WO2024080731A1 - Gènes marqueurs de méthylation pour le diagnostic du cancer du pancréas et leur utilisation - Google Patents

Gènes marqueurs de méthylation pour le diagnostic du cancer du pancréas et leur utilisation Download PDF

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WO2024080731A1
WO2024080731A1 PCT/KR2023/015604 KR2023015604W WO2024080731A1 WO 2024080731 A1 WO2024080731 A1 WO 2024080731A1 KR 2023015604 W KR2023015604 W KR 2023015604W WO 2024080731 A1 WO2024080731 A1 WO 2024080731A1
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methylation
genes
pancreatic cancer
mirlet7bhg
gene
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Korean (ko)
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문서윤
김원섭
허혜진
문재우
김경령
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주식회사 엔도믹스
주식회사 엔도큐라
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    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • 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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    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
    • 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
    • G16H50/20—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

Definitions

  • the present invention relates to methylation marker genes and uses thereof for diagnosing pancreatic cancer. More specifically, the present invention relates to a methylation marker gene that enables early diagnosis of pancreatic cancer using biological samples, such as blood samples, and its use.
  • Pancreatic cancer is the second most common cancer among digestive tract carcinomas in Korea, following stomach cancer, liver cancer, and colon cancer, and ranks 8th in overall cancer incidence and 5th among causes of cancer death.
  • the 5-year relative survival rate of pancreatic cancer patients is 12.2%, ranking last among the top 10 cancer types. This is because the pancreas is surrounded by several organs, making it difficult to detect cancer, and because there are no special symptoms in the early stages, most cases are discovered in an advanced state and are in a terminal state where curative surgery cannot be performed. Therefore, early detection of pancreatic cancer is very important to improve survival rate.
  • DNA methylation is an epigenetic modification that plays a central role in regulating gene expression.
  • DNA is transformed into 5-methylcytosine by attaching a methyl group (-CH3) to carbon 5 of cytosine.
  • DNA methylation mainly occurs at the cytosine group of CpG dinucleotides and occurs frequently in DNA regions where CpGs are concentrated, called CpG islands.
  • DNA methylation is recognized as playing an important role in the carcinogenesis of various solid cancers, including pancreatic cancer. It is known that during the course of cancer, DNA hypomethylation occurs throughout the genome, and local hypermethylation occurs frequently in some regions of CpG islands.
  • DNA methylation shows tissue-specific patterns, and for this reason, it is generally accepted that DNA methylation patterns are clinically meaningful information in the diagnosis of various cancers. For example, in cancer cells, if the CpG region of the promoter region of a tumor suppressor gene is abnormally hypermethylated, the expression of this gene may be suppressed, causing cancer.
  • NGS Next-Generation Sequencing
  • a biomarker that has been widely used in pancreatic cancer screening is the serum CA19-9 indicator, a cancer-specific antigen.
  • 10% of the population does not produce CA19-9 protein, so its level cannot be measured, and this protein can mostly be screened for late-stage pancreatic cancer.
  • CA19-9 protein has an elevated index value in many other diseases and has low specificity, so it is not recommended to use this value itself as a screening test for pancreatic cancer or as a basis for recurrence. Therefore, there is a need to discover biomarkers that can diagnose pancreatic cancer at an early stage.
  • the purpose of the present invention is to solve the problems of the prior art described above.
  • Another object of the present invention is to provide a methylation marker gene for diagnosing pancreatic cancer.
  • Another object of the present invention is to provide a method of providing information for diagnosing pancreatic cancer or a method of diagnosing pancreatic cancer.
  • Another object of the present invention is to provide a composition or kit for diagnosing pancreatic cancer.
  • Another object of the present invention is to provide a gene chip or gene panel for diagnosing pancreatic cancer.
  • Another object of the present invention is to provide a method for detecting methylation markers in individuals suspected of having pancreatic cancer or at risk of developing pancreatic cancer.
  • a representative configuration of the present invention to achieve the above object is as follows.
  • MIRLET7BHG MIRLET7B Host Gene
  • XXYLT1 Xyloside Xylosyltransferase 1
  • ZNF879 Zinc Finger Protein 879
  • EPS8L2 EPS8 Like 2
  • TRPC6 Transient Receptor Potential Cation Channel Subfamily C Member 6
  • genes or CpGs thereof selected from the group consisting of AVPR1A (Arginine Vasopressin Receptor 1A), GSC (Goosecoid Homeobox), TBCD (Tubulin Folding Cofactor D), MAFB (MAF BZIP Transcription Factor B), and TCEA2 (Transcription Elongation Factor A2) genes A new marker gene for pancreatic cancer diagnosis containing a region is provided.
  • MIRLET7BHG MIRLET7B Host Gene
  • XXYLT1 Xyloside Xylosyltransferase 1
  • ZNF879 Zinc Finger Protein 879
  • EPS8L2 EPS8 Like 2
  • TRPC6 Transient Receptor Potential Cation Channel Subfamily C Member 6
  • AVPR1A Argonal Vasopressin Receptor 1A
  • GSC Goosecoid Homeobox
  • TBCD Tubulin Folding Cofactor D
  • MAFB MAF BZIP Transcription Factor B
  • TCEA2 Transcription Elongation Factor A2 genes.
  • a method of providing information for diagnosing pancreatic cancer is provided, which includes measuring the methylation status of one or more genes or CpG regions thereof selected from the group consisting of.
  • one or more genes may include MIRLET7BHG.
  • the one or more genes may further include one or more genes selected from the group consisting of TRPC6, AVPR1A, EPS8L2, TBCD, and BNC1.
  • the one or more genes may further include one or more genes selected from the group consisting of EPS8L2 and BNC1.
  • the one or more genes may further include TRPC6, AVPR1A, or TBCD.
  • the step of measuring the methylation status includes measuring the methylation status of a marker gene or a CpG region thereof of a combination of (i), (ii), (iii), (iv), (v), or (vi) below. It may include: (i) BNC1, TRPC6 and MIRLET7BHG; (ii) BNC1, AVPR1A, and MIRLET7BHG; (iii) BNC1 and MIRLET7BHG; (iv) BNC1, MIRLET7BHG, and EPS8L2; (v) MIRLET7BHG and EPS8L2; or (vi) MIRLET7BHG, EPS8L2, and TBCD.
  • the one or more genes may include one or more genes selected from the group consisting of TBCD and EPS8L2.
  • the one or more genes may further comprise BNC1.
  • the biological sample can be blood, plasma, or serum.
  • the nucleic acid isolated from a biological sample may be cfDNA.
  • measuring the methylation status includes i) methylation of the gene or CpG region thereof selected from the group consisting of bisulfite, hydrogen sulfite, disulfite, salts thereof, and combinations thereof. It may include the step of treating the gene with an agent that detects the condition and ii) a primer that specifically amplifies the one or more genes.
  • the step of measuring methylation status includes methylation-specific polymerase chain reaction, real time methylation-specific polymerase chain reaction, methylation DNA-specific polymerase chain reaction. It can be performed by PCR using a binding protein, quantitative PCR, pyrosequencing, or bisulfite sequencing.
  • determining the methylation status may further include comparing a control methylation profile generated from the corresponding methylation measurement results of the corresponding marker in the control sample.
  • control methylation profile constitutes a model constructed by machine learning the methylation patterns of one or more genes obtained above, and may be used to identify pancreatic cancer patient-specific methylation patterns that are different from normal controls.
  • machine learning may be performed by one or more algorithms selected from the group consisting of random forests, logistic regression, support vector machines, decision trees, association rule mining, neural networks, and deep learning.
  • control sample may be a sample from a normal individual.
  • the pancreatic cancer may be early pancreatic cancer, metastatic pancreatic cancer, or recurrent or refractory pancreatic cancer.
  • MIRLET7BHG MIRLET7B Host Gene
  • XXYLT1 Xyloside One or more marker genes or their CpG region selected from the group consisting of Arginine Vasopressin Receptor 1A), GSC (Goosecoid Homeobox), TBCD (Tubulin Folding Cofactor D), MAFB (MAF BZIP Transcription Factor B), and TCEA2 (Transcription Elongation Factor A2)
  • a composition for diagnosing pancreatic cancer using nucleic acids isolated from a biological sample containing one or more agents selected from a specifically amplifying agent and an agent for detecting the methylation status of the one or more marker genes or CpG regions thereof is provided.
  • the one or more marker genes may include MIRLET7BHG.
  • the one or more marker genes may further include one or more genes selected from the group consisting of TRPC6, AVPR1A, EPS8L2, TBCD, and BNC1.
  • the one or more marker genes may further include one or more genes selected from the group consisting of EPS8L2 and BNC1.
  • the one or more marker genes may further include TRPC6, TBCD, or AVPR1A.
  • the composition comprises an agent that amplifies a marker gene or a CpG region thereof of a combination of (i), (ii), (iii), (iv), (v) or (vi) and the marker gene or CpG region thereof.
  • It may include one or more agents selected from agents that detect the methylation status of a region: (i) BNC1, TRPC6, and MIRLET7BHG; (ii) BNC1, AVPR1A, and MIRLET7BHG; (iii) BNC1 and MIRLET7BHG; (iv) BNC1, MIRLET7BHG, and EPS8L2; (v) MIRLET7BHG and EPS8L2; or (vi) MIRLET7BHG, EPS8L2, and TBCD.
  • agents selected from agents that detect the methylation status of a region: (i) BNC1, TRPC6, and MIRLET7BHG; (ii) BNC1, AVPR1A, and MIRLET7BHG; (iii) BNC1 and MIRLET7BHG; (iv) BNC1, MIRLET7BHG, and EPS8L2; (v) MIRLET7BHG and EPS8L2; or (vi) MIRLET7BHG,
  • the one or more marker genes may include one or more genes selected from the group consisting of TBCD and EPS8L2.
  • the one or more marker genes may further include BNC1.
  • the CpG region of a gene may have the following characteristics:
  • the amplifying agent may include a primer, probe, or antisense nucleotide that binds complementary to the gene.
  • the composition may include an agent that specifically amplifies one or more marker genes or CpG regions thereof and an agent that detects the methylation status of the one or more marker genes or CpG regions thereof.
  • the agent that measures methylation status can be a bisulfite, hydrogen sulfite, disulfite, or a combination thereof.
  • kits for diagnosing pancreatic cancer using nucleic acids isolated from a biological sample of an individual including a composition for diagnosing pancreatic cancer.
  • the kit may include a diagnostic nucleic acid chip on which a probe capable of hybridizing with a gene to be detected including the one or more marker genes or a CpG region thereof or a fragment including a CpG region thereof is immobilized. there is.
  • pancreatic cancer there is a method for treating pancreatic cancer, wherein (i) the above-described methylation marker gene or its CpG region in nucleic acid isolated from a biological sample of an individual is hypomethylated or hypermethylated compared to the normal control group. detecting; and (ii) administering therapy for pancreatic cancer in said individual.
  • a method for detecting methylation markers in an individual suspected of having or at risk of developing pancreatic cancer. Specifically, the method includes measuring the methylation status of one or more methylation marker genes in a biological sample obtained from the individual, wherein the one or more methylation marker genes include MIRLET7B Host Gene (MIRLET7BHG) and Xyloside Xylosyltransferase 1 (XXYLT1).
  • MIRLET7B Host Gene MIRLET7BHG
  • XXYLT1 Xyloside Xylosyltransferase 1
  • ZNF879 Zinc Finger Protein 879
  • EPS8L2 EPS8 Like 2
  • TRPC6 Transient Receptor Potential Cation Channel Subfamily C Member 6
  • AVPR1A Arginine Vasopressin Receptor 1A
  • GSC Goosecoid Homeobox
  • TBCD Tubulin Folding Cofactor D
  • MAFB MAF BZIP Transcription Factor B
  • TCEA2 Transcription Elongation Factor A2
  • a new methylation marker gene whose methylation level was differentially changed in a group of pancreatic cancer patients was discovered.
  • pancreatic cancer can be diagnosed with excellent sensitivity, specificity and/or accuracy.
  • the methylation marker gene is useful in that it enables early diagnosis of pancreatic cancer using blood-based biological samples.
  • Figure 1 is a diagram showing a process for establishing a pancreatic cancer identification model according to an embodiment of the present invention.
  • Figure 2 is a diagram showing a color chart showing the difference in methylation levels between pancreatic cancer patient group (33 cases) and normal control (42 cases) samples in the DMR of a new methylation marker gene.
  • Figure 3 shows the sensitivity values obtained by performing a leave-one-out test on samples of the patient group (33 cases) and the normal control group (42 cases) based on the combination of MIRLET7BHG and BNC1 according to an embodiment of the present invention, by cancer stage. This is a drawing showing the organized results.
  • pancreatic cancer As a result of research to secure blood-based methylation marker genes for diagnosing pancreatic cancer, the present inventors discovered new genes or gene combinations whose methylation levels were differentially changed in pancreatic cancer patient groups, and when using these marker genes or combinations of marker genes The present invention was completed by confirming that pancreatic cancer can be diagnosed with excellent sensitivity, specificity, and/or accuracy.
  • MIRLET7BHG MIRLET7B Host Gene
  • XXYLT1 Xyloside Xylosyltransferase 1
  • ZNF879 Zinc Finger Protein 879
  • EPS8L2 EPS8 Like 2
  • TRPC6 Transient Receptor Potential Cation Channel Subfamily C Member 6
  • genes or CpGs thereof selected from the group consisting of AVPR1A (Arginine Vasopressin Receptor 1A), GSC (Goosecoid Homeobox), TBCD (Tubulin Folding Cofactor D), MAFB (MAF BZIP Transcription Factor B), and TCEA2 (Transcription Elongation Factor A2) genes A marker gene for pancreatic cancer diagnosis containing a region is provided.
  • the marker gene for diagnosing pancreatic cancer may include each of the above genes or their CpG regions alone, or may include a combination of two or more genes or their CpG regions selected from the above genes. Additionally, the marker gene for diagnosing pancreatic cancer can be used in combination with other marker genes known in the art for diagnosing pancreatic cancer, such as BNC1.
  • the gene MIRLET7BHG is an RNA belonging to the lncRNA class, and diseases related to it include brachydactyly type B2 disease.
  • the protein encoded by the gene XXYLT1 is an alpha-1,3-xylosyltransferase enzyme that extends O-linked xylose-glucose disaccharides attached to EGF-like repeats in the extracellular domain of target proteins.
  • the protein encoded by gene ZNF879 is a transcriptional repressor containing an N-terminal kruppel-associated box (KRAB) domain and 13 C-terminal C2H2-type zinc finger domains.
  • KRAB N-terminal kruppel-associated box
  • EPS8L2 encodes a protein related to epidermal growth factor receptor pathway substrate 8 (EPS8), a substrate for the epidermal growth factor receptor, and the EPS8L2 protein is known to function involved in actin cytoskeleton remodeling.
  • EPS8L2 epidermal growth factor receptor pathway substrate 8
  • TRPC6 acts as a transient receptor potential channel of the TRPC subfamily, and diseases associated with it include depression, anxiety, and focal segmental glomerulosclerosis.
  • the protein encoded by the gene AVPR1A acts as a receptor for arginine vasopressin. This receptor mediates cell contraction and proliferation, platelet aggregation, release of clotting factors, and glycogenolysis.
  • the gene GSC encodes a member of the bicoid subfamily of the paired homeobox protein family, and the GSC protein acts as a transcription factor and can be self-regulated.
  • the gene TBCD is responsible for capturing and stabilizing intermediates of beta tubulin, and diseases associated with TBCD include encephalopathy and seborrheic dermatitis.
  • the gene MAFB is a basic leucine zipper (bZIP) transcription factor that plays an important role in the regulation of lineage-specific hematopoiesis, and the encoded nuclear protein represses ETS1-mediated transcription of erythroid-specific genes in myeloid cells.
  • bZIP basic leucine zipper
  • the protein encoded by the gene TCEA2 functions as a SII class transcription elongation factor in the nucleus and interacts with the basic transcription factor, general transcription factor IIB.
  • the protein encoded by the gene BNC1 is a zinc finger protein present in the basal cell layer of the epidermis and hair follicles, is abundantly expressed in germ cells, and is known to play a role in regulating the proliferation of keratinocytes.
  • nucleotide sequences of the genes can be found in the database provided by the National Center for Biotechnology Information (NCBI) maintained by the National Institutes of Health, the UniProt Knowledge Base (UniProtKB) and the Swiss-Prot database provided by the Swiss Bioinformatics Institute. It can be obtained from various DB engines, including , and can be appropriately selected by those skilled in the art.
  • NCBI National Center for Biotechnology Information
  • UniProtKB UniProt Knowledge Base
  • Swiss-Prot database provided by the Swiss Bioinformatics Institute. It can be obtained from various DB engines, including , and can be appropriately selected by those skilled in the art.
  • the marker gene for diagnosing pancreatic cancer may include one or more genes selected from the group consisting of MIRLET7BHG, EPS8L2, TRPC6, AVPR1A, and TBCD, or a CpG region thereof.
  • a marker gene for diagnosing pancreatic cancer may include each of the above genes or their CpG regions alone, or may include a combination of two or more marker genes or their CpG regions selected from the above genes.
  • the marker gene for diagnosing pancreatic cancer can be used in combination with other marker genes known in the art for diagnosing pancreatic cancer, such as a pancreatic cancer diagnostic marker gene such as BNC1.
  • the marker gene for diagnosing pancreatic cancer may be or include MIRLET7BHG or its CpG region.
  • the marker gene for pancreatic cancer diagnosis may be or include EPS8L2 or its CpG region.
  • the marker gene for diagnosing pancreatic cancer may be or include TRPC6 or its CpG region.
  • the marker gene for diagnosing pancreatic cancer may be or include AVPR1A or its CpG region.
  • the marker gene for diagnosing pancreatic cancer may be or include TBCD or its CpG region.
  • the marker gene for diagnosing pancreatic cancer includes MIRLET7BHG or a CpG region thereof, and may include one or more genes selected from the group consisting of TRPC6, AVPR1A, EPS8L2, TBCD, and BNC1, or a CpG region thereof.
  • the marker gene for diagnosing pancreatic cancer includes MIRLET7BHG or a CpG region thereof, and may include one or more genes selected from the group consisting of EPS8L2 and BNC1 or a CpG region thereof.
  • the marker gene for diagnosing pancreatic cancer may further include TRPC6 or its CpG region, TBCD or its CpG region, or AVPR1A or its CpG region.
  • the marker gene for diagnosing pancreatic cancer may be or include a combination of MIRLET7BHG or a CpG region thereof and EPS8L2 or a CpG region thereof.
  • the marker gene for diagnosing pancreatic cancer may be or include a combination of MIRLET7BHG or a CpG region thereof and TRPC6 or a CpG region thereof.
  • the marker gene for diagnosing pancreatic cancer may be or include a combination of MIRLET7BHG or a CpG region thereof and AVPR1A or a CpG region thereof.
  • the marker gene for pancreatic cancer diagnosis may be or include a combination of MIRLET7BHG or a CpG region thereof, EPS8L2 or a CpG region thereof, and TBCD or a CpG region thereof.
  • a marker gene for diagnosing pancreatic cancer can be used for diagnosing pancreatic cancer in combination with BNC1 or its CpG region.
  • the marker gene for diagnosing pancreatic cancer may include the following combination of marker genes or CpG regions thereof:
  • the marker gene for diagnosing pancreatic cancer may include TBCD or a CpG region thereof, EPS8L2 or a CpG region thereof, or both. These marker genes can be used in combination with other marker genes known in the art for diagnosing pancreatic cancer, such as BNC1.
  • the marker gene for diagnosing pancreatic cancer may include the following combination of marker genes or CpG regions thereof:
  • the methylation marker gene can diagnose pancreatic cancer with excellent sensitivity, specificity, and/or accuracy based on a biological sample isolated from an individual, such as a liquid sample, or provide information regarding the diagnosis of pancreatic cancer.
  • the methylation marker gene enables non-invasive diagnosis in that it shows excellent diagnostic accuracy when using liquid samples such as blood, plasma, and serum.
  • methylation refers to the attachment of a methyl group to the bases that make up DNA.
  • the methylation status may mean whether or not methylation occurs at a cytosine in a specific CpG region of a specific gene or the degree of methylation. If methylation occurs, it may interfere with the binding of transcription factors and suppress the expression of the gene in question. Expression suppression may occur relative to the degree of methylation. Conversely, when unmethylation or hypomethylation occurs, the expression of certain genes may increase. For this reason, DNA methylation is an epigenetic modification that plays a central role in regulating gene expression. A methyl group (-CH3) is attached to the 5th carbon of cytosine, transforming it into 5-methylcytosine. DNA methylation mainly occurs at the cytosine group of CpG dinucleotides and occurs in DNA regions where CpGs are concentrated, called CpG islands or CpG regions.
  • CpG region refers to a region of the DNA of a gene or a portion thereof where CpGs are concentrated, called a CpG island.
  • the CpG region may exist in a transcriptional control region such as a promoter region, a protein coding region (open reading frame, ORF), or a terminator region. It is known that during the course of cancer, DNA hypomethylation occurs throughout the genome, and local hypermethylation occurs frequently in some regions of CpG islands. For example, in cancer cells, if the CpG region of the promoter region of a cancer suppressor gene is abnormally hypermethylated, the expression of this gene may be suppressed, causing cancer. Methylation of CpG sites occurs early in cancer development, so it is useful for early diagnosis of cancer.
  • the CpG region of the gene may be a continuous sequence of 200 bp or more in which C and G are linked by phosphate, and may have any size ranging from 1 kb to 9 kb.
  • the CpG region of the gene may be located between +/- 2000 bases (2 kb) from the transcription start site (TSS) of the gene.
  • the CpG region of the gene may be the CpG region of the gene listed in Table 1 below or the methylation state of a portion of the cytosine contained therein. In Table 1 below, the CpG region is indicated as DMR (Differentially Methylated Region).
  • the base sequence of the human genome chromosome region is expressed according to The February 2009 Human reference sequence (GRCh37), but the specific sequence of the human genome chromosome region may change somewhat as the results of genome sequence research are updated. , depending on these changes, the expression of the human genomic chromosomal region of the present invention may be different. Accordingly, the human genome chromosomal region expressed according to The February 2009 Human reference sequence (GRCh37) of the present invention has been updated as a human reference sequence after the filing date of the present invention, so that the expression of the human genomic chromosomal region is the same as now. Even if it is changed differently, it will be obvious that the scope of the present invention extends to the changed human genome chromosomal region. These changes can be easily known by anyone with ordinary knowledge in the technical field to which the present invention pertains.
  • a method for providing information for diagnosing pancreatic cancer or a method for diagnosing pancreatic cancer comprising measuring the methylation status of the above-described marker gene or its CpG region in nucleic acid isolated from a biological sample of an individual. do.
  • a method for detecting a methylation marker in an individual suspected of having or at risk of developing pancreatic cancer comprising determining the methylation status of the marker gene or CpG region thereof in a sample obtained from the individual. do.
  • subject refers to mammals in need of a diagnosis of pancreatic cancer, such as primates (e.g. humans), companion animals (e.g. dogs, cats, etc.), domestic animals (e.g. cattle, pigs, horses, sheep, etc.) goats, etc.) and laboratory animals (e.g. rats, mice, guinea pigs, etc.).
  • primates e.g. humans
  • companion animals e.g. dogs, cats, etc.
  • domestic animals e.g. cattle, pigs, horses, sheep, etc.
  • laboratory animals e.g. rats, mice, guinea pigs, etc.
  • the individual is a human.
  • the biological sample may be, but is not limited to, blood, plasma, or serum.
  • the nucleic acid isolated from the biological sample may be cfDNA.
  • cfDNA refers to cell free DNA among genomic DNA.
  • Methods for separating or isolating genomic DNA or fragments thereof from the biological sample include phenol/chloroform extraction and SDS extraction (Tai et al., Plant Mol. Biol. Reporter, 8: 297-303, 1990) commonly used in the art. ), CTAB separation method (Cetyl Trimethyl Ammonium Bromide; Murray et al., Nuc. Res., 4321-4325, 1980), or a commercially available DNA extraction kit.
  • the biological sample may be subjected to a process of destruction and dissolution by enzymatic, chemical, or mechanical means.
  • Proteins and other contaminants are then removed from the DNA solution, for example by digestion with proteinase K, and genomic DNA is recovered from the solution.
  • Purification of DNA can be performed by a variety of methods, including salting out, organic extraction, or binding of DNA to a solid phase support. DNA isolation and purification methods can be selected by those skilled in the art taking into account several factors including time, cost, and required amount of DNA.
  • sample DNA when the sample DNA is not surrounded by a membrane (e.g., circulating or free DNA from a blood sample), standard methods in the art for isolation and/or purification of DNA can be used.
  • the method includes protein denaturing reagents, such as chaotropic salts such as guanidine hydrochloride or urea; or the use of detergents such as sodium dodecyl sulfate (SDS), cyanogen bromide.
  • chaotropic salts such as guanidine hydrochloride or urea
  • detergents such as sodium dodecyl sulfate (SDS), cyanogen bromide.
  • Alternative methods include, but are not limited to, ethanol precipitation or propanol precipitation, especially vacuum concentration by centrifugation.
  • filter devices e.g., ultrafiltration, silica surfaces or membranes, magnetic particles, polystyrol particles, polystyrol surfaces, positively charged surfaces and positively charged membranes, charged A charged film, a charged surface, a charged conversion film, or a charged conversion surface can be used.
  • DNA separated or isolated from the biological sample can be used as a method to measure the methylation status of the marker gene described above.
  • the step of measuring the methylation status comprises i) an agent that detects the methylation status of one or more genes or CpG regions thereof described above and/or ii) an agent that specifically detects the methylation state of one or more genes or CpG regions thereof described above. It may include the step of treating the DNA with a primer to amplify.
  • the agent that detects (or measures) the methylation status may be a compound that modifies a cytosine base or a methylation-sensitive restriction enzyme.
  • the compound that modifies the cytosine base may be a compound that modifies unmethylated cytosine or methylated cytosine. Specifically, it may be any one selected from the group consisting of bisulfite, hydrogen sulfite, disulfite, salts thereof, and combinations thereof. Additionally, it may be a TET protein that modifies methylated cytosine, but is not limited thereto. Methods for detecting methylation of a CpG region by modifying cytosine bases are well known in the art.
  • the methylation-sensitive restriction enzyme is a restriction enzyme that can specifically detect methylation of the CpG region and may be a restriction enzyme that contains CG as a recognition site.
  • a restriction enzyme that contains CG as a recognition site.
  • SmaI, SacII, EagI, HpaII, MspI, BssII, BstUI, NotI, etc. but are not limited thereto.
  • cleavage by restriction enzymes varies and can be detected through PCR or Southern Blot analysis.
  • Other methylation-sensitive restriction enzymes other than the above restriction enzymes are well known in the art.
  • the primers may include primers specific to the methylated allele sequence and/or primers specific to the unmethylated allele sequence of the one or more aforementioned marker genes.
  • the step of measuring the methylation status includes methylation-specific polymerase chain reaction, real time methylation-specific polymerase chain reaction, methylation It may be performed by, but is not limited to, PCR using a DNA-specific binding protein, quantitative PCR, pyrosequencing, or bisulfite sequencing. Other examples of PCR or sequencing listed above include MethyLight PCR, MehtyLight digital PCR, EpiTYPER, CpG island microarray, etc. Additionally, it can be measured using a detection method using TET protein (ten-eleven translocation protein).
  • TET protein ten-eleven translocation protein.
  • the TET protein is an enzyme that acts on DNA and is involved in the chemical change of bases. When treated with bisulfite, all Cs except methylated C are changed to T bases, but in TET protein, only methylated C is changed to T, making it efficient. Detection is possible.
  • the method may further include comparing the measured methylation level with the methylation level of the same marker gene or CpG region thereof in a control sample.
  • the step of measuring the methylation status may further include comparing the methylation profile with a control methylation profile generated from the corresponding methylation measurement result of the corresponding marker gene in the control sample.
  • control methylation profile constitutes a model constructed by machine learning the methylation patterns of one or more genes obtained, and may be used to identify pancreatic cancer patient-specific methylation patterns that are different from normal controls.
  • the machine learning may be performed by one or more algorithms selected from the group consisting of random forest, logistic regression, support vector machine, decision tree, association rule mining, neural network, and deep learning.
  • control sample may be a sample from a normal individual. Additionally, the control sample may be a sample from a pancreatic cancer patient, and the pancreatic cancer patient may be a patient with various pancreatic cancer stages.
  • the pancreatic cancer may be early pancreatic cancer, metastatic pancreatic cancer, or recurrent or refractory pancreatic cancer. At this time, each pancreatic cancer may have various stages.
  • the method for diagnosing pancreatic cancer or providing information for diagnosing pancreatic cancer according to the present invention includes (i) isolating nucleic acid from a biological sample of an individual, (ii) from the isolated nucleic acid, bisulfite, Processing any one selected from the group consisting of hydrogen sulfite, disulfite, salts thereof, and combinations thereof, (iii) amplifying the nucleic acid using primers specific for the marker gene described above. , and (iv) the marker genes described above by methylation-specific polymerase chain reaction, real-time methylation-specific polymerase chain reaction, PCR using methylated DNA-specific binding protein, quantitative PCR, pyrosequencing, or bisulfite sequencing. It may be implemented including measuring the methylation level of one or more CpG regions.
  • pancreatic cancer there is a method of treating pancreatic cancer, wherein (i) the above-described marker gene or its CpG region in the nucleic acid isolated from the biological sample of the individual is in a hypomethylated or hypermethylated state compared to the normal control group. detecting; and (ii) administering therapy for pancreatic cancer in said individual.
  • the method of treatment includes confirming that the subject has pancreatic cancer through additional analysis or diagnostic methods, such as tissue biopsy, before step (ii) when a hypomethylated state or a hypermethylated state is detected. Additional items may be included.
  • the treatment for pancreatic cancer may include surgery, radiation therapy, chemotherapy, targeted therapy, or a combination thereof, depending on the stage.
  • each marker gene such as each marker gene, “biological sample,” “CpG region,” “methylation,” and method for detecting methylation status, please refer to the above.
  • composition for diagnosing pancreatic cancer Composition for diagnosing pancreatic cancer
  • a composition comprising an agent for detecting or measuring the methylation status of one or more genes selected from the group consisting of the above-described marker genes or CpG regions thereof.
  • it is a composition for diagnosing pancreatic cancer using nucleic acids isolated from biological samples, and is an agent capable of specifically amplifying or hybridizing one or more genes or their CpG regions selected from the group consisting of the above-mentioned marker genes, and
  • a composition comprising one or more agents selected from agents that detect the methylation status of the one or more marker genes or CpG regions thereof is provided.
  • hybridization can be understood as the binding of an oligonucleotide to a complementary sequence similar to Watson-Crick base pairs in sample DNA, forming a duplex structure.
  • the biological sample may be, but is not limited to, blood, plasma, or serum.
  • the nucleic acid isolated from the biological sample may be cfDNA.
  • the agent may include one or more oligonucleotides, such as primers, probes, or antisense nucleotides, that bind complementary to the gene.
  • primer used in the present invention refers to a nucleic acid sequence that can form a base pair with a complementary template of a gene in a sample and serves as a starting point for copying the template strand.
  • the sequence of the primer does not necessarily have to be exactly the same as the sequence of the template, but just needs to be sufficiently complementary to hybridize with the template.
  • Primers can initiate DNA synthesis in the presence of four different nucleoside triphosphates and reagents for polymerization at appropriate buffer solutions and temperatures. PCR conditions and lengths of sense and antisense primers can be modified based on those known in the art.
  • probe used in the present invention refers to a substance that can specifically bind to a gene to be detected in a sample, and can specifically confirm the presence of the gene in the sample through this binding.
  • Probes may be manufactured in the form of oligonucleotide probes, single-stranded DNA probes, double-stranded DNA probes, RNA probes, etc. Selection of appropriate probes and hybridization conditions can be modified based on those known in the art.
  • antisense nucleotide used in the present invention refers to a nucleic acid-based molecule that has a complementary sequence to the target gene and can form a dimer with the target gene, and can be used to detect the target gene.
  • the antisense nucleotide may be of an appropriate length to increase detection specificity.
  • oligonucleotides such as primers, probes or antisense nucleotides can be preferably designed using known knowledge and techniques known in the art according to the sequence of a specific CpG region whose methylation status is to be analyzed.
  • the composition may include an agent for detecting the methylation status of the CpG region of the gene.
  • agent for detecting the methylation status please refer to the previous description.
  • the agent may be bisulfite, hydrogen sulfite, disulfite, a salt thereof, or a combination thereof.
  • the agent is not limited thereto.
  • Compounds that modify unmethylated cytosine bases, such as bisulfite, hydrogen sulfite, and disulfite, and methods for detecting methylation of genes by modifying unmethylated cytosine residues using the same are well known in the art. (WO 01/26536; US 2003/0148326 A1).
  • NGS can be used to determine the presence and extent of methylation by confirming the degree of conversion of the base sequence of the target gene region. Sequence analysis by NGS was performed using Illumina's MiSeq, NextSeq500, NextSeq550, Hiseq 2500, Hiseq 4000, Hiseq It can be performed using MGISEQ-T7, etc., but is not limited to this.
  • compositions for diagnosing pancreatic cancer using nucleic acids isolated from biological samples including an agent for detecting the methylation status of one or more genes selected from the group consisting of the above-described marker genes or a CpG region thereof. .
  • kits for diagnosing pancreatic cancer using nucleic acid isolated from a biological sample of an individual including the composition is provided.
  • a kit containing an agent for detecting or measuring the methylation status of one or more genes selected from the group consisting of the above-mentioned marker genes or their CpG region is provided.
  • the kit includes (i) one or more oligonucleotides, such as primers, that can hybridize under stringent or moderately stringent conditions to one or more of the pancreatic cancer-specific genes described above that are methylated in cancer but not methylated in non-cancerous tissue; Probe or antisense nucleotide; (ii) a container suitable for containing one or more oligonucleotides, such as primers, probes or antisense nucleotides, capable of hybridizing to the gene and a biological sample of interest (e.g., a nucleic acid isolated from the biological sample); (iii) means for detecting hybridization of (ii); and/or optionally (iv) instructions for use and interpretation of kit results.
  • one or more oligonucleotides such as primers, that can hybridize under stringent or moderately stringent conditions to one or more of the pancreatic cancer-specific genes described above that are methylated in cancer but not methylated in non-cancerous tissue
  • the kit may also contain other components, including hybridization solution, packaged in separate containers.
  • hybridization solution the nucleic acid of the gene and a plurality of primers, probes, or antisense nucleotides may hybridize.
  • the kit consists of one or more different component compositions, solutions, or devices suitable for the analysis method.
  • the kit may be a reverse transcription polymerase chain reaction (RT-PCR) kit, a DNA chip kit, an enzyme-linked immunosorbent assay (ELISA) kit, a protein chip kit, or a rapid kit.
  • RT-PCR reverse transcription polymerase chain reaction
  • ELISA enzyme-linked immunosorbent assay
  • the kit may additionally include polymerase agarose, a buffer solution required for electrophoresis, etc.
  • the kit is a diagnostic nucleic acid chip (CHIP) on which a probe capable of hybridizing with a target gene to be detected including the one or more marker genes or a CpG region thereof or a fragment including a CpG region thereof is immobilized, or May include a genetic panel.
  • CHIP diagnostic nucleic acid chip
  • a diagnostic nucleic acid chip or gene on which a probe capable of hybridizing with a detection target gene containing the above-described one or more marker genes or a CpG region thereof or a fragment containing a CpG region thereof is immobilized is provided.
  • the nucleic acid chip may be characterized in that an array of oligonucleotides and/or PNA (Peptide Nucleic Acid)-oligomers are bound to a solid phase and arranged on a solid phase, for example, in the form of a rectangular or hexagonal lattice.
  • the solid surface may be made of silicon, glass, polystyrene, aluminum, steel, iron, copper, nickel, silver or gold. Additionally, plastics such as nitrocellulose and nylon, which may exist in the form of pellets or also as a resin matrix, may also be used.
  • the oligonucleotide can be interpreted as a concept that includes all primers, probes, or antisense nucleotides, and the “PNA” refers to an artificially synthesized oligonucleotide.
  • Fluorescently labeled probes can also be used for scanning immobilized DNA chips, and the simple binding of Cy3 and Cy5 dyes to the 5'-OH of specific probes is particularly suitable for fluorescent labeling. Fluorescence detection of hybridized probes can be performed, for example, by confocal microscopy.
  • pancreatic cancer was classified from stage 0 to stage 4 by gastroenterologists according to the TNM staging system and the American Joint Committee on Cancer (AJCC) staging system.
  • AJCC American Joint Committee on Cancer
  • each sample was centrifuged at 3000 rpm for 15 minutes to separate plasma.
  • Extraction of cell-free DNA from separated plasma was performed using the MagMAXTM Cell-Free DNA Isolation Kit (Thermo fisher scientific). The extraction method was performed according to the manufacturer's manual.
  • Extracted cell-free DNA was quantified using a fluorescence intensity meter (Qubit Flex, Invitrogen), and DNA status was checked for DNA degradation and size using automated electrophoresis equipment (4150 Tapestation system, Agilent). .
  • Example 2 The cell-free DNA extracted in Example 2 was treated with bisulfite using the EZ DNA methylation-LightningTM kit (Zymo Research, USA).
  • Accel-NGS® Methyl-Seq DNA Library Kit (Swift Biosciences, USA) was used as a preparation reagent for library production. This process includes methylation adapter ligation, indexing of the library, and pure isolation of ligated DNA using AMPure XP beads.
  • the bisulfite-library was designed as a single mixing reaction using the fabricated panel, and the library was completed using the SureSelectXT Human Methyl Seq Kit (Agilent, USA). This process includes library hybridization, hybrid capture using streptavidin beads, library amplification, and pure separation using AMPure XP beads.
  • the length and amount of the library were measured using an Agilent Bioanalyzer 2200 (Agilent, USA) instrument and a high sensitivity chip, and the quality control (QC) conditions suggested by the manufacturer were measured. Satisfactory libraries were used for sequence analysis.
  • Bisulfite sequencing was performed on the library produced in Example 3 using next-generation sequencing equipment (NovaSeq 6000, Illumina). Quantity of bases produced from sequencing equipment, quality score (Q30), on-target ratio, average number of reads required for analysis by target region, Unique Molecular Identifier (UMI) duplication ratio, mapping The quality of the generated data was evaluated by checking the amount of data generated. Afterwards, a total of 3.7 million CpG sites out of 84 million bases of cell-free DNA were targeted and their methylation levels were analyzed.
  • next-generation sequencing equipment NovaSeq 6000, Illumina. Quantity of bases produced from sequencing equipment, quality score (Q30), on-target ratio, average number of reads required for analysis by target region, Unique Molecular Identifier (UMI) duplication ratio, mapping
  • UMI Unique Molecular Identifier
  • the degree of DNA methylation was measured for a total of 3.7 million CpG loci, which were the target regions captured in Example 4.
  • the calculated degree of methylation is expressed as a value ranging from 0 to 1, where a value of 0 means that the corresponding CpG locus is not completely methylated, and a value of 1 means that the corresponding CpG locus is completely methylated.
  • DMRs differentially methylated regions
  • the evaluation was conducted on a gene and DMR basis, and was conducted as a leave-one-out test using several machine learning algorithms.
  • the machine learning algorithms used were Support Vector Machine, Random Forest, Neural Network, and Deep Learning.
  • the 11 genes whose methylation levels were differentially changed in the pancreatic cancer patient group and the DMRs contained in each gene were selected (Table 2).
  • the 11 genes consisted of existing genes (BNC1) and novel genes (XXXLT1, ZNF879, EPS8L2, TRPC6, AVPR1A, GSC, TBCD, MAFB, TCEA2, and MIRLET7BHG).
  • Methylation levels in the DMRs of the above 11 genes using samples from 33 pancreatic cancer patients and 42 normal controls were analyzed through target region-based bisulfite sequencing, and the results are shown in Figure 2.
  • a pancreatic cancer identification model was established using a machine learning algorithm based on the methylation level in the DMR region present in the marker gene discovered in Example 5.
  • a typical modeling program is created through explicit programming in which the developer pre-programs it to output the final result when certain conditions are met for the initial input values.
  • machine learning trains the computer to find conditions under which the result will be a specific value when the initial input value is received. This learning process is a process of finding optimal parameters so that the result value can be properly derived for the input value, and the result of learning is the optimal parameter or weight value.
  • a model established using machine learning algorithms such as deep learning or neural networks can identify pancreatic cancer patient-specific methylation patterns that are different from normal controls by learning the methylation patterns of marker gene regions obtained from multiple normal control and pancreatic cancer patient samples. It can be said to be a mathematical model created for this purpose. Using the model created in this way, it is possible to infer and predict new patterns of data. Accordingly, the established model evaluates whether a given test sample shows a methylation pattern that appears in a pancreatic cancer patient sample, and derives a determination result as to whether the subject from which the test sample is derived is normal or has pancreatic cancer.
  • Deep learning algorithms are a type of machine learning that performs learning using multiple layers of artificial neural networks.
  • data analysts must be directly involved in determining which features should be extracted from the training data, while in the case of deep learning, the computer automatically extracts features from the training data and performs self-learning.
  • Table 3 The results of these deep learning tests are shown in Table 3.
  • Table 3 shows the sensitivity, specificity, and accuracy values calculated for the model established based on 2 to 3 of the 11 marker genes discovered in the present invention, as well as the corresponding values calculated when these genes are applied as single markers. The figures are presented together.
  • the sensitivity values obtained by performing a leave-one-out test using samples from 33 patients and 42 normal controls for the combination model of the methylation marker genes BNC1 and MIRLET7BHG are summarized by pancreatic cancer stage in Figure 3. Shown. As can be seen from Figure 3, the model showed a sensitivity of 50% for stage 1 and 100% for stages 2 to 4.
  • Non-patent Document 1 Eissa, Maryam AL, et al. Clinical epigenetics 11.1 (2019): 1-10; and Non-patent Document 2: Yi, Joo Mi, et al. al.
  • non-patent document 1 measured diagnostic markers for pancreatic cancer by performing quantitative methylation specific PCR (Quantitative Methylation Specific PCR). Specifically, in the case of non-patent document 1, a TaqMan probe was used, and in the case of non-patent document 2, SYBR was used.
  • Non-patent Document 1 Non-patent Document 2 genetic combination BNC1 ADAMTS1 BNC1+ ADAMTS1 BNC1 ADAMTS1 BNC1+ ADAMTS1 responsiveness(%) 64.1% 87.2% 97.3% 79.0% 48.0% 81.0% Specificity (%) 93.7% 95.8% 91.6% 89.0% 92.0% 85.0%
  • pancreatic cancer markers and their combinations identified in Examples 1 to 6 of the present invention were proven to be superior in terms of sensitivity, specificity, and accuracy (Table 3).
  • the combination of marker genes including BNC1, an existing marker gene, and MIRLET7BHG, a new marker was confirmed as an excellent marker in stages 2 to 4 pancreatic cancer, and also showed effective results in stage 1 pancreatic cancer (Figure 3), making it suitable for early diagnosis of pancreatic cancer. It can be useful.

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Abstract

La présente invention concerne un gène marqueur méthylé pour le diagnostic du cancer du pancréas et son utilisation. En tant qu'alternative au difficile diagnostic précoce du cancer du pancréas, la présente invention vise à améliorer la sensibilité, la spécificité et la précision du diagnostic par introduction d'un procédé d'analyse de méthylation à l'aide d'ADN libre circulant (ADNcf) dans le plasma. Un gène marqueur méthylé dont le niveau de méthylation est modifié de manière différentielle dans le groupe de patients avec un cancer du pancréas a été identifié selon la présente invention. Ainsi, le gène marqueur de méthylation de la présente invention peut être utilisé efficacement dans le diagnostic du cancer du pancréas.
PCT/KR2023/015604 2022-10-11 2023-10-11 Gènes marqueurs de méthylation pour le diagnostic du cancer du pancréas et leur utilisation WO2024080731A1 (fr)

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