CN116356018A - Circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis - Google Patents
Circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis Download PDFInfo
- Publication number
- CN116356018A CN116356018A CN202211610754.XA CN202211610754A CN116356018A CN 116356018 A CN116356018 A CN 116356018A CN 202211610754 A CN202211610754 A CN 202211610754A CN 116356018 A CN116356018 A CN 116356018A
- Authority
- CN
- China
- Prior art keywords
- cells
- hla
- ctcs
- tumor
- immune
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 206010028980 Neoplasm Diseases 0.000 title claims abstract description 85
- 206010027476 Metastases Diseases 0.000 title claims abstract description 69
- 102000037982 Immune checkpoint proteins Human genes 0.000 title claims abstract description 68
- 108091008036 Immune checkpoint proteins Proteins 0.000 title claims abstract description 68
- 230000009401 metastasis Effects 0.000 title claims abstract description 68
- 208000005443 Circulating Neoplastic Cells Diseases 0.000 title claims abstract description 14
- 230000002401 inhibitory effect Effects 0.000 title claims abstract description 14
- 101000986085 Homo sapiens HLA class I histocompatibility antigen, alpha chain E Proteins 0.000 claims abstract description 96
- 102100028970 HLA class I histocompatibility antigen, alpha chain E Human genes 0.000 claims abstract description 95
- 210000005266 circulating tumour cell Anatomy 0.000 claims abstract description 95
- 230000014509 gene expression Effects 0.000 claims abstract description 56
- 210000004027 cell Anatomy 0.000 claims description 118
- 206010061289 metastatic neoplasm Diseases 0.000 claims description 29
- 210000002865 immune cell Anatomy 0.000 claims description 28
- 229940126546 immune checkpoint molecule Drugs 0.000 claims description 28
- 210000004369 blood Anatomy 0.000 claims description 26
- 239000008280 blood Substances 0.000 claims description 26
- 238000012163 sequencing technique Methods 0.000 claims description 21
- 230000001394 metastastic effect Effects 0.000 claims description 17
- 208000008443 pancreatic carcinoma Diseases 0.000 claims description 17
- 206010061902 Pancreatic neoplasm Diseases 0.000 claims description 16
- 208000015486 malignant pancreatic neoplasm Diseases 0.000 claims description 16
- 201000002528 pancreatic cancer Diseases 0.000 claims description 16
- 239000003814 drug Substances 0.000 claims description 14
- 238000004458 analytical method Methods 0.000 claims description 11
- 201000011510 cancer Diseases 0.000 claims description 10
- 229940079593 drug Drugs 0.000 claims description 10
- 238000000034 method Methods 0.000 claims description 9
- 239000003795 chemical substances by application Substances 0.000 claims description 8
- 238000001415 gene therapy Methods 0.000 claims description 8
- 206010006187 Breast cancer Diseases 0.000 claims description 6
- 208000026310 Breast neoplasm Diseases 0.000 claims description 6
- 239000011324 bead Substances 0.000 claims description 6
- 201000001441 melanoma Diseases 0.000 claims description 6
- 206010009944 Colon cancer Diseases 0.000 claims description 4
- 239000006285 cell suspension Substances 0.000 claims description 4
- 229940126586 small molecule drug Drugs 0.000 claims description 4
- 238000012795 verification Methods 0.000 claims description 4
- 208000001333 Colorectal Neoplasms Diseases 0.000 claims description 3
- 201000007270 liver cancer Diseases 0.000 claims description 3
- 208000014018 liver neoplasm Diseases 0.000 claims description 3
- 230000008827 biological function Effects 0.000 claims description 2
- 238000009169 immunotherapy Methods 0.000 claims description 2
- 229940125644 antibody drug Drugs 0.000 claims 1
- 208000035269 cancer or benign tumor Diseases 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 claims 1
- 210000000822 natural killer cell Anatomy 0.000 abstract description 70
- 210000004881 tumor cell Anatomy 0.000 abstract description 57
- 230000000903 blocking effect Effects 0.000 abstract description 32
- 102100022682 NKG2-A/NKG2-B type II integral membrane protein Human genes 0.000 abstract description 26
- 101150069255 KLRC1 gene Proteins 0.000 abstract description 24
- 101100404845 Macaca mulatta NKG2A gene Proteins 0.000 abstract description 24
- 230000002147 killing effect Effects 0.000 abstract description 9
- 238000011282 treatment Methods 0.000 abstract description 9
- 238000001727 in vivo Methods 0.000 abstract description 6
- 230000017188 evasion or tolerance of host immune response Effects 0.000 abstract description 4
- 238000000338 in vitro Methods 0.000 abstract description 4
- 230000005764 inhibitory process Effects 0.000 abstract description 4
- 230000008685 targeting Effects 0.000 abstract description 4
- 230000002265 prevention Effects 0.000 abstract description 2
- 238000012216 screening Methods 0.000 abstract 1
- 210000004072 lung Anatomy 0.000 description 32
- 241000699670 Mus sp. Species 0.000 description 29
- 210000001519 tissue Anatomy 0.000 description 24
- 230000003993 interaction Effects 0.000 description 16
- 241000699666 Mus <mouse, genus> Species 0.000 description 15
- 230000017531 blood circulation Effects 0.000 description 14
- 101000971513 Homo sapiens Natural killer cells antigen CD94 Proteins 0.000 description 13
- 102100021462 Natural killer cells antigen CD94 Human genes 0.000 description 13
- 230000009467 reduction Effects 0.000 description 13
- 238000007621 cluster analysis Methods 0.000 description 12
- 238000011081 inoculation Methods 0.000 description 12
- 239000003446 ligand Substances 0.000 description 12
- 108090000623 proteins and genes Proteins 0.000 description 12
- 206010027457 Metastases to liver Diseases 0.000 description 11
- 229920000371 poly(diallyldimethylammonium chloride) polymer Polymers 0.000 description 11
- 230000000694 effects Effects 0.000 description 10
- 210000004185 liver Anatomy 0.000 description 10
- 238000001262 western blot Methods 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 9
- 230000004083 survival effect Effects 0.000 description 8
- 108091027967 Small hairpin RNA Proteins 0.000 description 7
- 238000001514 detection method Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 239000004055 small Interfering RNA Substances 0.000 description 7
- 238000002474 experimental method Methods 0.000 description 6
- 238000003125 immunofluorescent labeling Methods 0.000 description 6
- 101000738771 Homo sapiens Receptor-type tyrosine-protein phosphatase C Proteins 0.000 description 5
- 101000946843 Homo sapiens T-cell surface glycoprotein CD8 alpha chain Proteins 0.000 description 5
- 102100037422 Receptor-type tyrosine-protein phosphatase C Human genes 0.000 description 5
- 102100034922 T-cell surface glycoprotein CD8 alpha chain Human genes 0.000 description 5
- 210000001744 T-lymphocyte Anatomy 0.000 description 5
- 230000015572 biosynthetic process Effects 0.000 description 5
- 238000003197 gene knockdown Methods 0.000 description 5
- 238000002347 injection Methods 0.000 description 5
- 239000007924 injection Substances 0.000 description 5
- 239000013612 plasmid Substances 0.000 description 5
- 230000002829 reductive effect Effects 0.000 description 5
- 210000003462 vein Anatomy 0.000 description 5
- 102100030385 Granzyme B Human genes 0.000 description 4
- 101001009603 Homo sapiens Granzyme B Proteins 0.000 description 4
- 101001109503 Homo sapiens NKG2-C type II integral membrane protein Proteins 0.000 description 4
- 102100022683 NKG2-C type II integral membrane protein Human genes 0.000 description 4
- 102100021657 Tyrosine-protein phosphatase non-receptor type 6 Human genes 0.000 description 4
- 230000022534 cell killing Effects 0.000 description 4
- 238000000684 flow cytometry Methods 0.000 description 4
- 230000002440 hepatic effect Effects 0.000 description 4
- 230000037451 immune surveillance Effects 0.000 description 4
- 238000011503 in vivo imaging Methods 0.000 description 4
- 230000002018 overexpression Effects 0.000 description 4
- 210000005259 peripheral blood Anatomy 0.000 description 4
- 239000011886 peripheral blood Substances 0.000 description 4
- 238000003908 quality control method Methods 0.000 description 4
- 238000011002 quantification Methods 0.000 description 4
- 239000007787 solid Substances 0.000 description 4
- 239000000243 solution Substances 0.000 description 4
- 238000010186 staining Methods 0.000 description 4
- 238000011729 BALB/c nude mouse Methods 0.000 description 3
- 101000971538 Homo sapiens Killer cell lectin-like receptor subfamily F member 1 Proteins 0.000 description 3
- 101000946889 Homo sapiens Monocyte differentiation antigen CD14 Proteins 0.000 description 3
- 102100021458 Killer cell lectin-like receptor subfamily F member 1 Human genes 0.000 description 3
- 206010027458 Metastases to lung Diseases 0.000 description 3
- 102100035877 Monocyte differentiation antigen CD14 Human genes 0.000 description 3
- 210000003719 b-lymphocyte Anatomy 0.000 description 3
- 230000008614 cellular interaction Effects 0.000 description 3
- 208000029742 colonic neoplasm Diseases 0.000 description 3
- 230000029087 digestion Effects 0.000 description 3
- 230000012010 growth Effects 0.000 description 3
- 206010073071 hepatocellular carcinoma Diseases 0.000 description 3
- 238000011502 immune monitoring Methods 0.000 description 3
- 238000011534 incubation Methods 0.000 description 3
- 208000020816 lung neoplasm Diseases 0.000 description 3
- 239000003550 marker Substances 0.000 description 3
- 210000001616 monocyte Anatomy 0.000 description 3
- 210000000056 organ Anatomy 0.000 description 3
- 230000007170 pathology Effects 0.000 description 3
- 210000003240 portal vein Anatomy 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 230000002685 pulmonary effect Effects 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 239000013598 vector Substances 0.000 description 3
- 102100027203 B-cell antigen receptor complex-associated protein beta chain Human genes 0.000 description 2
- 238000011740 C57BL/6 mouse Methods 0.000 description 2
- 102000029816 Collagenase Human genes 0.000 description 2
- 108060005980 Collagenase Proteins 0.000 description 2
- 108020004414 DNA Proteins 0.000 description 2
- 101150084967 EPCAM gene Proteins 0.000 description 2
- 239000012981 Hank's balanced salt solution Substances 0.000 description 2
- 101000914491 Homo sapiens B-cell antigen receptor complex-associated protein beta chain Proteins 0.000 description 2
- 101000975496 Homo sapiens Keratin, type II cytoskeletal 8 Proteins 0.000 description 2
- 101000917858 Homo sapiens Low affinity immunoglobulin gamma Fc region receptor III-A Proteins 0.000 description 2
- 101001109508 Homo sapiens NKG2-A/NKG2-B type II integral membrane protein Proteins 0.000 description 2
- 101000946860 Homo sapiens T-cell surface glycoprotein CD3 epsilon chain Proteins 0.000 description 2
- 101000617285 Homo sapiens Tyrosine-protein phosphatase non-receptor type 6 Proteins 0.000 description 2
- 101000818522 Homo sapiens fMet-Leu-Phe receptor Proteins 0.000 description 2
- 238000012404 In vitro experiment Methods 0.000 description 2
- 102100023972 Keratin, type II cytoskeletal 8 Human genes 0.000 description 2
- 102100029193 Low affinity immunoglobulin gamma Fc region receptor III-A Human genes 0.000 description 2
- 241000699660 Mus musculus Species 0.000 description 2
- 108091000080 Phosphotransferase Proteins 0.000 description 2
- 206010041047 Slow virus infection Diseases 0.000 description 2
- 102100035794 T-cell surface glycoprotein CD3 epsilon chain Human genes 0.000 description 2
- 101710128901 Tyrosine-protein phosphatase non-receptor type 6 Proteins 0.000 description 2
- 230000003213 activating effect Effects 0.000 description 2
- 230000029918 bioluminescence Effects 0.000 description 2
- 238000005415 bioluminescence Methods 0.000 description 2
- 239000002771 cell marker Substances 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 239000003153 chemical reaction reagent Substances 0.000 description 2
- 229960002424 collagenase Drugs 0.000 description 2
- 201000010897 colon adenocarcinoma Diseases 0.000 description 2
- 238000002591 computed tomography Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 231100000433 cytotoxic Toxicity 0.000 description 2
- 230000001472 cytotoxic effect Effects 0.000 description 2
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000012636 effector Substances 0.000 description 2
- 238000010828 elution Methods 0.000 description 2
- 102100021145 fMet-Leu-Phe receptor Human genes 0.000 description 2
- 231100000844 hepatocellular carcinoma Toxicity 0.000 description 2
- 238000001990 intravenous administration Methods 0.000 description 2
- 230000003902 lesion Effects 0.000 description 2
- 208000037841 lung tumor Diseases 0.000 description 2
- 230000036210 malignancy Effects 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 210000000440 neutrophil Anatomy 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000011580 nude mouse model Methods 0.000 description 2
- 102000020233 phosphotransferase Human genes 0.000 description 2
- 230000002035 prolonged effect Effects 0.000 description 2
- 108020003175 receptors Proteins 0.000 description 2
- 102000005962 receptors Human genes 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 241000894007 species Species 0.000 description 2
- 230000009897 systematic effect Effects 0.000 description 2
- 238000002560 therapeutic procedure Methods 0.000 description 2
- 238000011269 treatment regimen Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 108091032973 (ribonucleotides)n+m Proteins 0.000 description 1
- 102100040121 Allograft inflammatory factor 1 Human genes 0.000 description 1
- 102100027205 B-cell antigen receptor complex-associated protein alpha chain Human genes 0.000 description 1
- 102100022005 B-lymphocyte antigen CD20 Human genes 0.000 description 1
- 108091003079 Bovine Serum Albumin Proteins 0.000 description 1
- 102100036301 C-C chemokine receptor type 7 Human genes 0.000 description 1
- 102100032532 C-type lectin domain family 10 member A Human genes 0.000 description 1
- 108010017009 CD11b Antigen Proteins 0.000 description 1
- 102100032912 CD44 antigen Human genes 0.000 description 1
- 102100029761 Cadherin-5 Human genes 0.000 description 1
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 1
- 208000006545 Chronic Obstructive Pulmonary Disease Diseases 0.000 description 1
- 102100033601 Collagen alpha-1(I) chain Human genes 0.000 description 1
- 102000053602 DNA Human genes 0.000 description 1
- 239000006144 Dulbecco’s modified Eagle's medium Substances 0.000 description 1
- 102000012804 EPCAM Human genes 0.000 description 1
- 102000018651 Epithelial Cell Adhesion Molecule Human genes 0.000 description 1
- 108010066687 Epithelial Cell Adhesion Molecule Proteins 0.000 description 1
- 102100027581 Forkhead box protein P3 Human genes 0.000 description 1
- 102100021186 Granulysin Human genes 0.000 description 1
- 102100030386 Granzyme A Human genes 0.000 description 1
- 101150074628 HLA-E gene Proteins 0.000 description 1
- 102100038006 High affinity immunoglobulin epsilon receptor subunit alpha Human genes 0.000 description 1
- 102100038009 High affinity immunoglobulin epsilon receptor subunit beta Human genes 0.000 description 1
- 101000890626 Homo sapiens Allograft inflammatory factor 1 Proteins 0.000 description 1
- 101000914489 Homo sapiens B-cell antigen receptor complex-associated protein alpha chain Proteins 0.000 description 1
- 101000897405 Homo sapiens B-lymphocyte antigen CD20 Proteins 0.000 description 1
- 101000716065 Homo sapiens C-C chemokine receptor type 7 Proteins 0.000 description 1
- 101000942296 Homo sapiens C-type lectin domain family 10 member A Proteins 0.000 description 1
- 101000868273 Homo sapiens CD44 antigen Proteins 0.000 description 1
- 101000794587 Homo sapiens Cadherin-5 Proteins 0.000 description 1
- 101000861452 Homo sapiens Forkhead box protein P3 Proteins 0.000 description 1
- 101001040751 Homo sapiens Granulysin Proteins 0.000 description 1
- 101001009599 Homo sapiens Granzyme A Proteins 0.000 description 1
- 101000878611 Homo sapiens High affinity immunoglobulin epsilon receptor subunit alpha Proteins 0.000 description 1
- 101000878594 Homo sapiens High affinity immunoglobulin epsilon receptor subunit beta Proteins 0.000 description 1
- 101001046668 Homo sapiens Integrin alpha-X Proteins 0.000 description 1
- 101000599940 Homo sapiens Interferon gamma Proteins 0.000 description 1
- 101001055144 Homo sapiens Interleukin-2 receptor subunit alpha Proteins 0.000 description 1
- 101000998120 Homo sapiens Interleukin-3 receptor subunit alpha Proteins 0.000 description 1
- 101001043809 Homo sapiens Interleukin-7 receptor subunit alpha Proteins 0.000 description 1
- 101000998020 Homo sapiens Keratin, type I cytoskeletal 18 Proteins 0.000 description 1
- 101000998011 Homo sapiens Keratin, type I cytoskeletal 19 Proteins 0.000 description 1
- 101000984199 Homo sapiens Leukocyte immunoglobulin-like receptor subfamily A member 4 Proteins 0.000 description 1
- 101000917839 Homo sapiens Low affinity immunoglobulin gamma Fc region receptor III-B Proteins 0.000 description 1
- 101001137987 Homo sapiens Lymphocyte activation gene 3 protein Proteins 0.000 description 1
- 101000972291 Homo sapiens Lymphoid enhancer-binding factor 1 Proteins 0.000 description 1
- 101001134216 Homo sapiens Macrophage scavenger receptor types I and II Proteins 0.000 description 1
- 101000934372 Homo sapiens Macrosialin Proteins 0.000 description 1
- 101000669513 Homo sapiens Metalloproteinase inhibitor 1 Proteins 0.000 description 1
- 101001109501 Homo sapiens NKG2-D type II integral membrane protein Proteins 0.000 description 1
- 101000947178 Homo sapiens Platelet basic protein Proteins 0.000 description 1
- 101001116302 Homo sapiens Platelet endothelial cell adhesion molecule Proteins 0.000 description 1
- 101000611936 Homo sapiens Programmed cell death protein 1 Proteins 0.000 description 1
- 101000716124 Homo sapiens T-cell surface glycoprotein CD1c Proteins 0.000 description 1
- 101000738413 Homo sapiens T-cell surface glycoprotein CD3 gamma chain Proteins 0.000 description 1
- 101000653540 Homo sapiens Transcription factor 7 Proteins 0.000 description 1
- 101000795074 Homo sapiens Tryptase alpha/beta-1 Proteins 0.000 description 1
- 206010061598 Immunodeficiency Diseases 0.000 description 1
- 208000029462 Immunodeficiency disease Diseases 0.000 description 1
- 206010062016 Immunosuppression Diseases 0.000 description 1
- 102100022338 Integrin alpha-M Human genes 0.000 description 1
- 102100022297 Integrin alpha-X Human genes 0.000 description 1
- 102100037850 Interferon gamma Human genes 0.000 description 1
- 102100026878 Interleukin-2 receptor subunit alpha Human genes 0.000 description 1
- 102100033493 Interleukin-3 receptor subunit alpha Human genes 0.000 description 1
- 102100021593 Interleukin-7 receptor subunit alpha Human genes 0.000 description 1
- 102100033421 Keratin, type I cytoskeletal 18 Human genes 0.000 description 1
- 102100033420 Keratin, type I cytoskeletal 19 Human genes 0.000 description 1
- 102000017578 LAG3 Human genes 0.000 description 1
- 241000713666 Lentivirus Species 0.000 description 1
- 102100025555 Leukocyte immunoglobulin-like receptor subfamily A member 4 Human genes 0.000 description 1
- 102100029185 Low affinity immunoglobulin gamma Fc region receptor III-B Human genes 0.000 description 1
- 108060001084 Luciferase Proteins 0.000 description 1
- 239000005089 Luciferase Substances 0.000 description 1
- 206010058467 Lung neoplasm malignant Diseases 0.000 description 1
- 102100022699 Lymphoid enhancer-binding factor 1 Human genes 0.000 description 1
- 210000004322 M2 macrophage Anatomy 0.000 description 1
- 102100025354 Macrophage mannose receptor 1 Human genes 0.000 description 1
- 102100034184 Macrophage scavenger receptor types I and II Human genes 0.000 description 1
- 102100025136 Macrosialin Human genes 0.000 description 1
- 108010031099 Mannose Receptor Proteins 0.000 description 1
- 102100039364 Metalloproteinase inhibitor 1 Human genes 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 108020005196 Mitochondrial DNA Proteins 0.000 description 1
- 102100022680 NKG2-D type II integral membrane protein Human genes 0.000 description 1
- 206010061309 Neoplasm progression Diseases 0.000 description 1
- 206010029379 Neutrophilia Diseases 0.000 description 1
- 102100036154 Platelet basic protein Human genes 0.000 description 1
- 102100024616 Platelet endothelial cell adhesion molecule Human genes 0.000 description 1
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical compound [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 description 1
- 102100040678 Programmed cell death protein 1 Human genes 0.000 description 1
- 206010060862 Prostate cancer Diseases 0.000 description 1
- 208000000236 Prostatic Neoplasms Diseases 0.000 description 1
- 206010056342 Pulmonary mass Diseases 0.000 description 1
- 238000000692 Student's t-test Methods 0.000 description 1
- 102100036014 T-cell surface glycoprotein CD1c Human genes 0.000 description 1
- 102100037911 T-cell surface glycoprotein CD3 gamma chain Human genes 0.000 description 1
- 101150057140 TACSTD1 gene Proteins 0.000 description 1
- 102100030627 Transcription factor 7 Human genes 0.000 description 1
- 102000004142 Trypsin Human genes 0.000 description 1
- 108090000631 Trypsin Proteins 0.000 description 1
- 102100029639 Tryptase alpha/beta-1 Human genes 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 108010029483 alpha 1 Chain Collagen Type I Proteins 0.000 description 1
- 230000025164 anoikis Effects 0.000 description 1
- 230000000259 anti-tumor effect Effects 0.000 description 1
- 230000010100 anticoagulation Effects 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- KMGARVOVYXNAOF-UHFFFAOYSA-N benzpiperylone Chemical compound C1CN(C)CCC1N1C(=O)C(CC=2C=CC=CC=2)=C(C=2C=CC=CC=2)N1 KMGARVOVYXNAOF-UHFFFAOYSA-N 0.000 description 1
- 238000001574 biopsy Methods 0.000 description 1
- 210000000481 breast Anatomy 0.000 description 1
- 201000008275 breast carcinoma Diseases 0.000 description 1
- 230000005773 cancer-related death Effects 0.000 description 1
- 231100000504 carcinogenesis Toxicity 0.000 description 1
- 238000005119 centrifugation Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000002512 chemotherapy Methods 0.000 description 1
- 229910052804 chromium Inorganic materials 0.000 description 1
- 239000011651 chromium Substances 0.000 description 1
- 210000003690 classically activated macrophage Anatomy 0.000 description 1
- 238000003501 co-culture Methods 0.000 description 1
- 230000008045 co-localization Effects 0.000 description 1
- 210000001072 colon Anatomy 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 230000034994 death Effects 0.000 description 1
- 230000000779 depleting effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000001079 digestive effect Effects 0.000 description 1
- 238000010494 dissociation reaction Methods 0.000 description 1
- 230000005593 dissociations Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 210000003162 effector t lymphocyte Anatomy 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 239000003480 eluent Substances 0.000 description 1
- 239000000839 emulsion Substances 0.000 description 1
- 210000002889 endothelial cell Anatomy 0.000 description 1
- 210000002919 epithelial cell Anatomy 0.000 description 1
- 210000003743 erythrocyte Anatomy 0.000 description 1
- 208000021045 exocrine pancreatic carcinoma Diseases 0.000 description 1
- 238000013401 experimental design Methods 0.000 description 1
- 238000010195 expression analysis Methods 0.000 description 1
- 239000013604 expression vector Substances 0.000 description 1
- 239000012091 fetal bovine serum Substances 0.000 description 1
- 210000002950 fibroblast Anatomy 0.000 description 1
- 235000011389 fruit/vegetable juice Nutrition 0.000 description 1
- 208000024200 hematopoietic and lymphoid system neoplasm Diseases 0.000 description 1
- 238000007490 hematoxylin and eosin (H&E) staining Methods 0.000 description 1
- 210000003630 histaminocyte Anatomy 0.000 description 1
- 230000005746 immune checkpoint blockade Effects 0.000 description 1
- 230000007813 immunodeficiency Effects 0.000 description 1
- 238000010166 immunofluorescence Methods 0.000 description 1
- 230000001506 immunosuppresive effect Effects 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 230000008611 intercellular interaction Effects 0.000 description 1
- 238000010253 intravenous injection Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000002843 lactate dehydrogenase assay Methods 0.000 description 1
- 238000002357 laparoscopic surgery Methods 0.000 description 1
- 239000004816 latex Substances 0.000 description 1
- 229920000126 latex Polymers 0.000 description 1
- 210000005228 liver tissue Anatomy 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 201000005202 lung cancer Diseases 0.000 description 1
- 239000006166 lysate Substances 0.000 description 1
- 210000002540 macrophage Anatomy 0.000 description 1
- 230000003211 malignant effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000001404 mediated effect Effects 0.000 description 1
- 239000002609 medium Substances 0.000 description 1
- 210000003071 memory t lymphocyte Anatomy 0.000 description 1
- 230000006510 metastatic growth Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 230000002438 mitochondrial effect Effects 0.000 description 1
- 229950001907 monalizumab Drugs 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 210000000066 myeloid cell Anatomy 0.000 description 1
- 210000000496 pancreas Anatomy 0.000 description 1
- 238000010827 pathological analysis Methods 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 230000037361 pathway Effects 0.000 description 1
- 239000008188 pellet Substances 0.000 description 1
- 230000010399 physical interaction Effects 0.000 description 1
- 239000013600 plasmid vector Substances 0.000 description 1
- 238000010837 poor prognosis Methods 0.000 description 1
- 229910052700 potassium Inorganic materials 0.000 description 1
- 239000011591 potassium Substances 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 239000002244 precipitate Substances 0.000 description 1
- 239000003761 preservation solution Substances 0.000 description 1
- 238000000513 principal component analysis Methods 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 238000001959 radiotherapy Methods 0.000 description 1
- 210000003289 regulatory T cell Anatomy 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000010839 reverse transcription Methods 0.000 description 1
- 238000012174 single-cell RNA sequencing Methods 0.000 description 1
- 150000003384 small molecules Chemical class 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000006228 supernatant Substances 0.000 description 1
- 238000001356 surgical procedure Methods 0.000 description 1
- 238000012353 t test Methods 0.000 description 1
- 239000012588 trypsin Substances 0.000 description 1
- 230000005740 tumor formation Effects 0.000 description 1
- 230000005751 tumor progression Effects 0.000 description 1
- 238000002255 vaccination Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- XOOUIPVCVHRTMJ-UHFFFAOYSA-L zinc stearate Chemical compound [Zn+2].CCCCCCCCCCCCCCCCCC([O-])=O.CCCCCCCCCCCCCCCCCC([O-])=O XOOUIPVCVHRTMJ-UHFFFAOYSA-L 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
- A61K45/00—Medicinal preparations containing active ingredients not provided for in groups A61K31/00 - A61K41/00
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
- A61K31/00—Medicinal preparations containing organic active ingredients
- A61K31/70—Carbohydrates; Sugars; Derivatives thereof
- A61K31/7088—Compounds having three or more nucleosides or nucleotides
- A61K31/7105—Natural ribonucleic acids, i.e. containing only riboses attached to adenine, guanine, cytosine or uracil and having 3'-5' phosphodiester links
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
- A61K31/00—Medicinal preparations containing organic active ingredients
- A61K31/70—Carbohydrates; Sugars; Derivatives thereof
- A61K31/7088—Compounds having three or more nucleosides or nucleotides
- A61K31/713—Double-stranded nucleic acids or oligonucleotides
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61K—PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES
- A61K39/00—Medicinal preparations containing antigens or antibodies
- A61K39/395—Antibodies; Immunoglobulins; Immune serum, e.g. antilymphocytic serum
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- A61P35/00—Antineoplastic agents
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- A61P35/00—Antineoplastic agents
- A61P35/04—Antineoplastic agents specific for metastasis
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6869—Methods for sequencing
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
- C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
- G01N33/56966—Animal cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
- G01N33/56966—Animal cells
- G01N33/56977—HLA or MHC typing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
- G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
- G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
- G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
- G01N2333/70503—Immunoglobulin superfamily, e.g. VCAMs, PECAM, LFA-3
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
- G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
- G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
- G01N2333/70503—Immunoglobulin superfamily, e.g. VCAMs, PECAM, LFA-3
- G01N2333/70539—MHC-molecules, e.g. HLA-molecules
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
- G01N2333/435—Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
- G01N2333/705—Assays involving receptors, cell surface antigens or cell surface determinants
- G01N2333/70596—Molecules with a "CD"-designation not provided for elsewhere in G01N2333/705
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Immunology (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Medicinal Chemistry (AREA)
- Molecular Biology (AREA)
- Organic Chemistry (AREA)
- Biochemistry (AREA)
- Biomedical Technology (AREA)
- Hematology (AREA)
- Animal Behavior & Ethology (AREA)
- Zoology (AREA)
- Veterinary Medicine (AREA)
- Microbiology (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Cell Biology (AREA)
- Analytical Chemistry (AREA)
- Public Health (AREA)
- Pharmacology & Pharmacy (AREA)
- Urology & Nephrology (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Biotechnology (AREA)
- Epidemiology (AREA)
- Wood Science & Technology (AREA)
- Food Science & Technology (AREA)
- Oncology (AREA)
- General Physics & Mathematics (AREA)
- Genetics & Genomics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Tropical Medicine & Parasitology (AREA)
- General Engineering & Computer Science (AREA)
- Biophysics (AREA)
- Hospice & Palliative Care (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- General Chemical & Material Sciences (AREA)
- Virology (AREA)
- Chemical Kinetics & Catalysis (AREA)
Abstract
The invention relates to a Circulating Tumor Cell (CTCs) immune check point and application thereof in inhibiting tumor metastasis, and HLA-E is obtained by screening: a series of specific immune checkpoints between CTCs, such as CD94-NKG2A, and NK cells, mediate immune escape from CTCs. The inhibition of CTCs and NK cells can be blocked by targeting the immune checkpoint, thereby restoring the killing effect of NK cells on CTCs. Blocking the binding of HLA-E on the surface of CTCs and CD94-NKG2A on the surface of NK cells by using an NKG2A binding antibody or inhibiting the expression of HLA-E can enhance the killing effect of NK cells on tumor cells in vitro and effectively inhibit tumor metastasis in vivo. The circulating tumor cell immune check point provides a new treatment target and a treatment scheme for clinical treatment and prevention of tumor metastasis.
Description
Technical Field
The invention belongs to the technical field of biological medicines, and particularly relates to a circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis.
Background
Metastasis and spread of tumor cells are the leading cause of cancer-related death. Tumor cells released into the blood circulation from primary focal tumor shedding are considered "seeds" of tumor metastasis, termed circulating tumor cells (Circulating Tumor cells, CTCs). CTCs, which leave the primary tumor foci or metastases and enter the peripheral blood circulation during tumor formation and progression, usually exist in the form of single cells and clusters of cells (two to tens of cells), are considered to be critical in causing tumor metastasis. CTCs are detected in the blood of various tumor species such as metastatic pancreatic cancer, breast cancer, lung cancer, colorectal cancer, prostate cancer, and are closely related to the decrease in tumor progression-free survival (PFS) and total survival (OS). Distant organ metastasis by CTC formation is a major cause of poor prognosis, recurrence of cancer and death in cancer patients. Most CTCs entering the blood circulation are usually deactivated due to shear stress of blood flow, anoikis, recognition and killing of immune cells, and only part of CTCs that have escaped through migration, adhesion and mutual aggregation can form tiny cancer plugs, and finally form metastasis. Thus, research on how CTCs can achieve immune surveillance that evades various immune cells in the blood circulation is an important basis for achieving the blocking of cancer metastasis.
The advent of Immune checkpoint blocking (Immune-checkpoint blockade, ICB) therapy has drastically changed the treatment options for a wide variety of cancer types, now being juxtaposed with radiotherapy, chemotherapy, surgery and molecular targeted drugs as the first line of choice for the treatment of cancer today. Although ICB therapy has been an unprecedented success, only a few patients have achieved good clinical responses and it is still necessary to find new immune checkpoints and develop new tumor treatment regimens. Currently, a great deal of research has been conducted to explore immune checkpoints between tumor cells and immune cells in the microenvironment of a solid tumor primary or metastatic tumor. CTCs are critical for tumor metastasis and recurrence, however immune checkpoints and immune escape involving CTCs are of little interest due to technical limitations.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a circulating tumor cell immune check point and identification and application thereof. The invention combines the micro-fluidic chip technology, the antibody capturing technology and the single-cell transcriptome sequencing technology, analyzes the interaction between the blood circulation and tumor-immune cells in primary and metastatic solid malignant tumors on a single-cell scale by utilizing bioinformatics, and screens out HLA-E: CD94-NKG2A represents immune checkpoint molecule pair closely related to CTC immune evasion, and provides an identification method and application of the circulating tumor immune checkpoint.
The technical scheme adopted by the invention is as follows:
a circulating tumor cell immune checkpoint for immunotherapy, the immune checkpoint molecule being a CTCs-specific immune checkpoint molecule comprising HLA-E: CD94-NKG2A, HLA-E: CD94-NKG2C and HLA-E: one or more of CD94-NKG 2E.
The identification method of the immune check point of the circulating tumor cells comprises the following steps:
(1) Capturing CTCs in blood, and collecting primary and metastatic malignant solid tumor samples to prepare single-cell suspension;
(2) Single cell transcriptome sequencing is carried out on the single cells obtained in the step (1), and immune check point molecules with specificity between CTCs and immune cells are obtained through analysis;
(3) And (3) performing functional verification on the immune checkpoint molecule obtained in the step (2).
The application of the circulating tumor cell immune check point in preparing a medicament for preventing or treating tumor metastasis.
Such tumors include, but are not limited to, pancreatic cancer, melanoma, breast cancer, colorectal cancer, and liver cancer.
Such agents that prevent or treat tumor metastasis include, but are not limited to, small molecule agents, antibody agents, and gene therapy agents.
The small molecule drug is a drug capable of inhibiting the expression level or biological function of the immune checkpoint molecule.
The monoclonal antibody is a binding antibody to the immune checkpoint molecule.
The monoclonal antibody is Mo Nali bead monoclonal antibody.
The gene therapy drug is designed aiming at the immune checkpoint molecule and comprises one or more of DNA drugs, RNA drugs and genetically modified cells.
The gene therapy medicine is one or more of sh-HLA-E, si-HLA-E, sh-NKG2A, si-NKG 2A.
The inventors of the present application have found in long-term studies that, since blood circulation is the primary pathway of CTCs metastasis to distant organs, studying the interactions between CTCs and immune cells in the blood stream may provide a strategy to block tumor metastasis by activating the host immune elimination system. Further studies have found that analysis of tumor-immune cell interactions in blood circulation and solid malignant lesions on a single cell scale can search for immune checkpoints to obtain CTCs by systematically dissecting immune-related molecular pairs between CTCs and immune cells.
The inventors analyzed pancreatic cancer primary foci tumors, portal venous blood and liver metastases by single cell transcriptome sequencing. Transcriptome characteristics of primary foci tumor cells, CTCs, and hepatic metastases tumor cells are characterized; the blood circulation and tumor cell-immune cell interactions in solid (primary and metastatic) malignancies were analyzed on a single cell scale using bioinformatics. Through the systematic profiling of immune-related molecule pairs, a specific immune checkpoint between CTCs and NK cells, HLA-E, was found: CD94-NKG2A, which mediates immune surveillance of CTCs against NK cells. In vitro experiments, it was found that blocking the binding of this immune checkpoint directly influences the in vitro killing ability of NK cells against tumor cells. In a mouse in vivo tumor metastasis model, HLA-E is blocked with either a blocking antibody to NKG2A or shHLA-E: CD94-NKG2A immune-checkpoint molecules can effectively inhibit tumor metastasis. Thus the present invention identifies a novel immune checkpoint between CTCs and NK cells, HLA-E: blocking this immune checkpoint is effective in inhibiting tumor metastasis by CD94-NKG 2A.
The beneficial effects of the invention are as follows:
1. immune checkpoint HLA-E identified by the invention: CD94-NKG2A is a CTCs-specific immune checkpoint that is highly expressed between CTCs and NK cells of the blood system, but is poorly expressed in primary and metastatic tumor microenvironments.
2. The immune check point HLA-E provided by the invention: CD94-NKG2A exists in CTCs of a plurality of cancer species such as pancreatic cancer, melanoma, liver cancer, breast cancer, colon cancer and the like, and can be widely used for treating distal metastasis of a plurality of tumors.
3. The present invention identifies immune checkpoint HLA-E in patient-derived blood: CD94-NKG2A is present in CTCs and NK cells, which pass through HLA-E: CD94-NKG2A binds.
4. Experiments prove that HLA-E is an immune check point of CTCs: CD94-NKG2A plays a role in evading the immune monitoring of NK cells, and blocking the immune check point can enhance the killing capacity of NK cells to tumor cells.
5. The method for inhibiting tumor metastasis provided by the invention uses specific antibodies and gene therapy drugs. Small molecule drugs and the like interfere the combination of HLA-E on the surface of CTCs and CD94-NKG2A on the surface of NK cells, so that the immunosuppression of the CTCs on the NK cells is relieved, the killing function of the NK cells is recovered, the CTCs are killed efficiently, and the tumor metastasis is effectively inhibited.
6. The invention is achieved by blocking immune checkpoint HLA-E: CD94-NKG2A realizes the prevention and treatment of tumor metastasis, and provides a new target and treatment strategy for inhibiting tumor metastasis by targeting CTCs in clinic.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram of clinical profiles of patient tissue for single cell transcriptome sequencing. Panel A is a CT image of the patient's pancreas, liver and portal vein system. Panel B is a representative image of primary and metastatic focus biopsies during the endoscopic procedure. Panel C is an H & E pathology staining of the primary foci and liver metastases.
FIG. 2 is a graph showing the result of dimension reduction clustering of single cell transcriptome sequencing data, wherein the abscissa and the ordinate represent the first and second principal components after dimension reduction of t-SNE, respectively, and each point represents a different cell. Visualization of cell subsets using a nonlinear t-SNE dimension reduction method.
FIG. 3 is a graph of single cell cluster analysis of primary/metastatic tumors and portal blood of PDACs based on single cell sequencing technology. Panel A is a bubble heat map of typical marker gene expression for each subtype of cell. Panel B shows all sequenced cells based on each cell subset in the t-SNE dimensionality reduction cluster analysis. Panel C is a plot of a t-SNE dimension-reduction cluster analysis of tissue sources of sequenced cells. Panel D is a plot of patient-derived t-SNE dimension-reduction cluster analysis of sequencing cells. FIG. E is a graph of t-SNE dimension-reducing cluster analysis of cell subtypes from primary focal tumors, portal venous blood, and metastatic focal tumors.
FIG. 4 is a graph of immune cell cluster analysis of PDAC portal venous blood, primary and liver metastases based on single cell sequencing technology. Panel A shows CD45 in all samples + (PTPRC + ) t-SNE dimensionality reduction cluster analysis of immune cell subpopulations. Panel B is a t-SNE dimension reduction cluster analysis of the tissue sources of each sequenced immune cell. Panel C is a heat map of typical marker gene expression for each cell subpopulation. Panel D shows the expression and distribution of each subtype of cell marker gene in the t-SNE assay.
FIG. 5 is a graph showing the interaction between tumor cells and immune cells of each subtype in portal blood, primary and hepatic metastases based on CellPhoneD analysis. (A) Interaction between primary tumor cells and immune cells. (B) interaction between CTCs and immune cells. (C) Interaction between metastatic tumor cells and immune cells. The lines in the figure represent the links between cognate receptors or ligands, and the thickness of the lines reflects the number and expression levels of the two intercellular ligand-receptor pairs.
FIG. 6 is a graph of immune checkpoint receptor-ligand analysis between tumor cells and immune cells of each subtype in portal blood, primary and hepatic metastases.
FIG. 7 is a bar graph showing HLA-E expression in CTCs derived from pancreatic cancer liver metastasis, primary and metastatic tumor cells.
FIG. 8 is a bar graph showing HLA-E expression levels in hepatocellular, breast, colon, melanoma, and pancreatic cancer-derived CTCs.
FIG. 9 is a bar graph showing the expression levels of HLA-E in pancreatic cancer mouse-derived CTCs.
FIG. 10 is a bar graph showing the relative expression amounts of KLRC1 (NKG 2A) and KLRD1 (CD 94) in immune cells in portal blood.
FIG. 11 is a graph showing the physical interactions of multiple immunofluorescent staining to detect isolated CTCs with NK in portal blood.
FIG. 12 shows detection of HLA-E and CD94 expression levels in CTCs-NK cell clusters by multiplex immunofluorescent staining.
FIG. 13 is a graph showing the interaction of CTCs with NK in multiple immunofluorescent staining for detection of PDAC liver metastases.
FIG. 14 is a graph of in vitro studies of HLA-E, CD94-NKG2A mediated escape of CTCs from NK immune monitoring. Panel A is a Western blot detection of the expression level of SU86.86 cells HLA-E when HLA-E is knocked out. Panel B is a graph of the expression level of SU86.86 cells HLA-E when the HLA-E is over-expressed by Western blot detection. Panel C is a flow cytometry analysis of NK cells positive for NKG2A and NKG2C in peripheral blood of PDAC patients. Panel D is the quantification of panel C. FIG. E is an LDH release experimental graph, and the killing capacity of NK to SU86.86 cells on tumor cells under the condition of different effective target ratios (E: T) is detected. And the F diagram shows the expression condition of NK cell cytotoxic effector GZMB and immune checkpoint related kinase SHP1 after the co-incubation of NK cells and shHLA-E SU86.8 by Western blot.
FIG. 15 is a graph showing the results of in vivo studies of the effect of blocking NKG2A with an NKG 2A-binding antibody on lung metastasis in mice. And A is an experimental design scheme. Panel B shows that mice were examined for lung metastasis growth by bioluminescence in vivo imaging 15 days after intravenous inoculation of KPC-Luc cells. Panel C is a statistical quantification of lung metastases from panel B. Panel D is a photograph of a lung metastasis nodule. Panel E is a lung H & E staining pattern.
FIG. 16 shows the expression of H2-T23 in KPC cells knocked out by Western blot detection shH 2-T23.
FIG. 17 is a graph showing the results of in vivo studies in which the expression of knockdown HLA-E reduces lung metastasis in mice. Panel A is a bioluminescence image of lung metastasis of Balb/c nude mice after injection of KPC-Luc cells knocked out of H2-T23. Panel B is a quantitative plot of A. Panel C is a representative visual image of the lungs of representative mice of each group. Panel D is a lung tumor nodule count. Panel E is an H & E staining of the lung.
FIG. 18 is a C57BL/6 mice in vivo blocking immune checkpoint HLA-E: results of CD94-NKG2A inhibition of lung metastasis in mice. Figure a is a design of a mouse lung metastasis protocol. Intravenous inoculation of C57BL/6 mice 5X 10 4 KPC-Luc/H2-T23 knockdown KPC-Luc cells were subjected to blocking treatment by injection of anti-NKG2A antibody (10 mg/kg) prior to vaccination. Panel B is a lung metastasis image of mice detected by in vivo imaging of the mice 15 days after intravenous injection of KPC-Luc cells. Panel C is a quantitative statistical plot of Panel B. Panel D is a photograph of mouse lung tissue. And E is a lung metastasis node number statistical graph. F graph is lung tissue H&E staining the picture.
FIG. 19 is a block immune checkpoint HLA-E: results of CD94-NKG2A studies showing that mice have prolonged survival.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, based on the examples herein, which are within the scope of the invention as defined by the claims, will be within the scope of the invention as defined by the claims.
The invention takes pancreatic cancer liver metastasis as a research object, and uses single cell transcriptome sequencing to analyze pancreatic primary focus tumor, portal vein blood and liver metastasis tumor. Transcriptome characteristics of pancreatic cancer primary foci tumor cells, CTCs and hepatic metastases tumor cells were characterized, and the interaction between blood circulation and tumor-immune cells in primary and metastatic solid malignancies was analyzed on a single cell scale using bioinformatics. Through the systematic profiling of immune-related molecule pairs, a specific immune checkpoint HLA-E, CD94-NKG2A, was found between CTCs and NK cells, which mediates immune surveillance of CTC immune evasion NKs.
In vitro experiments, it was found that overexpression or knockout of HLA-E expression of tumor cells directly affects NK cell killing ability in vitro on tumor cells. In a mouse in vivo tumor metastasis model, blocking HLA-E by using a blocking antibody of NKG2A or shHLA-E can effectively inhibit tumor metastasis by using an HLA-E CD94-NKG2A immune check point molecule, which shows that HLA-E CD94-NKG2A is a novel immune check point between CTC and NK cells.
The following describes the above technical scheme in detail with reference to specific embodiments.
The experimental methods used in the following examples are conventional methods unless otherwise specified. Materials, reagents and the like used in the examples described below are commercially available unless otherwise specified.
Example 1 Primary focal tumor, metastatic tumor and CTCs single cell transcriptome sequencing and banking
1. Sample collection
To find immune checkpoints specific for CTCs, we take pancreatic cancer liver metastasis as an example, primary foci, CTCs and metastatic foci of the same patient were collected for single cell transcriptome sequencing. First, we screened 6 untreated PDAC liver metastasis patients by computer tomography (Computed Tomography, CT) tumor markers (fig. 1A). Then, the patient's hepatic portal blood (hepatic portal vein, HPV), the living tissues of primary and liver metastatic lesions (fig. 1B) were collected by laparoscopic surgery, and histopathological verification was performed to confirm that the tissues taken were pancreatic primary foci tumor and metastatic foci tumor (fig. 1C). Primary foci and metastatic foci tumor tissues obtained in the operation are temporarily stored in tissue preservation solution and placed on ice, and then immediately sent to a laboratory for subsequent dissociation of single-cell samples and single-cell transcriptome sequencing; portal blood is stored in anticoagulation blood collection tubes and sent to the laboratory for subsequent isolation of CTCs and single cell transcriptome sequencing.
2. Preparation of single cell samples
The primary and metastatic tumor tissues were minced on ice with scissors. Subsequently, the tissue pieces were transferred to a 50ml centrifuge tube, and 20ml of a digestive juice was added thereto for digestion at 37℃for 15min; wherein the digestion solution contains 0.25% trypsin, 0.4mg/ml type I collagenase and 0.4mg/ml type IV collagenase. After complete digestion of the tumor tissue, the reaction was stopped with an equal volume of pre-chilled DMEM medium containing 10% fetal bovine serum, and the bulk debris was removed with a 70 μm cell screen and the single cell suspension was collected. Next, the single cell suspension was centrifuged at 500g for 5min at 4 ℃. Adding the centrifuged cell precipitate into erythrocyte lysate for cracking for 5min; the cell pellet was then collected by centrifugation at 500g at 4℃twice with HBSS (0.1% BSA). Then, the cells were resuspended with HBSS containing 0.1% bsa and PI was added and the live cells with good flow cytometry sorting status were used for single cell transcriptome sequencing.
3. Preparation of scRNA-seq library
After completion of the preparation of the single cell samples described above, single cell transcriptome libraries were prepared using a 10× Genomics Chromium 3'Gene Expression Kit V3 kit and sequenced. Specifically, target cells and corresponding 10×genomics reagents are added to a chromanum chip to generate latex droplets (Gel Bead in Emulsion, GEM) containing individual cells and individual gel beads, and subsequent reverse transcription, double-stranded DNA generation, library construction, and sequencing are performed. In the laboratory, we set the target capture cells for each sample to be 6,000-8,000. The final constructed library was sequenced on an Illumina HiSeq 4000 platform with a target sequencing depth of 100,000 reads per cell.
Example 2 identification of CTCs-specific immune checkpoint molecules
(1) Single cell transcriptome data preprocessing and quality control
The raw sequencing data image obtained by the sequencing is firstly converted into sequence information in Fastq format with 150 base pairs of double ends by using bcl2Fastq software of Illumina company. The resulting sequences were then aligned with human reference genome version GRCh38 using Cell range (v.3.0.0, 10 x Genomics) software to obtain a gene expression matrix. UMI tags that can specifically compare sequences to the exon regions of transcriptome genes will be used for subsequent statistical counting. The semat R package then performs subsequent quality control, we filtered cells and genes by three criteria: (1) Cells with gene expression numbers exceeding 7500 and less than 200 are excluded, because low quality cells typically have a lower number of gene expressions, while dual or multicellular gene expression numbers are typically higher; (2) Cells with more than 25% of mitochondrial gene numbers were removed, as dead cells generally showed high mitochondrial contamination; (3) excluding genes expressed in less than three cells. In addition, cells with a variety of different types of cell marker genes were identified as multicellular. After quality control, a total of 74,206 cells were measured for 18 samples, including 27,296 cells from primary focal tumor, 6,922 cells from liver metastasis tumor, and 9,988 cells from portal blood.
(2) Single cell transcriptome data dimension reduction and cluster analysis
After quality control of cells and genes, single cell transcriptome data was normalized using the semat (v.4.0.1) R software package, respectively, to eliminate differences between the individual cell data, and to perform subsequent reduced and unsupervised cluster analysis. Firstly, we use global scaling normalization method 'lognormal' to globally normalize the gene expression matrix of single cell collection, and take log value after dividing the expression value of the gene by the total expression value of the corresponding single cell and multiplying the product by a parameter factor (using default standard parameter 10000). Next, the first 2000 high variable genes were selected using the FindVariableFeateurs function, and the normalized data was scaled to z-score using the ScaleData function. And then carrying out principal component analysis (Principal Components Analysis, PCA) on the genes with high variables by using a RunPCA function, and carrying out dimension reduction treatment on the high-dimension data. After completion of dimension reduction, KNN plots were constructed using FindNeighbors functions to define weights between two cells. The Louvain algorithm was then applied to group similar cells by FindClusters function, with the resolution (resolution) parameter set to 1. The single cell transcriptome data was then subjected to dimensionality reduction cluster analysis using a non-linear t-SNE dimensionality reduction method (fig. 2).
(3) Copy number variation analysis and identification of cell types
Cell types were identified using the sciBet (v.1.0) R software package, classical marker genes and copy number variation combined. First, cell types were annotated according to classical cell markers, and a total of 29,930 Epithelial cells (Epithelial: EPCAM) + 、KRT8 + 、KRT18 + 、KRT19 + ) 1,675 fibroblasts (fibribelast: FAP (Fabry-Perot) + 、COL1A1 + 、DCN + ) 875 Endothelial cells (endoprostelial: VWF + 、CDH5 + 、ENG + 、PECAM1 + ) 523 CTCs (PTPRC) - 、PPBP + 、PF4 + 、CD9 + 、KRT8 + 、TIMP1 + ) 19,072 Myeloid cells (Myeloid: AIF1 + 、CD14 + 、LYZ + 、FPR1 + ) 1,448B cells (B cell: CD79A + 、CD79B + 、MS4A1 + ) 2,485 NK cells (NK cell: KLRF1 + 、KLRD1 + 、GNLY + ) 18,198T cells (T cell: CD3D + 、CD3E + 、CD3G + ) (FIG. 3A). Then, we performed t-SNE dimension-reduction clustering and visual analysis of all single cells based on cell type, tissue source and patient source (FIGS. 3B-D). And differences in cell types in primary focal tumor tissue, portal blood and metastatic focal tumor tissue were analyzed using t-SNE dimension reduction (FIG. 3E).
Whereas for PTPRC from portal venous blood, primary and hepatic metastases tumor tissue + (CD45 + ) We performed t alone-SNE dimension reduction cluster analysis (fig. 4a, b). All subtypes of immune cells were annotated according to classical immune cell markers, including NK cells (NKs; KLRD 1) + 、KLRF1 + ) NK-T cells (CD 3D) + 、CD3E + 、KLRD1 + 、KLRF1 + ) CD8 depleting T cells (CD 8 Ex; CD8A + 、PDCD1 + 、LAG3 + ) CD8 effector T cells (CD 8 EFF; CD8A + 、IFNG + 、GZMA + ) Memory T cells (Memory T; CD3D + 、CD44 + 、IL7R + 、LTB + ) Initial T cellT;CD3D + 、CCR7 + 、TCF7 + 、SELL + 、LEF1 + ) Treg cells (CD 4) + 、FOXP3 + 、IL2RA + ) B cells (CD 79A) + 、CD79B + ) Neutrophils (neutrophilie; CD14 - 、FCGR3B + 、FPR1 + ) Monocytes (Monocyte; CD14 + 、S100A12 + 、FCGR3A + ) M1 macrophages (M1 macrotage; FCGR3A + 、CD68 + 、ITGAX + 、ITGAM + ) M2 macrophages (M2 macrotage; CD163 + 、MRC1 + 、MSR1 + ) Classical DC cells (DCs; CD1C + 、FCER1A + 、CLEC10A + ) Plasma cell-like DCs (pDC; LILRA4 + 、IL3RA + ) And mast cells (mass cell; MS4A2 + 、TPSAB1 + 、KIT + ) (FIGS. 4C, D).
(4) Analysis of cell-cell interactions
To study the interactions between tumor cells and immune cells during tumor metastasis, we analyzed ligand-receptor pairs on the surface of tumor cells and immune cells of each subtype based on gene expression levels and differences using cellphondb. The CellPhoneDB database consists of 1396 ligand molecule pairs from UniProt, ensembl, PDB, IMEx and iuphas databases. Molecular pairing of potential interactions between tumor cells and immune cellsExpression of the relevant genes was extracted from single cell transcriptome data and aligned to a reference database. Wherein the molecular pairs of interactions between different types of cells are determined by: 1) Integrating the expression analysis of the ligand and receptor between each cell type to calculate the average expression level of the ligand; 2) The p value of the expression change is calculated by using empirical shuffling algorithm, and the ligand molecule pair with different change is screened. After ligand molecule pairs of different types of cell interactions are obtained by the method, the ligand molecule pairs are classified according to functions of the ligand molecule pairs by using a CellChat database. We found that ligand-receptor pairs that interact between primary foci of tumor cells, CTCs, metastatic focus of tumor cells and immune cells were significantly different, indicating that immune cell monitoring of tumor cells was dynamic during tumor metastasis (fig. 5A-C). Tumor cells and CD8 in primary and metastatic tumor microenvironment + There are complex and strong interactions between various immune cells such as T cells, macrophages, NKs, etc. While the interaction between CTCs and immune cells in the blood circulation is relatively simple, CTCs interact primarily with NK cells in the blood, suggesting that NK cells may be involved in immune monitoring of CTCs in the blood circulation.
(5) Identification of immune checkpoints specific for CTCs
We first screened all immune checkpoint molecule pairs in cellphonedab, then calculated the average expression levels of the ligand molecule pairs in tumor cells (including CTCs) and immune cells of each subtype, calculated p-values of expression changes using empirical shuffling algorithm, calculated immune checkpoint molecule pairs present between primary foci tumor cells, CTCs, metastatic foci tumor cells and immune cells of each subtype. We found that, in marked contrast to primary and metastatic tumor cells, there are some specific pairs of immune checkpoint molecules between CTCs and immune cells in the blood circulation (fig. 6). Several pairs of highly expressed, specific immune checkpoint molecules were found between CTCs and NK cells, including HLA-E where CTCs interact with NK: KLRC1 (NKG 2A), HLA-E: KLRC2 (NKG 2C) and HLA-E: KLRK1 (NKG 2D), and CD94-NKG2A where NK interacts with CTCs: HLA-E, CD94-NKG2C: HLA-E and CD94-NKG2E: HLA-E.
Example 3 verification of the Presence of HLA-E: CD94-NKG2A immune-checkpoint molecules between CTCs and NK cells
(1) Detection of HLA-E expression levels in CTCs
First, we calculated the expression levels of HLA-E in primary tumor cells, CTCs in blood and metastatic tumor cells after Log2 (tpm+1) normalization of gene expression values using the above CTCs transcriptome sequencing data and with primary tumor cells and metastatic tumor cells as controls. The results are shown in FIG. 7, which shows that HLA-E is highly expressed in CTCs compared to primary and metastatic tumor cells, suggesting that it may play a potential role in the metastasis of CTCs.
At the same time, we also examined the expression level of HLA-E in other tumor-derived CTCs. We calculated the expression levels of HLA-E in CTCs of different tumor origin using transcriptome data from hepatocellular carcinoma (HCC; CNP0000095, GSE 117623), PDAC (GSE 144561), breast cancer (BRCA; GSE67939, GSE 86978), colon adenocarcinoma (COAD; GSE 74369) and melanoma (SKCM; GSE 38495) sources in the database and normalizing the gene expression values with Log2 (tpm+1). The results are shown in FIG. 8, where HLA-E is highly expressed in hepatocellular carcinoma, pancreatic carcinoma, breast carcinoma, colon adenocarcinoma, and melanoma-derived CTCs, indicating broad spectrum applicability of the immune checkpoint molecule.
In addition, we examined the expression level of HLA-E in other mouse tumor-derived CTCs, and in mice the homologous gene of HLA-E was H2-T23, so that all the following references to H2-T23 refer to HLA-E. We calculated the expression level of H2-T23 (HLA-E) in mouse tumor-derived CTCs using transcriptome data from mouse pancreatic cancer (GSE 51372) in the database and normalizing the gene expression values with Log2 (tpm+1). As shown in FIG. 9, H2-T23 (HLA-E) was also highly expressed in mouse tumor-derived CTCs.
(2) Detection of expression levels of CD94 and NKG2A in NK cells
Immune checkpoint molecule pairs HLA-E were detected using single cell sequencing data: ligand molecules NKG2A (KLRC 1) and CD94 (KLRD 1) of CD94-NKG2A are expressed in immune cells of each subtype, such as monocytes, NK cells, B cells, DC cells, T cells, neutrophils, etc. As shown in fig. 10, NKG2A (KLRC 1) and CD94 (KLRD 1) were specifically highly expressed in NK cells, indicating that the ligand molecules of the immune checkpoint were mainly expressed in NK; HLA-E in CTCs binds to CD94-NKG2A on the surface of NK cells. The immune checkpoint molecule is present between CTCs and NK cells.
(3) CTCs were demonstrated to bind to NK cells to form CTCs-NK cell clusters in portal blood of patients with pancreatic cancer liver metastases.
To verify the interaction of CTCs with NK cells, CTCs in portal blood of patients with pancreatic cancer liver metastasis were captured using microfluidic chips. After elution of CTCs, epCAM/CD94 immunofluorescent staining was used to detect the presence of CTC-NK cell clusters in the eluate. As a result, as shown in FIG. 11, CTC-NK cell clusters were observed in the eluents of CTCs from multiple patients, indicating direct interactions between CTCs and NK cells.
(4) Immune checkpoint molecule HLA-E was demonstrated by HLA-E/CD94 multiplex immunofluorescent staining: CD94-NKG2A exists between CTCs and NK cells.
To verify immune checkpoint HLA-E: CD94-NKG2A exists between CTCs and NK cells. We captured CTCs in portal blood of PDAC liver transfer patients using microfluidic chips. After elution and collection of CTCs, HLA-E/CD94 immunofluorescent staining was used to detect whether the CTCs-NK cell cluster expressed HLA-E and CD94. The results are shown in FIG. 12, where HLA-E and CD94 protein expression was detected in CTCs and NK cells, respectively, indicating that this immune checkpoint molecule pair exists between CTCs and NK cells.
(5) The interacting CTCs-NK cell clusters were detected in patients with pancreatic cancer liver metastases.
We collected and examined pancreatic cancer hepatic metastasis patient primary foci and hepatic metastasis tumor tissues, and stained patient tissues by EpCAM/CD94 immunofluorescence for the presence of CTCs-NK cell clusters. As shown in fig. 13, we detected co-localization of CTCs with NK in a healthy liver tissue region near the metastasis; this result further demonstrates the interaction between CTCs and NK cells.
Example 4 blocking immune checkpoint HLA-E CD94-NKG2A enhances the killing ability of NK cells against tumor cells
In this example, we assessed the effect of the intervention immune checkpoint HLA-E: CD94-NKG2A on the ability of NK cells to kill tumor cells.
Blocking this immune checkpoint binding in two ways:
1) HLA-E protein is pre-expressed or knocked out in human PDAC cells SU86.86 by lentivirus over-expression and shRNA interference technology, and the binding of the HLA-E protein and NK cell surface NKG2A is interfered. For the expression of HLA-E of human tumor cells by shRNA interference technology, we designed shRNA sequences (table 1) targeting human HLA-E (shH-T23), cloned to pLKO.1-puro vector, extracted plasmids, then introduced into tumor cells by lentiviral infection technology to knock out the expression of HLA-E, and detected by Western blot, and as a result, the designed shRNA sequences effectively knock down the expression of HLA-E of human tumor cells as shown in FIG. 14A. For over-expression of HLA-E protein, after the HLA-E gene sequence is synthesized, the plasmid is cloned to a Plvx-puroz plasmid vector, then plasmid is extracted, recombinant plasmid is introduced into tumor cells to express the HLA-E protein by using a slow virus infection technology, and the expression of the HLA-E is detected by Western blot, so that the expression level of the HLA-E of human tumor cells is obviously up-regulated after the over-expression of the HLA-E is shown in a figure 14B.
TABLE 1 sequences for construction of shRNA expression vectors
2) NKG2A of the NK cells is blocked by adding Mo Nali bead monoclonal antibody (monalizumab) with the final concentration of 100 mug/ml into a co-culture system of the tumor cells and the NK cells, and the binding of the NKG2A with the tumor cells HLA-E is blocked.
First, NK cells were isolated from peripheral blood of PDAC patients, and after flow cytometry, NK cells derived from PDAC patients were found to highly express NK inhibitory protein NKG2A and significantly higher than activating protein NKG2C (shown in FIGS. 14C and D, the ratio of NKG2A and NKG2C in peripheral blood NK cells of PDAC patients was examined and quantified by flow cytometry.
NK cells were then co-incubated with SU86.86 tumor cells at different potency target ratios (5:1 and 10:1), after 24 hours of co-incubation, cell supernatants were collected and assayed for NK cell killing by LDH kit. The results are shown in FIG. 14E, where the LDH release assay detects NK's ability to kill tumor cells under different effective target ratio (E: T) conditions for SU86.86 cells. Data are shown in mean±se, n=3, p <0.05, p <0.01, t-test.
SU86.86 over-expressed HLA-E protected from NK cell killing at both different potency ratios. In contrast, after the shHLA-E is utilized to knock out the expression of SU86.86 cell HLA-E, the killing capacity of NK cells to tumor cells is obviously enhanced. Similarly, blocking NKG2A with Mo Nali bead mab also enhanced NK cell killing of SU86.86 and HLA-E overexpressing SU 86.86.
Example 5
In this example, WB verifies blocking CD94-NKG2A: HLA-E immune checkpoints increase NK activity.
SU86.86 tumor cells transfected with empty vector and shHLA-E were transfected with 5X 10 4 The density of individual cells/wells was seeded in 24-well plates and cultured overnight. The next day, NK cells were added in a ratio of 10:1 for co-incubation for 24 hours. NK cells were then collected and the activity of SHP-1 downstream of the NKG2A immune checkpoint was examined by western blot (Western blot) and the GZMB protein expression level that marks the NK cell activity. As shown in FIG. 14, after NK cells were co-incubated with shHLA-E SU86.8, western blot detected the cytotoxic effector of NK, GZMB, and immune checkpoint related kinase SHP1.
When HLA-E knockdown tumor cells were incubated with NK, the activity of SHP-1 downstream of the NKG2A immune checkpoint in NK cells was inhibited, while the expression of GZMB, which marks the activity of NK cells, was up-regulated (FIG. 14F). The above results indicate that tumor cells can pass through immune checkpoint HLA-E: CD94-NKG2A evades immune surveillance of NK cells.
Example 6
In this example, blocking of immune checkpoint HLA-E with anti-NKG2A antibodies was studied: effect of CD94-NKG2A on tumor metastasis in mice.
Next, blocking immune checkpoint HLA-E was studied in mice: whether CD94-NKG2A inhibited metastasis of tumor. Since Balb/c nude mice are immunodeficiency mice containing NK cells and without T cells, the nude mice are ideal models for researching NK cells and tumor cells; whereas the mouse PDAC KPC cells endogenously express H2-T23 proteins homologous to human HLA-E proteins (hereinafter, mouse H2-T23 corresponds to human HLA-E genes). Thus, in Balb/c nude mice as a model, tumor cell metastasis was reproduced by tail vein injection of luciferase-labeled KPC (KPC-Luc) cells.
To block tumor cells, which indicate binding of HLA-E to NK cell surface CD94-NKG2A, this immune checkpoint was blocked by two means: (1) blocking NK cell surface NKG2A with a blocking antibody; (2) mice were vaccinated with KPC cells that had been pre-knocked out H2-T23.
First, blocking NK cells with anti-NKG2A blocking antibodies suggests NKG2A. Specifically, 4 doses of anti-NKG2A antibody (10 mg/kg) are respectively injected into continuous tail veins before (day-1), during (day 0) and after ( day 1, 3 and 5) KPC-Luc cell inoculation for blocking treatment, so as to study the influence of blocking time on the growth of lung metastasis tumor; mice were intraperitoneally injected with potassium D-fluorescein (150 mg/kg) 15 days after inoculation, and mice were subjected to in vivo imaging to detect the intensity of pulmonary fluorescence signal for monitoring growth of lung metastasis (FIG. 15A).
The results show that anti-NKG2A has time dependence on inhibiting tumor metastasis, and the earlier the NKG2A is blocked, the better the effect of inhibiting tumor metastasis. Injection of anti-NKG2A antibody almost completely inhibited tumor metastasis before tumor inoculation (day-1); whereas tumor metastasis is only partially inhibited at day0 and day 1. NKG2A blockade was performed 3 days and 5 days after inoculation, with little inhibition of tumor metastasis (fig. 15b, c).
After the experiment is finished, collecting lung tissues of the mice, photographing, and counting the number of tumor nodules on the lung surface.
The results showed that, consistent with the trend of fluorescence signal quantification, almost no tumor nodules were observed in lung tissue of the anti-NKG2A antibody group injected prior to tumor inoculation (day-1); only a small number of lung metastasis nodules were observed in day0 and day1 groups; whereas day3 and day5 groups of lung metastasis nodules were comparable to the untreated control group (fig. 15d, e). Further H & E pathology analysis was performed on lung tissue, with results consistent with fluorescent signal and lung metastasis nodule count.
The above results indicate that immune checkpoint HLA-E is blocked with anti-NKG 2A: the anti-tumor effect of CD94-NKG2A is only effective against tumor cells in the blood circulation, but has no significant inhibitory effect on tumor cells that have been colonized in the metastatic organ.
Example 7
In this example, it was verified whether inhibition of tumor cell HLA-E expression, blocking of its binding to NK cell surface NKG2A, could inhibit tumor.
Specifically, we designed shRNA sequence (Table 1) targeting mouse HLA-E (shH 2-T23), cloned to pLKO.1-puro vector, extracted plasmid, then introduced into KPC cell by slow virus infection technique to knock out H2-T23 expression, and detected H2-T23 expression by Western blot.
The results showed that the designed shRNA sequence significantly reduced expression of KPC cell H2-T23, with shH2-T23-2 knockdown being most efficient (fig. 16). Therefore, shH2-T23 KPC cells were constructed using this sequence in experiments, and subsequent animal experiments were performed.
KPC cells stably expressing shH2-T23 were then inoculated into nude mice by tail vein injection. Similar to the anti-NKG2A antibody blocking results, decreasing the expression of KPC cell surface H2-T23 (HLA-E) significantly alleviated the formation of tumor cell lung metastases (FIGS. 17A, B).
After the experiment is finished, collecting lung tissues of the mice, photographing, and counting the number of tumor nodules on the lung surface. The results showed that lowering H2-T23 significantly reduced the number of lung tumor nodules with few tumors observed in the lung tissue of group shH-T23 (fig. 17c, d). At the same time, the lung tissue was subjected to H & E staining for pathological analysis, and the results were consistent with morphological observation, and formation of tumor metastasis was hardly detected even at the pathological level (FIG. 17E)
Example 8
In this example, it was confirmed that blocking immune checkpoint HLA-E, CD94-NKG2A, also inhibited mouse metastasis in immunized complete mice C57/BL6 mice.
To further verify the role of this immune checkpoint molecule in fully immunized mice, C57/BL6 immunized fully mice were vaccinated 5X 10 with tail veins 4 The KPC-Luc cells are used for constructing a mouse lung transfer model; and blocks this immune checkpoint by two means: (1) Four doses of anti-NKG2A antibody (10 mg/kg) were continuously injected intravenously to block NK cell surface NKG2A starting the day before inoculation (day-1); (2) Inoculation modeling was performed with KPC cells pre-knocked out H2-T23 (FIG. 18A).
Mice were examined for lung metastatic growth using in vivo imaging of the mice 15 days after inoculation.
The results showed that both anti-NKG2A pre-blocking and shH2-T23 pre-knockout significantly inhibited lung metastasis formation (fig. 18B). Quantification of pulmonary fluorescence signals revealed that anti-NKG2A and shH2-T23 reduced pulmonary metastasis fluorescence signals by 63-fold and 115-fold, respectively (FIG. 18C). Lung nodule counts and pathology analysis further showed that anti-NKG2A and shH2-T23 significantly reduced the formation of lung metastases in mice compared to untreated control (fig. 18D-F).
Example 9
In this example, blocking immune checkpoint HLA-E, CD94-NKG2A, was examined to increase survival in mice.
To investigate the effect of blocking immune checkpoint HLA-E: CD94-NKG2A on survival of mice, we used Balb/c nude tail veins to inoculate KPC cells in another independent cohort (5X 10 4 Constructing a mouse lung transfer model; and blocks this immune checkpoint by two means: (1) Four doses of anti-NKG2A antibody (10 mg/kg) were continuously injected intravenously to block NK cell surface NKG2A starting the day before inoculation (day-1); (2) Inoculation modeling was performed with KPC cells pre-knocked out of H2-T23. Then, the survival of the mice was observed, and a Kaplan-Meier survival curve of the mice was drawn. As shown in FIG. 19, blocking NKG2A with anti-NKG2A antibody and decreasing the expression of tumor cell HLA-E (H2-T23) significantly prolonged the survival of lung metastatic mice.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A circulating tumor cell immune checkpoint for immunotherapy, characterized in that said immune checkpoint molecule is a CTCs-specific immune checkpoint molecule comprising HLA-E: CD94-NKG2A, HLA-E: CD94-NKG2C and HLA-E: one or more of CD94-NKG 2E.
2. The method for identifying the immune checkpoint of the circulating tumor cells according to claim 1, comprising the following steps:
(1) Capturing CTCs in blood, and collecting primary and metastatic malignant solid tumor samples to prepare single-cell suspension;
(2) Single cell transcriptome sequencing is carried out on the single cells obtained in the step (1), and immune check point molecules with specificity between CTCs and immune cells are obtained through analysis;
(3) And (3) performing functional verification on the immune checkpoint molecule obtained in the step (2).
3. Use of the circulating tumor cell immune checkpoint of claim 1 in the manufacture of a medicament for preventing or treating tumor metastasis.
4. The use according to claim 3, wherein the neoplasm includes, but is not limited to, pancreatic cancer, melanoma, breast cancer, colorectal cancer and liver cancer.
5. The use according to claim 3, wherein the medicament for preventing or treating tumor metastasis includes, but is not limited to, small molecule drugs, antibody drugs and gene therapy drugs.
6. The use according to claim 5, wherein the small molecule drug is a drug capable of inhibiting the expression level or biological function of the immune checkpoint molecule.
7. The use according to claim 5, wherein the monoclonal antibody is a binding antibody to the immune checkpoint molecule.
8. The use of claim 7, wherein the monoclonal antibodies include, but are not limited to, mo Nali bead mab.
9. The use of claim 7, wherein the gene therapy agent is a gene therapy agent designed for the immune checkpoint molecule, including but not limited to one or more of DNA agents, RNA agents, genetically engineered cells.
10. The use according to claim 9, wherein the gene therapy drug comprises, but is not limited to, one or more of sh-HLA-E, si-HLA-E, sh-NKG2A, si-NKG 2A.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211610754.XA CN116356018B (en) | 2022-12-14 | 2022-12-14 | Circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211610754.XA CN116356018B (en) | 2022-12-14 | 2022-12-14 | Circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis |
Publications (2)
Publication Number | Publication Date |
---|---|
CN116356018A true CN116356018A (en) | 2023-06-30 |
CN116356018B CN116356018B (en) | 2024-05-17 |
Family
ID=86925882
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202211610754.XA Active CN116356018B (en) | 2022-12-14 | 2022-12-14 | Circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116356018B (en) |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20190314445A1 (en) * | 2018-03-16 | 2019-10-17 | Deutsches Rheuma-Forschungszentrum Berlin | Activation and expansion of nkg2c+ nk cells |
CN110575537A (en) * | 2019-09-06 | 2019-12-17 | 刘慧宁 | Composition of DC vaccine and NKG2A antagonist and application of composition in resisting breast cancer or liver cancer |
CN112639137A (en) * | 2018-07-02 | 2021-04-09 | 茵赛德斯有限公司 | Methods for detecting cancer-associated cell populations, screening for metastatic cancer and treating same |
CN113429472A (en) * | 2020-05-22 | 2021-09-24 | 百奥赛图(北京)医药科技股份有限公司 | Non-human animal humanized by CD94 and NKG2A genes and preparation method and application thereof |
US20220334122A1 (en) * | 2021-04-09 | 2022-10-20 | Cytogen, Inc. | Method for treating cancer using immune checkpoint inhibitor |
-
2022
- 2022-12-14 CN CN202211610754.XA patent/CN116356018B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20190314445A1 (en) * | 2018-03-16 | 2019-10-17 | Deutsches Rheuma-Forschungszentrum Berlin | Activation and expansion of nkg2c+ nk cells |
CN112639137A (en) * | 2018-07-02 | 2021-04-09 | 茵赛德斯有限公司 | Methods for detecting cancer-associated cell populations, screening for metastatic cancer and treating same |
CN110575537A (en) * | 2019-09-06 | 2019-12-17 | 刘慧宁 | Composition of DC vaccine and NKG2A antagonist and application of composition in resisting breast cancer or liver cancer |
CN113429472A (en) * | 2020-05-22 | 2021-09-24 | 百奥赛图(北京)医药科技股份有限公司 | Non-human animal humanized by CD94 and NKG2A genes and preparation method and application thereof |
US20220334122A1 (en) * | 2021-04-09 | 2022-10-20 | Cytogen, Inc. | Method for treating cancer using immune checkpoint inhibitor |
Non-Patent Citations (5)
Title |
---|
MARIE DENIS MUSQUER等: "High-Density of FcγRIIIA+ (CD16+) Tumor-Associated Neutrophils in Metastases Improves the Therapeutic Response of Cetuximab in Metastatic Colorectal Cancer Patients, Independently of the HLA-E/CD94-NKG2A Axis", FRONTIERS IN ONCOLOGY, vol. 11, pages 84478 * |
PASCALE ANDRE等: "Anti-NKG2A mAb Is a Checkpoint Inhibitor that Promotes Anti-tumor Immunity by Unleashing Both T and NK Cells", CELL, vol. 175, pages 1732 * |
XUEWEN DENG等: "Harnessing NK Cells to Control Metastasis", VACCINES, vol. 10, pages 2018 * |
张思汗等: "肿瘤免疫治疗药物的开发现状及展望", 临床与病理杂志, vol. 41, no. 10, pages 2447 - 2460 * |
曹朔文等: "基于HLA-E功能特点的肿瘤免疫治疗新策略", 中国肿瘤生物治疗杂志, vol. 29, no. 5, pages 383 - 390 * |
Also Published As
Publication number | Publication date |
---|---|
CN116356018B (en) | 2024-05-17 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Liu et al. | Immune checkpoint HLA-E: CD94-NKG2A mediates evasion of circulating tumor cells from NK cell surveillance | |
Zhang et al. | Single‐cell RNA sequencing in cancer research | |
Leader et al. | Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification | |
CN108753817A (en) | The enhanced cell for enhancing the method for the anti-cancer ability of cell and being obtained using this method | |
Giannini et al. | Immune profiling of thyroid carcinomas suggests the existence of two major phenotypes: an ATC-like and a PDTC-like | |
Zhang et al. | Single-cell RNA-seq analysis reveals microenvironmental infiltration of plasma cells and hepatocytic prognostic markers in HCC with cirrhosis | |
Alvisi et al. | Multimodal single-cell profiling of intrahepatic cholangiocarcinoma defines hyperactivated Tregs as a potential therapeutic target | |
Ruf et al. | Tumor-associated macrophages trigger MAIT cell dysfunction at the HCC invasive margin | |
Cheng et al. | Systematic pan-cancer analysis of KLRB1 with prognostic value and immunological activity across human tumors | |
Zhang et al. | Single-cell RNA sequencing in lung cancer: revealing phenotype shaping of stromal cells in the microenvironment | |
CN115427585A (en) | Method for identifying functional disease-specific regulatory T cells | |
Wei et al. | Integrative analysis of biomarkers through machine learning identifies stemness features in colorectal cancer | |
Pullikuth et al. | Bulk and single-cell profiling of breast tumors identifies TREM-1 as a dominant immune suppressive marker associated with poor outcomes | |
Zhou et al. | Single-cell CRISPR screens in vivo map T cell fate regulomes in cancer | |
Liu et al. | Discovery of core gene families associated with liver metastasis in colorectal cancer and regulatory roles in tumor cell immune infiltration | |
Ida et al. | Tissue-resident memory T cells correlate with the inflammatory tumor microenvironment and improved prognosis in head and neck squamous cell carcinoma | |
Shiao et al. | Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer | |
Wu et al. | Advances in immunotyping of colorectal cancer | |
CN112274643A (en) | Application of RBPJ as drug target in preparation of drugs for inhibiting T cell exhaustion | |
CN116356018B (en) | Circulating tumor cell immune check point and application thereof in inhibiting tumor metastasis | |
Beebe et al. | Defining the molecular landscape of cancer-associated stroma in cutaneous squamous cell carcinoma | |
Huang et al. | Sirpα on tumor-associated myeloid cells restrains antitumor immunity in colorectal cancer independent of its interaction with CD47 | |
WO2023154549A1 (en) | Urothelial tumor microenvironment (tme) types | |
He et al. | Cell differentiation trajectory in liver cirrhosis predicts hepatocellular carcinoma prognosis and reveals potential biomarkers for progression of liver cirrhosis to hepatocellular carcinoma | |
Li et al. | Integrated single-cell transcriptome analysis of the tumor ecosystems underlying cervical cancer metastasis |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant |