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WO2023231280A1 - Produit pour l'évaluation du risque de récidive chez un patient atteint d'un cancer pulmonaire - Google Patents

Produit pour l'évaluation du risque de récidive chez un patient atteint d'un cancer pulmonaire Download PDF

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Publication number
WO2023231280A1
WO2023231280A1 PCT/CN2022/127455 CN2022127455W WO2023231280A1 WO 2023231280 A1 WO2023231280 A1 WO 2023231280A1 CN 2022127455 W CN2022127455 W CN 2022127455W WO 2023231280 A1 WO2023231280 A1 WO 2023231280A1
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Prior art keywords
lung cancer
recurrence
markers
adjuvant chemotherapy
positive integer
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Ceased
Application number
PCT/CN2022/127455
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English (en)
Chinese (zh)
Inventor
饶皑炳
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Shenzhen Luwei Biotechnology Biomanifold Technology Co Ltd
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Shenzhen Luwei Biotechnology Biomanifold Technology Co Ltd
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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
    • G—PHYSICS
    • 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
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • G16B25/10—Gene or protein expression profiling; Expression-ratio estimation or normalisation
    • G—PHYSICS
    • 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
    • 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
    • C12Q2600/158—Expression markers

Definitions

  • CFH complement Factor H
  • This gene is a member of the complement activation regulator (RCA) gene cluster and encodes a protein with 20 short consensus repeats (SCR) domains. It plays a role in the regulation of complement activation. It plays a vital role.
  • KIAA0355 also known as GARRE1, Granule Associated Rac And RHOG Effector 1
  • GARRE1 Granule Associated Rac And RHOG Effector 1
  • OXCT1 (3-Oxoacid CoA-Transferase 1) is the 3-oxoacetate CoA-Transferase 1 gene.
  • the encoded protein is a homodimeric mitochondrial matrix enzyme that catalyzes the reversible transfer of coenzyme A from succinyl-CoA to acetoacetate. , plays a central role in extrahepatic ketone body catabolism.
  • the specific regimen of adjuvant chemotherapy can be a regimen including cisplatin (P), specifically a double-drug regimen including cisplatin, such as TP (paclitaxel + cisplatin), GP (gemcitabine + cisplatin), DP (docetaxel) + cisplatin), AP (pemetrexed + cisplatin), LP (paclitaxel liposome + cisplatin), etc. It is understandable that for some patients who cannot tolerate cisplatin, carboplatin can be used instead.
  • the markers when there is adjuvant chemotherapy, include at least one, at least two, at least three of AGFG2, PGGT1B, ZKSCAN7, KIAA0355, SNRPB, MAOB, UTP20, DHCR7, CFH, GPX2, Elevated levels of at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, and at least one, at least of CDC42BPA, ECI2, CCND2, RHEB, KIAA1109, PIK3CG A decrease in two, at least three, at least four, at least five, or at least six levels indicates a higher risk of relapse.
  • markers include ADAM8, ANGPT2, CAMP, CPE, CYP1A1, DDR2, DOPEY2, E2F3, EP300, EPHA2, FANCL, GABPA, KRT17, MIS18A, NDRG1, NOTCH1, At least two, at least three, at least four, at least five, at least six, at least seven, at least eight of NXT2, OXCT1, PBRM1, PITRM1, RNF43, SCGB2A2, SLC39A6, STC1, STC2, TSPYL5 and TUBG1 , at least nine, at least ten, at least eleven, at least twelve, at least thirteen, at least fourteen, at least fifteen, at least sixteen, at least seventeen, at least eighteen, at least Nineteen, at least twenty, at least twenty-one, at least twenty-two, at least twenty-three, at least twenty-four, at least twenty-five, at least twenty-six and all twenty-seven .
  • the reagent detects the mRNA expression level of the marker.
  • the marker includes at least N 1 of AGFG2, CCND2, CDC42BPA, CFH, DHCR7, ECI2, GPX2, KIAA0355, KIAA1109, MAOB, PGGT1B, PIK3CG, RHEB, SNRPB, UTP20 and ZKSCAN7, N 1 is optionally selected from a positive integer from 1 to 16.
  • markers include ADAM8, ANGPT2, CAMP, CPE, CYP1A1, DDR2, DOPEY2, E2F3, EP300, EPHA2, FANCL, GABPA, KRT17, MIS18A, NDRG1, NOTCH1, At least N 2 of NXT2, OXCT1, PBRM1, PITRM1, RNF43, SCGB2A2, SLC39A6, STC1, STC2, TSPYL5 and TUBG1, and N 2 is optionally a positive integer from 1 to 27; for example, at least two or at least three of them , at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven, at least twelve, at least thirteen, at least fourteen, at least Fifteen, at least sixteen, at least seventeen, at least eighteen, at least nineteen, at least twenty, at least twenty-one, at least twenty-two, at least twenty-three, at least twenty
  • the markers include at least one, at least two, at least three, at least four, at least five of AGFG2, PGGT1B, ZKSCAN7, KIAA0355, SNRPB, MAOB, UTP20, DHCR7, CFH, and GPX2 at least one, at least six, at least seven, at least eight, at least nine, at least ten, and/or at least one, at least two, at least three, at least CDC42BPA, ECI2, CCND2, RHEB, KIAA1109, PIK3CG Four, at least five, at least six.
  • the reagent detects the mRNA expression level of the marker.
  • the memory may optionally include memory located remotely relative to the processor, and these remote memories may be connected to the processor through a network.
  • Examples of the above-mentioned networks include but are not limited to the Internet, intranets, local area networks, mobile communication networks and combinations thereof.
  • the scoring module mathematically correlates expression levels to obtain scores including ADAM8, ANGPT2, CAMP, CPE, CYP1A1, DDR2, DOPEY2, E2F3, EP300, EPHA2, FANCL, GABPA, KRT17, MIS18A,
  • the expression levels of at least one of NDRG1, NOTCH1, NXT2, OXCT1, PBRM1, PITRM1, RNF43, SCGB2A2, SLC39A6, STC1, STC2, TSPYL5 and TUBG1 were mathematically correlated to obtain a recurrence score, and AGFG2, CCND2, CDC42BPA, CFH
  • the expression levels of at least one of , DHCR7, ECI2, GPX2, KIAA0355, KIAA1109, MAOB, PGGT1B, PIK3CG, RHEB, SNRPB, UTP20 and ZKSCAN7 were mathematically correlated to obtain another recurrence score, and lung cancer patients were mathematically correlated to
  • Linear models were constructed based on one or more of the above two sets of gene sets as markers to calculate the recurrence scores of the two lung cancers with or without adjuvant chemotherapy.
  • Individualized treatment plans can be implemented for patients based on two recurrence scores: those with high recurrence scores from adjuvant chemotherapy should be given the first choice of other treatment options without adjuvant chemotherapy; those with high recurrence scores without adjuvant chemotherapy should be given first choice with adjuvant chemotherapy.
  • two lung cancer recurrence scores should be compared with each other based on the same or close standards. For example, the two can be standardized and transformed in a set way and then compared in absolute size, or the two can be directly compared. The relative size of the scores to their corresponding thresholds, and so on.
  • a total of 46 lung cancer gene expression data sets were selected from the U.S. Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases, including full transcriptome data of 6597 lung cancer tissue sections. After excluding gene transcripts with extremely low expression (the number of samples with non-zero expression does not exceed 10), miRNA and lncRNA were eliminated, and the common genes of these data sets were selected, resulting in a gene number of 8366.
  • GEO Gene Expression Omnibus
  • TCGA Cancer Genome Atlas
  • columns 1-34 include sample and patient information, including basic information such as patient age and gender, lung cancer pathological classification, mutation status of driver genes such as ALK, EGFR, KRAS, and TP53, as well as recurrence-free survival (RFS), overall survival ( OS) indicators and long-term clinical prognosis information, etc.
  • basic information such as patient age and gender, lung cancer pathological classification, mutation status of driver genes such as ALK, EGFR, KRAS, and TP53, as well as recurrence-free survival (RFS), overall survival ( OS) indicators and long-term clinical prognosis information, etc.
  • RFS recurrence-free survival
  • OS overall survival
  • NCHEMO's Nx and CHEMO's Tx there is no statistically significant difference between the non-recurrence and recurrence groups, but for NCHEMO's Tx, the average value of the recurrence group is 0.03 higher than that of the non-recurrence group, which is statistically significant; for CHEMO's Nx, the recurrence The average value of the group is 0.51 higher than that of the non-recurrence group, which is also statistically significant.
  • the formula score for calculating the risk of lung cancer recurrence without adjuvant chemotherapy 0.4322 ⁇ PBRM1+0.3548 ⁇ GABPA+0.3147 ⁇ DDR2+0.3003 ⁇ SCGB2A2+0.275 ⁇ CAMP+0.2562 ⁇ ADAM8+0.2284 ⁇ RNF43+0.2239 ⁇ PITRM1+0.222 ⁇ STC2+ 0.2097 ⁇ TUBG1+0.2044 ⁇ E2F3+0.2039 ⁇ ANGPT2+0.2011 ⁇ NXT2+0.1644 ⁇ NDRG1+0.1589 ⁇ CYP1A1+0.1533 ⁇ DOPEY2+0.1409 ⁇ SLC39A6+0.1201 ⁇ OXCT1+0.0815 ⁇ KRT17-0.0 657 ⁇ CPE-0.0665 ⁇ TSPYL5-0.157 ⁇ STC1-0.1615 ⁇ FANCL-0.1786 ⁇ EPHA2-0.2235 ⁇ EP300-0.2285 ⁇ NOTCH1-0.2628 ⁇ MIS18A.
  • the abbreviation of the marker in the formula represents the normal
  • the formula score for calculating the risk of lung cancer recurrence under adjuvant chemotherapy 0.5931 ⁇ AGFG2+0.5562 ⁇ PGGT1B+0.4632 ⁇ ZKSCAN7+0.3192 ⁇ KIAA0355+0.2759 ⁇ SNRPB+0.2276 ⁇ MAOB+0.2107 ⁇ UTP20+0.145 ⁇ DHCR7+0.1276 ⁇ CFH+0.06 13 ⁇ GPX2-0.212 ⁇ CDC42BPA-0.2196 ⁇ ECI2-0.2914 ⁇ CCND2-0.3073 ⁇ RHEB-0.405 ⁇ KIAA1109-0.4517 ⁇ PIK3CG.
  • the abbreviation of the marker in the formula represents the normalized value of the expression level of the corresponding marker.

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  • Bioinformatics & Cheminformatics (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • General Health & Medical Sciences (AREA)
  • Organic Chemistry (AREA)
  • Biotechnology (AREA)
  • Medical Informatics (AREA)
  • Evolutionary Biology (AREA)
  • Immunology (AREA)
  • Zoology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Wood Science & Technology (AREA)
  • Molecular Biology (AREA)
  • Analytical Chemistry (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Theoretical Computer Science (AREA)
  • Pathology (AREA)
  • Data Mining & Analysis (AREA)
  • Microbiology (AREA)
  • Hospice & Palliative Care (AREA)
  • Software Systems (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Databases & Information Systems (AREA)
  • Bioethics (AREA)
  • Oncology (AREA)
  • Epidemiology (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Public Health (AREA)
  • Biochemistry (AREA)
  • General Engineering & Computer Science (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Medicines That Contain Protein Lipid Enzymes And Other Medicines (AREA)

Abstract

La présente invention concerne l'utilisation d'un réactif pour détecter des marqueurs dans la préparation d'un produit destiné à évaluer le risque de récidive chez des patients atteints de cancer pulmonaire. Un premier aspect de la présente invention concerne l'utilisation du réactif pour la détection de marqueurs dans la préparation du produit pour l'évaluation du risque de récidive chez des patients atteints de cancer pulmonaire. Différents modèles concernant le risque de récidive sont établis pour les patients atteints de cancer pulmonaire recevant une chimiothérapie adjuvante et ne recevant pas de chimiothérapie adjuvante, différents moyens de traitement adjuvant pour les patients atteints de cancer pulmonaire sont distingués, le risque de récidive chez les patients est prédit au moyen de deux ensembles de marqueurs, et un moyen de traitement adjuvant approprié peut ainsi être sélectionné à partir de ces deux ensembles. Pour les patients présentant un risque de récidive plus élevé s'ils reçoivent une chimiothérapie adjuvante que s'ils n'en reçoivent pas, d'autres régimes thérapeutiques en plus de la chimiothérapie adjuvante sont préférés, tandis que la chimiothérapie adjuvante est privilégiée pour les patients présentant un risque de récidive plus élevé s'ils ne reçoivent pas de chimiothérapie adjuvante.
PCT/CN2022/127455 2022-05-31 2022-10-25 Produit pour l'évaluation du risque de récidive chez un patient atteint d'un cancer pulmonaire Ceased WO2023231280A1 (fr)

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CN114934117A (zh) * 2022-05-31 2022-08-23 深圳市陆为生物技术有限公司 评价肺癌患者复发风险的产品

Citations (5)

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WO2013151677A1 (fr) * 2012-04-02 2013-10-10 Broad Institute, Inc. Mutations touchant le gène ddr2 et cancer
CN109735619A (zh) * 2018-12-21 2019-05-10 中国科学院北京基因组研究所 与非小细胞肺癌预后相关的分子标志物及其应用
CN111394456A (zh) * 2020-03-19 2020-07-10 中国医学科学院肿瘤医院 早期肺腺癌患者预后评估系统及其应用
CN114622015A (zh) * 2021-05-13 2022-06-14 四川大学华西医院 一种基于循环肿瘤DNA预测非小细胞肺癌术后复发的NGS panel及其用途
CN114934117A (zh) * 2022-05-31 2022-08-23 深圳市陆为生物技术有限公司 评价肺癌患者复发风险的产品

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CN114512184B (zh) * 2021-10-11 2024-10-29 上海市胸科医院 一种用于预测癌症疗效和预后的方法及其装置和应用

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* Cited by examiner, † Cited by third party
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WO2013151677A1 (fr) * 2012-04-02 2013-10-10 Broad Institute, Inc. Mutations touchant le gène ddr2 et cancer
CN109735619A (zh) * 2018-12-21 2019-05-10 中国科学院北京基因组研究所 与非小细胞肺癌预后相关的分子标志物及其应用
CN111394456A (zh) * 2020-03-19 2020-07-10 中国医学科学院肿瘤医院 早期肺腺癌患者预后评估系统及其应用
CN114622015A (zh) * 2021-05-13 2022-06-14 四川大学华西医院 一种基于循环肿瘤DNA预测非小细胞肺癌术后复发的NGS panel及其用途
CN114934117A (zh) * 2022-05-31 2022-08-23 深圳市陆为生物技术有限公司 评价肺癌患者复发风险的产品

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LU, YAN ET AL.: "Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients", PLOS ONE., vol. 7, no. 1, 23 January 2012 (2012-01-23), XP055177681, DOI: 10.1371/journal.pone.0030880 *
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