ ID NO: 1-28.
  • Figure 1 shows the ROC curve of the diagnostic effect of scheme 1 (COL10A1, COL17A1, CYYR1, ZHX2 as combined markers)
  • Figure 2 shows the ROC curve of the diagnostic effect of scheme 2 (COL10A1, COL17A1, and CYYR1 as combined markers)
  • Figure 3 shows the ROC curve of the diagnostic effect of scheme 3 (COL10A1, ZHX2 as combined markers)
  • the inventors After extensive and in-depth research, the inventors first developed a combination of markers for the diagnosis of pancreatic cancer with high sensitivity and specificity. Specifically, through database research, the mRNA expression profile levels of pancreatic cancer and normal pancreatic tissue samples were analyzed, and 37 specific mRNA markers were screened for the first time using statistical methods. The serum level test proved that 14 specific mRNA markers were selected, which can effectively distinguish pancreatic cancer patients from healthy people, so that corresponding adjuvant therapy or intervention therapy can be carried out as early as possible for patients with high risk of pancreatic cancer. The present invention has been accomplished on this basis.
  • sample refers to material specifically associated with a subject from which specific information about the subject can be determined, calculated or inferred.
  • a sample may consist in whole or in part of biological material from a subject.
  • the term "expression” includes the production of mRNA from a gene or part of a gene, and includes the production of a protein encoded by RNA or a gene or part of a gene, as well as the production of a test substance associated with expression.
  • a binding ligand eg, antibody
  • binding of a binding ligand to a gene or other oligonucleotide, protein or protein fragment, and chromogenic moieties of the binding ligand are all included within the scope of the term "expression”.
  • an increase in half-dot density on an immunoblot such as a Western blot is also within the scope of the term "expression” on a biological molecule basis.
  • the term "reference value” or “control reference value” refers to a value that is statistically related to a particular result when compared to the result of an assay.
  • the reference value is determined by comparing mRNA expression and/or protein expression of pancreatic cancer risk markers and performing statistical analysis. Some of these studies are shown in the Examples section herein. However, studies from the literature and user experience with the methods disclosed herein can also be used to generate or adjust reference values. Reference values can also be determined by taking into account circumstances and outcomes particularly relevant to the patient's ethnic group, medical history, genetics, age, and other factors.
  • pancreatic cancer risk markers of the present invention refers to one or more markers shown in Table A and/or Table B.
  • pancreatic cancer risk marker protein of the present invention refers to having any one or more of the pancreatic cancer risk markers of the present invention.
  • pancreatic cancer risk marker gene and “pancreatic cancer risk marker polynucleotide” are used interchangeably, and all refer to any pancreatic cancer risk marker shown in Table A and/or Table B nucleotide sequence of the substance.
  • nucleotide changes are also acceptable.
  • a nucleic acid sequence encoding it can be constructed based on it, and specific probes can be designed based on the nucleotide sequence.
  • the full-length nucleotide sequence or its fragments can usually be obtained by PCR amplification, recombination or artificial synthesis.
  • primers can be designed according to the nucleotide sequence of the pancreatic cancer risk marker disclosed in the present invention, especially the open reading frame sequence, and a commercially available cDNA library or a routine known to those skilled in the art can be used to Methods
  • the prepared cDNA library was used as a template to amplify related sequences. When the sequence is long, it is often necessary to carry out two or more PCR amplifications, and then splice together the amplified fragments in the correct order.
  • recombinant methods can be used to obtain the relevant sequences in large quantities. This is usually cloned into a vector, then transformed into a cell, and then isolated from the proliferated host cell by conventional methods about the sequence.
  • related sequences can also be synthesized by artificial synthesis, especially when the fragment length is relatively short. Often, fragments with very long sequences are obtained by synthesizing multiple small fragments and then ligating them.
  • the DNA sequence encoding the protein of the present invention can be obtained completely through chemical synthesis. This DNA sequence can then be introduced into various existing DNA molecules (such as vectors) and cells known in the art.
  • the polynucleotide sequence of the present invention can be used to express or produce recombinant pancreatic cancer risk markers.
  • antibody of the present invention and “specific antibody against pancreatic cancer risk markers” are used interchangeably and refer to antibodies that can be used to specifically bind and detect the pancreatic cancer risk markers of the present invention.
  • the antibodies against pancreatic cancer risk markers (Table A and/or Table B) of the present invention include specific polyclonal antibodies and monoclonal antibodies, especially monoclonal antibodies.
  • the present invention includes not only complete monoclonal or polyclonal antibodies, but also immunologically active antibody fragments, such as Fab' or (Fab) 2 fragments; antibody heavy chains; antibody light chains; genetically engineered single-chain Fv molecules ( Ladner et al., US Patent No. 4,946,778); or chimeric antibodies, such as antibodies that have the binding specificity of a murine antibody but retain portions of the antibody from humans.
  • immunologically active antibody fragments such as Fab' or (Fab) 2 fragments
  • antibody heavy chains such as antibody heavy chains; antibody light chains; genetically engineered single-chain Fv molecules ( Ladner et al., US Patent No. 4,946,778); or chimeric antibodies, such as antibodies that have the binding specificity of a murine antibody but retain portions of the antibody from humans.
  • Antibodies of the present invention can be prepared by various techniques known to those skilled in the art. For example, purified human pancreatic cancer risk marker gene products, or antigenic fragments thereof, can be administered to animals to induce polyclonal antibody production. Similarly, cells expressing human pancreatic cancer risk marker proteins or antigenic fragments thereof can be used to immunize animals to produce antibodies. Antibodies of the invention may also be monoclonal antibodies. Such monoclonal antibodies can be prepared using hybridoma technology.
  • Antibodies against human pancreatic cancer risk marker proteins can be used in immunohistochemical techniques to detect human pancreatic cancer risk marker proteins in specimens (especially tissue samples or blood samples). Since pancreatic cancer risk marker proteins exist in blood samples or tissue samples, their expression levels can be detected.
  • the present invention Based on the differential expression of pancreatic cancer risk markers in tissue samples or blood samples, the present invention also provides a corresponding method for judging the risk of pancreatic cancer.
  • the invention relates to a diagnostic test method for quantitatively and locally detecting the protein level or mRNA level of pancreatic cancer risk markers. These assays are well known in the art. Human pancreatic cancer risk marker proteins detected in the trial The level or mRNA level can be used to judge (including auxiliary judgment) whether there is a risk of pancreatic cancer.
  • a preferred method is to quantitatively detect mRNA or cDNA by PCR/qPCR/RT-PCR.
  • a preferred method is quantitative detection of mRNA or cDNA, sequencing.
  • the polynucleotides of pancreatic cancer risk markers can be used for the diagnosis of pancreatic cancer risk.
  • a part or all of the polynucleotides of the present invention can be fixed on microarrays or DNA chips as probes for differential expression analysis and gene diagnosis of genes in analysis.
  • the present invention can also detect at the protein level.
  • antibodies against pancreatic cancer risk markers can be immobilized on protein chips to detect pancreatic cancer risk proteins in samples.
  • pancreatic cancer risk markers can be used as judgment markers for pancreatic cancer risk.
  • the present invention also provides a kit for judging the risk of pancreatic cancer.
  • the kit contains a detection reagent for detecting genes, mRNA, cDNA, proteins, or combinations thereof of pancreatic cancer risk markers.
  • the kit contains an antibody or immunoconjugate against a pancreatic cancer risk marker of the present invention, or an active fragment thereof; or a primer or primer pair that specifically amplifies mRNA or cDNA of a pancreatic cancer risk marker , probe or chip.
  • the kit further includes a label or instructions.
  • the present invention uses blood samples, which is more suitable for early screening and diagnosis, and has the characteristics of faster, more convenient and low cost.
  • the marker combination established by the present invention has higher specificity and more accurate detection results.
  • the inventors used the mRNA expression profiles of pancreatic cancer (cancerous tissues and paracancerous tissues) in the TCGA database and the GEO database, grouped samples according to the pathological stages of pancreatic cancer, and obtained a group by comparing the expression profiles of different sample groups.
  • pancreatic cancer cancerous tissues and paracancerous tissues
  • Differentially expressed mRNAs between pancreatic cancer and normal pancreatic tissue samples were used as candidates, and on this basis, different algorithms were used to calculate and screen the molecular markers, and a multi-marker joint classifier with high classification accuracy (including 2 or two or more mRNA markers).
  • SVM support vector machine
  • a classifier composed of these mRNA markers can predict whether a sample has pancreatic cancer, and its prediction accuracy can reach up to 93.90%. Based on the group of mRNA markers of the present invention, it can be developed into an RT-PCR kit for early screening of pancreatic cancer.
  • pancreatic cancer samples 4 genes with a significantly higher frequency of positive rates of pancreatic cancer were selected when used alone, and the effect of single use in serum was further evaluated.
  • ZHX2, CYYR1, COL10A1, and COL17A1 all have good sensitivity, specificity, and accuracy when used alone. Among them, the sensitivity (%), specificity (%), and accuracy (%) of the ZHX2 gene are particularly prominent when used alone.
  • Figure 1 shows the ROC effect of the combination of four markers, COL10A1, COL17A1, CYYR1 and ZHX2, in Scheme 1.
  • the scoring calculation formula is:
  • the cutoff value is set at: -1.22
  • Figure 2 shows the ROC effect of the combination of three markers, COL10A1, COL17A1 and CYYR1, in Scheme 2.
  • the scoring calculation formula is:
  • the cutoff value is set at: -1.58
  • Figure 3 shows the ROC effect of the combination of two markers, COL10A1 and ZHX2, in Scheme 3.
  • the scoring calculation formula is:
  • the cutoff value is set at: -3.75
  • Embodiment 5 detection reagent and application
  • the following detection methods and detection reagents are used for detection.
  • the detection method comprises the following steps:
  • Primer F and primer R sequences for each marker are as follows:

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Abstract

本发明提供了用于预测胰腺癌发生风险的生物标志物、方法和诊断设备。具体地，本发明提供了胰腺癌发生风险的标志物的基因、mRNA、cDNA、蛋白质或其检测试剂的用途，用于制备/建立判断发生风险的诊断试剂或试剂盒/模型。研究表明，胰腺癌风险标志物可作为判断胰腺癌发生的标记物，具有高灵敏度和特异性。

Description

用于预测胰腺癌发生风险的生物标志物、方法和诊断设备 技术领域
本发明涉及临床医学领域，具体地涉及用于预测胰腺癌发生风险的生物标志物、方法和诊断设备。
背景技术
胰腺癌被称为癌中之王，是最致命的癌症之一。大多数胰腺癌患者在早期并没有任何特殊的临床症状，因此大多数胰腺癌患者都错过了最佳的治疗时期。在过去的几十年间，没有发现可以显著提高患者生存率的方法，胰腺癌患者5年生存率仅有5％-15％，总体生存率约为6％，且仅有20％的患者在发现时可以进行手术治疗。因而及时有效的诊断在胰腺癌防治过程中扮演着重要的角色。
目前胰腺癌的主要诊断方法主要以包括超声检查、电子计算机断层扫描(Computed Tomography，CT)、以及核磁共振的影像学技术为主，但这些影像学技术还无法满足胰腺癌早期筛查的需求。血液肿瘤标志物检测只需要少量血液样本，具有微创、安全的优点，是进行肿瘤筛查诊断的理想方式。一些肿瘤抗原被用作胰腺癌诊断的相关指标，其中应用最广的是糖类抗原199(Carbohydrate antigen 199，CA199)，但这类标志物敏感度、特异性均较低，限制了其在胰腺癌筛查诊断中的应用。目前还没有有效且准确的生物标志物用于胰腺癌筛查和诊断。
综上所述，寻找新的具有诊断或联合诊断价值的胰腺癌标志物，并针对性地进行靶向药物研发是当务之急。因此，本领域迫切需要开发有高灵敏度和特异性的胰腺癌特异标志物，用于胰腺癌的早期诊断或有效治疗、或评估疾病的预后效果。
发明内容
本发明的目的就是提供一种高灵敏和高特异性的胰腺癌标志物及其在临床诊断和治疗中的用途。
在本发明的第一方面，提供了一种胰腺癌风险标志物的基因、mRNA、cDNA、蛋白、或其检测试剂的用途，用于制备一诊断试剂或试剂盒，所述诊断试剂或试剂盒用于判断胰腺癌的发生风险；
其中，所述的胰腺癌风险标志物选自下组：
(A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250。
在另一优选例中，所述胰腺癌风险标志物还包括选自下组B的任一标志物、或其组合：(B1)COL10A1；(B2)COL17A1；(B3)CDH3；(B4)CUZD1；(B5)GPT；(B6)SLC45A4；(B7)SQLE。
在另一优选例中，所述的胰腺癌风险标志物为mRNA或cDNA。
在另一优选例中，所述胰腺癌风险标志物还包括选自A1至A7中的至少2种。
在另一优选例中，所述胰腺癌风险标志物选自A1至A7中一个或多个标志物与B1至B7中一个或多个标志物所构成的组合。
在另一优选例中，所述的A1-A7标志物选自表A:
表A
在另一优选例中，所述的B1-B7标志物选自表B:
表B

在另一优选例中，所述的胰腺癌风险标志物组合为：(A1)ZHX2；(A2)CYYR1；(B1)COL10A1；(B2)COL17A1。
在另一优选例中，所述胰腺癌风险标志物组合为：(A2)CYYR1；(B1)COL10A1；(B2)COL17A1。
在另一优选例中，所述胰腺癌风险标志物组合为：(A1)ZHX2；(B1)COL10A1。
在本发明的第二方面，提供了一种试剂盒，所述的试剂盒含有一检测试剂，所述检测试剂用于检测胰腺癌风险标志物的基因、mRNA、cDNA、蛋白、或其组合，
其中，所述的胰腺癌风险标志物选择下组：
(A)选自A1至A7中两个或两个以上标志物的组合；
(B)选自A1至A7中一个或多个标志物与B1至B7中一个或多个标志物所构成的组合。
在另一优选例中，所述检测试剂包括：
(a)针对所述胰腺癌风险标志物的特异性抗体、特异性结合分子；和/或
(b)特异性扩增所述胰腺癌风险标志物的mRNA或cDNA的引物或引物对、探针或芯片(如核酸芯片或蛋白质芯片)。
在另一优选例中，所述胰腺癌风险标志物表A和/或表B中所示的任一标志物的基因、mRNA、cDNA、或蛋白来源于人。
在另一优选例中，所述的对象为人。
在另一优选例中，所述的对象为非肿瘤患者、肿瘤患者。
在另一优选例中，所述肿瘤患者包括胰腺癌。
在另一优选例中，所述胰腺癌风险标志物的基因、mRNA、cDNA、或蛋白来源于人。
在另一优选例中，所述检测是针对离体样本的检测。
在另一优选例中，所述的离体样本包括：组织样本、细胞样本、血液样本、血清样本。
在另一优选例中，所述的检测试剂偶联有或带有可检测标记。
在另一优选例中，所述可检测标记选自下组：生色团、化学发光基团、荧光团、同位素或酶。
在另一优选例中，所述的抗体是单克隆抗体或多克隆抗体。
在另一优选例中，所述诊断试剂包括抗体、引物、探针、测序文库、核酸芯片(如DNA芯片)或蛋白质芯片。
在另一优选例中，所述的核酸芯片包括基片和点样在基片上的特异性寡核苷酸探针，所述的特异性寡核苷酸探针包括与任一所述的胰腺癌风险标志物的多核苷酸(mRNA或cDNA)特异性结合的探针。
在另一优选例中，所述的蛋白质芯片包括基片和点样在基片上的特异性抗体，所述的特异性抗体包括抗所述胰腺癌风险标志物的特异性抗体。
在另一优选例中，所述的抗体是单克隆抗体或多克隆抗体。
在另一优选例中，所述的试剂盒含有胰腺癌风险标志物的基因、mRNA、cDNA和/或蛋白作为对照品或质控品。
在另一优选例中，所述的试剂盒还包括标签或说明书，所述标签或说明书注明所述试剂盒用于(a)判断胰腺癌的发生风险，和/或(b)对胰腺癌治疗效果进行评价。
在另一优选例中，所述的试剂包括引物、探针、gRNA或其组合，更佳地为用于PCR、qPCR、RT-PCR的引物对或探针。
在另一优选例中，所述胰腺癌风险标志物的检测可通过如下的方法进行检测：测序、PCR、或其组合。
在另一优选例中，所述胰腺癌风险标志物的检测可定量检测。
在本发明的第三方面，提供了一种检测方法，包括步骤：
(a)提供一检测样本，所述检测样本选自血液样本；
(b)检测所述检测样本中胰腺癌风险标志物基因的表达量，记为C1；和
(c)将所述胰腺癌风险标志物浓度C1与对照参比值C0进行比较；
其中，所述的胰腺癌风险标志物选自下组：
(A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250；
如果检测对象的胰腺癌风险的检测结果满足以下条件时，则提示所述对象的胰 腺癌发生风险高：
(1)当某一标志物在检测对象中是表A中上调的标志物，且所述标志物的表达水平高于参考值或标准值C0时，所述检测对象发生胰腺癌风险高；
(2)当某一标志物在检测对象中是表A中下调的标志物，且所述标志物的表达水平低于参考值或标准值C0时，所述检测对象发生胰腺癌风险高。
在本发明的第四方面，提供了一种胰腺癌诊断设备，所述设备包括：
(a)输入模块，所述输入模块用于输入某一对象血液样本的胰腺癌风险标志物数据；
其中所述的风险标志基因包括选自下组：
(A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250；
(b)处理模块，所述处理模块对于输入的标志物基因按照预定的打分公式进行计算，获得风险度评分；并且将所述评分与截点值(Cut-off)进行比较，从而获得判别结果，其中，当所述风险度评分高于所述截点值(Cut-off)时，则提示该对象为胰腺癌患者；当所述风险度评分低于所述截点值(Cut-off)时，则提示该对象为非胰腺癌患者；和
(c)输出模块，所述输出模块用于输出所述的诊断结果。
在另一优选例中，所述的打分公式为：
其中，所述Wi为各基因的权重值；所述Pi为各基因的表达水平。
在另一优选例中，所述打分公式可通过人工计算。
在另一优选例中，所述打分公式可通过设计计算机辅助程序实现自动计算。
在本发明的第五方面，提供了一种检测胰腺癌风险标志物组合表达水平的方法，其特征在于，包括步骤：
(a)提供一种血清样本；
(b)提取所述血清样本的总RNA；
(c)对步骤(b)中获得的产物RNA进行反转录；
(d)对步骤(c)中获得的反转录产物进行荧光定量PCR，从而获取风险标志物基因表达水平；
其中，所述风险标志物选自下组：
(A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250。
在另一优选例中，所述方法是非诊断非治疗性的方法；
在另一优选例中，所述方法是体外方法。
在另一优选例中，步骤(d)中在定量PCR时，各基因对应的上下游特异引物序列分别为：SEQ ID NO:1-28。
应理解，在本发明范围内中，本发明的上述各技术特征和在下文(如实施例)中具体描述的各技术特征之间都可以互相组合，从而构成新的或优选的技术方案。限于篇幅，在此不再一一累述。
附图说明
图1显示了方案1(COL10A1、COL17A1、CYYR1、ZHX2作为组合标志物)诊断效果ROC曲线图
图2显示了方案2(COL10A1、COL17A1、CYYR1作为组合标志物)诊断效果ROC曲线图
图3显示了方案3(COL10A1、ZHX2作为组合标志物)诊断效果ROC曲线图
具体实施方式
本发明人经过广泛而深入的研究，首次开发了一种高灵敏度和高特异性的胰腺癌诊断的标志物组合。具体地，通过数据库研究，分析了胰腺癌与正常胰腺组织样本的mRNA表达谱水平，用统计学方法，首次从中筛选出37个特异性的mRNA标志物。经血清水平检验证明，从中挑选出14个特异性的mRNA标志物，可非常有效地区分胰腺癌患者和健康人，以便于对胰腺癌高风险患者尽早地进行对应的辅助治疗或干预治疗。在此基础上完成了本发明。
术语
本文中使用的术语“样品”或“样本”是指与受试者特异地相关联的材料，从其中可以确定、计算或推断出与受试者有关的特定信息。样本可以全部或部分由来自受试者的生物材料构成。
如本文所用，术语“表达”包括mRNA从基因或基因部分的产生，并且包括由RNA或基因或基因部分所编码的蛋白质的产生，还包括与表达相关的检测物质的出 现。例如，cDNA，结合配体(如抗体)与基因或其它寡核苷酸、蛋白质或蛋白质片段的结合以及结合配体的显色部分都包括在术语“表达”的范围内。因此，在免疫印迹如Western印迹上半点密度的增加也处于以生物学分子为基础的术语“表达”的范围内。
如本文所用，术语“参比值”或“对照参比值”是指当与分析结果相比时与特定结果统计学相关的值。在优选的实施方案中，参比值是根据对比较胰腺癌风险标志物的mRNA表达和/或蛋白的表达，并进行统计学分析来确定的。在本文的实施例部分中显示了一些这样的研究。但是，来自文献的研究和本文公开的方法的用户经验也可用于生产或调整参比值。参比值也可以通过考虑与患者的族群、医疗史、遗传学、年龄和其它因素特别相关的情况和结果来确定。
胰腺癌风险标志物
如本文所用，术语“本发明的胰腺癌风险标志物”指表A和/或表B中所示的一种或多种标志物。
在本发明中，术语“本发明的胰腺癌风险标志物蛋白”、“本发明蛋白”、“本发明的多肽”、或“表A和/或表B中所示的标志物”可互换使用，都指具有本发明的胰腺癌风险标志物中任何一种或多种。
在本发明中，术语“胰腺癌风险标志物基因”、“胰腺癌风险标志物的多核苷酸”可互换使用，都指表A和/或表B中所示的任一胰腺癌风险标志物的核苷酸序列。
需理解的是，当编码相同的氨基酸时，密码子中核苷酸的取代是可接受的。另外需理解的是，由核苷酸取代而产生保守的氨基酸取代时，核苷酸的变换也是可被接受的。
在得到了胰腺癌风险标志物的信息的情况下，可根据其构建出编码它的核酸序列，并且根据核苷酸序列来设计特异性探针。核苷酸全长序列或其片段通常可以用PCR扩增法、重组法或人工合成的方法获得。对于PCR扩增法，可根据本发明所公开的胰腺癌风险标志物的核苷酸序列，尤其是开放阅读框序列来设计引物，并用市售的cDNA库或按本领域技术人员已知的常规方法所制备的cDNA库作为模板，扩增而得有关序列。当序列较长时，常常需要进行两次或多次PCR扩增，然后再将各次扩增出的片段按正确次序拼接在一起。
一旦获得了有关的序列，就可以用重组法来大批量地获得有关序列。这通常是将其克隆入载体，再转入细胞，然后通过常规方法从增殖后的宿主细胞中分离得到 有关序列。
此外，还可用人工合成的方法来合成有关序列，尤其是片段长度较短时。通常，通过先合成多个小片段，然后再进行连接可获得序列很长的片段。
目前，已经可以完全通过化学合成来得到编码本发明蛋白(或其片段，衍生物)的DNA序列。然后可将该DNA序列引入本领域中已知的各种现有的DNA分子(如载体)和细胞中。
通过常规的重组DNA技术，可利用本发明的多核苷酸序列可用来表达或生产重组的胰腺癌风险标志物。
特异性抗体
在本发明中，术语“本发明抗体”和“抗胰腺癌风险标志物的特异性抗体”可互换使用，指可用于特异性地结合并检测本发明的胰腺癌风险标志物的抗体。
本发明的针对胰腺癌风险标志物(表A和/或表B)的抗体，包括具有特异性的多克隆抗体和单克隆抗体，尤其是单克隆抗体。
本发明不仅包括完整的单克隆或多克隆抗体，而且还包括具有免疫活性的抗体片段，如Fab'或(Fab)2片段；抗体重链；抗体轻链；遗传工程改造的单链Fv分子(Ladner等人，美国专利No.4,946,778)；或嵌合抗体，如具有鼠抗体结合特异性但仍保留来自人的抗体部分的抗体。
本发明的抗体可以通过本领域内技术人员已知的各种技术进行制备。例如，纯化的人胰腺癌风险标志物的基因产物或者其具有抗原性的片段，可被施用于动物以诱导多克隆抗体的产生。与之相似的，表达人胰腺癌风险标志物蛋白或其具有抗原性的片段的细胞可用来免疫动物来生产抗体。本发明的抗体也可以是单克隆抗体。此类单克隆抗体可以利用杂交瘤技术来制备。
抗人胰腺癌风险标志物蛋白的抗体可用于免疫组织化学技术中，检测标本(尤其是组织样本或血液样本)中的人胰腺癌风险标志物蛋白。由于胰腺癌风险标志物蛋白存在于血液样本或组织样本中，因此其表达量可成为检测对象。
检测方法
基于胰腺癌风险标志物在组织样本或血液样本中差异表达，本发明还提供了相应的判断胰腺癌风险的方法。
本发明涉及定量和定位检测胰腺癌风险标志物的蛋白水平或mRNA水平的诊断试验方法。这些试验是本领域所熟知的。试验中所检测的人胰腺癌风险标志物蛋白 水平或mRNA水平，可以用于判断(包括辅助判断)是否具有胰腺癌风险。
一种优选的方法是对mRNA或cDNA，进行PCR/qPCR/RT-PCR进行定量检测。
一种优选的方法是对mRNA或cDNA，测序进行定量检测。
胰腺癌风险标志物的多核苷酸可用于胰腺癌风险的诊断。本发明的多核苷酸的一部分或全部可作为探针固定在微阵列或DNA芯片上，用于分析中基因的差异表达分析和基因诊断。
此外，本发明还可以在蛋白水平进行检测。例如，抗胰腺癌风险标志物的抗体可以固定在蛋白质芯片上，用于检测样本中的胰腺癌风险蛋白。
检测试剂盒
基于胰腺癌风险标志物与胰腺癌风险的相关性，因此胰腺癌风险标志物可以作为胰腺癌风险的判断标志物。
本发明还提供了一种判断胰腺癌风险的试剂盒，所述的试剂盒含有一检测试剂，所述检测试剂用于检测胰腺癌风险标志物的基因、mRNA、cDNA、蛋白、或其组合。优选地，所述试剂盒含有本发明的抗胰腺癌风险标志物的抗体或免疫偶联物，或其活性片段；或者含有特异性扩增胰腺癌风险标志物的mRNA或cDNA的引物或引物对、探针或芯片。
在另一优选例中，所述的试剂盒还包括标签或说明书。
本发明的主要优点包括：
(1)与现有影像学技术相比，本发明采用血液样本，更适用于早期筛查诊断，且具有更快速、更便捷、低成本的特点。
(2)与现有肿瘤抗原检测方法相比，本发明建立的标志物组合具有更高的特异性，检测结果更准确。
下面结合具体实施例，进一步阐述本发明。应理解，这些实施例仅用于说明本发明而不用于限制本发明的范围。下列实施例中未注明具体条件的实验方法，通常按照常规条件，例如Sambrook等人，分子克隆：实验室手册(New York:Cold Spring Harbor Laboratory Press,1989)中所述的条件，或按照制造厂商所建议的条件。除非另外说明，否则百分比和份数是重量百分比和重量份数。
实施例1胰腺癌诊断标志物的筛选和确定
具体地，本发明人采用TCGA数据库和GEO数据库中的胰腺癌(癌组织和癌旁组织)的mRNA表达谱，根据胰腺癌病理分期对样本分组，通过比较不同样本组的表达谱,得到一组胰腺癌与正常胰腺组织样本间差异表达的mRNA。以这些差异mRNA作为候选，使用支持向量机(SVM)模型进行计算，在此基础上采用不同的算法对分子标志物进行计算筛选，得到分类准确度较高的多标志物联合分类器(含2个或2个以上mRNA标志物)。由这些mRNA标志物组成的分类器，可预测样本是否有胰腺癌，其预测准确度达最高可达93.90％。基于本发明的这组mRNA标志物，可以开发成RT-PCR试剂盒用于胰腺癌的早期筛查。
实施例2胰腺癌诊断标志物的验证(血样)
我们收集了229例血清样本，用于验证了分类器的准确性，其中胰腺癌131例，健康志愿者98例。
实施例3胰腺癌诊断标志物单用
选取胰腺癌样本中，单用时胰腺癌阳性率出现频率显著较高的4个基因，并进一步在评估血清中的单用效果。
结果如表1所示：
表1标志物在血清中单用效果
ZHX2、CYYR1、COL10A1、和COL17A1在单用时均具有良好的灵敏度、特异度和准确率。其中，ZHX2基因单用时灵敏度(％)、特异度(％)、准确率(％)等性能尤为突出。
实施例4胰腺癌诊断标志物的组合应用
在本实施例中，进一步验证多个胰腺癌诊断标志物的组合在血清样本中检测效果。
结果分别如图1-图3所示。
图1显示了方案1 COL10A1、COL17A1、CYYR1和ZHX2这4种标志物组合时的ROC效果。
其中，采用打分计算公式为：
得分＝3.2*COL10A1+0.1*ZHX2-2*CYYR1-2.5*COL17A1，
截断值定为：-1.22
229例样本的验证结果为：
图2显示了方案2 COL10A1、COL17A1和CYYR1这3种标志物组合时的ROC效果。
其中，采用打分计算公式为：
得分＝3.6*COL10A1-2*CYYR1-2.8*COL17A1
截断值定为：-1.58
229例样本的验证结果为：
图3显示了方案3 COL10A1和ZHX2这2种标志物组合时的ROC效果。
其中，采用打分计算公式为：
得分＝4.1*COL10A1-0.2*ZHX2-5.8*COL17A1
截断值定为：-3.75
229例样本的验证结果为：
实施例5检测试剂和应用
在本实施例中，采用以下检测方法和检测试剂进行检测。
检测方法包括以下步骤：
(1)收集的血清样本提取总RNA。
(2)将提取的RNA去除基因组DNA，具体为：按如下成分于冰上配制反应混合液，为了保证反应液配制的准确性，进行各项反应时，应先按反应数+2的量配制Master Mix，然后再分装到每个反应管中，最后加入RNA样品。反应步骤：42℃ 2min，4℃5min。
(3)将上述产物RNA进行反转录，具体为：反应液配制请在冰上进行。为了保证反应液配制的准确性，进行各项反应时，应先按反应数+2的量配制Master Mix，然后再分装10ul到每个反应管中。瞬时离心混匀后立即进行反转录反应。(TB green qPCR法)。反应步骤：37℃15min，85℃5sec，4℃5min。
(4)将上述反转录产物进行荧光定量PCR，具体为：
板稀释，将20ul反转录cDNA模板中加入180ul的RNase Free dH2O，将模板稀释10倍。
荧光定量PCR仪器，LC480II,反应步骤：预变性:95℃30sec，PCR:45cycles(95℃5sec，60℃30sec，Single)，Melting curve：(95℃5sec，60℃1min，95℃continuous)
针对每个标志物的引物F和引物R序列如下：

(5)将上步检测获得的标志物基因表达水平，代入到计算公式中，获得检测结果。
在本发明提及的所有文献都在本申请中引用作为参考，就如同每一篇文献被单 独引用作为参考那样。此外应理解，在阅读了本发明的上述讲授内容之后，本领域技术人员可以对本发明作各种改动或修改，这些等价形式同样落于本申请所附权利要求书所限定的范围。

Claims (15)

  1. 一种胰腺癌风险标志物的基因、mRNA、cDNA、蛋白、或其检测试剂的用途，其特征在于，用于制备一诊断试剂或试剂盒，所述诊断试剂或试剂盒用于判断胰腺癌的发生风险；
    其中，所述的胰腺癌风险标志物选自下组：
    (A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250。
  2. 如权利要求1所述的用途，其特征在于，所述胰腺癌风险标志物还包括选自下组B的任一标志物、或其组合：(B1)COL10A1；(B2)COL17A1；(B3)CDH3；(B4)CUZD1；(B5)GPT；(B6)SLC45A4；(B7)SQLE。
  3. 如权利要求1所述的用途，其特征在于，所述胰腺癌风险标志物还包括选自A1至A7中的至少2种。
  4. 如权利要求1所述的用途，其特征在于，所述胰腺癌风险标志物选自A1至A7中一个或多个标志物与B1至B7中一个或多个标志物所构成的组合。
  5. 如权利要求1所述的方法，其特征在于，所述的胰腺癌风险标志物组合为：(A1)ZHX2；(A2)CYYR1；(B1)COL10A1；(B2)COL17A1。
  6. 如权利要求1所述的方法，其特征在于，所述胰腺癌风险标志物组合为：(A2)CYYR1；(B1)COL10A1；(B2)COL17A1。
  7. 如权利要求1所述的方法，其特征在于，所述胰腺癌风险标志物组合为：(A1)ZHX2；(B1)COL10A1。
  8. 一种试剂盒，其特征在于，所述的试剂盒含有一检测试剂，所述检测试剂用于检测胰腺癌风险标志物的基因、mRNA、cDNA、蛋白、或其组合，
    其中，所述的胰腺癌风险标志物选择下组：
    (A)选自A1至A7中两个或两个以上标志物的组合；
    (B)选自A1至A7中一个或多个标志物与B1至B7中一个或多个标志物所构成的组合。
  9. 如权利要求8所述的试剂盒，其特征在于，所述检测是针对离体样本的检测，所述的离体样本包括：组织样本、细胞样本、血液样本、或血清样本。
  10. 如权利要求8所述的试剂盒，其特征在于，所述的试剂盒还包括标签或说明书，所述标签或说明书注明所述试剂盒用于(a)判断胰腺癌的发生风险，和/或(b)对胰腺癌治疗效果进行评价。
  11. 一种检测方法，其特征在于，包括步骤：
    (a)提供一检测样本，所述检测样本选自血液样本；
    (b)检测所述检测样本中胰腺癌风险标志物基因的表达量，记为C1；和
    (c)将所述胰腺癌风险标志物浓度C1与对照参比值C0进行比较；
    其中，所述的胰腺癌风险标志物选自下组：
    (A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250；
    如果检测对象的胰腺癌风险的检测结果满足以下条件时，则提示所述对象的胰腺癌发生风险高：
    (1)当某一标志物在检测对象中是表A中上调的标志物，且所述标志物的表达水平高于参考值或标准值C0时，所述检测对象发生胰腺癌风险高；
    (2)当某一标志物在检测对象中是表A中下调的标志物，且所述标志物的表达水平低于参考值或标准值C0时，所述检测对象发生胰腺癌风险高。
  12. 一种胰腺癌诊断设备，其特征在于，所述设备包括：
    (a)输入模块，所述输入模块用于输入某一对象血液样本的胰腺癌风险标志物数据；
    其中所述的风险标志基因包括选自组下组：
    (A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250；
    (b)处理模块，所述处理模块对于输入的标志物基因按照预定的打分公式进行计算，获得风险度评分；并且将所述评分与截点值(Cut-off)进行比较，从而获得判别结果，其中，当所述风险度评分高于所述截点值(Cut-off)时，则提示该对象为胰腺癌患者；当所述风险度评分低于所述截点值(Cut-off)时，则提示该对象为非胰腺癌患者；和
    (c)输出模块，所述输出模块用于输出所述的诊断结果。
  13. 如权利要求12所述的胰腺癌诊断设备，其特征在于，所述的打分公式为：
    其中，所述Wi为各基因的权重值；所述Pi为各基因的表达水平。
  14. 一种检测胰腺癌风险标志物组合表达水平的方法，其特征在于，包括步骤：
    (a)提供一种血清样本；
    (b)提取所述血清样本的总RNA；
    (c)对步骤(b)中获得的产物RNA进行反转录；
    (d)对步骤(c)中获得的反转录产物进行荧光定量PCR，从而获取风险标志物基因表达水平；
    其中，所述风险标志物选自下组：
    (A)选自A1至A7的任一标志物、或其组合：(A1)ZHX2；(A2)CYYR1；(A3)GJA4；(A4)GSDME；(A5)LYNX1；(A6)RARP10；(A7)ZNF250。
  15. 如权利要求14所述的方法，其特征在于，步骤(d)中在定量PCR时，各基因对应的上下游特异引物序列分别为：SEQ ID NO:1-28。
PCT/CN2023/072981 2022-01-28 2023-01-18 用于预测胰腺癌发生风险的生物标志物、方法和诊断设备 WO2023143326A1 (zh)

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