JP5970123B1 - Detection of pancreatic cancer by gene expression analysis - Google Patents
Detection of pancreatic cancer by gene expression analysis Download PDFInfo
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- JP5970123B1 JP5970123B1 JP2015237140A JP2015237140A JP5970123B1 JP 5970123 B1 JP5970123 B1 JP 5970123B1 JP 2015237140 A JP2015237140 A JP 2015237140A JP 2015237140 A JP2015237140 A JP 2015237140A JP 5970123 B1 JP5970123 B1 JP 5970123B1
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Abstract
【課題】膵臓癌に関連して発現が変動する遺伝子を解析して、膵臓癌を検出する方法並びに検出試薬の提供。【解決手段】特定の56個又は47個の遺伝子セットの塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを含む膵臓癌を検出するための試薬、並びに特定の56個又は47個の遺伝子の発現レベルを測定し、該発現レベルに基づいて膵臓癌を検出する方法。【選択図】なしA method and reagent for detecting pancreatic cancer by analyzing a gene whose expression varies in relation to pancreatic cancer is provided. A reagent for detecting pancreatic cancer comprising a nucleotide comprising the nucleotide sequence of a specific 56 or 47 gene set or a nucleotide comprising a partial sequence thereof, as well as a specific 56 or 47 gene A method of measuring an expression level and detecting pancreatic cancer based on the expression level. [Selection figure] None
Description
本発明は、末梢血液を材料とし遺伝子発現解析を利用した膵臓癌の検出に関する。 The present invention relates to detection of pancreatic cancer using gene expression analysis using peripheral blood as a material.
膵臓癌は日本人で部位別がん死亡数(男女計)順位が5番目の消化器系悪性腫瘍であり
、厚生労働省調べでは年間2万3千人の患者が死亡する。癌の発見が非常に難しく、早期に発見されることは稀である。膵臓癌と診断された75%の症例は既に手術不能例であり、発見後1〜2年以内に死亡する極めて予後不良の消化器癌である(国立がんセンターがん対策情報センター調べhttp://ganjoho.jp/public/cancer/data/pancreas.html)。膵臓癌の診断技術の進歩が望まれてから久しく未だ有用な早期診断法は確立されていない。
Pancreatic cancer is a digestive malignant tumor with the fifth highest number of cancer deaths by sex (gender total) in Japanese, and 23,000 patients die annually according to a survey by the Ministry of Health, Labor and Welfare. Cancer is very difficult to detect and is rarely detected early. 75% of cases diagnosed with pancreatic cancer are already inoperable cases and have a very poor prognosis of gastrointestinal cancers that die within 1 to 2 years after discovery (according to National Cancer Center Cancer Control Information Center http: //ganjoho.jp/public/cancer/data/pancreas.html). A useful early diagnosis method has not been established for a long time since the advancement of diagnostic technology for pancreatic cancer has been desired.
昨今、DNAマイクロアレイ技術の発展、及びヒトゲノム解読によって、全遺伝子を対象
とした網羅的遺伝子発現解析が可能になった。これにより、新しい癌の診断・予後予測、治療後の再発率の予測などが可能になった。本発明者らのグループは、膵臓癌における遺伝子発現プロファイルを解析し、遺伝子発現プロファイルによる膵臓癌の特異的検出方法を開発し(特許文献1を参照)、DNAマイクロアレイを用いた検出方法を実施している。
Recently, development of DNA microarray technology and human genome decoding have enabled comprehensive gene expression analysis for all genes. This has made it possible to diagnose and predict a new cancer, predict the recurrence rate after treatment, and so on. Our group analyzed a gene expression profile in pancreatic cancer, developed a specific detection method for pancreatic cancer based on the gene expression profile (see Patent Document 1), and carried out a detection method using a DNA microarray. ing.
本発明は、患者への侵襲も低く、且つ患者からの遺伝子抽出も容易な方法で、膵臓癌に関連して発現が変動する遺伝子を解析して、膵臓癌を検出する方法、並びに膵臓癌を検出するための検出試薬の提供を目的とする。 The present invention relates to a method for detecting pancreatic cancer by analyzing a gene whose expression varies in relation to pancreatic cancer by a method with low invasion to a patient and easy gene extraction from the patient. An object is to provide a detection reagent for detection.
本発明者らは、リアルタイムPCRによる検出方法がDNAマイクロアレイを用いた検出方法より低コストで行うことができ、またより迅速な検出が可能になることに鑑み、リアルタイムPCRによる膵臓癌の検出方法を開発すべく膵臓癌患者における遺伝子発現プロファイ
ルを解析した。
In view of the fact that the detection method using real-time PCR can be performed at a lower cost than the detection method using a DNA microarray, and more rapid detection is possible, a method for detecting pancreatic cancer using real-time PCR has been proposed. The gene expression profile in pancreatic cancer patients was analyzed for development.
その結果、膵臓癌と関連した56個の遺伝子セットAと47個の遺伝子セットBの2セットの遺伝子セットを見出し、さらにこれらの遺伝子セットの発現レベルと膵臓癌の関係を統計的に判別解析し、56個又は47個の遺伝子の発現レベルにより膵臓癌陽性か陰性かを判別できる判別式を開発し、本発明を完成させるに至った。 As a result, two gene sets of 56 gene sets A and 47 gene sets B related to pancreatic cancer were found, and the relationship between the expression level of these gene sets and pancreatic cancer was statistically discriminated and analyzed. A discriminant that can discriminate whether pancreatic cancer is positive or negative based on the expression level of 56 or 47 genes has been developed, and the present invention has been completed.
さらに、本発明は膵臓患者から単離したCD4陽性T細胞及びマクロファージにおいて、
それぞれ、特定の遺伝子の発現が上昇していることを見出し、被験体からCD4陽性T細胞
又はマクロファージを単離し、これらの細胞における上記特定の遺伝子発現のレベルを測定することにより、膵臓癌を検出し得ることを見出し本発明を完成させるに至った。
Furthermore, the present invention relates to CD4 positive T cells and macrophages isolated from pancreatic patients,
Detecting pancreatic cancer by finding that the expression of a specific gene is elevated, isolating CD4-positive T cells or macrophages from a subject, and measuring the level of the specific gene expression in these cells As a result, the present invention has been completed.
すなわち、本発明は以下のとおりである。
[1] 以下の56個の遺伝子セットA又は47個の遺伝子セットBの20個の遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを含む膵臓癌を検出するための試薬:
遺伝子セットA
(1)Abhydrolase domain containing 3 (ABHD3)
(2)Abl-interactor 1 (ABI1)
(3)Acyl-CoA synthetase long-chain family member 3 (ACSL3)
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(5)ATPase, Class VI, type 11B (ATP11B)
(6)UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 5 (B3GNT5)
(7)BTB and CNC homology 1, basic leucine zipper transcription factor 1 (BACH1)
(8)Chromosome 11 open reading frame 2 (C11orf2)
(9)Chromosome 2 open reading frame 81 (C2orf81)
(10)Cyclin Y-like 1 (CCNYL1)
(11)Centromere protein N (CENPN)
(12)Complement factor H-related 3 (CFHR3)
(13)C-type lectin domain family 4, member D (CLEC4D)
(14)Collagen, type XVII, alpha 1 (COL17A1)
(15)Cytochrome b5 reductase 4 (CYB5R4)
(16)DENN/MADD domain containing 1B (DENND1B)
(17)Enoyl CoA hydratase domain containing 3 (ECHDC3)
(18)Ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)
(19)Family with sequence similarity 198, member B (FAM198B)
(20)Family with sequence similarity 49, member B (FAM49B)
(21)Fatty acyl CoA reductase 1 (FAR1)
(22)Fibrinogen-like 2 (FGL2)
(23)Fibronectin type III domain containing 3B (FNDC3B)
(24)Fucose-1-phosphate guanylyltransferase (FPGT)
(25)UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 4 (GalNAc-T4) (GALNT4)
(26)HEAT repeat containing 5A (HEATR5A)
(27)HIV-1 Tat interactive protein 2, 30kDa (HTATIP2)
(28)Interferon gamma receptor 1 (IFNGR1)
(29)IKBKB interacting protein (IKBIP)
(30)Lactate dehydrogenase A (LDHA)
(31)Lysophosphatidic acid receptor 6 (LPAR6)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(33)Minichromosome maintenance complex binding protein (MCMBP)
(34)Mesoderm induction early response 1 homolog (Xenopus laevis) (MIER1)(35)Nuclear factor (erythroid-derived 2)-like 2 (NFE2L2)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)
(37)Oxysterol binding protein-like 8 (OSBPL8)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(39)Protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L)
(40)PR domain containing 5 (PRDM5)
(41)Protein tyrosine phosphatase, receptor type, C (PTPRC)
(42)RAB10, member RAS oncogene family (RAB10)
(43)Ribosomal protein, large, P1 (RPLP1)
(44)Ras-related GTP binding D (RRAGD)
(45)Solute carrier family 22, member 15 (SLC22A15)
(46)Solute carrier family 44, member 1 (SLC44A1)
(47)Schlafen family member 12 (SLFN12)
(48)S1 RNA binding domain 1 (SRBD1)
(49)Tet oncogene family member 2 (TET2)
(50)Transducin-like enhancer of split 2 (E(sp1) homolog, Drosophila) (TLE2)
(51)Ubiquitin-conjugating enzyme E2W (putative) (UBE2W)
(52)Ubiquitination factor E4A (UBE4A)
(53)Ubiquitin specific peptidase 15 (USP15)
(54)WD repeat and SOCS box containing 1 (WSB1)
(55)Zinc finger E-box binding homeobox 2 (ZEB2)
(56)Zinc metallopeptidase (STE24 homolog, S. cerevisiae) (ZMPSTE24)
遺伝子セットB
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8)Chromosome 11 open reading frame 2 (C11orf2)
(10)Cyclin Y-like 1 (CCNYL1)
(13)C-type lectin domain family 4, member D (CLEC4D)
(15)Cytochrome b5 reductase 4 (CYB5R4)
(28)Interferon gamma receptor 1 (IFNGR1)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43)Ribosomal protein, large, P1 (RPLP1)
(52)Ubiquitination factor E4A (UBE4A)
(53)Ubiquitin specific peptidase 15 (USP15)
(57)Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58)Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)
(APBB1)
(59)BCL2-related protein A1 (BCL2A1)
(60)Chromosome 9 open reading frame 72 (C9orf72)
(61)Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62)CD36 molecule (thrombospondin receptor) (CD36)
(63)CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64)CD58 molecule (CD58)
(65)CTAGE family, member 5 (CTAGE5)
(66)V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67)F-box and leucine-rich repeat protein 5 (FBXL5)
(68)Glucuronidase, beta (GUSB)
(69)Huntingtin interacting protein 1 related (HIP1R)
(70)High mobility group box 2 (HMGB2)
(71)Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72)IlvB (bacterial acetolactate synthase)-like (ILVBL)
(73)IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74)Mbt domain containing 1 (MBTD1)
(75)Milk fat globule-EGF factor 8 protein (MFGE8)
(76)Nascent polypeptide-associated complex alpha subunit (NACA)
(77)Nuclear receptor coactivator 5 (NCOA5)
(78)Non-POU domain containing, octamer-binding (NONO)
(79)Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80)Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81)Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82)RAB14, member RAS oncogene family (RAB14)
(83)RNA binding motif protein 14 (RBM14)
(84)Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)(85)Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86)Serglycin (SRGN)
(87)TATA box binding protein (TBP)
(88)Transmembrane protein 167A (TMEM167A)
(89)Thioredoxin (TXN)
(90)Vascular endothelial growth factor B (VEGFB)
(91)Zinc finger protein 764 (ZNF764)
That is, the present invention is as follows.
[1] A reagent for detecting pancreatic cancer comprising a nucleotide comprising the nucleotide sequence of 20 genes of the following 56 gene sets A or 47 gene sets B, or a nucleotide comprising a partial sequence thereof:
Gene set A
(1) Abhydrolase domain containing 3 (ABHD3)
(2) Abl-interactor 1 (ABI1)
(3) Acyl-CoA synthetase long-chain family member 3 (ACSL3)
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(5) ATPase, Class VI, type 11B (ATP11B)
(6) UDP-GlcNAc: betaGal beta-1,3-N-acetylglucosaminyltransferase 5 (B3GNT5)
(7) BTB and CNC homology 1, basic leucine zipper transcription factor 1 (BACH1)
(8) Chromosome 11 open reading frame 2 (C11orf2)
(9) Chromosome 2 open reading frame 81 (C2orf81)
(10) Cyclin Y-like 1 (CCNYL1)
(11) Centromere protein N (CENPN)
(12) Complement factor H-related 3 (CFHR3)
(13) C-type lectin domain family 4, member D (CLEC4D)
(14) Collagen, type XVII, alpha 1 (COL17A1)
(15) Cytochrome b5 reductase 4 (CYB5R4)
(16) DENN / MADD domain containing 1B (DENND1B)
(17) Enoyl CoA hydratase domain containing 3 (ECHDC3)
(18) Ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)
(19) Family with sequence similarity 198, member B (FAM198B)
(20) Family with sequence similarity 49, member B (FAM49B)
(21) Fatty acyl CoA reductase 1 (FAR1)
(22) Fibrinogen-like 2 (FGL2)
(23) Fibronectin type III domain containing 3B (FNDC3B)
(24) Fucose-1-phosphate guanylyltransferase (FPGT)
(25) UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 4 (GalNAc-T4) (GALNT4)
(26) HEAT repeat containing 5A (HEATR5A)
(27) HIV-1 Tat interactive protein 2, 30kDa (HTATIP2)
(28) Interferon gamma receptor 1 (IFNGR1)
(29) IKBKB interacting protein (IKBIP)
(30) Lactate dehydrogenase A (LDHA)
(31) Lysophosphatidic acid receptor 6 (LPAR6)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(33) Minichromosome maintenance complex binding protein (MCMBP)
(34) Mesoderm induction early response 1 homolog (Xenopus laevis) (MIER1) (35) Nuclear factor (erythroid-derived 2) -like 2 (NFE2L2)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A)
(37) Oxysterol binding protein-like 8 (OSBPL8)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(39) Protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L)
(40) PR domain containing 5 (PRDM5)
(41) Protein tyrosine phosphatase, receptor type, C (PTPRC)
(42) RAB10, member RAS oncogene family (RAB10)
(43) Ribosomal protein, large, P1 (RPLP1)
(44) Ras-related GTP binding D (RRAGD)
(45) Solute carrier family 22, member 15 (SLC22A15)
(46) Solute carrier family 44, member 1 (SLC44A1)
(47) Schlafen family member 12 (SLFN12)
(48) S1 RNA binding domain 1 (SRBD1)
(49) Tet oncogene family member 2 (TET2)
(50) Transducin-like enhancer of split 2 (E (sp1) homolog, Drosophila) (TLE2)
(51) Ubiquitin-conjugating enzyme E2W (putative) (UBE2W)
(52) Ubiquitination factor E4A (UBE4A)
(53) Ubiquitin specific peptidase 15 (USP15)
(54) WD repeat and SOCS box containing 1 (WSB1)
(55) Zinc finger E-box binding homeobox 2 (ZEB2)
(56) Zinc metallopeptidase (STE24 homolog, S. cerevisiae) (ZMPSTE24)
Gene set B
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8) Chromosome 11 open reading frame 2 (C11orf2)
(10) Cyclin Y-like 1 (CCNYL1)
(13) C-type lectin domain family 4, member D (CLEC4D)
(15) Cytochrome b5 reductase 4 (CYB5R4)
(28) Interferon gamma receptor 1 (IFNGR1)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43) Ribosomal protein, large, P1 (RPLP1)
(52) Ubiquitination factor E4A (UBE4A)
(53) Ubiquitin specific peptidase 15 (USP15)
(57) Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58) Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)
(APBB1)
(59) BCL2-related protein A1 (BCL2A1)
(60) Chromosome 9 open reading frame 72 (C9orf72)
(61) Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62) CD36 molecule (thrombospondin receptor) (CD36)
(63) CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64) CD58 molecule (CD58)
(65) CTAGE family, member 5 (CTAGE5)
(66) V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67) F-box and leucine-rich repeat protein 5 (FBXL5)
(68) Glucuronidase, beta (GUSB)
(69) Huntingtin interacting protein 1 related (HIP1R)
(70) High mobility group box 2 (HMGB2)
(71) Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72) IlvB (bacterial acetolactate synthase) -like (ILVBL)
(73) IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74) Mbt domain containing 1 (MBTD1)
(75) Milk fat globule-EGF factor 8 protein (MFGE8)
(76) Nascent polypeptide-associated complex alpha subunit (NACA)
(77) Nuclear receptor coactivator 5 (NCOA5)
(78) Non-POU domain containing, octamer-binding (NONO)
(79) Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80) Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81) Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82) RAB14, member RAS oncogene family (RAB14)
(83) RNA binding motif protein 14 (RBM14)
(84) Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA) (85) Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86) Serglycin (SRGN)
(87) TATA box binding protein (TBP)
(88) Transmembrane protein 167A (TMEM167A)
(89) Thioredoxin (TXN)
(90) Vascular endothelial growth factor B (VEGFB)
(91) Zinc finger protein 764 (ZNF764)
[2] 一部配列を含むヌクレオチドがPCR用プライマーである、[1]の膵臓癌を検出する
ための試薬。
[2] The reagent for detecting pancreatic cancer according to [1], wherein a nucleotide containing a partial sequence is a primer for PCR.
[3] 被験体における以下の56個の遺伝子セットA又は47個の遺伝子セットBの56個又は47個の遺伝子の発現レベルを測定し、該発現レベルに基づいて膵臓癌を検出する方法:
遺伝子セットA
(1)Abhydrolase domain containing 3 (ABHD3)
(2)Abl-interactor 1 (ABI1)
(3)Acyl-CoA synthetase long-chain family member 3 (ACSL3)
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(5)ATPase, Class VI, type 11B (ATP11B)
(6)UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 5 (B3GNT5)
(7)BTB and CNC homology 1, basic leucine zipper transcription factor 1 (BACH1)
(8)Chromosome 11 open reading frame 2 (C11orf2)
(9)Chromosome 2 open reading frame 81 (C2orf81)
(10)Cyclin Y-like 1 (CCNYL1)
(11)Centromere protein N (CENPN)
(12)Complement factor H-related 3 (CFHR3)
(13)C-type lectin domain family 4, member D (CLEC4D)
(14)Collagen, type XVII, alpha 1 (COL17A1)
(15)Cytochrome b5 reductase 4 (CYB5R4)
(16)DENN/MADD domain containing 1B (DENND1B)
(17)Enoyl CoA hydratase domain containing 3 (ECHDC3)
(18)Ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)
(19)Family with sequence similarity 198, member B (FAM198B)
(20)Family with sequence similarity 49, member B (FAM49B)
(21)Fatty acyl CoA reductase 1 (FAR1)
(22)Fibrinogen-like 2 (FGL2)
(23)Fibronectin type III domain containing 3B (FNDC3B)
(24)Fucose-1-phosphate guanylyltransferase (FPGT)
(25)UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 4 (GalNAc-T4) (GALNT4)
(26)HEAT repeat containing 5A (HEATR5A)
(27)HIV-1 Tat interactive protein 2, 30kDa (HTATIP2)
(28)Interferon gamma receptor 1 (IFNGR1)
(29)IKBKB interacting protein (IKBIP)
(30)Lactate dehydrogenase A (LDHA)
(31)Lysophosphatidic acid receptor 6 (LPAR6)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(33)Minichromosome maintenance complex binding protein (MCMBP)
(34)Mesoderm induction early response 1 homolog (Xenopus laevis) (MIER1)(35)Nuclear factor (erythroid-derived 2)-like 2 (NFE2L2)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)
(37)Oxysterol binding protein-like 8 (OSBPL8)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(39)Protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L)
(40)PR domain containing 5 (PRDM5)
(41)Protein tyrosine phosphatase, receptor type, C (PTPRC)
(42)RAB10, member RAS oncogene family (RAB10)
(43)Ribosomal protein, large, P1 (RPLP1)
(44)Ras-related GTP binding D (RRAGD)
(45)Solute carrier family 22, member 15 (SLC22A15)
(46)Solute carrier family 44, member 1 (SLC44A1)
(47)Schlafen family member 12 (SLFN12)
(48)S1 RNA binding domain 1 (SRBD1)
(49)Tet oncogene family member 2 (TET2)
(50)Transducin-like enhancer of split 2 (E(sp1) homolog, Drosophila) (TLE2)
(51)Ubiquitin-conjugating enzyme E2W (putative) (UBE2W)
(52)Ubiquitination factor E4A (UBE4A)
(53)Ubiquitin specific peptidase 15 (USP15)
(54)WD repeat and SOCS box containing 1 (WSB1)
(55)Zinc finger E-box binding homeobox 2 (ZEB2)
(56)Zinc metallopeptidase (STE24 homolog, S. cerevisiae) (ZMPSTE24)
遺伝子セットB
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8)Chromosome 11 open reading frame 2 (C11orf2)
(10)Cyclin Y-like 1 (CCNYL1)
(13)C-type lectin domain family 4, member D (CLEC4D)
(15)Cytochrome b5 reductase 4 (CYB5R4)
(28)Interferon gamma receptor 1 (IFNGR1)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43)Ribosomal protein, large, P1 (RPLP1)
(52)Ubiquitination factor E4A (UBE4A)
(53)Ubiquitin specific peptidase 15 (USP15)
(57)Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58)Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)
(APBB1)
(59)BCL2-related protein A1 (BCL2A1)
(60)Chromosome 9 open reading frame 72 (C9orf72)
(61)Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62)CD36 molecule (thrombospondin receptor) (CD36)
(63)CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64)CD58 molecule (CD58)
(65)CTAGE family, member 5 (CTAGE5)
(66)V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67)F-box and leucine-rich repeat protein 5 (FBXL5)
(68)Glucuronidase, beta (GUSB)
(69)Huntingtin interacting protein 1 related (HIP1R)
(70)High mobility group box 2 (HMGB2)
(71)Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72)IlvB (bacterial acetolactate synthase)-like (ILVBL)
(73)IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74)Mbt domain containing 1 (MBTD1)
(75)Milk fat globule-EGF factor 8 protein (MFGE8)
(76)Nascent polypeptide-associated complex alpha subunit (NACA)
(77)Nuclear receptor coactivator 5 (NCOA5)
(78)Non-POU domain containing, octamer-binding (NONO)
(79)Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80)Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81)Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82)RAB14, member RAS oncogene family (RAB14)
(83)RNA binding motif protein 14 (RBM14)
(84)Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)(85)Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86)Serglycin (SRGN)
(87)TATA box binding protein (TBP)
(88)Transmembrane protein 167A (TMEM167A)
(89)Thioredoxin (TXN)
(90)Vascular endothelial growth factor B (VEGFB)
(91)Zinc finger protein 764 (ZNF764)
[3] A method for measuring pancreatic cancer based on the expression level of 56 or 47 genes of the following 56 gene sets A or 47 gene sets B in a subject:
Gene set A
(1) Abhydrolase domain containing 3 (ABHD3)
(2) Abl-interactor 1 (ABI1)
(3) Acyl-CoA synthetase long-chain family member 3 (ACSL3)
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(5) ATPase, Class VI, type 11B (ATP11B)
(6) UDP-GlcNAc: betaGal beta-1,3-N-acetylglucosaminyltransferase 5 (B3GNT5)
(7) BTB and CNC homology 1, basic leucine zipper transcription factor 1 (BACH1)
(8) Chromosome 11 open reading frame 2 (C11orf2)
(9) Chromosome 2 open reading frame 81 (C2orf81)
(10) Cyclin Y-like 1 (CCNYL1)
(11) Centromere protein N (CENPN)
(12) Complement factor H-related 3 (CFHR3)
(13) C-type lectin domain family 4, member D (CLEC4D)
(14) Collagen, type XVII, alpha 1 (COL17A1)
(15) Cytochrome b5 reductase 4 (CYB5R4)
(16) DENN / MADD domain containing 1B (DENND1B)
(17) Enoyl CoA hydratase domain containing 3 (ECHDC3)
(18) Ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)
(19) Family with sequence similarity 198, member B (FAM198B)
(20) Family with sequence similarity 49, member B (FAM49B)
(21) Fatty acyl CoA reductase 1 (FAR1)
(22) Fibrinogen-like 2 (FGL2)
(23) Fibronectin type III domain containing 3B (FNDC3B)
(24) Fucose-1-phosphate guanylyltransferase (FPGT)
(25) UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 4 (GalNAc-T4) (GALNT4)
(26) HEAT repeat containing 5A (HEATR5A)
(27) HIV-1 Tat interactive protein 2, 30kDa (HTATIP2)
(28) Interferon gamma receptor 1 (IFNGR1)
(29) IKBKB interacting protein (IKBIP)
(30) Lactate dehydrogenase A (LDHA)
(31) Lysophosphatidic acid receptor 6 (LPAR6)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(33) Minichromosome maintenance complex binding protein (MCMBP)
(34) Mesoderm induction early response 1 homolog (Xenopus laevis) (MIER1) (35) Nuclear factor (erythroid-derived 2) -like 2 (NFE2L2)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A)
(37) Oxysterol binding protein-like 8 (OSBPL8)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(39) Protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L)
(40) PR domain containing 5 (PRDM5)
(41) Protein tyrosine phosphatase, receptor type, C (PTPRC)
(42) RAB10, member RAS oncogene family (RAB10)
(43) Ribosomal protein, large, P1 (RPLP1)
(44) Ras-related GTP binding D (RRAGD)
(45) Solute carrier family 22, member 15 (SLC22A15)
(46) Solute carrier family 44, member 1 (SLC44A1)
(47) Schlafen family member 12 (SLFN12)
(48) S1 RNA binding domain 1 (SRBD1)
(49) Tet oncogene family member 2 (TET2)
(50) Transducin-like enhancer of split 2 (E (sp1) homolog, Drosophila) (TLE2)
(51) Ubiquitin-conjugating enzyme E2W (putative) (UBE2W)
(52) Ubiquitination factor E4A (UBE4A)
(53) Ubiquitin specific peptidase 15 (USP15)
(54) WD repeat and SOCS box containing 1 (WSB1)
(55) Zinc finger E-box binding homeobox 2 (ZEB2)
(56) Zinc metallopeptidase (STE24 homolog, S. cerevisiae) (ZMPSTE24)
Gene set B
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8) Chromosome 11 open reading frame 2 (C11orf2)
(10) Cyclin Y-like 1 (CCNYL1)
(13) C-type lectin domain family 4, member D (CLEC4D)
(15) Cytochrome b5 reductase 4 (CYB5R4)
(28) Interferon gamma receptor 1 (IFNGR1)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43) Ribosomal protein, large, P1 (RPLP1)
(52) Ubiquitination factor E4A (UBE4A)
(53) Ubiquitin specific peptidase 15 (USP15)
(57) Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58) Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)
(APBB1)
(59) BCL2-related protein A1 (BCL2A1)
(60) Chromosome 9 open reading frame 72 (C9orf72)
(61) Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62) CD36 molecule (thrombospondin receptor) (CD36)
(63) CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64) CD58 molecule (CD58)
(65) CTAGE family, member 5 (CTAGE5)
(66) V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67) F-box and leucine-rich repeat protein 5 (FBXL5)
(68) Glucuronidase, beta (GUSB)
(69) Huntingtin interacting protein 1 related (HIP1R)
(70) High mobility group box 2 (HMGB2)
(71) Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72) IlvB (bacterial acetolactate synthase) -like (ILVBL)
(73) IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74) Mbt domain containing 1 (MBTD1)
(75) Milk fat globule-EGF factor 8 protein (MFGE8)
(76) Nascent polypeptide-associated complex alpha subunit (NACA)
(77) Nuclear receptor coactivator 5 (NCOA5)
(78) Non-POU domain containing, octamer-binding (NONO)
(79) Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80) Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81) Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82) RAB14, member RAS oncogene family (RAB14)
(83) RNA binding motif protein 14 (RBM14)
(84) Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA) (85) Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86) Serglycin (SRGN)
(87) TATA box binding protein (TBP)
(88) Transmembrane protein 167A (TMEM167A)
(89) Thioredoxin (TXN)
(90) Vascular endothelial growth factor B (VEGFB)
(91) Zinc finger protein 764 (ZNF764)
[4] 被験体の遺伝子の発現レベルを、被験体の末梢血細胞のmRNAを用いて測定する、[
3]の膵臓癌を検出する方法。
[4] The level of gene expression in the subject is measured using mRNA of the peripheral blood cells of the subject.
[3] The method for detecting pancreatic cancer according to [3].
[5] 遺伝子の発現レベルを、[3]の56個の遺伝子セットA又は47個の遺伝子セットBの56個又は47個の遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドをターゲットとした定量PCRにより測定する、[3]又は[4]の膵
臓癌を検出する方法。
[5] Targeting the expression level of a gene to a nucleotide comprising the nucleotide sequence of 56 or 47 genes of 56 gene sets A or 47 gene sets B of [3] or a partial sequence thereof The method for detecting pancreatic cancer according to [3] or [4], which is measured by quantitative PCR.
[6] 以下の工程を含む、[3]〜[5]のいずれかの膵臓癌を検出する方法:
(1)被験体より採取した末梢血細胞よりmRNAを抽出する工程;
(2)遺伝子セットAの56個の遺伝子又は遺伝子セットBの47個の遺伝子をPCRによ
り増幅し、Ct(Cycle threshold)値を得て、GAPDH等のハウスキーピング遺伝子のCt値により標準化し、標準化Ct値を得る工程;
(3)遺伝子セットA又は遺伝子セットBの各遺伝子の標準化Ct値を判別式に代入し、膵臓癌が陽性である確率を算出する工程。
[6] A method for detecting pancreatic cancer according to any of [3] to [5], comprising the following steps:
(1) A step of extracting mRNA from peripheral blood cells collected from a subject;
(2) 56 genes of gene set A or 47 genes of gene set B are amplified by PCR, Ct (Cycle threshold) values are obtained, standardized by Ct values of housekeeping genes such as GAPDH, and standardized Obtaining a Ct value;
(3) A step of substituting the standardized Ct value of each gene of gene set A or gene set B into a discriminant and calculating the probability that pancreatic cancer is positive.
[7] 以下の判別式を用いて膵臓癌を検出する[6]の膵臓癌を検出する方法であって、以下の判別式から算出される数値が0より大きい場合に膵臓癌陽性であると判定する、[6]の膵臓癌を検出する方法:
式:intercept + Σ(beta i × X i)
[式において、intercept は定数、beta iは遺伝子セットAの56個の遺伝子又は遺伝子
セットBの47個の遺伝子のi番目の遺伝子に対する係数、x iは遺伝子セットAの56
個の遺伝子又は遺伝子セットBの47個の遺伝子のi番目の遺伝子の標準化Ct値であり、
Σは遺伝子セットAの56個の遺伝子又は遺伝子セットBの47個の遺伝子のそれぞれの遺伝子のbeta × Xを合計することを示す。]。
[7] The method for detecting pancreatic cancer according to [6], wherein pancreatic cancer is detected using the following discriminant, and when the numerical value calculated from the following discriminant is greater than 0: [6] The method for detecting pancreatic cancer according to [6]
Expression: intercept + Σ (beta i × X i)
[In the formula, intercept is a constant, beta i is a coefficient for the 56th gene of gene set A or 47th gene of gene set B for the i th gene, x i is 56 of gene set A
A standardized Ct value of the i-th gene of the 47 genes of the gene or gene set B,
Σ indicates that the beta × X of each of 56 genes in gene set A or 47 genes in gene set B is summed. ].
[8] 56個の遺伝子セットAを用いる判別式におけるintercept及び各遺伝子のbeta i
が以下に示す値である、[7]の膵臓癌を検出する方法:
intercept: -298.018
[7] The method for detecting pancreatic cancer, wherein is a value shown below:
intercept: -298.018
[9] 47個の遺伝子セットBを用いる判別式におけるintercept及び各遺伝子のbeta i
が以下に示す値である、[7]の膵臓癌を検出する方法:
intercept:-329.963
[7] The method for detecting pancreatic cancer, wherein is a value shown below:
intercept: -329.963
[10] 被験体から単離したCD4陽性T細胞における膵臓癌特異的遺伝子又は被験体から
単離したマクロファージにおける膵臓癌特異的遺伝子の発現レベルを測定し膵臓癌を検出するための試薬であって、以下の(a)〜(g)のCD4陽性T細胞における7個の膵臓癌特異的
遺伝子の少なくとも1個、又は以下の(c)、(f)、(g)及び(h)のマクロファージにおける4個の膵臓癌特異的遺伝子の少なくとも1個の遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを含む膵臓癌を検出するための試薬:
(a) Fas cell surface death receptor (FAS)
(b) BCL2-associated X protein (BAX)
(c) hydroxyprostaglandin dehydrogenase 15-(NAD) (HPGD)
(d) interleukin 6 (IL-6)
(e) interleukin 7 (IL-7)
(f) peroxisome proliferator-activated receptor gamma (PPARG)
(g) epidermal growth factor receptor pathway substrate 8 (EPS8)
(h) interleukin 15 (IL-15)。
[10] A reagent for detecting pancreatic cancer by measuring the expression level of a pancreatic cancer-specific gene in CD4-positive T cells isolated from a subject or a pancreatic cancer-specific gene in macrophages isolated from a subject, At least one of the seven pancreatic cancer specific genes in CD4 positive T cells of (a) to (g) below, or in macrophages of (c), (f), (g) and (h) below: Reagent for detecting pancreatic cancer comprising a nucleotide comprising a nucleotide sequence of at least one gene of four pancreatic cancer-specific genes or a nucleotide comprising a partial sequence thereof:
(a) Fas cell surface death receptor (FAS)
(b) BCL2-associated X protein (BAX)
(c) hydroxyprostaglandin dehydrogenase 15- (NAD) (HPGD)
(d) interleukin 6 (IL-6)
(e) interleukin 7 (IL-7)
(f) peroxisome proliferator-activated receptor gamma (PPARG)
(g) epidermal growth factor receptor pathway substrate 8 (EPS8)
(h) interleukin 15 (IL-15).
[11] 一部配列を含むヌクレオチドがPCR用プライマーである、[10]の膵臓癌を検出
するための試薬。
[11] The reagent for detecting pancreatic cancer according to [10], wherein the nucleotide containing a partial sequence is a primer for PCR.
[12] 被験体からCD4陽性T細胞又はマクロファージを単離し、単離したCD4陽性T細胞における、以下の(a)〜(g)のCD4陽性T細胞における7個の膵臓癌特異的遺伝子の少なく
とも1個、又は以下の(c)、(f)、(g)及び(h)のマクロファージにおける4個の膵臓癌特異的遺伝子の少なくとも1個の遺伝子の発現レベルを測定し、該発現レベルに基づいて膵臓癌を検出する方法:
(a) Fas cell surface death receptor (FAS)
(b) BCL2-associated X protein (BAX)
(c) hydroxyprostaglandin dehydrogenase 15-(NAD) (HPGD)
(d) interleukin 6 (IL-6)
(e) interleukin 7 (IL-7)
(f) peroxisome proliferator-activated receptor gamma (PPARG)
(g) epidermal growth factor receptor pathway substrate 8 (EPS8)
(h) interleukin 15 (IL-15)。
[12] CD4 positive T cells or macrophages are isolated from a subject, and at least 7 pancreatic cancer specific genes in CD4 positive T cells of the following (a) to (g) in the isolated CD4 positive T cells: The expression level of at least one gene of four pancreatic cancer-specific genes in one or the following macrophages (c), (f), (g) and (h) is measured and based on the expression level How to detect pancreatic cancer:
(a) Fas cell surface death receptor (FAS)
(b) BCL2-associated X protein (BAX)
(c) hydroxyprostaglandin dehydrogenase 15- (NAD) (HPGD)
(d) interleukin 6 (IL-6)
(e) interleukin 7 (IL-7)
(f) peroxisome proliferator-activated receptor gamma (PPARG)
(g) epidermal growth factor receptor pathway substrate 8 (EPS8)
(h) interleukin 15 (IL-15).
[13] 被験体の遺伝子の発現レベルを、被験体のCD4陽性T細胞又はマクロファージのmRNAを用いて測定する、[12]の膵臓癌を検出する方法。 [13] The method for detecting pancreatic cancer according to [12], wherein the expression level of the gene of the subject is measured using mRNA of a CD4 positive T cell or macrophage of the subject.
[14] 遺伝子の発現レベルを、[12]のCD4陽性T細胞における7個の膵臓癌特異的遺
伝子の少なくとも1個、又はマクロファージにおける4個の膵臓癌特異的遺伝子の少なくとも1個の遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドをターゲットとした定量PCRにより測定する、[12]又は[13]の膵臓癌を検出する方法
。
[14] The expression level of the gene is determined based on at least one of seven pancreatic cancer-specific genes in CD4 positive T cells of [12] or at least one gene of four pancreatic cancer-specific genes in macrophages. The method for detecting pancreatic cancer according to [12] or [13], which is measured by quantitative PCR targeting a nucleotide comprising a sequence or a nucleotide comprising a partial sequence thereof.
本発明の56個の遺伝子セットA又は47個の遺伝子セットBの2セットの遺伝子セットの遺伝子のリアルタイムPCRで測定した発現レベルに基づいて、被験体が膵臓癌に罹患
しているか否かを高精度で判定することができる。特に、統計的解析により開発した遺伝子セットA又は遺伝子セットBの56個又は47個の遺伝子の発現レベルを変数とした判別式を用いることにより、容易にかつ高精度に膵臓癌を検出することが可能である。
Based on the expression levels measured by real-time PCR of the genes of two gene sets of 56 gene sets A or 47 gene sets B of the present invention, it is determined whether or not the subject is suffering from pancreatic cancer. It can be determined with accuracy. In particular, pancreatic cancer can be detected easily and with high accuracy by using a discriminant using the expression levels of 56 or 47 genes of gene set A or gene set B developed by statistical analysis as variables. Is possible.
また、本発明のCD4陽性T細胞における7つの膵臓癌特異的遺伝子、又はマクロファー
ジにおける4つの膵臓癌特異的遺伝子のリアルタイムPCRで測定した発現レベルに基づいて、被験体が膵臓癌に罹患しているか否かを高精度で判定することができる。
Whether the subject is suffering from pancreatic cancer based on the expression level measured by real-time PCR of the seven pancreatic cancer-specific genes in the CD4-positive T cells of the present invention or the four pancreatic cancer-specific genes in macrophages. Whether or not can be determined with high accuracy.
以下、本発明を詳細に説明する。
1.遺伝子発現解析による膵臓癌の検出
本発明の方法で用いる遺伝子は、膵臓癌で発現レベルが変動する91個の遺伝子である。これらの91個の遺伝子の発現レベルを測定し発現プロファイルを解析することにより膵臓癌を検出することができる。
Hereinafter, the present invention will be described in detail.
1. Detection of pancreatic cancer by gene expression analysis The genes used in the method of the present invention are 91 genes whose expression levels vary in pancreatic cancer. Pancreatic cancer can be detected by measuring the expression level of these 91 genes and analyzing the expression profile.
本発明の方法で用いる遺伝子は、以下に述べる方法で選択することができる。医師が膵臓癌であると判断した患者を膵臓癌群とし、該膵臓癌群及び健常人群から末梢血単核球を採取し、該単核球からトータルmRNAを単離する。単離したmRNAをヒト遺伝子を含むDNAマ
イクロアレイに適用し、遺伝子の発現レベルを測定し、階層的クラスタリング分析を行い、膵臓癌群と健常人群とで発現レベルに差がある遺伝子を選択する。マイクロアレイ解析で選択された遺伝子について膵臓癌群と健常人群に関してリアルタイムPCRを用いて発現
解析を行う。この際、GAPDH(グリセルアルデヒド3リン酸デヒドロゲナーゼ)等のハウスキーピング遺伝子をコントロールとして発現を解析すればよい。最終的にリアルタイムPCR解析により膵臓癌群で健常人群と発現レベルが異なる遺伝子を膵臓癌特異的遺伝子とし
て選択することができる。
The gene used in the method of the present invention can be selected by the method described below. A patient determined by the doctor to have pancreatic cancer is defined as a pancreatic cancer group, peripheral blood mononuclear cells are collected from the pancreatic cancer group and healthy human group, and total mRNA is isolated from the mononuclear cells. The isolated mRNA is applied to a DNA microarray containing human genes, the gene expression level is measured, hierarchical clustering analysis is performed, and genes having a difference in expression level between the pancreatic cancer group and the healthy human group are selected. For genes selected by microarray analysis, expression analysis is performed using real-time PCR for pancreatic cancer group and healthy human group. At this time, expression may be analyzed using a housekeeping gene such as GAPDH (glyceraldehyde 3-phosphate dehydrogenase) as a control. Finally, a gene whose expression level is different from that of a healthy group in a pancreatic cancer group can be selected as a pancreatic cancer-specific gene by real-time PCR analysis.
本発明で用いる遺伝子は以下に示す91個の遺伝子である。かっこ内に遺伝子のSymbol、NCBI RefSeqID及び配列番号を示す。
(1)Abhydrolase domain containing 3 (ABHD3)(NM_138340.4)(配列番号1)
(2)Abl-interactor 1 (ABI1)(NM_005470.3)(配列番号2)
(3)Acyl-CoA synthetase long-chain family member 3 (ACSL3)(NM_004457.3)(配列番号3)
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)(NM_001628.2)(配列番号4)
(5)ATPase, Class VI, type 11B (ATP11B)(NM_014616.2)(配列番号5)
(6)UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 5 (B3GNT5)
(NM_032047.4)(配列番号6)
(7)BTB and CNC homology 1, basic leucine zipper transcription factor 1 (BACH1)(NM_001186.3)(配列番号7)
(8)Chromosome 11 open reading frame 2 (C11orf2)(NM_013265.3)(配列番号8)(vacuolar protein sorting 51 homolog (S. cerevisiae) (VPS51)とも呼ぶ)
(9)Chromosome 2 open reading frame 81 (C2orf81)(NM_001145054.1)(配列番
号9)
(10)Cyclin Y-like 1 (CCNYL1)(NM_152523.2)(配列番号10)
(11)Centromere protein N (CENPN)(NM_018455.5)(配列番号11)
(12)Complement factor H-related 3 (CFHR3)(NM_021023.5)(配列番号12)
(13)C-type lectin domain family 4, member D (CLEC4D)(NM_080387.4)(配列番号13)
(14)Collagen, type XVII, alpha 1 (COL17A1)(NM_000494.3)(配列番号14)(15)Cytochrome b5 reductase 4 (CYB5R4)(NM_016230.3)(配列番号15)
(16)DENN/MADD domain containing 1B (DENND1B)(NM_001195215.1)(配列番号
16)
(17)Enoyl CoA hydratase domain containing 3 (ECHDC3)(NM_024693.4)(配列番号17)
(18)Ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1)(NM_001776.5)(配列番号18)
(19)Family with sequence similarity 198, member B (FAM198B)(NM_016613.6
)(配列番号19)
(20)Family with sequence similarity 49, member B (FAM49B)(NM_016623.4)
(配列番号20)
(21)Fatty acyl CoA reductase 1 (FAR1)(NM_032228.5)(配列番号21)
(22)Fibrinogen-like 2 (FGL2)(NM_006682.2)(配列番号22)
(23)Fibronectin type III domain containing 3B (FNDC3B)(NM_022763.3)(配列番号23)
(24)Fucose-1-phosphate guanylyltransferase (FPGT)(NM_003838.4)(配列番
号24)
(25)UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 4 (GalNAc-T4) (GALNT4)(NM_003774.4)(配列番号25)
(26)HEAT repeat containing 5A (HEATR5A)(NM_015473.3)(配列番号26)
(27)HIV-1 Tat interactive protein 2, 30kDa (HTATIP2)(NM_006410.4)(配列番号27)
(28)Interferon gamma receptor 1 (IFNGR1)(NM_000416.2)(配列番号28)
(29)IKBKB interacting protein (IKBIP)(NM_201612.2)(配列番号29)
(30)Lactate dehydrogenase A (LDHA)(NM_005566.3)(配列番号30)
(31)Lysophosphatidic acid receptor 6 (LPAR6)(NM_005767.5)(配列番号31)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)(NM_015884.3)(配列番号32)
(33)Minichromosome maintenance complex binding protein (MCMBP)(NM_024834.3)(配列番号33)
(34)Mesoderm induction early response 1 homolog (Xenopus laevis) (MIER1)(NM_020948.3)(配列番号34)
(35)Nuclear factor (erythroid-derived 2)-like 2 (NFE2L2)(NM_006164.4)(配列番号35)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)(NM_001031716.2)(配列番号36)(nucleic acid binding protein 1 (NABP1)とも呼ぶ)
(37)Oxysterol binding protein-like 8 (OSBPL8)(NM_020841.4)(配列番号3
7)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)(NM_006347.3)(配列番号38)
(39)Protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L)(NM_006663.3)(配列番号39)
(40)PR domain containing 5 (PRDM5)(NM_018699.3)(配列番号40)
(41)Protein tyrosine phosphatase, receptor type, C (PTPRC)(NM_002838.4)(配列番号41)
(42)RAB10, member RAS oncogene family (RAB10)(NM_016131.4)(配列番号4
2)
(43)Ribosomal protein, large, P1 (RPLP1)(NM_001003.2)(配列番号43)
(44)Ras-related GTP binding D (RRAGD)(NM_021244.4)(配列番号44)
(45)Solute carrier family 22, member 15 (SLC22A15)(NM_018420.2)(配列番号45)
(46)Solute carrier family 44, member 1 (SLC44A1)(NM_080546.4)(配列番号46)
(47)Schlafen family member 12 (SLFN12)(NM_018042.4)(配列番号47)
(48)S1 RNA binding domain 1 (SRBD1)(NM_018079.4)(配列番号48)
(49)Tet oncogene family member 2 (TET2)(NM_017628.4)(配列番号49)
(50)Transducin-like enhancer of split 2 (E(sp1) homolog, Drosophila) (TLE2)(NM_003260.4)(配列番号50)
(51)Ubiquitin-conjugating enzyme E2W (putative) (UBE2W)(NM_018299.4)(配列番号51)
(52)Ubiquitination factor E4A (UBE4A)(NM_004788.3)(配列番号52)
(53)Ubiquitin specific peptidase 15 (USP15)(NM_006313.2)(配列番号53
)
(54)WD repeat and SOCS box containing 1 (WSB1)(NM_015626.8)(配列番号54)
(55)Zinc finger E-box binding homeobox 2 (ZEB2)(NM_014795.3)(配列番号
55)
(56)Zinc metallopeptidase (STE24 homolog, S. cerevisiae) (ZMPSTE24)(NM_005857.4)(配列番号56)
(57)Alanyl-tRNA synthetase domain containing 1 (AARSD1)(NM_025267.3)(
配列番号57)
(58)Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)
(APBB1)(NM_001164.4)(配列番号58)
(59)BCL2-related protein A1 (BCL2A1)(NM_004049.3)(配列番号59)
(60)Chromosome 9 open reading frame 72 (C9orf72)(NM_018325.4)(配列番号60)
(61)Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)(NM_006135.2)(配列番号61)
(62)CD36 molecule (thrombospondin receptor) (CD36)(NM_000072.3)(配列
番号62)
(63)CD3e molecule, epsilon (CD3-TCR complex) (CD3E)(NM_000733.3)(配列番号63)
(64)CD58 molecule (CD58)(NM_001779.2)(配列番号64)
(65)CTAGE family, member 5 (CTAGE5)(NM_005930.3)(配列番号65)
(66)V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)(NM_005238.3)(配列番号66)
(67)F-box and leucine-rich repeat protein 5 (FBXL5)(NM_012161.3)(配列
番号67)
(68)Glucuronidase, beta (GUSB)(NM_000181.3)(配列番号68)
(69)Huntingtin interacting protein 1 related (HIP1R)(NM_003959.2)(配列番号69)
(70)High mobility group box 2 (HMGB2)(NM_002129.3)(配列番号70)
(71)Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)(NM_007355.3)(配列番号71)
(72)IlvB (bacterial acetolactate synthase)-like (ILVBL)(NM_006844.4)(
配列番号72)
(73)IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)(NM_000884.2
)(配列番号73)
(74)Mbt domain containing 1 (MBTD1)(NM_017643.2)(配列番号74)
(75)Milk fat globule-EGF factor 8 protein (MFGE8)(NM_005928.2)(配列番
号75)
(76)Nascent polypeptide-associated complex alpha subunit (NACA)(NM_005594.4)(配列番号76)
(77)Nuclear receptor coactivator 5 (NCOA5)(NM_020967.2)(配列番号77)(78)Non-POU domain containing, octamer-binding (NONO)(NM_007363.4)(配
列番号78)
(79)Peptidylprolyl isomerase A (cyclophilin A) (PPIA)(NM_021130.4)(配列番号79)
(80)Protein phosphatase 4, regulatory subunit 2 (PPP4R2)(NM_174907.2)(配列番号80)
(81)Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)(NM_001010915.3)(配列番号81)(3-hydroxyacyl-CoA dehydratase 4 (HACD4)とも呼ぶ
)
(82)RAB14, member RAS oncogene family (RAB14)(NM_016322.3)(配列番号8
2)
(83)RNA binding motif protein 14 (RBM14)(NM_006328.3)(配列番号83)
(84)Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)(NM_004168.3)(配列番号84)
(85)Speedy homolog E3 (Xenopus laevis) (SPDYE3)(NM_001004351.4)(配列
番号85)
(86)Serglycin (SRGN)(NM_002727.2)(配列番号86)
(87)TATA box binding protein (TBP)(NM_003194.4)(配列番号87)
(88)Transmembrane protein 167A (TMEM167A)(NM_174909.4)(配列番号88)
(89)Thioredoxin (TXN)(NM_003329.3)(配列番号89)
(90)Vascular endothelial growth factor B (VEGFB)(NM_003377.4)(配列番号90)
(91)Zinc finger protein 764 (ZNF764)(NM_033410.3)(配列番号91)
上記91個の遺伝子(1)〜(91)の塩基配列をそれぞれ配列表の配列番号1〜91に示す。
The genes used in the present invention are the 91 genes shown below. The symbol of the gene, NCBI RefSeqID and the sequence number are shown in parentheses.
(1) Abhydrolase domain containing 3 (ABHD3) (NM_138340.4) (SEQ ID NO: 1)
(2) Abl-interactor 1 (ABI1) (NM_005470.3) (SEQ ID NO: 2)
(3) Acyl-CoA synthetase long-chain family member 3 (ACSL3) (NM_004457.3) (SEQ ID NO: 3)
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1) (NM_001628.2) (SEQ ID NO: 4)
(5) ATPase, Class VI, type 11B (ATP11B) (NM_014616.2) (SEQ ID NO: 5)
(6) UDP-GlcNAc: betaGal beta-1,3-N-acetylglucosaminyltransferase 5 (B3GNT5)
(NM_032047.4) (SEQ ID NO: 6)
(7) BTB and CNC homology 1, basic leucine zipper transcription factor 1 (BACH1) (NM_001186.3) (SEQ ID NO: 7)
(8) Chromosome 11 open reading frame 2 (C11orf2) (NM_013265.3) (SEQ ID NO: 8) (also called vacuolar protein sorting 51 homolog (S. cerevisiae) (VPS51))
(9) Chromosome 2 open reading frame 81 (C2orf81) (NM_001145054.1) (SEQ ID NO: 9)
(10) Cyclin Y-like 1 (CCNYL1) (NM_152523.2) (SEQ ID NO: 10)
(11) Centromere protein N (CENPN) (NM_018455.5) (SEQ ID NO: 11)
(12) Complement factor H-related 3 (CFHR3) (NM_021023.5) (SEQ ID NO: 12)
(13) C-type lectin domain family 4, member D (CLEC4D) (NM_080387.4) (SEQ ID NO: 13)
(14) Collagen, type XVII, alpha 1 (COL17A1) (NM_000494.3) (SEQ ID NO: 14) (15) Cytochrome b5 reductase 4 (CYB5R4) (NM_016230.3) (SEQ ID NO: 15)
(16) DENN / MADD domain containing 1B (DENND1B) (NM_001195215.1) (SEQ ID NO: 16)
(17) Enoyl CoA hydratase domain containing 3 (ECHDC3) (NM_024693.4) (SEQ ID NO: 17)
(18) Ectonucleoside triphosphate diphosphohydrolase 1 (ENTPD1) (NM_001776.5) (SEQ ID NO: 18)
(19) Family with sequence similarity 198, member B (FAM198B) (NM_016613.6
(SEQ ID NO: 19)
(20) Family with sequence similarity 49, member B (FAM49B) (NM_016623.4)
(SEQ ID NO: 20)
(21) Fatty acyl CoA reductase 1 (FAR1) (NM_032228.5) (SEQ ID NO: 21)
(22) Fibrinogen-like 2 (FGL2) (NM_006682.2) (SEQ ID NO: 22)
(23) Fibronectin type III domain containing 3B (FNDC3B) (NM_022763.3) (SEQ ID NO: 23)
(24) Fucose-1-phosphate guanylyltransferase (FPGT) (NM_003838.4) (SEQ ID NO: 24)
(25) UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 4 (GalNAc-T4) (GALNT4) (NM_003774.4) (SEQ ID NO: 25)
(26) HEAT repeat containing 5A (HEATR5A) (NM_015473.3) (SEQ ID NO: 26)
(27) HIV-1 Tat interactive protein 2, 30 kDa (HTATIP2) (NM_006410.4) (SEQ ID NO: 27)
(28) Interferon gamma receptor 1 (IFNGR1) (NM_000416.2) (SEQ ID NO: 28)
(29) IKBKB interacting protein (IKBIP) (NM_201612.2) (SEQ ID NO: 29)
(30) Lactate dehydrogenase A (LDHA) (NM_005566.3) (SEQ ID NO: 30)
(31) Lysophosphatidic acid receptor 6 (LPAR6) (NM_005767.5) (SEQ ID NO: 31)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2) (NM_015884.3) (SEQ ID NO: 32)
(33) Minichromosome maintenance complex binding protein (MCMBP) (NM_024834.3) (SEQ ID NO: 33)
(34) Mesoderm induction early response 1 homolog (Xenopus laevis) (MIER1) (NM_020948.3) (SEQ ID NO: 34)
(35) Nuclear factor (erythroid-derived 2) -like 2 (NFE2L2) (NM_006164.4) (SEQ ID NO: 35)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A) (NM_001031716.2) (SEQ ID NO: 36) (also called nucleic acid binding protein 1 (NABP1))
(37) Oxysterol binding protein-like 8 (OSBPL8) (NM_020841.4) (SEQ ID NO: 3
7)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH) (NM_006347.3) (SEQ ID NO: 38)
(39) Protein phosphatase 1, regulatory (inhibitor) subunit 13 like (PPP1R13L) (NM_006663.3) (SEQ ID NO: 39)
(40) PR domain containing 5 (PRDM5) (NM_018699.3) (SEQ ID NO: 40)
(41) Protein tyrosine phosphatase, receptor type, C (PTPRC) (NM_002838.4) (SEQ ID NO: 41)
(42) RAB10, member RAS oncogene family (RAB10) (NM_016131.4) (SEQ ID NO: 4
2)
(43) Ribosomal protein, large, P1 (RPLP1) (NM_001003.2) (SEQ ID NO: 43)
(44) Ras-related GTP binding D (RRAGD) (NM_021244.4) (SEQ ID NO: 44)
(45) Solute carrier family 22, member 15 (SLC22A15) (NM_018420.2) (SEQ ID NO: 45)
(46) Solute carrier family 44, member 1 (SLC44A1) (NM_080546.4) (SEQ ID NO: 46)
(47) Schlafen family member 12 (SLFN12) (NM_018042.4) (SEQ ID NO: 47)
(48) S1 RNA binding domain 1 (SRBD1) (NM_018079.4) (SEQ ID NO: 48)
(49) Tet oncogene family member 2 (TET2) (NM_017628.4) (SEQ ID NO: 49)
(50) Transducin-like enhancer of split 2 (E (sp1) homolog, Drosophila) (TLE2) (NM_003260.4) (SEQ ID NO: 50)
(51) Ubiquitin-conjugating enzyme E2W (putative) (UBE2W) (NM_018299.4) (SEQ ID NO: 51)
(52) Ubiquitination factor E4A (UBE4A) (NM_004788.3) (SEQ ID NO: 52)
(53) Ubiquitin specific peptidase 15 (USP15) (NM_006313.2) (SEQ ID NO: 53
)
(54) WD repeat and SOCS box containing 1 (WSB1) (NM_015626.8) (SEQ ID NO: 54)
(55) Zinc finger E-box binding homeobox 2 (ZEB2) (NM_014795.3) (SEQ ID NO: 55)
(56) Zinc metallopeptidase (STE24 homolog, S. cerevisiae) (ZMPSTE24) (NM_005857.4) (SEQ ID NO: 56)
(57) Alanyl-tRNA synthetase domain containing 1 (AARSD1) (NM_025267.3) (
SEQ ID NO: 57)
(58) Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65)
(APBB1) (NM_001164.4) (SEQ ID NO: 58)
(59) BCL2-related protein A1 (BCL2A1) (NM_004049.3) (SEQ ID NO: 59)
(60) Chromosome 9 open reading frame 72 (C9orf72) (NM_018325.4) (SEQ ID NO: 60)
(61) Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1) (NM_006135.2) (SEQ ID NO: 61)
(62) CD36 molecule (thrombospondin receptor) (CD36) (NM_000072.3) (SEQ ID NO: 62)
(63) CD3e molecule, epsilon (CD3-TCR complex) (CD3E) (NM_000733.3) (SEQ ID NO: 63)
(64) CD58 molecule (CD58) (NM_001779.2) (SEQ ID NO: 64)
(65) CTAGE family, member 5 (CTAGE5) (NM_005930.3) (SEQ ID NO: 65)
(66) V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1) (NM_005238.3) (SEQ ID NO: 66)
(67) F-box and leucine-rich repeat protein 5 (FBXL5) (NM_012161.3) (SEQ ID NO: 67)
(68) Glucuronidase, beta (GUSB) (NM_000181.3) (SEQ ID NO: 68)
(69) Huntingtin interacting protein 1 related (HIP1R) (NM_003959.2) (SEQ ID NO: 69)
(70) High mobility group box 2 (HMGB2) (NM_002129.3) (SEQ ID NO: 70)
(71) Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1) (NM_007355.3) (SEQ ID NO: 71)
(72) IlvB (bacterial acetolactate synthase) -like (ILVBL) (NM_006844.4) (
SEQ ID NO: 72)
(73) IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2) (NM_000884.2
(SEQ ID NO: 73)
(74) Mbt domain containing 1 (MBTD1) (NM_017643.2) (SEQ ID NO: 74)
(75) Milk fat globule-EGF factor 8 protein (MFGE8) (NM_005928.2) (SEQ ID NO: 75)
(76) Nascent polypeptide-associated complex alpha subunit (NACA) (NM_005594.4) (SEQ ID NO: 76)
(77) Nuclear receptor coactivator 5 (NCOA5) (NM_020967.2) (SEQ ID NO: 77) (78) Non-POU domain containing, octamer-binding (NONO) (NM_007363.4) (SEQ ID NO: 78)
(79) Peptidylprolyl isomerase A (cyclophilin A) (PPIA) (NM_021130.4) (SEQ ID NO: 79)
(80) Protein phosphatase 4, regulatory subunit 2 (PPP4R2) (NM_174907.2) (SEQ ID NO: 80)
(81) Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2) (NM_001010915.3) (SEQ ID NO: 81) (also called 3-hydroxyacyl-CoA dehydratase 4 (HACD4))
(82) RAB14, member RAS oncogene family (RAB14) (NM_016322.3) (SEQ ID NO: 8
2)
(83) RNA binding motif protein 14 (RBM14) (NM_006328.3) (SEQ ID NO: 83)
(84) Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA) (NM_004168.3) (SEQ ID NO: 84)
(85) Speedy homolog E3 (Xenopus laevis) (SPDYE3) (NM_001004351.4) (SEQ ID NO: 85)
(86) Serglycin (SRGN) (NM_002727.2) (SEQ ID NO: 86)
(87) TATA box binding protein (TBP) (NM_003194.4) (SEQ ID NO: 87)
(88) Transmembrane protein 167A (TMEM167A) (NM_174909.4) (SEQ ID NO: 88)
(89) Thioredoxin (TXN) (NM_003329.3) (SEQ ID NO: 89)
(90) Vascular endothelial growth factor B (VEGFB) (NM_003377.4) (SEQ ID NO: 90)
(91) Zinc finger protein 764 (ZNF764) (NM_033410.3) (SEQ ID NO: 91)
The nucleotide sequences of the 91 genes (1) to (91) are shown in SEQ ID NOs: 1 to 91 in the sequence listing, respectively.
本発明の方法において用いるヌクレオチドは、上記配列を含むヌクレオチド又はその断片配列からなるヌクレオチドを含む。また、本発明に用いるヌクレオチドは、上記配列番号で示される塩基配列を有するヌクレオチドとストリンジェントな条件下でハイブリダイズするヌクレオチド及びその断片配列からなるヌクレオチドも含まれる。このようなヌクレオチドとしては、例えば、上記塩基配列との配列同一性の程度が、全体の平均で約80%以上、好ましくは約90%以上、より好ましくは約95%以上、特に好ましくは約98%以上である塩基配列を含有するヌクレオチド等を挙げることができる。ハイブリダイゼーションは、カレント・プロトコールズ・イン・モレキュラー・バイオロジー(Current protocols in molecular biology(edited by Frederick M. Ausubel et al., 1987))に記載の
方法等、当業界で公知の方法あるいはそれに準じる方法に従って行なうことができる。また、市販のライブラリーを使用する場合、添付の使用説明書に記載の方法に従って行なうことができる。ここで、「ストリンジェントな条件」とは、例えば、「1XSSC、0.1% SDS、37℃」程度の条件であり、より厳しい条件としては「0.5XSSC、0.1% SDS、42℃」
程度の条件であり、さらに厳しい条件としては「0.2XSSC、0.1% SDS、65℃」程度の条
件である。このようにハイブリダイゼーションの条件が厳しくなるほどプローブ配列と高い配列同一性を有するヌクレオチドを単離し得る。ただし、上記のSSC、SDS及びに温度の条件の組み合わせは例示であり、当業者であればハイブリダイゼーションのストリンジェンシーを決定する上記もしくは他の要素(例えば、プローブ濃度、プローブの長さ、ハイブリダイゼーションの反応時間など)を適宜組み合わせることにより、上記と同様のストリンジェンシーを実現することが可能である。さらに、これらの遺伝子はバリアントを有する場合もあり、本発明で用いる遺伝子には上記遺伝子のバリアントも含まれる。バリアントの塩基配列は遺伝子データベースにアクセスすることにより得ることができる。本発明のヌクレオチドは該バリアントの塩基配列を含むヌクレオチド又はその断片配列からなるヌクレオチドも含む。
The nucleotide used in the method of the present invention includes a nucleotide comprising the above-described sequence or a nucleotide sequence thereof. The nucleotides used in the present invention also include nucleotides that hybridize under stringent conditions with nucleotides having the base sequence shown by the above SEQ ID NOs and nucleotide fragments thereof. As such nucleotides, for example, the degree of sequence identity with the above-mentioned base sequence is about 80% or more, preferably about 90% or more, more preferably about 95% or more, and particularly preferably about 98% as a whole. And nucleotides containing a base sequence that is at least%. Hybridization is a method known in the art such as the method described in Current protocols in molecular biology (edited by Frederick M. Ausubel et al., 1987) or the like. It can be done according to the method. Moreover, when using a commercially available library, it can carry out according to the method as described in an attached instruction manual. Here, “stringent conditions” are, for example, “1XSSC, 0.1% SDS, 37 ° C.” conditions, and more stringent conditions are “0.5XSSC, 0.1% SDS, 42 ° C.”
The more severe condition is “0.2XSSC, 0.1% SDS, 65 ° C.”. Thus, nucleotides having higher sequence identity with the probe sequence can be isolated as the hybridization conditions become more severe. However, combinations of the above SSC, SDS, and temperature conditions are exemplary, and those skilled in the art will understand the above or other factors that determine the stringency of hybridization (eg, probe concentration, probe length, hybridization). It is possible to achieve the same stringency as described above by appropriately combining the reaction time and the like. Furthermore, these genes may have variants, and the genes used in the present invention include variants of the above genes. The base sequence of the variant can be obtained by accessing a gene database. The nucleotide of the present invention also includes a nucleotide comprising the nucleotide sequence of the variant or a fragment sequence thereof.
また、本発明で用いるヌクレオチドは、上記遺伝子のセンス鎖よりなるヌクレオチド、
アンチセンス鎖よりなるヌクレオチドのいずれをも用いることができる。
The nucleotide used in the present invention is a nucleotide comprising a sense strand of the above gene,
Any nucleotide consisting of an antisense strand can be used.
本発明において、遺伝子の発現レベルとは、遺伝子の発現量、発現強度又は発現頻度をいい、通常、遺伝子に対応する転写産物の産生量、又はその翻訳産物の産生量、活性等により解析することができる。また、発現プロファイルとは、各遺伝子の発現レベルに関する情報をいう。遺伝子の発現レベルは、絶対値で表してもよく、また相対値で表してもよい。なお、発現プロファイルを発現パターンという場合もある。 In the present invention, the expression level of a gene refers to the expression level, expression intensity, or expression frequency of the gene, and is usually analyzed based on the production amount of the transcription product corresponding to the gene or the production amount, activity, etc. of the translation product. Can do. Moreover, an expression profile means the information regarding the expression level of each gene. The gene expression level may be expressed as an absolute value or a relative value. The expression profile may be referred to as an expression pattern.
本発明の方法において、被験体における上記91の遺伝子のうち、(1)〜(56)までの56遺伝子の遺伝子セットA、又は(4)、(8)、(10)、(13)、(15)、(28)、(32)、(36)、(38)、(43)、(52)、(53)及び(57)〜(91)の47遺伝子の遺伝子セットBの発現レベルを指標に膵臓癌を検出する。 In the method of the present invention, among the 91 genes in the subject, the gene set A of 56 genes from (1) to (56), or (4), (8), (10), (13), ( 15), (28), (32), (36), (38), (43), (52), (53) and the expression level of the gene set B of 47 genes of (57) to (91) as an index To detect pancreatic cancer.
発現レベルの測定は、遺伝子の転写産物、すなわちmRNAの測定により行ってもよいし、遺伝子の翻訳産物、すなわちタンパク質の測定により行ってもよい。好ましくは、遺伝子の転写産物の測定により行なう。遺伝子の転写産物には、mRNAから逆転写されて得られたcDNAも含まれる。 The expression level may be measured by measuring a gene transcription product, ie, mRNA, or by measuring a gene translation product, ie, protein. Preferably, it is carried out by measuring a gene transcription product. A gene transcription product also includes cDNA obtained by reverse transcription from mRNA.
遺伝子の転写産物の測定は、上記の遺伝子の塩基配列の全部又は一部を含むヌクレオチドをプローブ又はプライマーとして用いて遺伝子発現の程度を測定すればよい。遺伝子発現の程度は、定量しようとする遺伝子又はその断片をターゲットとした定量PCR法、マイ
クロアレイ(マイクロチップ)を用いた方法、ノーザンブロット法等で測定することが可能である。好ましくは定量PCR法で遺伝子発現を測定する。
The gene transcript may be measured by measuring the degree of gene expression using nucleotides containing all or part of the base sequence of the gene as a probe or primer. The degree of gene expression can be measured by a quantitative PCR method targeting a gene to be quantified or a fragment thereof, a method using a microarray (microchip), a Northern blot method, or the like. Preferably, gene expression is measured by quantitative PCR.
定量PCR法としては、アガロースゲル電気泳動法、蛍光プローブ法、RT-PCR法、リアル
タイムPCR法、ATAC-PCR法(Kato,K.et al.,Nucl.Acids Res.,25,4694-4696,1997)、Taqman
PCR法(SYBR(登録商標)グリーン法)(Schmittgen TD,Methods25,383-385,2001)、Body Map法(Gene,174,151-158(1996))、Serial analysis of gene expression(SAGE)法(米国特許第527,154号、第544,861号、欧州特許公開第0761822号)、MAGE法(Micro-analysis
of Gene Expression)(特開2000-232888号)等がある。リアルタイムPCRとしては、例えばTaqMan(登録商標)プローブを用いた方法等が挙げられる。ここに挙げた方法はいずれも公知の方法で行うことができる。
Quantitative PCR methods include agarose gel electrophoresis, fluorescent probe method, RT-PCR method, real-time PCR method, ATAC-PCR method (Kato, K. et al., Nucl. Acids Res., 25, 4694-4696, 1997), Taqman
PCR method (SYBR (registered trademark) Green method) (Schmittgen TD, Methods 25, 383-385, 2001), Body Map method (Gene, 174, 151-158 (1996)), Serial analysis of gene expression (SAGE) method (US patent) No.527,154, No.544,861, European Patent Publication No.0761822), MAGE method (Micro-analysis
of Gene Expression) (Japanese Patent Laid-Open No. 2000-232888). Examples of real-time PCR include a method using a TaqMan (registered trademark) probe. Any of the methods mentioned here can be carried out by known methods.
PCR法は公知の手法で行うことができる。用いるプライマーの塩基長は、5〜50、好ま
しくは10〜30、さらに好ましくは15〜25である。通常、標的遺伝子の塩基配列に基づいてフォワードプライマー及びリバースプライマーが設計される。本発明の方法において、配列番号1〜91の標的遺伝子の塩基配列に基づいてプライマーの配列を設計することができる。
The PCR method can be performed by a known method. The base length of the primer used is 5 to 50, preferably 10 to 30, and more preferably 15 to 25. Usually, a forward primer and a reverse primer are designed based on the base sequence of the target gene. In the method of the present invention, a primer sequence can be designed based on the base sequence of the target gene of SEQ ID NOs: 1 to 91.
これらの方法を用いて、上記遺伝子の全部又は一部から転写されたメッセンジャーRNA
(mRNA)の量を測定すればよい。
Messenger RNA transcribed from all or part of the above gene using these methods
What is necessary is just to measure the quantity of (mRNA).
DNAマイクロアレイ(DNAチップ)は、前記遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを適当な基板上に固定化することにより作製することができる。 A DNA microarray (DNA chip) can be prepared by immobilizing nucleotides comprising the base sequence of the gene or nucleotides including a partial sequence thereof on an appropriate substrate.
固定基板としては、ガラス板、石英板、シリコンウェハーなどが挙げられる。基板の大きさとしては、例えば3.5mm×5.5mm、18mm×18mm、22mm×75mmなどが挙げられるが、これは基板上のプローブのスポット数やそのスポットの大きさなどに応じて様々に設定することができる。ポリヌクレオチド又はその断片の固定化方法としては、ヌクレオチドの荷電
を利用して、ポリリジン、ポリエチレンイミン、ポリアルキルアミンなどのポリ陽イオンで表面処理した固相担体に静電結合させたり、アミノ基、アルデヒド基、エポキシ基などの官能基を導入した固相表面に、アミノ基、アルデヒド基、SH基、ビオチンなどの官能基を導入したヌクレオチドを共有結合により結合させることもできる。固定化は、アレイ機を用いて行えばよい。上記20個の遺伝子又はその断片を基板に固相化してDNAマイクロ
アレイを作製し、該DNAマイクロアレイと蛍光物質で標識した被験体由来のmRNAまたはcDNAを接触させ、ハイブリダイズさせ、DNAマイクロアレイ上の蛍光強度を測定することにより、mRNAの種類と量を決定することができる。その結果、被験体において発現が変動している遺伝子がわかり、遺伝子発現プロファイルを得ることができる。被験体由来のmRNAを標識する蛍光物質は、限定されず、市販の蛍光物質を用いることができる。例えば、Cy3
、Cy5等を用いればよい。mRNAの標識は公知の方法で行うことができる。DNAマイクロアレイを用いた方法は、上記遺伝子のmRNAにハイブリダイズするヌクレオチドプローブの使用により測定することができる。測定に用いるプローブの塩基長は、10〜50bp、好ましくは15〜25bpである。
Examples of the fixed substrate include a glass plate, a quartz plate, and a silicon wafer. Examples of the size of the substrate include 3.5 mm × 5.5 mm, 18 mm × 18 mm, 22 mm × 75 mm, etc., which are variously set according to the number of probe spots on the substrate and the size of the spots. be able to. As a method for immobilizing a polynucleotide or a fragment thereof, it is possible to electrostatically bind to a solid phase carrier surface-treated with a polycation such as polylysine, polyethyleneimine, polyalkylamine, etc. A nucleotide having a functional group such as an amino group, an aldehyde group, an SH group, or biotin can be covalently bonded to a solid phase surface into which a functional group such as an aldehyde group or an epoxy group has been introduced. Immobilization may be performed using an array machine. The 20 genes or fragments thereof are immobilized on a substrate to prepare a DNA microarray. The DNA microarray is contacted with mRNA or cDNA derived from a subject labeled with a fluorescent substance, hybridized, and fluorescent on the DNA microarray. By measuring the intensity, the type and amount of mRNA can be determined. As a result, a gene whose expression is fluctuating in a subject can be known, and a gene expression profile can be obtained. The fluorescent substance for labeling mRNA derived from a subject is not limited, and a commercially available fluorescent substance can be used. For example, Cy3
, Cy5 or the like may be used. mRNA can be labeled by a known method. The method using a DNA microarray can be measured by using a nucleotide probe that hybridizes to the mRNA of the above gene. The base length of the probe used for measurement is 10 to 50 bp, preferably 15 to 25 bp.
遺伝子の翻訳産物の測定は、翻訳されたタンパク質を定量するか、又はタンパク質の活性を測定すればよい。タンパク質の定量はELISA等の免疫測定法により行うことができる
。
The translation product of the gene may be measured by quantifying the translated protein or measuring the activity of the protein. Protein quantification can be performed by immunoassay methods such as ELISA.
遺伝子の転写産物を測定する場合の試料は、被験体の細胞を用い、細胞からmRNAを抽出単離すればよい。細胞は、限定されないが、血液中の細胞が好ましく、その中でも末梢血液中の白血球、特に単核球(PBMC)が好ましい。単核球は、血液成分分離装置を用いたアフェレーシスによって単離することもできるし、末梢血液から密度勾配遠心分離法により単離してもよい。密度勾配遠心分離による単核球の単離は、公知のFicoll-Paque(登録商標)比重遠心法により行うことができる。 As a sample for measuring a gene transcript, the subject's cells may be used, and mRNA may be extracted and isolated from the cells. The cells are not limited, but are preferably cells in blood, among which leukocytes in peripheral blood, particularly mononuclear cells (PBMC) are preferred. Mononuclear cells can be isolated by apheresis using a blood component separator, or can be isolated from peripheral blood by density gradient centrifugation. Isolation of mononuclear cells by density gradient centrifugation can be performed by a known Ficoll-Paque (registered trademark) specific gravity centrifugation method.
本発明の方法により、被験体が膵臓癌に罹患しているか否かを評価判定し、膵臓癌に罹患するリスクの程度を評価判定することができる。また、被験体が膵臓癌に罹患するリスクが高いか否かを評価判定することができる。さらに、膵臓癌に罹患している被験体における病態予測、予後予測が可能になる。本発明は、膵臓癌に罹患しているか否か、あるいは罹患するリスクが高いかの判定、並びに病態予測及び予後予測を行うための補助的データを取得する方法でもある。 According to the method of the present invention, it is possible to evaluate and determine whether or not a subject has pancreatic cancer, and to evaluate and determine the degree of risk of having pancreatic cancer. Further, it can be evaluated whether or not the subject has a high risk of suffering from pancreatic cancer. Furthermore, it is possible to predict a disease state and prognosis in a subject suffering from pancreatic cancer. The present invention is also a method for obtaining auxiliary data for determining whether or not a patient has pancreatic cancer or having a high risk of suffering, and for predicting a disease state and prognosis.
例えば、被験体において、上記56個の遺伝子セットA又は47個の遺伝子セットBのうち、膵臓癌患者において発現が亢進する遺伝子の発現が亢進しているか、膵臓癌患者において発現が減弱する遺伝子の発現が減弱しているか、あるいは膵臓癌患者において発現が亢進する遺伝子の発現が亢進し、かつ膵臓癌患者において発現が減弱する遺伝子の発現が減弱している場合、被験体は膵臓癌に罹患していると評価判定することができ、又は被験体は膵臓癌に罹患するリスクが大きいと評価判定することができる。例えば、膵臓癌患者において発現が亢進する遺伝子の発現が健常人に比べ有意に亢進している場合、又は膵臓癌患者において発現が減弱する遺伝子の発現が健常人に比べ有意に減弱している場合、被験体は膵臓癌に罹患しているか、又は膵臓癌に罹患するリスクが高いと評価判定することができる。ここで、有意に亢進しているとは、統計学的に有意差をもって発現が亢進していると決定できることをいい、例えば遺伝子発現の絶対値又は相対値が1.2倍以上、好
ましくは1.5倍以上、さらに好ましくは2倍以上に亢進している場合をいう。また、有意
に減弱しているとは、統計学的に有意差をもって発現が減弱していると決定できることをいい、例えば遺伝子発現の絶対値又は相対値が3分の2以下、好ましくは2分の1以下、さらに好ましくは3分の1以下に減弱している場合をいう。ここで、評価、判定とは予測ともいう。また、本発明において、上記の膵臓癌に罹患しているか否かの評価判定、膵臓癌に罹患するリスクの評価判定、病態予測、予後予測等を広く膵臓癌の検出という。
For example, in a subject, among the 56 gene sets A or 47 gene sets B, the expression of a gene whose expression is increased in a pancreatic cancer patient is increased, or a gene whose expression is attenuated in a pancreatic cancer patient. A subject suffers from pancreatic cancer if expression is attenuated or expression of a gene that is upregulated in pancreatic cancer patients is increased and expression of a gene that is attenuated in pancreatic cancer patients is attenuated. Or the subject can be assessed to be at high risk for suffering from pancreatic cancer. For example, when the expression of a gene whose expression is increased in a pancreatic cancer patient is significantly increased compared to a healthy person, or the expression of a gene whose expression is decreased in a pancreatic cancer patient is significantly attenuated compared to a healthy person The subject can be evaluated as having pancreatic cancer or having a high risk of having pancreatic cancer. Here, significantly increased means that it can be determined that expression is statistically significantly increased, for example, the absolute value or relative value of gene expression is 1.2 times or more, preferably 1.5 times or more More preferably, it refers to a case where it is enhanced by 2 times or more. Also, “significantly attenuated” means that it can be determined that expression is attenuated with a statistically significant difference. For example, the absolute value or relative value of gene expression is 2/3 or less, preferably 2 minutes. Or less, more preferably 1/3 or less. Here, evaluation and determination are also called prediction. In the present invention, the above-described evaluation determination as to whether or not the patient suffers from pancreatic cancer, evaluation evaluation of the risk of suffering from pancreatic cancer, disease state prediction, prognosis prediction, and the like are widely referred to as detection of pancreatic cancer.
また、上記56個の遺伝子セットA又は47個の遺伝性セットBのすべての遺伝子発現プロファイルを得て、発現プロファイルを解析することにより、被験体の病態又は膵臓癌に罹患するリスクを評価判定することができる。被験体から得られた発現プロファイルが膵臓癌患者群で得られた発現プロファイルと類似している場合、被験体は膵臓癌に罹患していると評価判定することができ、被験体から得られた発現プロファイルが膵臓癌群で得られた発現プロファイルと類似している場合、被験体は膵臓癌に罹患しているか、又は膵臓癌に罹患するリスクが大きいと評価判定することができる。また、被験体から得られた発現プロファイルを健常人で得られた発現プロファイルと比較し、健常人の発現プロファイルとの相違により、評価判定することもできる。 In addition, by obtaining all gene expression profiles of the 56 gene sets A or 47 heritable sets B and analyzing the expression profiles, the disease state of the subject or the risk of suffering from pancreatic cancer is evaluated and determined. be able to. If the expression profile obtained from the subject is similar to the expression profile obtained in the pancreatic cancer patient group, the subject can be assessed as having pancreatic cancer and obtained from the subject. When the expression profile is similar to the expression profile obtained in the pancreatic cancer group, it can be determined that the subject is suffering from pancreatic cancer or has a high risk of suffering from pancreatic cancer. Moreover, the expression profile obtained from the subject can be compared with the expression profile obtained in a healthy person, and evaluation can be made based on the difference from the expression profile of the healthy person.
遺伝子発現プロファイルは、蛍光強度等の発現シグナルのパターンが、デジタル数値で又は色を有する画像で記録される。遺伝子発現プロファイルの比較は、例えばパターン比較ソフトウェアを用いて行うことができ、判別分析、コックスハザード分析等を利用することができる。あらかじめ病態を評価判定し、病態予測又は予後予測を行うための判別分析モデルを構築し、該判別分析モデルに被験体から得られた遺伝子発現プロファイルに関するデータを入力し、病態を評価判定し、病態予測又は予後予測を行うこともできる。例えば、判別分析により判別式を得て、蛍光強度と病態、病態予測又は予後予測を関連付け、判別式に被験体の発現シグナル数値を代入することにより、病態を評価判定し、病態予測又は予後予測を行うことができる。 The gene expression profile is recorded as an image in which a pattern of an expression signal such as fluorescence intensity is a digital value or a color. Comparison of gene expression profiles can be performed using, for example, pattern comparison software, and discriminant analysis, Cox hazard analysis, or the like can be used. Establish a discriminant analysis model to evaluate and determine the pathological condition in advance, perform pathological or prognostic prediction, input data on the gene expression profile obtained from the subject to the discriminant analysis model, evaluate and determine the pathological condition, Prediction or prognosis can also be performed. For example, a discriminant is obtained by discriminant analysis, the fluorescence intensity is associated with a disease state, a disease state prediction or a prognosis prediction, and the expression signal value of the subject is substituted into the discriminant to evaluate and determine the disease state. It can be performed.
本発明は、本発明の56個の遺伝子セットA又は47個の遺伝子セットBの塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを含む膵臓癌を検出するための試薬又はキットを包含する。該試薬は、前記遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドをプライマー又はプローブとして含む試薬であり、また前記遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを固相化したマイクロアレイ等の基板である。PCRキットの場合、他に熱安定性ポリメラーゼ、
逆転写酵素、デオキシヌクレオチド3リン酸、ヌクレオチド3リン酸等を含んでいてもよい。
The present invention includes a reagent or kit for detecting pancreatic cancer comprising a nucleotide comprising the nucleotide sequence of 56 gene sets A or 47 gene sets B of the present invention or a nucleotide sequence including a partial sequence thereof. The reagent is a reagent comprising a nucleotide comprising the nucleotide sequence of the gene or a nucleotide comprising a partial sequence thereof as a primer or probe, and a nucleotide comprising the nucleotide sequence of the gene or a nucleotide comprising a partial sequence thereof as a solid phase. A microarray substrate. In the case of a PCR kit, in addition to a thermostable polymerase,
It may contain reverse transcriptase, deoxynucleotide triphosphate, nucleotide triphosphate and the like.
この試薬又はキットは、上記56個の遺伝子セットA又は47個の遺伝子セットBのそれぞれの56個又は47個の遺伝子の全ての遺伝子の一部配列を含むヌクレオチドを含んでいる。 This reagent or kit contains a nucleotide containing a partial sequence of all of the 56 genes or 47 genes of the 56 gene sets A or 47 gene sets B, respectively.
また、本発明の方法において、あらかじめ膵臓癌に罹患しているか否かを検出し、膵臓癌に罹患するリスクの程度を評価判定し、又は病態予測若しくは予後予測を行うための判別式を構築し、当該判別式に被験体から得られた56個の遺伝子セットA又は47個の遺伝子セットBの発現レベルに関するデータを入力し、膵臓癌に罹患しているか否かを検出し、膵臓癌に罹患するリスクの程度を評価判定し、又は病態予測若しくは予後予測を行うこともできる。例えば、判別分析により判別式を得て、発現レベルと病態、病態予測又は予後予測を関連付け、判別式に被験体の発現レベルを代入することにより、病態を評価判定し、病態予測又は予後予測を行うことができる。発現レベルを示す数値としては、例えば、リアルタイムPCRによって目的遺伝子の増幅を行ったときの増幅産物がある一定量に
達したときのサイクル数(Cycle threshold: Ct)が挙げられる。横軸に増幅のサイクル数、縦軸にPCR増幅産物量をプロットして、増幅曲線を作成し、PCR増幅産物量の値に閾値(Threshold)を設定したときに閾値と増幅曲線が交わる点のサイクル数がCt値となる。プ
ローブを用いた場合は、蛍光強度を用いることもできる。発現レベルを測定するときは、被験体の状態に関らず普遍的に一定レベルで発現している遺伝子の発現レベルに対する相対値を用いるのが好ましい。普遍的に一定レベルで発現している遺伝子として、ハウスキーピング遺伝子が挙げられ、例えば、グリセロアルデヒド3リン酸デヒドロゲナーゼ(GAP
DH)が挙げられる。同一サンプルにおいて、各遺伝子の発現レベルの測定と同時にGAPDH
の発現レベルを内部標準として測定し、各遺伝子の発現レベルをGAPDHの発現レベルに対
する相対値で表せばよい。例えば、リアルタイムPCRで発現レベルを測定する場合、発現
量が一定のハウスキーピング遺伝子(内部標準)について、リアルタイムPCRを行い、Ct
値を求める。次いで、目的の遺伝子についてハウスキーピング遺伝子と同じ条件でリアルタイムPCRを行い、Ct値を求める。目的の遺伝子のCt値をハウスキーピング遺伝子のCt値
で除し、標準化Ct値を求めて、判別式作成のための遺伝子定量値として用いればよい。一方、各遺伝子の発現レベルが蛍光強度で表される場合、各遺伝子の蛍光強度をGAPDHの蛍
光強度で除すればよい。
Further, in the method of the present invention, it is detected whether or not the patient is previously suffering from pancreatic cancer, the degree of risk of suffering from pancreatic cancer is evaluated and determined, or a discriminant for constructing a disease state prediction or prognosis prediction is constructed. The data on the expression level of 56 gene sets A or 47 gene sets B obtained from the subject is input to the discriminant, and it is detected whether or not the patient has pancreatic cancer. It is also possible to evaluate and evaluate the degree of risk, or to predict the disease state or prognosis. For example, a discriminant is obtained by discriminant analysis, the expression level is associated with a disease state, a disease state prediction or a prognosis prediction. It can be carried out. Examples of the numerical value indicating the expression level include the cycle number (Cycle threshold: Ct) when the amplification product reaches a certain amount when the target gene is amplified by real-time PCR. Plot the number of amplification cycles on the horizontal axis and the amount of PCR amplification product on the vertical axis, create an amplification curve, and set the threshold value (Threshold) to the value of PCR amplification product amount. The number of cycles is the Ct value. When a probe is used, fluorescence intensity can also be used. When measuring the expression level, it is preferable to use a relative value to the expression level of a gene that is universally expressed at a constant level regardless of the state of the subject. Examples of genes that are universally expressed at a certain level include housekeeping genes, such as glyceraldehyde 3-phosphate dehydrogenase (GAP).
DH). GAPDH simultaneously with the measurement of the expression level of each gene in the same sample
And the expression level of each gene may be expressed as a relative value to the expression level of GAPDH. For example, when measuring the expression level by real-time PCR, real-time PCR is performed on a housekeeping gene (internal standard) with a constant expression level.
Find the value. Next, real-time PCR is performed on the target gene under the same conditions as the housekeeping gene to obtain a Ct value. The Ct value of the target gene is divided by the Ct value of the housekeeping gene to obtain a standardized Ct value, which can be used as a gene quantitative value for creating a discriminant. On the other hand, when the expression level of each gene is expressed by fluorescence intensity, the fluorescence intensity of each gene may be divided by the fluorescence intensity of GAPDH.
判別分析は、2群以上の母集団から抽出した標本データを得て、どの母集団に属するか不明のサンプルデータがある場合に、このサンプルデータがどの母集団に属するか調べる方法である。本発明においては56個の遺伝子セットA及び47個の遺伝子セットBのそれぞれの56個又は47個の遺伝子の発現レベルに関する数値からなる多変量データ(x1、x2、・・・xn)を説明変数として用いて、判別分析を行う。 Discriminant analysis is a method of obtaining sample data extracted from two or more populations and examining which population the sample data belongs to when there is unknown sample data belonging to which population. In the present invention, multivariate data (x1, x2,... Xn) composed of numerical values related to the expression levels of 56 genes or 47 genes of 56 gene sets A and 47 gene sets B are used as explanatory variables. To perform discriminant analysis.
このような判別分析の手法は公知であり、代表的な判別分析法として、サポートベクターマシン(support vector machine:SVM)による判別、線形判別関数による判別、ロジスティック回帰分析等があり、どのような手法を用いてもよいが、非線形への拡張が可能な線形カーネルをもつサポートベクターマシン(support vector machine; SVM)を用いることが好ましい。 Such discriminant analysis methods are known, and typical discriminant analysis methods include discriminating with a support vector machine (SVM), discriminating with a linear discriminant function, logistic regression analysis, etc. However, it is preferable to use a support vector machine (SVM) having a linear kernel that can be extended to nonlinear.
サポートベクターマシンを用いた判別式の作成においては、1つのサンプルをテストセット(testing set)とし、他を訓練セット(training set)とする交差検証法(Leave-one-out cross-validation; LOOCV)を行えばよい。 In creating discriminants using support vector machines, cross-validation (LOOCV) with one sample as the testing set and the other as the training set Can be done.
本発明の方法においては、リアルタイムPCRを用いて発現レベルを測定し、サポートベ
クターマシンを用いて構築した以下の判別式Iを用いればよい。
式I:intercept + Σ(beta i × X i) > 0 ならば 膵臓癌陽性
[式Iにおいて、intercept は定数、beta iは遺伝子セットAの56個の遺伝子又は遺伝
子セットBの47個の遺伝子のi番目の遺伝子に対する係数、X iは遺伝子セットAの56個の遺伝子又は遺伝子セットBの47個の遺伝子のi番目の遺伝子の標準化Ct値であり、
Σは遺伝子セットAの56個の遺伝子又は遺伝子セットBの47個の遺伝子のそれぞれの遺伝子のbeta × Xを合計することを示す。]
56個の遺伝子セットA及び47個の遺伝子セットBについて上記の式Iにそれぞれの遺伝子のCt値を入れ計算し、算出された数値が0を超える場合に、膵臓癌が陽性であると判定することができる。ここで、膵臓癌が陽性であるとは、膵臓癌に罹患していると判定することができ、膵臓癌に罹患するリスクが高いと判定することができることをいう。
In the method of the present invention, the expression level is measured using real-time PCR, and the following discriminant I constructed using a support vector machine may be used.
If formula I: intercept + Σ (beta i × X i)> 0, pancreatic cancer positive
[In Formula I, intercept is a constant, beta i is a coefficient for the 56th gene in gene set A or 47th gene in gene set B for the i th gene, and X i is 56 genes or genes in gene set A. It is the normalized Ct value of the i-th gene of 47 genes of set B,
Σ indicates that the beta × X of each of 56 genes in gene set A or 47 genes in gene set B is summed. ]
The 56 gene sets A and 47 gene sets B are calculated by putting the Ct value of each gene into the above formula I, and when the calculated numerical value exceeds 0, it is determined that pancreatic cancer is positive. be able to. Here, that pancreatic cancer is positive means that it can be determined that the patient is suffering from pancreatic cancer and the risk of suffering from pancreatic cancer can be determined to be high.
ここで、(1)〜(56)までの56遺伝子の遺伝子セットA、又は(4)、(8)、(10)、(13)、(15)、(28)、(32)、(36)、(38)、(43)、(52)、(53)及び(57)〜(91)の47遺伝子の遺伝子セットBについて、interceptの値及び各遺伝子のbetaは以下のとおりである。遺伝子セットA及びBの各遺伝
子のbetaは、それぞれ、表3及び4に示す。
遺伝子セットAのintercept: -298.018
遺伝子セットBのintercept: -329.963
Here, gene set A of 56 genes from (1) to (56), or (4), (8), (10), (13), (15), (28), (32), (36 ), (38), (43), (52), (53), and the gene set B of 47 genes of (57) to (91), the value of intercept and the beta of each gene are as follows. The beta of each gene in gene sets A and B is shown in Tables 3 and 4, respectively.
Gene set A intercept: -298.018
Gene set B intercept: -329.963
本発明の方法による膵臓癌の検出は、例えば、以下の工程で行う。
(1)被験体より採取した末梢血細胞よりmRNAを抽出する。
(2)遺伝子セットAの56個の遺伝子又は遺伝子セットBの47個の遺伝子をPCRによ
り増幅し、Ct(Cycle threshold)値を得て、GAPDH等のハウスキーピング遺伝子のCt値に
より標準化し、標準化Ct値を得る。
(3)遺伝子セットAについては、遺伝子セットAの各遺伝子の標準化Ct値を判別式Aに代入し、膵臓癌が陽性である確率Pを求める。遺伝子セットBについては、遺伝子セットBの各遺伝子の標準化Ct値を判別式Bに代入し、Pを求める。
(4)Pが0を超える場合に、前記被験体は膵臓癌が陽性であると評価判定することができる。
Detection of pancreatic cancer by the method of the present invention is performed, for example, in the following steps.
(1) mRNA is extracted from peripheral blood cells collected from a subject.
(2) 56 genes of gene set A or 47 genes of gene set B are amplified by PCR, Ct (Cycle threshold) values are obtained, standardized by Ct values of housekeeping genes such as GAPDH, and standardized Get the Ct value.
(3) For gene set A, the standardized Ct value of each gene in gene set A is substituted into discriminant A to determine the probability P that pancreatic cancer is positive. For gene set B, P is obtained by substituting the standardized Ct value of each gene of gene set B into discriminant B.
(4) When P exceeds 0, the subject can be evaluated and judged to be positive for pancreatic cancer.
本発明は本発明の膵臓癌を検出する方法により、被験体の膵臓癌を検出するシステムを包含する。 The present invention includes a system for detecting pancreatic cancer in a subject by the method for detecting pancreatic cancer of the present invention.
本発明の膵臓癌を検出するシステムは、
(a) 被験体の遺伝子発現プロファイルに関するデータを入力する手段、ここで入力され
る遺伝子発現プロファイルに関するデータとは、例えば、各遺伝子における標準化Ct値等の各遺伝子の発現レベルを示すデータである;
(b) 構築した判別式を記憶している記憶手段、
(c) (a)の入力手段を用いて入力したデータを(b)の記憶手段に記憶されている判別式に
適用して、膵臓癌の病態の決定を行うためのデータ処理手段、及び
(d) 予測された膵臓癌の病態の決定、病態予測、予後予測を出力する出力手段、
を含むシステムである。
The system for detecting pancreatic cancer of the present invention comprises:
(a) means for inputting data relating to the gene expression profile of the subject, and the data relating to the gene expression profile input here is data indicating the expression level of each gene such as a standardized Ct value in each gene;
(b) storage means for storing the constructed discriminant,
(c) applying data input using the input means of (a) to the discriminant stored in the storage means of (b), data processing means for determining the pathological condition of pancreatic cancer, and
(d) Output means for outputting the predicted pathological condition of the pancreatic cancer, pathological condition prediction, prognosis prediction,
It is a system including
(a)のデータを入力する手段は、キーボード又はデータを記憶した外部記憶装置等を含
む。(b)の記憶手段はハードディスク等を含む。データ処理手段は、記憶手段から判別モ
デルを受け取るとともに、入力されたデータを処理して、処理結果を出力手段に送り、出力手段で処理結果が表示される。データ処理手段は、データを演算処理する中央演算処理装置(CPU)等を含む。また、出力手段は、結果を表示するモニタやプリンタを含む。
The means for inputting data in (a) includes a keyboard or an external storage device storing data. The storage means (b) includes a hard disk or the like. The data processing means receives the discrimination model from the storage means, processes the input data, sends the processing result to the output means, and the processing result is displayed by the output means. The data processing means includes a central processing unit (CPU) that performs arithmetic processing on data. The output means includes a monitor and a printer for displaying the result.
本発明のシステムは、市販のパーソナルコンピュータ等を用いて構築することが可能である。 The system of the present invention can be constructed using a commercially available personal computer or the like.
2.CD4陽性T細胞又はマクロファージにおける膵臓癌特異的遺伝子
被験体のCD4陽性T細胞又はマクロファージ中の遺伝子発現レベルを測定し、発現プロ
ファイルを解析することにより膵臓癌を検出することができる。
2. Pancreatic cancer-specific gene in CD4-positive T cells or macrophages Pancreatic cancer can be detected by measuring the gene expression level in CD4-positive T cells or macrophages of a subject and analyzing the expression profile.
CD4陽性T細胞又はマクロファージは、被験体の末梢血より単離すればよく、CD4陽性T細胞は、CD4の発現を指標に単離することができ、マクロファージはCD14の発現を指標に
単離することができる。これらの細胞の単離は、FACS、フローサイトメーターを用いて行うことができ、例えばFACS vantage(ベクトン・ディッキンソン社製)、FACS Calibur(ベ
クトン・ディッキンソン社製)等を用いることができる。また、抗CD4抗体又は抗CD14抗体を結合させた磁性粒子を用いて、磁気分離装置により単離することができる。このような磁気分離装置として、例えばautoMACS(登録商標)(Miltenyi Biotec)等が挙げられる。
CD4 positive T cells or macrophages may be isolated from the peripheral blood of the subject, CD4 positive T cells can be isolated using CD4 expression as an indicator, and macrophages are isolated using CD14 expression as an indicator. be able to. These cells can be isolated using a FACS or a flow cytometer. For example, FACS vantage (Becton Dickinson), FACS Calibur (Becton Dickinson) or the like can be used. Further, it can be isolated by a magnetic separation apparatus using magnetic particles to which an anti-CD4 antibody or an anti-CD14 antibody is bound. Examples of such a magnetic separation device include autoMACS (registered trademark) (Miltenyi Biotec).
CD4陽性T細胞又はマクロファージにおける膵臓癌特異的遺伝子の発現レベルは、単離
したCD4陽性細胞又はマクロファージからトータルRNAを抽出し、1.と同様にして測定することができる。
The expression level of pancreatic cancer-specific gene in CD4-positive T cells or macrophages is determined by extracting total RNA from isolated CD4-positive cells or macrophages. It can be measured in the same manner.
膵臓癌患者のCD4陽性T細胞において、以下の(a)〜(g)の7つの遺伝子の発現レベルが
上昇している。これら7つの遺伝子をCD4陽性T細胞における膵臓癌特異的遺伝子と呼ぶ
。従って、被験体から単離した、CD4陽性細胞において、これらの7つの遺伝子の少なく
とも1個、例えば、1個、2個、3個、4個、5個、6個又は7個の遺伝子、好ましくは7個すべての遺伝子の発現レベルが健常人に対して上昇している場合、該被験体は膵臓癌
に罹患していると評価判定することができ、又は被験体は膵臓癌に罹患するリスクが大きいと評価判定することができる。
Expression levels of the following seven genes (a) to (g) are increased in CD4 positive T cells of pancreatic cancer patients. These seven genes are called pancreatic cancer specific genes in CD4 positive T cells. Thus, in CD4 positive cells isolated from a subject, at least one of these seven genes, for example 1, 2, 3, 4, 5, 6 or 7 genes, preferably Can assess that the subject is suffering from pancreatic cancer, or the subject is at risk of suffering from pancreatic cancer if the expression levels of all seven genes are elevated relative to a healthy person It can be judged that the evaluation is large.
(a) Fas cell surface death receptor (FAS) (NM_000043.4)(配列番号92)
(b) BCL2-associated X protein (BAX) (NM_004324.3)(配列番号93)
(c) hydroxyprostaglandin dehydrogenase 15-(NAD) (HPGD) (NM_ 000860.5)(配列番号94)
(d) interleukin 6 (IL-6) (NM_000600.3)(配列番号95)
(e) interleukin 7 (IL-7) (NM_000880.3)(配列番号96)
(f) peroxisome proliferator-activated receptor gamma (PPARG) (NM_ 005037.5)(配列番号97)
(g) epidermal growth factor receptor pathway substrate 8 (EPS8) (NM_004447.5)(配列番号98)
また、膵臓癌患者のマクロファージにおいて、上記の(c) HPGD、(f) PPARG、(g) EPS8及び(h) interleukin 15 (IL-15) (NM_ 000585.4)(配列番号99)の4つの発現が上昇している。これら4つの遺伝子をマクロファージにおける膵臓癌特異的遺伝子と呼ぶ。従って、被験体から単離したマクロファージにおいて、これらの4つの遺伝子の少なくとも1個、例えば、1個、2個、3個又は4個の遺伝子、好ましくは4個すべての遺伝子の発現レベルが健常人に対して上昇している場合、該被験体は膵臓癌に罹患していると評価判定することができ、又は被験体は膵臓癌に罹患するリスクが大きいと評価判定することができる。
(a) Fas cell surface death receptor (FAS) (NM_000043.4) (SEQ ID NO: 92)
(b) BCL2-associated X protein (BAX) (NM_004324.3) (SEQ ID NO: 93)
(c) hydroxyprostaglandin dehydrogenase 15- (NAD) (HPGD) (NM_ 000860.5) (SEQ ID NO: 94)
(d) interleukin 6 (IL-6) (NM_000600.3) (SEQ ID NO: 95)
(e) interleukin 7 (IL-7) (NM_000880.3) (SEQ ID NO: 96)
(f) peroxisome proliferator-activated receptor gamma (PPARG) (NM_005037.5) (SEQ ID NO: 97)
(g) epidermal growth factor receptor pathway substrate 8 (EPS8) (NM_004447.5) (SEQ ID NO: 98)
In addition, in the macrophages of pancreatic cancer patients, the four expressions (c) HPGD, (f) PPARG, (g) EPS8, and (h) interleukin 15 (IL-15) (NM — 000585.4) (SEQ ID NO: 99) are expressed. It is rising. These four genes are called pancreatic cancer specific genes in macrophages. Accordingly, in a macrophage isolated from a subject, a healthy person has an expression level of at least one of these four genes, for example 1, 2, 3 or 4 genes, preferably all 4 genes. If the subject is elevated, the subject can be assessed as suffering from pancreatic cancer, or the subject can be assessed as having an increased risk of suffering from pancreatic cancer.
また、CD4陽性T細胞における7つの膵臓癌特異的遺伝子とマクロファージにおける4
つの膵臓癌特異的遺伝子に共通する(c)HPGD遺伝子、(f)PPARG遺伝子及び(g)ESP8遺伝子の3つの遺伝子をCD4陽性T細胞及びマクロファージにおける膵臓癌特異的遺伝子と呼ぶ。
In addition, 7 pancreatic cancer-specific genes in CD4-positive T cells and 4 in macrophages
The three genes (c) HPGD gene, (f) PPARG gene, and (g) ESP8 gene common to two pancreatic cancer-specific genes are called pancreatic cancer-specific genes in CD4-positive T cells and macrophages.
被験体からCD4陽性T細胞又はマクロファージにおいて、(c)HPGD遺伝子、(f)PPARG遺伝子及び(g)ESP8遺伝子の3つの遺伝子の少なくとも1個、例えば、1個、2項又は3個の
遺伝子、好ましくは3個すべての遺伝子の発現レベルが健常人に対して上昇している場合、該被験体は膵臓癌に罹患していると評価判定することができ、又は被験体は膵臓癌に罹患するリスクが大きいと評価判定することができる。
In a CD4 positive T cell or macrophage from a subject, at least one of three genes, (c) HPGD gene, (f) PPARG gene, and (g) ESP8 gene, such as one, two or three genes, Preferably, if the expression levels of all three genes are elevated in healthy individuals, the subject can be assessed as suffering from pancreatic cancer, or the subject is suffering from pancreatic cancer It can be judged that the risk is high.
さらに、CD4陽性T細胞における膵臓癌特異的遺伝子とマクロファージにおける膵臓癌
特異的遺伝子の発現レベルを組合せて測定し、膵臓癌に罹患していると評価判定することができ、又は被験体は膵臓癌に罹患するリスクが大きいと評価判定することができる。すなわち、被験体から単離したCD4陽性T細胞における7つの膵臓癌特異的遺伝子の少なく
とも1個の遺伝子、及び被験体から単離したマクロファージにおける4つの膵臓癌特異的遺伝子の少なくとも1個の遺伝子、好ましくはCD4陽性T細胞における7個すべての遺伝子とマクロファージにおける4個すべての遺伝子の計11個の遺伝子の発現レベルを測定し、これらの遺伝子の発現レベルが健常人に対して上昇している場合、該被験体は膵臓癌に罹患していると評価判定することができ、又は被験体は膵臓癌に罹患するリスクが大きいと評価判定することができる。
Further, the expression level of a pancreatic cancer-specific gene in CD4-positive T cells and the pancreatic cancer-specific gene in macrophages can be measured in combination to evaluate and determine that the subject is suffering from pancreatic cancer, or the subject is pancreatic cancer It can be judged that the risk of suffering from is high. At least one gene of seven pancreatic cancer-specific genes in CD4 positive T cells isolated from a subject and at least one gene of four pancreatic cancer-specific genes in macrophages isolated from a subject; Preferably, when the expression levels of a total of 11 genes of all 7 genes in CD4 positive T cells and all 4 genes in macrophages are measured and the expression levels of these genes are elevated in healthy individuals The subject can be evaluated and determined to have pancreatic cancer, or the subject can be evaluated and determined to have a high risk of having pancreatic cancer.
本発明は、本発明のCD4陽性T細胞における7つの膵臓癌特異的遺伝子セット、又はマ
クロファージにおける4つの膵臓癌特異的遺伝子セットの塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを含む膵臓癌を検出するための試薬又はキットを包含する。該試薬は、前記遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドをプライマー又はプローブとして含む試薬であり、また前記遺伝子の塩基配列からなるヌクレオチド又はその一部配列を含むヌクレオチドを固相化したマイクロアレイ等の基板である。PCRキットの場合、他に熱安定性ポリメラーゼ、逆転写酵素、デオキ
シヌクレオチド3リン酸、ヌクレオチド3リン酸等を含んでいてもよい。
The present invention relates to a pancreatic cancer comprising a nucleotide comprising the nucleotide sequence of seven pancreatic cancer-specific gene sets in the CD4-positive T cells of the present invention, or four pancreatic cancer-specific gene sets in macrophages, or a nucleotide comprising a partial sequence thereof. A reagent or kit for detecting. The reagent is a reagent comprising a nucleotide comprising the nucleotide sequence of the gene or a nucleotide comprising a partial sequence thereof as a primer or probe, and a nucleotide comprising the nucleotide sequence of the gene or a nucleotide comprising a partial sequence thereof as a solid phase. A microarray substrate. In the case of a PCR kit, a thermostable polymerase, reverse transcriptase, deoxynucleotide triphosphate, nucleotide triphosphate and the like may be included.
この試薬又はキットは、上記CD4陽性T細胞における7つの膵臓癌特異的遺伝子セット
、又はマクロファージにおける4つの膵臓癌特異的遺伝子セットのそれぞれの7つ又は4つの遺伝子の少なくとも1つ、好ましくは全ての遺伝子の一部配列を含むヌクレオチドを含んでいる。
This reagent or kit comprises at least one of the seven pancreatic cancer-specific gene sets in the CD4 positive T cells, or at least one of the four pancreatic cancer-specific gene sets in macrophages, preferably all It contains nucleotides that contain part of the gene sequence.
本発明を以下の実施例によって具体的に説明するが、本発明はこれらの実施例によって限定されるものではない。 The present invention will be specifically described by the following examples, but the present invention is not limited to these examples.
実施例1 遺伝子発現解析による膵臓癌の検出
本実施例において、用いた材料及び実験の方法は以下の通りであった。
対象
医師が膵臓癌と診断した患者から採取した血液を膵臓癌症例とした。対照群としては自治体主催における住民健診において同意を得た受診者の善意により提供された血液を下記検査項目により検索し正常値を示した受診者のみを健常人とした。
Example 1 Detection of Pancreatic Cancer by Gene Expression Analysis In this example, the materials and experimental methods used were as follows.
Subjects Blood collected from patients diagnosed with pancreatic cancer was defined as a pancreatic cancer case. As a control group, the blood provided by the good will of the examinees who obtained consent from the local government-sponsored medical checkups was searched according to the following test items, and only those who showed normal values were considered healthy.
検査項目
収縮期血圧、拡張期血圧、赤血球数、白血球数、ヘモグロビン値、ヘマトクリット値、肝機能(GOT、GPT、γ-GTP)、腎機能(クレアチニン値)、脂質代謝(LDL-c、HDL-c、総コレステロール値)、尿タンパク、尿鮮血
Test items Systolic blood pressure, diastolic blood pressure, red blood cell count, white blood cell count, hemoglobin level, hematocrit level, liver function (GOT, GPT, γ-GTP), renal function (creatinine level), lipid metabolism (LDL-c, HDL- c, total cholesterol level), urine protein, urine fresh blood
末梢血液採取およびRNA抽出
パクスジーンRNA採血管(日本ベクトン・ディッキンソン株式会社 医療機器製造販売
認証番号:218AFBZX00014000)を用いて、患者より末梢血液を採取した。
Peripheral blood collection and RNA extraction Peripheral blood was collected from a patient using a Paxgene RNA blood collection tube (Nippon Becton Dickinson Co., Ltd. Medical Device Manufacturing and Sales Certification Number: 218AFBZX00014000).
RNA抽出及びハイブリダイゼーション
パクスジーンRNA採血管よりPAXgene Blood RNA Kit(PreAnalytiX GmbH,Hombrechtikon,Switzerland)を用いて、プロトコールにしたがってRNAを抽出した。
RNA extraction and hybridization RNA was extracted from a Paxgene RNA blood collection tube using the PAXgene Blood RNA Kit (PreAnalytiX GmbH, Hombrechtikon, Switzerland) according to the protocol.
マイクロアレイ解析
抽出したRNAを元にQuickAmp Labeling Kit,1color(Agilent Technologies, Santa Clara, CA)を用いてRNAを増幅し、同時にCy3色素にてラベル化を行った。ラベル化RNAをGene Expression Hybridization Kit(Agilent Technologies, Santa Clara, CA)を使用して混合した後、Whole Human Genomeマイクロアレイ(Agilent Technologies, Santa Clara, CA)にハイブリダイゼーションを行った。マイクロアレイによる解析は膵臓癌検体17
例、健常人検体13例を行った。なお、RNAの増幅からハイブリダイゼーションまでの行程
はAgilent Technologiesが公表している実験プロトコールに従って作業を行った。
Microarray analysis Based on the extracted RNA, RNA was amplified using QuickAmp Labeling Kit, 1color (Agilent Technologies, Santa Clara, Calif.), And simultaneously labeled with Cy3 dye. Labeled RNA was mixed using Gene Expression Hybridization Kit (Agilent Technologies, Santa Clara, Calif.), And then hybridized to Whole Human Genome microarray (Agilent Technologies, Santa Clara, Calif.). Microarray analysis shows pancreatic cancer specimens17
For example, 13 healthy subjects were used. The steps from RNA amplification to hybridization were performed according to an experimental protocol published by Agilent Technologies.
マイクロアレイのイメージ解析及び遺伝子の選出
マイクロアレイ上の各スポットの蛍光強度はマイクロアレイスキャナ(Agilent Technologies, Santa Clara, CA)にて獲得した。獲得したイメージはFeature Extraction ソフトウェア(Agilent Technologies, Santa Clara, CA)にて各スポットの蛍光強度の数値
化を行った。この数値化により、そのスポット上に配置されているプローブの蛍光強度が算定された。
Microarray image analysis and gene selection The fluorescence intensity of each spot on the microarray was acquired with a microarray scanner (Agilent Technologies, Santa Clara, CA). The acquired images were digitized for the fluorescence intensity of each spot using Feature Extraction software (Agilent Technologies, Santa Clara, CA). By this numerical conversion, the fluorescence intensity of the probe arranged on the spot was calculated.
GeneSpring GX(Agilent Technologies, Santa Clara, CA)を用いて、マイクロアレイ上の全プローブの蛍光強度数値のノーマライゼーションを行った。 GeneSpring GX (Agilent Technologies, Santa Clara, CA) was used to normalize the fluorescence intensity values of all probes on the microarray.
各プローブの発現増強減弱を示すノーマライズされた数値を元に各プローブの蛍光強度およびFlag情報から各遺伝子発現量の解析を行い、膵臓癌群と健常人群とで遺伝子発現量に差がある解析結果となった遺伝子を364個選出した。 Analyze each gene expression from the fluorescence intensity and Flag information of each probe based on the normalized values indicating the expression enhancement and attenuation of each probe, and the analysis results that there is a difference in gene expression between the pancreatic cancer group and the healthy group 364 genes were selected.
リアルタイムPCRによる遺伝子発現量の測定
上記364個の遺伝子にハウスキーピング遺伝子16個、実験コントロール3個、18SrRNAを1個追加し合計384個とし、これら384個について一度にリアルタイムPCRでの測定が可能なCustom Profiler RT2 PCR Arrays(QIAGEN GmbH, Hilden, Germany)を用いて癌症例およ
び健常人に関して遺伝子発現量の測定を行った。リアルタイムPCR装置はLightCycler(登録商標) 480 リアルタイムPCRシステム(F. Hoffmann-La Roche Ltd, Basel, Switzerland)を使用した。リアルタイムPCRによる測定は膵臓癌検体28例、健常人検体27例を行っ
た。なお、リアルタイムPCRにおける測定作業はQIAGENが公表しているRT2 HT First Strand HandbookおよびRT2 Profiler PCR Array Handbookに従った。
Measurement of gene expression level by real-time PCR 16 housekeeping genes, 3 experimental controls and 1 18S rRNA are added to the above 364 genes for a total of 384. Real-time PCR can be measured for these 384 at once. The gene expression level was measured for cancer cases and healthy individuals using Custom Profiler RT 2 PCR Arrays (QIAGEN GmbH, Hilden, Germany). As the real-time PCR apparatus, a LightCycler (registered trademark) 480 real-time PCR system (F. Hoffmann-La Roche Ltd, Basel, Switzerland) was used. Measurement by real-time PCR was performed on 28 pancreatic cancer samples and 27 healthy subjects. The measurement work in real-time PCR was in accordance with RT 2 HT First Strand Handbook and RT 2 Profiler PCR Array Handbook published by QIAGEN.
リアルタイムPCRによる遺伝子発現量測定結果の解析および膵臓癌特異的遺伝子の選出
まずハウスキーピング遺伝子16個の中からコントロール遺伝子として測定数値(Ct値)の標準化に使用するコントロール遺伝子を設定した後に、リアルタイムPCRによる測定を
おこなった365個の遺伝子のCt値をコントロール遺伝子のCt値で標準化した。その標準化
された数値を用いて統計的手法による解析を行った結果、膵臓癌特異的遺伝子を選出した。
Analysis of gene expression measurement results by real-time PCR and selection of pancreatic cancer-specific genes First, set a control gene to be used for standardization of measurement values (Ct values) from 16 housekeeping genes, then real-time PCR The Ct values of 365 genes measured by the above were standardized with the Ct values of control genes. As a result of statistical analysis using the standardized numerical values, a pancreatic cancer specific gene was selected.
本実施例において以下の結果が得られた。
コントロール遺伝子
ハウスキーピング遺伝子15個の中で、膵臓癌検体28例におけるCt値の平均が24.71、健
常人検体27例におけるCt値の平均が24.59であり、膵臓癌群と健常人群との有意差検定に
おけるp値が0.4565であり有意差が無いことが確認できたことから、コントロール遺伝子
を「GAPDH」に決定した。
In this example, the following results were obtained.
Control genes Among 15 housekeeping genes, the average Ct value in 28 pancreatic cancer specimens was 24.71, the average Ct value in 27 healthy specimens was 24.59, and a significant difference test between the pancreatic cancer group and the healthy group Since it was confirmed that the p-value was 0.4565 and there was no significant difference, the control gene was determined to be “GAPDH”.
膵臓癌特異的遺伝子
膵臓癌検体28例、健常人検体27例のリアルタイムPCRの測定結果から得られたCt値を標
準化し統計的解析手法により解析した結果、リストにある91個の遺伝子を膵臓癌特異的遺伝子として選出した。選出した遺伝子を表5に示す。
Pancreatic cancer-specific genes Standardized Ct values obtained from real-time PCR measurement results of 28 pancreatic cancer specimens and 27 healthy human specimens, and analyzed by statistical analysis. Selected as a specific gene. Table 5 shows the selected genes.
このうち、膵臓癌が陽性/陰性の判定には以下の2セットのいずれかの遺伝子群を用い
て判定を行う事ができる。
<セットA>
No.1〜56までの56遺伝子
<セットB>
No.4、8、10、13、15、28、32、36、38、43、52、53及び57〜91までの47遺伝子
Among these, determination of whether pancreatic cancer is positive / negative can be performed using one of the following two sets of gene groups.
<Set A>
56 genes from No. 1 to 56 <Set B>
47 genes from No.4, 8, 10, 13, 15, 28, 32, 36, 38, 43, 52, 53 and 57-91
膵臓癌判定式および判定結果
膵臓癌の陽性/陰性の判定には、以下の判別式を使用する。判別式の構築方法の詳細については後述する。
式I : intercept + Σ(beta i × X i) > 0 ならば 膵臓癌陽性
[式Iにおいて、intercept は定数、beta iは56個(セットA)もしくは47個(セットB)の遺伝子のi番目の遺伝子に対する係数、X iは56個(セットA)もしくは47個(セットB)の遺伝子のi番目の遺伝子の標準化Ct値であり、Σは56個(セットA)もしくは
47個(セットB)の遺伝子のそれぞれの遺伝子のbeta × Xを合計することを示す。]
Pancreatic cancer judgment formula and judgment result The following discriminant formula is used for the positive / negative judgment of pancreatic cancer. Details of the discriminant construction method will be described later.
If formula I: intercept + Σ (beta i × X i)> 0, pancreatic cancer positive
[In formula I, intercept is a constant, beta i is a coefficient for the i-th gene of 56 (set A) or 47 (set B), and X i is 56 (set A) or 47 (set B). ) Represents the standardized Ct value of the i-th gene, and Σ represents the sum of beta × X of each of 56 (set A) or 47 (set B) genes. ]
セットAの場合はIntercept=-298.018であり、セットBの場合はIntercept=-329.963となる。betaはそれぞれ表6の通りである。遺伝子セットA及び遺伝子セットBに対する判別式を、それぞれ、判別式A及び判別式Bと呼ぶ。 In the case of set A, Intercept = −298.018, and in the case of set B, Intercept = −329.963. Each beta is as shown in Table 6. The discriminants for gene set A and gene set B are called discriminant A and discriminant B, respectively.
これらの判別式を用いてクロスバリデーションによる感度・特異度の推定を膵臓癌検体28例、健常人検体27例に行ったところ、以下の結果となった。
セットA: 感度93%、特異度100%
セットB: 感度89%、特異度96%
When these discriminants were used to estimate sensitivity and specificity by cross-validation in 28 pancreatic cancer specimens and 27 healthy specimens, the following results were obtained.
Set A: 93% sensitivity, 100% specificity
Set B: Sensitivity 89%, specificity 96%
以下に膵臓癌検出のための判別式の作成方法について詳細に記す。
金沢大学および関連医療機関で収集され、リアルタイムPCR解析が実施された55例(膵
がん28例、健常人27例)の遺伝子発現データに対して、遺伝子間の相関構造を正則化したFisherの線形判別法を用いて判別を行った。なお、遺伝子の選択には、線形カーネルをもつサポートベクターマシンと逐次変数消去法を応用した方法を用いた。全55例の内、一つの症例をテストセット、残り全てを訓練セットとする交差検証法(leave-one-out cross-validation; LOOCV)を実施した。なお、遺伝子選択は交差検証のステップ毎に行った。
判別精度の評価には、感度、特異度を主に用いた。判別に用いる遺伝子数を変化させたところ、LOOCVによる判別精度は遺伝子数が56個程度でほぼピークとなり、それ以上ではほ
ぼ横ばいであった。なお、56個のときの感度は0.93、特異度は1.00であった。
The method for creating a discriminant for detecting pancreatic cancer is described in detail below.
Fisher's regularization of the correlation structure between genes for gene expression data of 55 cases (28 cases of pancreatic cancer, 27 cases of healthy people) collected at Kanazawa University and related medical institutions and subjected to real-time PCR analysis Discrimination was performed using a linear discriminant method. For gene selection, a support vector machine with a linear kernel and a method applying the sequential variable elimination method were used. A cross-validation (leave-one-out cross-validation; LOOCV) was performed, with one case being the test set and all the remaining being the training set. Gene selection was performed at each cross-validation step.
Sensitivity and specificity were mainly used for evaluation of discrimination accuracy. When the number of genes used for discrimination was changed, the discrimination accuracy by LOOCV reached a peak when the number of genes was about 56, and was almost flat beyond that. The sensitivity at the time of 56 was 0.93, and the specificity was 1.00.
最後に、全55例を訓練セットとみなして、以上の方法を適用し、56個の遺伝子を選択し、将来の患者の判別に用いる判別アルゴリズムを作製した。 Finally, all 55 cases were regarded as a training set, the above method was applied, 56 genes were selected, and a discrimination algorithm used to discriminate future patients was created.
実施例2 CD4陽性T細胞及びマクロファージにおける膵臓癌特異的遺伝子
本実施例において、用いた材料及び実験の方法は以下の通りであった。
Example 2 Pancreatic Cancer Specific Gene in CD4 Positive T Cells and Macrophages In this example, the materials used and the experimental methods were as follows.
対象
医師が画像、細胞診等、臨床診療上膵臓癌と診断した患者から採取した血液を膵臓癌症例とした。対象群としては健診において同意を得て、明らかな癌を有しない受診者のみを健常人とした。
Subjects Blood collected from patients diagnosed with pancreatic cancer in clinical practice, such as images and cytology, was defined as a pancreatic cancer case. As a subject group, consent was obtained during a medical examination, and only those who did not have an obvious cancer were regarded as healthy persons.
末梢血液採取および細胞の単離
ヘパリン添加採血管を用いて患者より末梢血液を採取し、フィコール密度勾配遠心分離法(Sigma-Aldrich, St. Louis, MO, USA)にて、末梢血単核球(PBMCs)を分離した。
分離したPBMCsをビーズ標識抗CD4抗体、ビーズ標識抗CD14抗体(Miltenyi Biotec, Cologne, Germany)と反応させた後、磁気カラムを用いてCD4陽性T細胞とCD14陽性細胞(マクロファージ)を単離した。
Peripheral blood collection and cell isolation Peripheral blood was collected from patients using heparinized blood collection tubes, and peripheral blood mononuclear cells by Ficoll density gradient centrifugation (Sigma-Aldrich, St. Louis, MO, USA) (PBMCs) were isolated.
The separated PBMCs were reacted with a bead-labeled anti-CD4 antibody and a bead-labeled anti-CD14 antibody (Miltenyi Biotec, Cologne, Germany), and then CD4-positive T cells and CD14-positive cells (macrophages) were isolated using a magnetic column.
単離した細胞より、Micro RNA Isolation kit (STRATAGENE, La Jolla, CA, USA)を用
い、製造元のプロトコールにしたがってRNAを抽出した。
RNA was extracted from the isolated cells using a Micro RNA Isolation kit (STRATAGENE, La Jolla, CA, USA) according to the manufacturer's protocol.
マイクロアレイ試験法
抽出したRNAを元にQuick Amp Labeling Kit,1color (Agilent Technologies, Santa Clara, CA, USA) を用いてRNA を増幅し、同時にCy3色素にてラベル化を行った。ラベル化RNAをGene Expression Hybridization kit (Agilent Technologies, Santa Clara, CA, USA)を使用し混合した後、Whole Human Genome マイクロアレイ(Agilent Technologies, Santa Clara, CA, USA)にハイブリダイゼーションを行った。なお、RNA増幅からハイブリダイゼーションまでの工程はAgilent Technologiesが公表している実験プロトコールに従って作業を行った。
Microarray test method RNA was amplified using Quick Amp Labeling Kit, 1color (Agilent Technologies, Santa Clara, CA, USA) based on the extracted RNA, and simultaneously labeled with Cy3 dye. The labeled RNA was mixed using a Gene Expression Hybridization kit (Agilent Technologies, Santa Clara, CA, USA), and then hybridized to a Whole Human Genome microarray (Agilent Technologies, Santa Clara, CA, USA). The steps from RNA amplification to hybridization were performed according to the experimental protocol published by Agilent Technologies.
アレイデータ解析および遺伝子の選出(1)
マイクロアレイ上の各スポットの蛍光強度はマイクロアレイスキャナー(Agilent Technologies, Santa Clara, CA, USA)にて獲得した。獲得したイメージファイルはFeature Extractionソフトウェア(Agilent Technologies, Santa Clara, CA, USA)にて各スポットの蛍光強度の数値化を行った。この数値化により、そのスポット上に配置されているプローブの蛍光強度が算定された。
Array data analysis and gene selection (1)
The fluorescence intensity of each spot on the microarray was acquired with a microarray scanner (Agilent Technologies, Santa Clara, CA, USA). The acquired image files were digitized for the fluorescence intensity of each spot using Feature Extraction software (Agilent Technologies, Santa Clara, CA, USA). By this numerical conversion, the fluorescence intensity of the probe arranged on the spot was calculated.
算定された数値を基にBRB array tools(NCI, http://linus.nci.nih.gov/BRB-ArrayTools.html)を用いて遺伝子発現解析を行った。膵臓癌症例31例と健常人22例のCD4陽性T細胞およびマクロファージの発現量に統計学的に有意差のあり、生物学的特徴に意義のある5
遺伝子PPARG(peroxisome proliferator-activated receptor gamma)**, EPS8(epidermal growth factor receptor pathway substrate 8)**,HPGD(hydroxyprostaglandin dehydrogenase 15-(NAD))**,FAS(Fas cell surface death receptor)**,BAX (BCL2-associated X protein)**を選出した。(**P<0.01)
Based on the calculated values, gene expression analysis was performed using BRB array tools (NCI, http://linus.nci.nih.gov/BRB-ArrayTools.html). There is a statistically significant difference in the expression levels of CD4-positive T cells and macrophages in 31 cases of pancreatic cancer and 22 cases of healthy individuals, and the biological characteristics are significant5
Genes PPARG (peroxisome proliferator-activated receptor gamma) **, EPS8 (epidermal growth factor receptor pathway substrate 8) **, HPGD (hydroxyprostaglandin dehydrogenase 15- (NAD)) **, FAS (Fas cell surface death receptor) **, BAX (BCL2-associated X protein) ** was selected. (** P <0.01)
血清中サイトカインおよびケモカイン濃度測定ならびに遺伝子の選出(2)
膵臓癌症例および健常人における血清中のサイトカインおよびケモカイン濃度をMultiplex Bead Immunoassays kit, Human Cytokine 27-Plex Panel (Invitrogen, Carlsbad, CA, USA)で測定した。血清は膵臓癌症例50例と健常人27例から得た。Interleukin (IL)-6**,IL-7**, IL-15**,IL-8*のサイトカイン濃度が健常人と比較して膵臓癌症例で有意に上
昇した。また、MCP-1**,IP-10**のケモカイ濃度もまた有意な上昇を示した。膵臓癌症例
と健常人の血清中サイトカインおよびケモカイン濃度に有意差のあるタンパクを6個選出
した。(**P<0.01,*P<0.05)
Serum cytokine and chemokine concentration measurement and gene selection (2)
Serum cytokine and chemokine concentrations in pancreatic cancer cases and healthy individuals were measured with Multiplex Bead Immunoassays kit, Human Cytokine 27-Plex Panel (Invitrogen, Carlsbad, CA, USA). Serum was obtained from 50 pancreatic cancer cases and 27 healthy people. Interleukin (IL) -6 **, IL-7 **, IL-15 **, and IL-8 * cytokine levels were significantly increased in pancreatic cancer cases compared to healthy individuals. Moreover, the chemokai concentration of MCP-1 ** and IP-10 ** also showed a significant increase. Six proteins with significant differences in serum cytokine and chemokine concentrations in pancreatic cancer cases and healthy individuals were selected. (** P <0.01, * P <0.05)
リアルタイムPCRによる遺伝子発現量の測定
上記(1)(2)より選出された11遺伝子を使用し、膵臓癌症例31例のCD4陽性T細胞およびマクロファージ、健常人22例のCD4陽性T細胞およびマクロファージより、リアルタイムPCRにて発現解析を行った。
Measurement of gene expression level by real-time PCR Using 11 genes selected from (1) and (2) above, from CD4 positive T cells and macrophages in 31 pancreatic cancer cases, CD4 positive T cells and macrophages in 22 healthy people Then, expression analysis was performed by real-time PCR.
RNAについては、High-Capacity cDNA Reverse Transcription Kit(Applied Biosystems, Foster City, CA, USA)にてRNAを鋳型とするcDNAを合成した。合成されたcDNAに増幅試薬と選出されたターゲット遺伝子のプローブおよびハウスキーピング遺伝子(18S ribosomal RNA)のプローブを混合した後、リアルタイムPCR装置Rotor-Gene Q(QIAGEN GmbH, Hilden, Germany)を用いたマルチプレックスPCRアッセイで発現量の測定を行った。 For RNA, cDNA using RNA as a template was synthesized using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA). After mixing the synthesized cDNA with the selected target gene probe and the housekeeping gene (18S ribosomal RNA) probe, the synthesized cDNA was mixed with the real-time PCR device Rotor-Gene Q (QIAGEN GmbH, Hilden, Germany). The expression level was measured by plex PCR assay.
定量方法はターゲット遺伝子およびハウスキーピング遺伝子の検量線から算出されたそれぞれの定量値をもとに、ターゲット遺伝子の定量値をハウスキーピング遺伝子の定量値で除算するTwo Standard Curve法で発現量を算出した結果、膵臓癌特異的遺伝子を選出した。なお、逆転写から発現量の定量までの工程はQIAGENのプロトコールにしたがって作業を行った。 The quantification method was based on the respective quantitative values calculated from the calibration curves of the target gene and housekeeping gene, and the expression level was calculated by the Two Standard Curve method, which divides the quantitative value of the target gene by the quantitative value of the housekeeping gene. As a result, pancreatic cancer specific genes were selected. The steps from reverse transcription to quantification of the expression level were performed according to the QIAGEN protocol.
本実施例において以下の結果が得られた。
CD4陽性T細胞における膵臓癌特異的遺伝子
膵臓癌31症例と健常人22例のCD4陽性T細胞において、リアルタイムPCRで11遺伝子の発
現量を測定し解析した結果FAS**,BAX**,HPGD**,IL-6*,IL-7*,PPARG*,EPS8*遺伝子は健常
人と比較して膵臓癌症例で有意に上昇した。前記7遺伝子をCD4陽性T細胞における膵臓癌
特異的遺伝子として選出した。(**P<0.01,*P<0.05)
In this example, the following results were obtained.
Pancreatic cancer-specific genes in CD4 + T cells FAS **, BAX **, HPGD * as a result of measuring and analyzing the expression level of 11 genes by real-time PCR in CD4 + T cells of 31 cases of pancreatic cancer and 22 cases of healthy individuals *, IL-6 *, IL-7 *, PPARG *, and EPS8 * genes were significantly elevated in pancreatic cancer cases compared to healthy individuals. The 7 genes were selected as pancreatic cancer specific genes in CD4-positive T cells. (** P <0.01, * P <0.05)
マクロファージにおける膵臓癌特異的遺伝子
膵臓癌31症例と健常人22例のマクロファージにおいて、リアルタイムPCRで11遺伝子の
発現量を測定し解析した結果、EPS8**,HPGD**,IL-15*,PPARG*遺伝子は健常人と比較して
膵臓癌症例で有意に上昇した。前記4遺伝子をマクロファージにおける膵臓癌特異的遺伝
子として選出した。(**P<0.01,*P<0.05)
Pancreatic cancer-specific genes in macrophages As a result of measuring and analyzing the expression levels of 11 genes by real-time PCR in macrophages of 31 cases of pancreatic cancer and 22 cases of healthy individuals, EPS8 **, HPGD **, IL-15 *, PPARG * The gene was significantly elevated in pancreatic cancer cases compared to healthy individuals. The four genes were selected as pancreatic cancer specific genes in macrophages. (** P <0.01, * P <0.05)
CD4陽性T細胞とマクロファージにおける膵臓癌特異的遺伝子
CD4陽性T細胞とマクロファージで共に健常人と比較し膵臓癌症例で有意に上昇したPPARG,EPS8, HPGDの3遺伝子をCD4陽性T細胞およびマクロファージにおける膵臓癌特異的遺伝
子とした。
Pancreatic cancer-specific genes in CD4-positive T cells and macrophages
Three genes, PPARG, EPS8, and HPGD, which were significantly elevated in pancreatic cancer cases compared with healthy individuals in both CD4 positive T cells and macrophages, were designated as pancreatic cancer specific genes in CD4 positive T cells and macrophages.
本発明により、低侵襲で簡便かつ高精度な膵臓癌検出が可能になる。 According to the present invention, pancreatic cancer can be detected with minimal invasiveness and with high accuracy.
Claims (8)
遺伝子セットB
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8)Chromosome 11 open reading frame 2 (C11orf2)
(10)Cyclin Y-like 1 (CCNYL1)
(13)C-type lectin domain family 4, member D (CLEC4D)
(15)Cytochrome b5 reductase 4 (CYB5R4)
(28)Interferon gamma receptor 1 (IFNGR1)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43)Ribosomal protein, large, P1 (RPLP1)
(52)Ubiquitination factor E4A (UBE4A)
(53)Ubiquitin specific peptidase 15 (USP15)
(57)Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58)Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65) (APBB1)
(59)BCL2-related protein A1 (BCL2A1)
(60)Chromosome 9 open reading frame 72 (C9orf72)
(61)Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62)CD36 molecule (thrombospondin receptor) (CD36)
(63)CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64)CD58 molecule (CD58)
(65)CTAGE family, member 5 (CTAGE5)
(66)V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67)F-box and leucine-rich repeat protein 5 (FBXL5)
(68)Glucuronidase, beta (GUSB)
(69)Huntingtin interacting protein 1 related (HIP1R)
(70)High mobility group box 2 (HMGB2)
(71)Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72)IlvB (bacterial acetolactate synthase)-like (ILVBL)
(73)IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74)Mbt domain containing 1 (MBTD1)
(75)Milk fat globule-EGF factor 8 protein (MFGE8)
(76)Nascent polypeptide-associated complex alpha subunit (NACA)
(77)Nuclear receptor coactivator 5 (NCOA5)
(78)Non-POU domain containing, octamer-binding (NONO)
(79)Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80)Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81)Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82)RAB14, member RAS oncogene family (RAB14)
(83)RNA binding motif protein 14 (RBM14)
(84)Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)
(85)Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86)Serglycin (SRGN)
(87)TATA box binding protein (TBP)
(88)Transmembrane protein 167A (TMEM167A)
(89)Thioredoxin (TXN)
(90)Vascular endothelial growth factor B (VEGFB)
(91)Zinc finger protein 764 (ZNF764) A reagent for measuring the expression level of only 47 genes of the following gene set B and detecting pancreatic cancer based on the expression level, comprising the nucleotide sequences of 47 genes of the gene set B Reagent for detecting pancreatic cancer comprising a nucleotide or a nucleotide comprising a partial sequence thereof:
Gene set B
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8) Chromosome 11 open reading frame 2 (C11orf2)
(10) Cyclin Y-like 1 (CCNYL1)
(13) C-type lectin domain family 4, member D (CLEC4D)
(15) Cytochrome b5 reductase 4 (CYB5R4)
(28) Interferon gamma receptor 1 (IFNGR1)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43) Ribosomal protein, large, P1 (RPLP1)
(52) Ubiquitination factor E4A (UBE4A)
(53) Ubiquitin specific peptidase 15 (USP15)
(57) Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58) Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65) (APBB1)
(59) BCL2-related protein A1 (BCL2A1)
(60) Chromosome 9 open reading frame 72 (C9orf72)
(61) Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62) CD36 molecule (thrombospondin receptor) (CD36)
(63) CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64) CD58 molecule (CD58)
(65) CTAGE family, member 5 (CTAGE5)
(66) V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67) F-box and leucine-rich repeat protein 5 (FBXL5)
(68) Glucuronidase, beta (GUSB)
(69) Huntingtin interacting protein 1 related (HIP1R)
(70) High mobility group box 2 (HMGB2)
(71) Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72) IlvB (bacterial acetolactate synthase) -like (ILVBL)
(73) IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74) Mbt domain containing 1 (MBTD1)
(75) Milk fat globule-EGF factor 8 protein (MFGE8)
(76) Nascent polypeptide-associated complex alpha subunit (NACA)
(77) Nuclear receptor coactivator 5 (NCOA5)
(78) Non-POU domain containing, octamer-binding (NONO)
(79) Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80) Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81) Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82) RAB14, member RAS oncogene family (RAB14)
(83) RNA binding motif protein 14 (RBM14)
(84) Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)
(85) Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86) Serglycin (SRGN)
(87) TATA box binding protein (TBP)
(88) Transmembrane protein 167A (TMEM167A)
(89) Thioredoxin (TXN)
(90) Vascular endothelial growth factor B (VEGFB)
(91) Zinc finger protein 764 (ZNF764)
遺伝子セットB
(4)Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8)Chromosome 11 open reading frame 2 (C11orf2)
(10)Cyclin Y-like 1 (CCNYL1)
(13)C-type lectin domain family 4, member D (CLEC4D)
(15)Cytochrome b5 reductase 4 (CYB5R4)
(28)Interferon gamma receptor 1 (IFNGR1)
(32)Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36)Oligonucleotide/oligosaccharide-binding fold containing 2A (OBFC2A)
(38)Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43)Ribosomal protein, large, P1 (RPLP1)
(52)Ubiquitination factor E4A (UBE4A)
(53)Ubiquitin specific peptidase 15 (USP15)
(57)Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58)Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65) (APBB1)
(59)BCL2-related protein A1 (BCL2A1)
(60)Chromosome 9 open reading frame 72 (C9orf72)
(61)Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62)CD36 molecule (thrombospondin receptor) (CD36)
(63)CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64)CD58 molecule (CD58)
(65)CTAGE family, member 5 (CTAGE5)
(66)V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67)F-box and leucine-rich repeat protein 5 (FBXL5)
(68)Glucuronidase, beta (GUSB)
(69)Huntingtin interacting protein 1 related (HIP1R)
(70)High mobility group box 2 (HMGB2)
(71)Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72)IlvB (bacterial acetolactate synthase)-like (ILVBL)
(73)IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74)Mbt domain containing 1 (MBTD1)
(75)Milk fat globule-EGF factor 8 protein (MFGE8)
(76)Nascent polypeptide-associated complex alpha subunit (NACA)
(77)Nuclear receptor coactivator 5 (NCOA5)
(78)Non-POU domain containing, octamer-binding (NONO)
(79)Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80)Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81)Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82)RAB14, member RAS oncogene family (RAB14)
(83)RNA binding motif protein 14 (RBM14)
(84)Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)
(85)Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86)Serglycin (SRGN)
(87)TATA box binding protein (TBP)
(88)Transmembrane protein 167A (TMEM167A)
(89)Thioredoxin (TXN)
(90)Vascular endothelial growth factor B (VEGFB)
(91)Zinc finger protein 764 (ZNF764) A method for measuring the expression level of only 47 genes in the following gene set B in a subject and assisting detection of pancreatic cancer based on the expression level:
Gene set B
(4) Aldo-keto reductase family 1, member B1 (aldose reductase) (AKR1B1)
(8) Chromosome 11 open reading frame 2 (C11orf2)
(10) Cyclin Y-like 1 (CCNYL1)
(13) C-type lectin domain family 4, member D (CLEC4D)
(15) Cytochrome b5 reductase 4 (CYB5R4)
(28) Interferon gamma receptor 1 (IFNGR1)
(32) Membrane-bound transcription factor peptidase, site 2 (MBTPS2)
(36) Oligonucleotide / oligosaccharide-binding fold containing 2A (OBFC2A)
(38) Peptidylprolyl isomerase H (cyclophilin H) (PPIH)
(43) Ribosomal protein, large, P1 (RPLP1)
(52) Ubiquitination factor E4A (UBE4A)
(53) Ubiquitin specific peptidase 15 (USP15)
(57) Alanyl-tRNA synthetase domain containing 1 (AARSD1)
(58) Amyloid beta (A4) precursor protein-binding, family B, member 1 (Fe65) (APBB1)
(59) BCL2-related protein A1 (BCL2A1)
(60) Chromosome 9 open reading frame 72 (C9orf72)
(61) Capping protein (actin filament) muscle Z-line, alpha 1 (CAPZA1)
(62) CD36 molecule (thrombospondin receptor) (CD36)
(63) CD3e molecule, epsilon (CD3-TCR complex) (CD3E)
(64) CD58 molecule (CD58)
(65) CTAGE family, member 5 (CTAGE5)
(66) V-ets erythroblastosis virus E26 oncogene homolog 1 (avian) (ETS1)
(67) F-box and leucine-rich repeat protein 5 (FBXL5)
(68) Glucuronidase, beta (GUSB)
(69) Huntingtin interacting protein 1 related (HIP1R)
(70) High mobility group box 2 (HMGB2)
(71) Heat shock protein 90kDa alpha (cytosolic), class B member 1 (HSP90AB1)
(72) IlvB (bacterial acetolactate synthase) -like (ILVBL)
(73) IMP (inosine 5'-monophosphate) dehydrogenase 2 (IMPDH2)
(74) Mbt domain containing 1 (MBTD1)
(75) Milk fat globule-EGF factor 8 protein (MFGE8)
(76) Nascent polypeptide-associated complex alpha subunit (NACA)
(77) Nuclear receptor coactivator 5 (NCOA5)
(78) Non-POU domain containing, octamer-binding (NONO)
(79) Peptidylprolyl isomerase A (cyclophilin A) (PPIA)
(80) Protein phosphatase 4, regulatory subunit 2 (PPP4R2)
(81) Protein tyrosine phosphatase-like A domain containing 2 (PTPLAD2)
(82) RAB14, member RAS oncogene family (RAB14)
(83) RNA binding motif protein 14 (RBM14)
(84) Succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA)
(85) Speedy homolog E3 (Xenopus laevis) (SPDYE3)
(86) Serglycin (SRGN)
(87) TATA box binding protein (TBP)
(88) Transmembrane protein 167A (TMEM167A)
(89) Thioredoxin (TXN)
(90) Vascular endothelial growth factor B (VEGFB)
(91) Zinc finger protein 764 (ZNF764)
(1)被験体より採取した末梢血細胞よりmRNAを抽出する工程;
(2)遺伝子セットBの47個の遺伝子をPCRにより増幅し、Ct(Cycle threshold)値を得て、GAPDH等のハウスキーピング遺伝子のCt値により標準化し、標準化Ct値を得る工程;
(3)遺伝子セットBの各遺伝子の標準化Ct値を判別式に代入し、膵臓癌が陽性である確
率を算出する工程。 The method for assisting detection of pancreatic cancer according to any one of claims 3 to 5, comprising the following steps:
(1) A step of extracting mRNA from peripheral blood cells collected from a subject;
(2) Amplifying 47 genes of gene set B by PCR, obtaining a Ct (Cycle threshold) value, normalizing with a Ct value of a housekeeping gene such as GAPDH, and obtaining a normalized Ct value;
(3) A step of substituting the standardized Ct value of each gene of gene set B into the discriminant and calculating the probability that pancreatic cancer is positive.
式:intercept + Σ(beta i × X i)
[式において、intercept は定数、beta iは遺伝子セットBの47個の遺伝子のi番目の遺伝子に対する係数、x iは遺伝子セットBの47個の遺伝子のi番目の遺伝子の標準化Ct値であり、Σは遺伝子セットBの47個の遺伝子のそれぞれの遺伝子のbeta × Xを合計することを示す。]。 The method of assisting detection of pancreatic cancer according to claim 6, wherein the detection of pancreatic cancer is assisted by using the following discriminant, wherein pancreatic cancer is positive when a numerical value calculated from the following discriminant is greater than 0: The method of assisting detection of pancreatic cancer according to claim 6, wherein the method is determined to be:
Expression: intercept + Σ (beta i × X i)
[In the formula, intercept is a constant, beta i is a coefficient for the i-th gene of 47 genes in gene set B, x i is the standardized Ct value of the i-th gene of 47 genes in gene set B, Σ indicates that the beta × X of each of the 47 genes in gene set B is summed. ].
intercept:-329.963
intercept: -329.963
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