WO2021241980A1 - Composition pour la prédiction de pronostic de cancer et kit la comprenant - Google Patents

Composition pour la prédiction de pronostic de cancer et kit la comprenant Download PDF

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WO2021241980A1
WO2021241980A1 PCT/KR2021/006492 KR2021006492W WO2021241980A1 WO 2021241980 A1 WO2021241980 A1 WO 2021241980A1 KR 2021006492 W KR2021006492 W KR 2021006492W WO 2021241980 A1 WO2021241980 A1 WO 2021241980A1
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cancer
acta2
znf667
fendrr
group
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PCT/KR2021/006492
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Korean (ko)
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정재호
신민규
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연세대학교 산학협력단
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • 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
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/136—Screening for pharmacological compounds
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to a composition for predicting cancer prognosis, a kit comprising the same, and a method for predicting cancer prognosis.
  • Cancer is a cell mass composed of undifferentiated cells that proliferate indefinitely while ignoring the necessary condition in the tissue, unlike normal cells, which can proliferate and suppress regularly and in a controlled manner according to individual needs.
  • Such unrestricted proliferation of cancer cells infiltrates into surrounding tissues and, in more severe cases, metastasizes to other organs of the body, causing severe pain and eventually death.
  • Cancer is broadly classified into blood cancer and solid cancer, and occurs in almost all parts of the body, such as stomach cancer, pancreatic cancer, breast cancer, oral cancer, liver cancer, uterine cancer, esophageal cancer, and skin cancer.
  • therapeutic agents are being used for the treatment of specific cancers, surgery, radiation therapy, and anticancer drug treatment using chemotherapeutic agents that inhibit cell proliferation are the main methods up to now.
  • chemotherapeutic agents since it is not a targeted therapy, the biggest problem with existing chemotherapeutic agents is the side effects and drug resistance due to cytotoxicity, which is a major factor that ultimately causes the treatment to fail despite the initial successful response to the anticancer agent. Therefore, in order to overcome the limitations of these chemotherapeutic agents, there is a continuous need to develop targeted therapeutics with a clear anticancer mechanism.
  • Gastric cancer is the third leading cause of cancer-related death and ranks fourth among the most common cancers.
  • personalized pharmaceuticals clinically and biologically close molecular analysis is required.
  • understanding of biological complexity has been improved through omics studies of gastric cancer at the whole genome level, and in particular, prognosis using biomarkers and responsiveness to adjuvant chemotherapy through analysis of mRNA gene expression data.
  • Great advances have been made in forecasting.
  • Molecular profiling at different levels in gastric cancer is expected to lead to the development of personalized treatment strategies.
  • lncRNA long non-coding RNA
  • the lncRNA acts as an important substance in the path of cancer, and is related to the development and progression of cancer.
  • the lncRNA is a transcript of 200 or more nucleotides without protein-coding potential. They have a higher number of constituent nucleotides than the protein-coding gene, are restricted to specific cell/tissue types to a greater extent than mRNA, and are promising as cancer-type specific therapeutic targets.
  • RNA-targeting Nucleic acid-based (RNA-targeting) therapeutics have shown clinical success in several diseases and preclinical success in some cancers by targeting lncRNA. However, there have been no reports of lncRNA targets in gastric cancer, and sufficient studies have not been conducted on their clinical relevance and biological functions.
  • One object of the present invention is to provide a biomarker composition for predicting the diagnosis, prognosis or therapeutic responsiveness of cancer.
  • Another object of the present invention is to provide a composition for diagnosing cancer, prognosis or predicting therapeutic responsiveness, and a kit comprising the same.
  • Another object of the present invention is to provide a method for providing information for predicting diagnosis, prognosis, or treatment responsiveness of cancer.
  • cancer is gastric cancer, ovarian cancer, colorectal cancer, breast cancer, liver cancer, pancreatic cancer, cervical cancer, thyroid cancer, parathyroid cancer, non-small cell lung cancer, prostate cancer, gallbladder cancer, biliary tract cancer, non-Hodgkin's lymphoma, Hodgkin's lymphoma, blood Cancer, bladder cancer, kidney cancer, melanoma, colon cancer, bone cancer, skin cancer, head cancer, uterine cancer, rectal cancer, brain tumor, perianal cancer, fallopian tube carcinoma, endometrial carcinoma, vaginal cancer, vulvar carcinoma, esophageal cancer, small intestine cancer, endocrine adenocarcinoma, part It may be renal cancer, soft tissue sarcoma, urethral cancer, penile cancer, ureter cancer, renal cell carcinoma, renal pelvic carcinoma, CNS central nervoussystem tumor, primary CNS lymphoma, spinal cord tumor, brainstem glioma or pituitary
  • ZNF667-AS1 ZNF667 Antisense RNA 1 (Head To Head)
  • RP11-572C15.6 FENDRR (FOXF1 Adjacent Non-Coding Developmental Regulatory RNA)
  • ACTA2-AS1 ACTA2 Antisense RNA 1
  • ZNF667-AS1 ZNF667 Antisense RNA 1 (Head To Head)
  • RP11-572C15.6 FENDRR
  • FENDRR F1 Adjacent Non-Coding Developmental Regulatory RNA
  • ACTA2-AS1 ACTA2 Antisense RNA 1
  • ACTA2 Antisense RNA 1 each are long-ratio
  • the ZNF667-AS1 may be represented by SEQ ID NO: 1
  • the RP11-572C15.6 may be represented by SEQ ID NO: 2
  • the FENDRR is SEQ ID NO: 3
  • the ACTA2-AS1 may be represented by SEQ ID NO: 4, but is not limited thereto.
  • biomarker composition for diagnosis of cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1.
  • the "target individual” refers to an individual who is uncertain whether or not the onset of the cancer has a high probability of onset.
  • the "biological sample” refers to any material, biological fluid, tissue or cell obtained from or derived from an individual, for example, whole blood, leukocytes, peripheral blood mononuclear peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate (nasal aspirate), breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid , amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid), joint aspirate, organ secretions, cells, cell extract, or cerebrospinal fluid, but is not limited thereto.
  • control group may be a normal control group that does not develop cancer.
  • the "diagnosis” refers to determining the susceptibility of a subject to a specific disease or disorder, determining whether the subject currently has a specific disease or disorder, or having a specific disease or disorder Determining a subject's prognosis (e.g., identifying a pre-metastatic or metastatic cancer state, staging the cancer, or determining the responsiveness of a cancer to treatment), or therametrics (e.g., for treatment efficacy); monitoring the state of an object to provide information).
  • the diagnosis is to determine whether or not the above-described cancer is onset or the possibility (risk) of the occurrence.
  • composition for diagnosis of cancer comprising an agent capable of measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1.
  • the agent capable of measuring the expression level of RP11-572C15.6, FENDRR or ACTA2-AS1 may include one or more selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene.
  • the "primer” is a fragment recognizing a target gene sequence, including a pair of forward and reverse primers, but preferably, a primer pair that provides analysis results having specificity and sensitivity. High specificity can be conferred when the primer's nucleic acid sequence is a sequence that is inconsistent with a non-target sequence present in the sample, thus amplifying only the target gene sequence containing the complementary primer binding site and not causing non-specific amplification. .
  • the "probe” refers to a substance capable of specifically binding to a target substance to be detected in a sample, and refers to a substance capable of specifically confirming the presence of a target substance in a sample through the binding.
  • the type of probe is not limited as a material commonly used in the art, but preferably PNA (peptide nucleic acid), LNA (locked nucleic acid), peptide, polypeptide, protein, RNA or DNA, and most preferably It is PNA.
  • the probe is a biomaterial derived from or similar thereto, or manufactured in vitro, and includes, for example, enzymes, proteins, antibodies, microorganisms, animal and plant cells and organs, neurons, DNA, and It may be RNA, and DNA includes cDNA, genomic DNA, and oligonucleotides, RNA includes genomic RNA, mRNA, and oligonucleotides, and examples of proteins include antibodies, antigens, enzymes, peptides, and the like.
  • kits for diagnosis of cancer comprising the composition for diagnosis of cancer according to the present invention.
  • the kit of the present invention may include a primer, a probe, or an antisense nucleotide selectively recognizing a marker for diagnosis of cancer, as well as one or more other component compositions, solutions, or devices suitable for an analysis method.
  • the cancer diagnosis kit of the present invention may be a microarray chip kit, a gene amplification kit, or a nanostring kit, but is not limited thereto.
  • the present invention comprising measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 in a biological sample isolated from a subject of interest, It relates to a method of providing information for diagnosis of cancer.
  • the biological sample refers to any material, biological fluid, tissue or cell obtained from or derived from an individual, for example, whole blood, leukocytes, peripheral blood mononuclear cells ( peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum, tears, mucus, nasal washes, nasal aspirate aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid (amniotic fluid), glandular fluid, pancreatic fluid, lymph fluid, pleural fluid, nipple aspirate, bronchial aspirate, synovial fluid , joint aspirate, organ secretions, cells, cell extracts, or cerebrospinal fluid, but are not limited thereto.
  • peripheral blood mononuclear cells peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum, tears, mucus
  • nasal washes nasal aspirate aspirate, breath, urine, semen
  • the present invention may include measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 in the biological sample isolated as described above.
  • the agent for measuring the expression level of the RP11-572C15.6, FENDRR or ACTA2-AS1 gene may include one or more selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene. have.
  • RT-PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • cancer when the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 measured with respect to a biological sample of a target individual increases compared to the control group, cancer occurs or can be predicted to have a high probability of developing the disease.
  • a biomarker composition for predicting the prognosis of cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1.
  • control group is a normal control group without cancer, the median value of the patient population with cancer (or the average value of the patient), or the median value of the patient population with high treatment responsiveness among patients with cancer (or average value of the patient).
  • the term “prediction of prognosis” refers to a process of predicting the treatment result of a pathological condition by collecting data on the progress of the pathological state and the treatment process.
  • the prognosis prediction may be interpreted as determining the probability of death after treatment of cancer, or the probability of death due to recurrence or metastasis after treatment, but is not limited thereto.
  • composition for predicting the prognosis of cancer comprising an agent capable of measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 .
  • the agent capable of measuring the expression level of RP11-572C15.6, FENDRR or ACTA2-AS1 may include one or more selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene.
  • the analysis method for measuring the amount of the gene includes reverse transcription polymerase reaction (RT-PCR), Competitive RT-PCR, Real-time RT-PCR, RNase protection assay (RPA), Northern blotting, DNA chip, etc.
  • RT-PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • Northern blotting DNA chip, etc.
  • the present invention is not limited thereto.
  • kits for predicting the prognosis of cancer comprising the composition for predicting the prognosis of cancer according to the present invention.
  • the kit of the present invention may include a primer, a probe, or an antisense nucleotide that selectively recognizes a marker for predicting the prognosis of cancer, as well as one or more other component compositions, solutions, or devices suitable for the analysis method.
  • the kit for predicting cancer prognosis of the present invention may be a microarray chip kit, a gene amplification kit, or a nanostring kit, but is not limited thereto.
  • the present invention comprising measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 in a biological sample isolated from a subject of interest, It relates to a method of providing information for predicting the prognosis of cancer.
  • the biological sample is whole blood, leukocytes, peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum , tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid ), nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cell, cell extract or cerebrospinal fluid, but is not limited thereto.
  • the present invention may include measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 in the biological sample isolated as described above.
  • the agent for measuring the expression level of the RP11-572C15.6, FENDRR or ACTA2-AS1 gene may include one or more selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene. have.
  • RT-PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • the prognosis when the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1 measured with respect to the biological sample of the subject of the present invention is increased compared to the control group, the prognosis is poor can be predicted that
  • a biomarker composition for predicting therapeutic responsiveness to an anticancer agent for cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1, a biomarker composition for predicting therapeutic responsiveness to an anticancer agent for cancer would like to provide
  • the prognosis when the expression level of RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 is increased compared to the control in the biological sample isolated from the subject of interest, the prognosis can be predicted to be poor. have.
  • control group means a normal control group without cancer, the median value of the patient population with cancer (or the average value of the patient), or the median value of the patient population with high treatment responsiveness among patients with cancer (or average value of the patient).
  • the anticancer agent may be an immune anticancer agent or an immunotherapeutic agent.
  • the immunotherapy or immunotherapeutic agent includes monoclonal antibodies, chimeric antigen receptor (CAR) T-cells, NK-cells, dendritic cells (DC), adoptive cell transfer (ACT), immune checkpoint modulators, cytokines, cancer vaccine, adjuvant, oncolytic virus, or a combination thereof, wherein said monoclonal antibody is PD-1, PD-L1, CTLA-4, IDO, TIM-3, LAG-3, 4- a signaling molecule selected from the group consisting of 1BB, OX40, MERTK, CD27, GITR, B7.1, TGF- ⁇ , BTLA, VISTA, arginase, MICA, MICB, B7-H4, CD28, CD137, and HVEM; It may be to modulate, and a preferred example may be an anti-PD-1 antibody or an anti-PD-L1 antibody, and specific examples, i
  • immunotherapy refers to a method of treating a disease by stimulating the immune system, and in the present invention, it means treating gastrointestinal cancer.
  • Passive immunotherapy is a treatment method that attacks cancer cells by injecting immune response components, such as immune cells, antibodies, and cytokines, made in large amounts outside the body, into cancer patients. It is a therapeutic method that attacks cancer cells by activating or producing them.
  • therapeutic responsiveness prediction refers to predicting whether a patient will respond favorably or non-preferably to an immune anticancer agent, or predicting the risk of resistance to an anticancer agent, prognosis of a patient after immunotherapy That is, it means predicting recurrence, metastasis, survival, or disease-free survival.
  • RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 for an anticancer agent for cancer comprising an agent capable of measuring the expression level of one or more genes selected from the group consisting of It relates to a composition for predicting therapeutic responsiveness.
  • the agent capable of measuring the expression level of RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 is one selected from the group consisting of primers, probes and antisense nucleotides specifically binding to the gene. may include more than one.
  • RT -PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • the treatment responsiveness is predicted to be low.
  • kits for predicting therapeutic responsiveness to an anticancer agent for cancer comprising the composition for predicting the prognosis of cancer according to the present invention.
  • the kit of the present invention may include a primer, a probe, or an antisense nucleotide that selectively recognizes a marker for predicting the prognosis of cancer, as well as one or more other component compositions, solutions, or devices suitable for the analysis method.
  • the kit for predicting cancer prognosis of the present invention may be a microarray chip kit, a gene amplification kit, or a nanostring kit, but is not limited thereto.
  • measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 in a biological sample isolated from a subject of interest It relates to a method of providing information for predicting therapeutic responsiveness to an anticancer agent of cancer, including.
  • the biological sample is whole blood, leukocytes, peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum , tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid ), nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cell, cell extract or cerebrospinal fluid, but is not limited thereto.
  • the present invention may include measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 in the biological sample isolated as described above.
  • the agent for measuring the expression level of the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is at least one selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene may include
  • the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is a process for confirming the presence and expression level of the gene.
  • As an analysis method for measuring the amount of the gene reverse transcription polymerase reaction (RT-PCR) , Competitive RT-PCR, Real-time RT-PCR, RNase protection assay (RPA), Northern blotting, DNA chip, etc.
  • RT-PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • Northern blotting DNA chip, etc.
  • the present invention is not limited thereto.
  • the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 measured with respect to a biological sample of a target individual is increased compared to the control group , it can be predicted that the treatment responsiveness will be low.
  • cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1, epithelial-mesenchymal transition (EMT) ) to provide a diagnostic biomarker composition.
  • group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1, epithelial-mesenchymal transition (EMT) to provide a diagnostic biomarker composition.
  • epithelial mesenchymal metastasis subtype when the expression level of RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 is increased compared to the control in the biological sample isolated from the subject of interest, epithelial mesenchymal metastasis subtype can be predicted to be highly probable.
  • control group means a normal control group without cancer, the median value of the patient population with cancer (or the average value of the patient), or the median value of the patient population with high treatment responsiveness among patients with cancer (or average value of the patient).
  • epithelial mesenchymal transition refers to a process in which epithelial cells are transformed into mesenchymal cells. That is, it is a mutational process that loses the appearance of epithelial cells and acquires the characteristics of mesenchymal cells, which is known as an important process for individual formation and development, and is related to cancer cell growth, drug resistance, invasion and metastasis.
  • epithelial-middle of cancer comprising an agent capable of measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 It relates to a composition for diagnosing lobe metastasis (EMT).
  • EMT lobe metastasis
  • the agent capable of measuring the expression level of RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 is one selected from the group consisting of primers, probes and antisense nucleotides specifically binding to the gene. may include more than one.
  • RT -PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • epithelial mesenchymal metastasis subtype when the expression level of RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 is increased compared to the control in the biological sample isolated from the subject of interest, epithelial mesenchymal metastasis subtype can be predicted to be highly probable.
  • the present invention relates to a kit for diagnosing epithelial-mesenchymal metastasis (EMT) of cancer, comprising the composition for diagnosing epithelial-mesenchymal metastasis (EMT) of cancer according to the present invention.
  • EMT epithelial-mesenchymal metastasis
  • the kit of the present invention may include a primer, a probe, or an antisense nucleotide that selectively recognizes a marker for predicting the prognosis of cancer, as well as one or more other component compositions, solutions, or devices suitable for the analysis method.
  • the kit for predicting cancer prognosis of the present invention may be a microarray chip kit, a gene amplification kit, or a nanostring kit, but is not limited thereto.
  • measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 in a biological sample isolated from a subject of interest It relates to an information providing method for diagnosing epithelial-mesenchymal metastasis (EMT) of cancer, including.
  • EMT epithelial-mesenchymal metastasis
  • the biological sample is whole blood, leukocytes, peripheral blood mononuclear cells, buffy coat, plasma, serum, sputum , tears, mucus, nasal washes, nasal aspirate, breath, urine, semen, saliva, peritoneal washings, ascites, cystic fluid, meningeal fluid, amniotic fluid, glandular fluid, pancreatic fluid, lymph fluid, pleural fluid ), nipple aspirate, bronchial aspirate, synovial fluid, joint aspirate, organ secretions, cell, cell extract or cerebrospinal fluid, but is not limited thereto.
  • the present invention may include measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 in the biological sample isolated as described above.
  • the agent for measuring the expression level of the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is at least one selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene may include
  • the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is a process for confirming the presence and expression level of the gene.
  • As an analysis method for measuring the amount of the gene reverse transcription polymerase reaction (RT-PCR) , Competitive RT-PCR, Real-time RT-PCR, RNase protection assay (RPA), Northern blotting, DNA chip, etc.
  • RT-PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • Northern blotting DNA chip, etc.
  • the present invention is not limited thereto.
  • the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 measured with respect to a biological sample of a target individual is increased compared to the control group , it can be predicted that cancer cells are highly likely to contain epithelial-mesenchymal transition subtypes.
  • the method comprising: treating a candidate drug to a biological sample isolated from a cancer subject or an animal model of cancer; And measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 in a biological sample or cancer disease animal model treated with the candidate agent, It relates to a method of screening a drug for the prevention or treatment of cancer.
  • the agent for measuring the expression level of the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is at least one selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene may include
  • the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is a process for confirming the presence and expression level of the gene.
  • As an analysis method for measuring the amount of the gene reverse transcription polymerase reaction (RT-PCR) , Competitive RT-PCR, Real-time RT-PCR, RNase protection assay (RPA), Northern blotting, DNA chip, etc.
  • RT-PCR reverse transcription polymerase reaction
  • RPA RNase protection assay
  • Northern blotting DNA chip, etc.
  • the present invention is not limited thereto.
  • the candidate agent is used to prevent cancer or It may further include the step of determining the drug for treatment.
  • the method comprising: treating a candidate drug to a biological sample isolated from a cancer subject or an animal model of cancer; And measuring the expression level of one or more genes selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1 in a biological sample or cancer disease animal model treated with the candidate agent,
  • the present invention relates to a method for screening a substance that inhibits epithelial-mesenchymal cell metastasis (EMT) of cancer.
  • EMT epithelial-mesenchymal cell metastasis
  • the agent for measuring the expression level of the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is at least one selected from the group consisting of primers, probes and antisense nucleotides that specifically bind to the gene may include
  • the RP11-572C15.6, FENDRR, ACTA2-AS1 or ZNF667-AS1 gene is a process for confirming the presence and expression level of the gene.
  • As an analysis method for measuring the amount of the gene reverse transcription polymerase reaction (RT-PCR) , Competitive RTR, Real-time RT-PCR, RNase protection assay (RPA), Northern blotting, DNA chip, etc. It is not limited.
  • the candidate agent is administered to the epithelium of cancer- It may further comprise the step of determining as a mesenchymal cell metastasis inhibitor.
  • the present invention it is possible to accurately and conveniently diagnose gastric cancer, particularly among cancers, at an early stage, and furthermore, it is possible to predict the prognosis of cancer or the therapeutic responsiveness to an anticancer agent, so that the most appropriate treatment method for cancer patients can be selected.
  • Each data is presented in matrix form, with rows representing individual genes and columns representing each tissue.
  • each cell represents the expression level of a gene in an individual tissue, and red and green represent the relative high and low expression levels represented by scale bars (log2 conversion scale).
  • Fig. 2 shows the prognostic relevance of LNC6 subtypes
  • Figure 2b shows a phylogenetic tree in the predictive model, and the patients were classified into subtypes with high predictability.
  • OS overall survival
  • RFS recurrence-free survival
  • RFS recurrence-free survival period
  • Fig. 4 relates to a subset of L6C anticancer drug resistance and epithelial phenotype
  • This analysis included AJCC stage II, III, or IV patients without primary metastasis.
  • CTX relapse-free survival
  • Figure 5a shows the responsiveness to pembrolizumab according to the LNC6 subtype, and
  • Figures 5b and 5c show the therapeutic responsiveness
  • the predictability of L6C subtypes and L6F subtypes is shown in those who show and those who show non-reactivity.
  • Figure 5d shows the normalized enrichment score (NES) of the up-regulated lncRNA in the L6E subtype in the treatment-responsive and non-responsive subjects.
  • CR means complete response
  • PR means partial response
  • SD stable disease
  • PD means progressive disease.
  • Figure 6 shows the cell type components in each LNC6 subtype
  • Figures 6a and 6b are the averaged xCell scores of TCGA cohort samples in each LNC6 subtype
  • Figure 6a shows the 5 cell type family components in each LNC6 subtype.
  • Figure 6b shows the components of 64 cell types in each LNC6 subtype.
  • FIG. 7 shows in vitro demonstration of the relationship between lncRNA and stem-like features
  • Figure 7b is the result of analyzing the ZNF667-AS1 knockdown efficiency by qRT-PCR after siRNA transformation in the EMT subtype gastric cancer cell line
  • Figure 7f shows the results of Western blot analysis using the EMT marker protein shown in the siRNA-transformed EMT subtype gastric cancer cell line
  • Figure 7g shows the MTS assay of oxaliplatin or 5FU in the siRNA-transformed EMT subtype gastric cancer cell line. shows the half maximal inhibitory concentration (IC 50 ) from
  • X-axis is LNC6 subtype
  • Y-axis is arranged in hierarchical clustering.
  • the 725 gastric developmental TFs identified at the level of mRNA abundance the 723 TFs whose expression levels were available in the TCGA cohort were shown. included in the analysis. TFs highly expressed in the early embryonic stage were classified into Group 1, and TFs highly expressed in the late embryonic stage or maturation stage were classified into Group 2, and the Y-axis was arranged from top to bottom according to the standard deviation in the TF groups and samples.
  • FIG. 11 shows specific gene mutations and copy number changes associated with the LNC6 subtype
  • FIG. 12 relates to the differential methylation of miRNA and protein expression and DNA in the TCGA STAD cohort
  • Figures 12a to 12c are multiple 2 to confirm the subtype-specific methylation of miRNA and protein expression and DNA in the TCGA data set -
  • Rho Spearman correlation coefficients
  • biomarker composition for diagnosis of cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1.
  • a biomarker composition for predicting the prognosis of cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR and ACTA2-AS1.
  • a biomarker composition for predicting therapeutic responsiveness to an anticancer agent for cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1, a biomarker composition for predicting therapeutic responsiveness to an anticancer agent for cancer would like to provide
  • cancer comprising at least one selected from the group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1, epithelial-mesenchymal transition (EMT) ) to provide a diagnostic biomarker composition.
  • group consisting of RP11-572C15.6, FENDRR, ACTA2-AS1 and ZNF667-AS1, epithelial-mesenchymal transition (EMT) to provide a diagnostic biomarker composition.
  • a total of 12,727 lncRNA expression profiles and mRNA expression profiles were downloaded from the TCGA gastric adenocarcinoma (STAD) cohort consisting of 258 tumors, and then converted to a log2 base. Somatic mutations, copy-number alteration (CNA) and clinical data of TCGA STAD were downloaded from cBioPortal for Cancer Genomics. DNA methylation, miRNA expression and protein expression data from reverse phase protein array (RPPA) were downloaded from the UCSC Xena platform.
  • STAD gastric adenocarcinoma
  • Cluster analysis and visualization of lncRNA data were performed through Gene Cluster 3.0 and Java TreeView.
  • 258 TCGA STAD patients were classified into 6 clusters: 25 as L6A, 66 as L6B, 51 as L6C, 51 as L6D, 14 as L6E, and 51 as L6F.
  • multiple two-class t tests were performed on all possible combinations of the six subtypes.
  • five 2-sample t-tests were performed (L6A vs. L6B, L6A vs. L6C, L6A vs. L6D, L6A vs.
  • L6E, and L6A vs. L6A vs. L6A. L6F comparison) (P ⁇ 0.05).
  • lncRNAs with significant differences in expression in the 5 possible comparisons corresponded to the following 262 subtype-specific lncRNAs: 24 L6A, 67 L6B, 20 L6C, 55 L6D , 30 were classified as L6E, and 66 as L6F.
  • the lncRNA subtype signature was converted into an mRNA subtype signature by identifying the mRNA whose expression is specific to the LNC6 subtype, and the mRNA signature was independently verified using the mRNA expression data. applied to the cohort. Subtype-specific mRNA expression signatures were confirmed by multiple two-class t tests. For subtype L6A selection, five two-sample t-tests were performed (L6A vs. L6B, L6A vs. L6C, L6A vs. L6D, L6A vs. L6E, and L6A vs. L6F comparisons) (P ⁇ 0.001). .
  • the top 200 mRNAs were selected for each subtype according to the log ratio. Genes with significant differences in 4 comparisons were considered subtype-specific if the number of genes with significantly different expression in 5 possible comparisons was less than 200.
  • BCCP Bayesian compound covariate predictor
  • BCCP model was constructed based on lncRNA expression data in TCGA cohort for LNC6 subtype prediction in immunotherapy cohort and cancer cell line. Due to differences in the reference genome annotation version in the dataset, only 241 of the 262 subtype-specific lncRNAs were used.
  • lncRNA expression was analyzed from raw RNA sequencing data.
  • Pembrolizumab and 29 DNA-fingerprint GC cell lines were performed on 45 samples obtained from patients with metastatic GC who participated in Phase 2 clinical trials. Reads were aligned with the reference human genome GRCh38 according to the methods of the International Cancer Genome Consortium using STAR 2.6.0c.
  • Uniquely mapped reads for each non-coding RNA were calculated using the Rsubread package (ver. 1.34.0) with Gencode annotation (Release 22). Fragments per kilobase of transcript per million mapped reads (FPKM) values were calculated according to its definition using R ( https://www.r-project.org/).
  • TCGA subtypes and microsatellite instability (MSI) status were defined.
  • the BCCP model was applied to predict the benefits of different molecular subtypes and immunotherapy.
  • GIST gastrointestinal stromal tumor
  • ACRG Asian Cancer Research Group
  • ssGSEA Single-sample GSEA
  • GSEA Gene Set Enrichment Analysis
  • IPA Ingenuity Pathway Analysis
  • TCGA cohort transcripts by a gene signature-based method (xCell).
  • the 64 cell types were grouped into 5 cell type families, and the score of each cell type family was calculated as the sum of the cell type scores it contained.
  • Stem cell ability for each subtype was evaluated from the expression level of transcription factors that are expressed differently in the developmental stage of the mouse stomach.
  • 725 gastric developmental transcription factors identified at the mRNA abundance level 723 of the available expression level values in the TCGA cohort were used for analysis.
  • Each subtype cell cycle phase was evaluated from the expression level of S-phase abundant lncRNA identified by initial RNA capture sequencing.
  • lncRNA-mediated transcriptional network changes identified in LncRNA Modulator Atlas in Pan-cancer LncMAP
  • altered lncRNA-transcription factor gene triplets for each cancer type were identified by integrating paired lncRNA and gene expression profiles with genome-wide transcriptional regulation. Thereafter, only triplets containing immune-related genes obtained from the ImmPort project were used for analysis (17,572 triplets in STAD). The degree of immune regulation was defined as the number of triplets composed of each lncRNA.
  • CNA genes from TCGA cohort data were filtered by Q-value ( ⁇ 0.25) and frequency (>5%).
  • DNA methylation data were filtered to standard deviation >0.15, and if there was a significant difference in ⁇ -values in all five possible comparisons (P ⁇ 0.01), it was considered subtype specific, and a total of 38,476 subtype specific probes were identified.
  • L6A was 451, L6B 773, L6C 84, L6D 10, L6E 28,803, and L6F 8,355.
  • miRNA data were filtered for missing values ( ⁇ 20% of cohorts) and were considered subtype-specific if there was a significant difference (P ⁇ 0.05) in all five possible comparisons, and 143 subtype-specific miRNAs were identified: 17 L6A, 4 L6B, 0 L6C, 4 L6D, 8 L6E, and 110 L6F.
  • Proteins with a significant difference (P ⁇ 0.05) in all five possible comparisons were considered subtype-specific, resulting in a total of 40 subtype-specific proteins: 3 for L6A, 1 for L6B, 0 for L6C, 1 L6D, 10 L6E, and 25 L6F.
  • HM450 probes were annotated to lncRNA genes. Gene fusion cases were downloaded from the TCGA cohort, and data on gene fusion among 258 patients were available for 183 patients.
  • the gastric cancer cell line was cultured in RPMI-1640 medium containing 10% fetal bovine serum and penicillin/streptomycin (100ug/L each), wherein the culture was performed in a humidified incubator containing 5% CO 2 37 It was carried out under temperature conditions of °C.
  • ZNF667-AS1 knockdown by siRNA (Thermofisher Scientific) shown in Table 1 was performed using mirus transformation reagent (Mirus bio).
  • Cancer cells transformed with si-non-target or si-ZNF667-AS1 were inoculated into 96-well plates at an amount of 2X10 3 cells/well and cultured overnight before drug treatment, and 20uL CellTiter 96 AQueous One solution per well (MTS, Promega ) was maintained in the presence of drug for 72 h before addition. After incubating the plate for 3 hours, absorbance was measured at 490 nm using an ELISA reader (Bio tek).
  • a 24-well plate containing an 8-um-pore size chamber insert (Corning Costar) was used. did 2 X 10 5 cells in 200uL FBS-free culture medium were loaded into each filter insert (upper chamber), 700uL of culture medium containing 10% FBS was added to each lower chamber, and cultured at 37°C for 16 hours. did After harvesting, the bottom of the insert was fixed and dyed with crystal violet. The number of migrating or infiltrating cells was measured using an EVOS M7000 imaging system (Thermofisher Scientific).
  • the primary antibodies used were: ZNF667 (1:2000, Abcam, ab106432), N-Cadherin (1:1000, Cell signaling, 4061S), E-Cadherin (1:1000, Cell signaling, 14472S), Vimentin (1:1000, Cell signaling, 5741) and GAPDH (1:1000, Sigma, G9545). After washing 5 times with TBS-T, the blots were incubated with mustard radish hydrogen peroxide-conjugated secondary antibody and visualized with enhanced chemi-luminescence detection (ECL plus kit, Pierce).
  • lncRNA genes with unique expression for each subtype were identified: a total of 262 lncRNAs with distinct expression in the six subtypes corresponded to a total of 262 (Fig. 1b; Table 3).
  • LNC6 subtypes in the TCGA cohort represent sex, ethnicity, tumor location and stage of cancer, histological grade, and Loren subtype (Table 4).
  • the majority of L6A and L6E patients were male (84% and 100%).
  • the majority of L6A and L6D patients were from Western countries (96% and 92%).
  • Such ethnic differences were not found in the molecular subtypes of gastric cancer.
  • L6A patients had the highest proportion of the proximal part of the tumor (36%), whereas L6F patients had the lowest proportion (10%).
  • gastric cancer is usually diagnosed after advanced stage in Western countries, L6A subtype tumors showed a relatively low cancer stage.
  • L6C tumors also showed relatively low cancer stage, but L6E and L6F tumors showed high stage and histological grade.
  • the L6F subtype was rich in the diffuse subtype in the Loren classification.
  • the L6C probability corresponds to a positive predictive marker of response to immunotherapy
  • the L6F probability corresponds to a negative predictive marker of response to immunotherapy.
  • the deviation corresponds to 0 or 1, so that the predicted probability of the L6E subtype does not stratify immunotherapy responders and non-responders, although it is specifically upregulated in the L6E subtype.
  • L6F tumors are predicted to consist of stromal cells, that is, lymphoid epithelial cells, fibroblasts, chondrocytes, pericytes, and adipocytes, suggesting that the immune response is limited in L6F tumors (Fig. 6b). ).
  • L6F subtype showed the most significant association with clinical outcomes such as poor prognosis, early recurrence, and resistance to chemotherapy.
  • L6F-like gastric cancer cell lines were identified by applying BCCP predictors for L6F subtype to lncRNA expression data from 29 gastric cancer cell lines.
  • L6F probability showed a high correlation with epithelial-mesenchymal transition (EMT) subtype (Fig. 7a).
  • EMT epithelial-mesenchymal transition
  • L6A subtype was expressed through activation of metabolic pathways such as glycosylation, oxidative phosphorylation and fatty acid metabolism.
  • Hepatocyte nuclear factor-4 ⁇ (HNF4 ⁇ ) was predicted to be the most important upstream regulator of L6A.
  • the L6C subtype is associated with activation of the G2M checkpoint, E2F target, DNA repair, MYC target and MTORC1 signal, while the L6D subtype is associated with protein release and activation of KRAS signaling.
  • the L6E subtype is associated with the activation of an interferon response that maintains the activated immunity of the L6E subtype.
  • the L6F subtype is associated with activation of Wnt/ ⁇ -catenin signaling, TGF- ⁇ signaling, EMT, and angiogenesis.
  • TGF- ⁇ and Twist1 which are major regulators of EMT, are known as upstream regulators of the L6F subtype.
  • the molecular characteristics of the LNC6 subtype were further investigated using genomic and proteome data from TCGA data.
  • the L6B subtype was defined as a high copy number change, and only some genes were expressed differently among the LNC6 subtypes (Fig. 11a).
  • the L6C subtype is characterized by a high mutation burden, and many genes were mutated differently among the LNC6 subtypes (Fig. 11b).
  • the L6E subtype was characterized by a hypermethylation pattern (Fig. 12a), and the L6F subtype was characterized by the most distinct expression pattern of miRNAs and proteins (Figs. 12b and 12c) and a recurrent (15.4%) CLDN18-ARHGAP fusion.
  • the epigenetic background of subtype-specific lncRNAs and the identified epigenetic regulated lncRNAs were identified ( FIG. 13 ).
  • L6A and L6B subtypes were abundant in chromosomal instability (CIN) and microsatellite stability (MSS) subtypes.
  • the L6C subtype was abundant in the microsatellite instability (MSI) subtype, and the L6D subtype was mixed with a number of other molecular subtypes.
  • the L6E subtype corresponded to 100% Epstein-Barr virus (EBV) subtype, and the L6F subtype was abundant in the genetically stable (GS) subtype, the MP subtype and the EMT subtype.
  • the present invention relates to a composition for predicting cancer prognosis, a kit comprising the same, and a method for predicting cancer prognosis.

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La présente invention concerne une composition pour une prédiction de pronostic du cancer, un kit la comprenant et un procédé de prédiction de pronostic de cancer.
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KR20240133598A (ko) 2023-02-28 2024-09-04 아주대학교산학협력단 N6-메틸아데노신 제어 rp11-108m9.4를 이용한 재발성 간암 진단 또는 치료 용도

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