Composition for predicting and evaluating efficacy of cancer treatment and detection method

Abstract

The present invention relates to a composition for predicting and evaluating the efficacy of cancer treatment and a detection method. The content of a specific subtype of immune cells in peripheral blood, peripheral immune organs or tumor tissue of a patient who has been treated with a treatment method under test is detected, so as to predict or evaluate the efficacy of the treatment method. The following specific steps are comprised: first performing separation to obtain immune cells in peripheral blood, peripheral immune organs or tumor tissue, then co-incubating the obtained immune cells with nanoparticles and / or microparticles loaded with tumor whole-cell antigens for a period of time and using a method such as flow cytometry, chemiluminescence or a magnetic bead method to detect the content of T cell subtypes and / or B cell subtypes containing specific cell markers in the obtained immune cells. Whether a certain cancer treatment method is effective can be determined on the basis of the content of T cell subtypes and / or B cell subtypes containing specific cell markers.

Description

Composition and detection method for predicting and evaluating efficacy of cancer treatment TECHNICAL FIELD

[0001] The present application relates to the field of immunoassay, in particular to a composition and detection method for predicting and evaluating efficacy of cancer treatment. BACKGROUND

[0002] Cancer immunotherapy or radiotherapy is only effective for a part of cancer patients, if the patients who can effectively respond to the treatment can be predicted or evaluated, the resources can be saved and the treatment plan can be timely increased or replaced. Immune cells refer to cells involved in or related to immune response, including innate lymphocytes, various phagocytes and lymphocytes capable of recognizing antigens and producing specific immune response, such as T cells, B cells, NK cells, DC cells, macrophages, granulocytes and mast cells. T cells are the main force of the body to recognize and kill cancer cells, and B cells can assist the activation and recognition of T cells.

[0003] In the prior art, when evaluating the effect of immunotherapy, the content of immune cells (especially CD4+T and CD8+T cells) in the body after treatment is detected, and it is considered that the higher the content is, the better the effect of immunotherapy is. However, in fact, it is not accurate to simply judge according to the number of immune cells. After the treatment of cancer patients, the content and proportion of various immune cells in the body will change, but it is not particularly clear which subtype content increase is conducive to cancer immunotherapy and which subtype content decrease is conducive to cancer immunotherapy, and there is no report on the evaluation of the efficacy of the treatment method.

[0004] SUMMARY

[0005] The present application aims to provide a biomarker for predicting or evaluating the efficacy of cancer immunotherapy and a detection technology thereof, which predicts or evaluates the efficacy of the treatment method by detecting the content of specific B cell and / or T cell subtypes in immune cells in the peripheral blood, peripheral immune organs or tumor tissues of patients after treatment. Specifically, the following steps are included: first, immune cells in the peripheral blood, peripheral immune organs or tumor tissues are isolated, then the obtained immune cells are co-incubated with nanoparticles and / or microparticles loaded with tumor whole cell antigens for a period of time, and the content of T cell subtypes and / or B cell subtypes containing specific cell markers in the obtained immune cells is detected by flow cytometry, chemiluminescence method or magnetic bead method. According to the content of T cell subtypes and / or B cell subtypes containing specific cell markers, it can be judged whether a certain cancer immunotherapy method is effective.

[0006] The cell markers described herein include, but are not limited to, CD22, CTLA4, CD55, RAMP3, Nr4A3, DUSP10, PDE4d, Ciita, CXCR5, CD72, CD38, S100A2, S100A3, S100A8, S100A9, S100A4, S100A5, S100A6, S100A7, S100A10, Eif2ak3, various granzymes, Ikzf2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra (CD25), NGP, CXCL2, IL1b, KLRK1, itgax, fgl2, CCL3, GZMK, FASL, KLRC1, KLRA7, KLRA1, KLRE1, RETnLG, Lyz2, LCN2, Ltf, Chil3, Mki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4,DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8, EMB, PLCXD2, RNF19A, DBF4, PJA1, RAMP3, TIPRL, SATB1, EIF2AK3, BLK, POU2af1, MEF2C, BMP2K, SNX30, FCRLA, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, LITAF, FCRL1, H2-Oa, SWAp70, PXDC1, Pold4, SNN, CXCR5, zfp318, ICOS, LKZF2, RORA, TNFRSF4, CISH, CD72, CD24a, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, FCRL1, GGA2, H2-Oa, BLK, SNN, PAX5, Ly6D, SCD1, PML, ZFP38, PJA1, TECPR, GALNT6, EXT1, GM20186, camk2d, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1, or one or more of the proteins encoded thereby.

[0007] Use of a composition for detecting biomarkers in the manufacture of a product for predicting or evaluating the therapeutic effect of a treatment method on a tumor patient, said product predicting or evaluating the therapeutic effect of a treatment method on a tumor patient by detecting the content of specific B cell subtypes and / or T cell subtypes in immune cells in peripheral blood, peripheral immune organs or tumor tissues of healthy individuals or before treatment, and the content of specific B cell subtypes and / or T cell subtypes in immune cells in peripheral blood, peripheral immune organs or tumor tissues after at least one treatment,

[0008] The composition contains: (a) a sample to be tested, (b) stimulating particles for activating biomarkers in the sample to be tested, and (c) reagents necessary for detecting biomarkers in the method;

[0009] The biomarkers include: (I) biomarkers for identifying B cells and / or T cells, and (II) biomarkers for evaluating therapeutic effect;

[0010] The sample to be tested is a blood sample, which is obtained from a body treated by the treatment method;

[0011] The stimulating particles are nanoparticles or microparticles loaded with tumor whole cell antigens,

[0012] The product is used for detecting the content of specific B cell subtypes and / or T cell subtypes containing the biomarkers for evaluating therapeutic effect,

[0013] In the present application, "pass" means "predicting or evaluating that the treatment method has a good therapeutic effect on a tumor patient", and "fail" means "predicting or evaluating that the treatment method has a poor therapeutic effect on a tumor patient".

[0014] In the present application, the biomarkers for identifying B cells and / or T cells include, but are not limited to, CD3, CD4, CD8, CD19, B220, etc.

[0015] The biomarker and the detection technology thereof are used to judge the standard of the cancer treatment method, wherein the B cell proportion of one or more of S100A8, S100A9, RETnLG, Lyz2, CXCL2, CAMK2D, NGP, Ltf, Chil3, IL1b, LCN2 or the protein encoded thereby in the body with better treatment effect is not significantly increased compared with that before treatment (the "not significantly" mentioned in the present application refers to p>0.05 compared with two groups), or the B cell proportion of one or more of S100A8, S100A9, RETnLG, Lyz2, CXCL2, CAMK2D, NGP, Ltf, Chil3, IL1b, LCN2 or the protein encoded thereby in the body with poor treatment effect is significantly increased compared with that of a healthy individual (the "significantly" mentioned in the present application refers to p<0.05 compared with two groups); the B cell proportion of one or more of DUSP10, FCRL1, H2-Oa, SWAP70, Ciita, PXDC1, POLD4, SNN, CXCR5, ZFP318, Eif2ak3, BLK, POU2af1, MEF2C, BMP2K, SNX30, FCRLA, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, CD22, LITAF or the protein encoded thereby in the body with better treatment effect is not significantly decreased compared with that before treatment (the "not significantly" mentioned in the present application refers to p>0.05 compared with two groups), or the B cell proportion of one or more of DUSP10, FCRL1, H2-Oa, SWAP70, Ciita, PXDC1, POLD4, SNN, CXCR5, ZFP318, Eif2ak3, BLK, POU2af1, MEF2C, BMP2K, SNX30, FCRLA, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, CD22, LITAF or the protein encoded thereby in the body with poor treatment effect is significantly decreased compared with that of a healthy individual (the "significantly" mentioned in the present application refers to p<0.05 compared with two groups).

[0016] The method has good treatment effect on the body expressing CD22, CTLA4, CD55, RAMP3, Nr4A3, DUSP10, PDE4d, Ciita, CXCR5, CD72, CD38, S100A2, S100A3, S100A8, S100A9, S100A4, S100A5, S100A6, S100A7, S100A10, granzyme A (GZMA), granzyme B (GZMB), granzyme C (GZMC), granzyme D (GZMD), granzyme E (GZME), granzyme F (GZMF), granzyme G (GZMG), granzyme G (GZMG), granzyme H (GZMH), granzyme I (GZMI), granzyme J (GZMJ), granzyme K (GZMK), granzyme L (GZML), granzyme M (GZMM), Ikzf2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra (CD25), NGP, CXCL2, IL1b, KLRK1, itgax, fgl2, CCL3, GZMK, FASL, KLRC1, KLRA7, KLRA1, KLRE1, RETnLG, Lyz2, LCN2, Ltf, Chil3, Mki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1,an elevated or reduced T cell proportion of one or more of CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8, EMB, PLCXD2, RNF19A, DBF4, PJA1, TIPRL, SATB1, EIF2AK3, BLK, POU2af1, MEF2C, BMP2K, SNX30, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, LITAF, FCRL1, PXDC1, Pold4, SNN, zfp318, ICOS, LKZF2, RORA, TNFRSF4, CISH, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, GGA2, H2-Oa, PAX5, Ly6D, SCD1, PML, ZFP38, TECPR, GALNT6, EXT1, GM20186, camk2d, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1, or one or more of the proteins encoded thereby.

[0017] The biomarker and its detection technology according to the present application, the standard for judging the effective treatment method of cancer is that the CD3 of one or more of PDE4D, DUSP10, EMB, endoplasmic reticulum stress kinase PERK (EIF2AK3), NR4A3, RAMP3, PLCXD2, RNF19A, DBF4, PJA1, RAMP3, TIPRL, SATB1, CD79b, CD22, CD24a, CD55 (decay-accelerating factor, DAF), CD72, CD38, Cilt a, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, FCRL1, GGA2, H2-Oa, BLK, SNN, PAX5, Ly6D, SCD1, PML, ZFP38, PJA1, TECPR, GALNT6, EXT1 (exostosin glycosyltransferase 1), GM20186, CXCR5 or one or more proteins encoded by the same are expressed in the body with better treatment effect + The proportion of T cells is not significantly reduced compared with before treatment (the "not significantly" mentioned in the present application means p>0.05 compared between two groups), or the CD3 of one or more of PDE4D, DUSP10, EMB, endoplasmic reticulum stress kinase PERK (EIF2AK3), NR4A3, RAMP3, PLCXD2, RNF19A, DBF4, PJA1, RAMP3, TIPRL, SATB1, CD79b, CD22, CD24a, CD55 (decay-accelerating factor, DAF), CD72, CD38, Cilt a, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, FCRL1, GGA2, H2-Oa, BLK, SNN, PAX5, Ly6D, SCD1, PML, ZFP38, PJA1, TECPR, GALNT6, EXT1 (exostosin glycosyltransferase 1), GM20186, CXCR5 or one or more proteins encoded by the same are expressed in the body with poor treatment effect + The proportion of T cells is significantly reduced compared with healthy individuals (the "significantly" mentioned in the present application means p<0.05 compared between two groups). The CD3 of one or more of S100A8, S100A9, RETnLG, Lyz2, Camk2d, CXCL2, NGP, Ltf, Chil3, IL1b, LCN2 or one or more proteins encoded by the same are expressed in the body with better treatment effect+ T cell proportion is not significantly increased compared to before treatment (the "not significantly" referred to in the present application means p>0.05 compared between two groups), or the CD3 + T cell proportion is significantly increased compared to healthy individuals (the "significantly" referred to in the present application means p<0.05 compared between two groups).

[0018] The biomarker and the detection technology thereof described in the present application, the standard for judging the effectiveness of the cancer treatment method is: in the body with better treatment effect, one or more of S100A4, S100A8, S100A9, Ikzf2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra, CTLA4, IL2Rb, CD44, FOXP3, CCR2, S100A6, S100A11, S100A13, CXCR5, CXCR6 or one or more of the proteins encoded thereby is expressed + T cell proportion is not significantly increased compared to before treatment (the "not significantly" referred to in the present application means p>0.05 compared between two groups), or the CD4 + T cell proportion is significantly increased compared to healthy individuals (the "significantly" referred to in the present application means p<0.05 compared between two groups); in the body with better treatment effect, one or more of EMB, RAMP3, PLCXD2, RNF19A, DBF4, PJA1, TIPRL, SATB1, IFNGr2, DUSP10, eif2ak3, PDE4d, Nr4a3 or one or more of the proteins encoded thereby is expressed + T cell proportion is not significantly decreased compared to before treatment (the "not significantly" referred to in the present application means p>0.05 compared between two groups), or the CD4+ The proportion of T cells was significantly lower compared to healthy individuals (the "significant" referred to in the present invention means p<0.05 compared between the two groups).

[0019] The biomarker and its detection technology described in the application, the biomarker judges the standard of effective cancer treatment method: the body with better treatment effect expresses GZMA, GZMB, S100A4, KLRG1, CXCR3, CX3CR1, S1PR5, IL2Ra, KLRK1, itgax, fgl2, S100A8, S100A9, CCL3, GZMK, FASL, KLRC1, Ki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM,CD8 for one or more of CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8, CTLA4, Myb, EOMES, PTMS, SLAMF7, ITGB1, GZMK, CCL5, CTLA2a, CCR5, CD44 or one or more of the proteins encoded thereby +T cell proportions were not significantly increased (as referred to herein "not significantly" means p>0.05) compared to pre-treatment, or in bodies with poor treatment efficacy, expression of GZMA, GZMB, S100A4, KLRG1, CXCR3, CX3CR1, S1PR5, IL2Ra, KLRK1, itgax, fgl2, S100A8, S100A9, CCL3, GZMK, FASL, KLRC1, Ki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI,CD8 of one or more of PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8, CTLA4, Myb, EOMES, PTMS, SLAMF7, ITGB1, GZMK, CCL5, CTLA2a, CCR5, CD44 or one or more of the proteins encoded thereby, + The proportion of T cells is significantly higher than that of healthy individuals (the "significantly" mentioned in the present application means p<0.05 compared between the two groups); or the CD8 of one or more of DUSP10, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1 expressed in the body with better treatment effect + The proportion of T cells is not significantly lower than that before treatment (the "not significantly" mentioned in the present application means p>0.05 compared between the two groups), or the CD8 of one or more of DUSP10, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1 expressed in the body with poor treatment effect + The proportion of T cells is significantly lower than that of healthy individuals (the "significantly" mentioned in the present application means p<0.05 compared between the two groups).

[0020] The T cells mentioned in the present application are CD3 + T cells, CD3 + CD8 + T cells, CD3 + CD4 + Any one of T cells or a combination thereof.

[0021] The biomarkers and detection techniques mentioned in the present application can be used to detect the content of T cell subtypes and / or B cell subtypes containing biomarkers in the immune cells obtained from the peripheral blood, peripheral immune organs or tumor tissues.

[0022] The nano / microparticles loaded with whole cell antigens are incubated with antigen presenting cells alone, or the nano / microparticles are incubated with antigen presenting cells and T cells at the same time, and the concentration of the nano / microparticles is 2.5 ng / mL to 50 mg / mL; the incubation time is 1-168 hours, preferably 24-72 hours.

[0023] The biomarker machine detection technology described in the present application can obtain immune cells from peripheral blood, peripheral immune organs or tumor tissues, and then detect the obtained mixed immune cells containing antigen presenting cells and T cells after co-incubation with nanoparticles / microparticles loaded with tumor tissue antigen components for 24-72 hours, or the nanoparticles and / or microparticles loaded with tumor whole cell antigens can be first co-incubated with antigen presenting cells to activate the antigen presenting cells, and then the activated antigen presenting cells are co-incubated with T cells to activate the T cells; after the nanoparticles and / or microparticles loaded with tumor whole cell antigens are first co-incubated with antigen presenting cells to activate the antigen presenting cells, the antigen presenting cells can be co-incubated with T cells without special treatment, or the antigen presenting cells can be co-incubated with T cells after being treated by fixation, irradiation, illumination, modification, inactivation, mineralization, etc.

[0024] The immune cells of peripheral blood or peripheral immune system obtained by separation in the present application are from the same individual or allogeneic, and the sample body has undergone at least one treatment of radiotherapy, immunotherapy, chemotherapy, particle therapy and vaccine therapy during the separation and extraction of the above-mentioned cells.

[0025] The various types of T cells described in the present application can be used alone or in combination as needed.

[0026] The number ratio of the antigen presenting cells to T cells described in the present application is greater than 0.1:1; the nanoparticles or microparticles loaded with tumor tissue or cancer cell whole cell antigens are selected from nanoparticles with a particle size of 1 nm-1000 nm or microparticles with a particle size of 1 μm-1000 μm.

[0027] In the preferred technical solution of the present application, the antigen presenting cells co-incubated with T cells and nanoparticles and / or microparticles are derived from autologous, allogeneic, cell lines, stem cells or any mixture thereof; the co-incubated antigen presenting cells are B cells, dendritic cells, macrophages or any mixture of the three.

[0028] In the preferred technical solution of the present application, the antigen presenting cells are derived from autologous antigen presenting cells, allogeneic antigen presenting cells, antigen presenting cell lines or antigen presenting cells differentiated from stem cells, and are preferably any one or a combination of dendritic cells (DC), B cells and macrophages; more preferably, more than one combination of antigen presenting cells is used.

[0029] In the preferred technical solution of the present application, the cell concentration of T cells during detection or co-incubation is (0.01-100) × 10 7 / ml, preferably (0.05-5) × 10 7(0.01-100)×10 7 cells / ml, preferably (0.05-5)×10 7 cells / ml.

[0030] The biomarker and detection technology thereof according to the present application are characterized in that the tumor whole cell antigen is a cell lysate component of tumor tissue and / or cancer cells, comprising one or both of water-soluble components and non-water-soluble components generated after cell lysis of tumor tissue and / or cancer cells, and the water-soluble components and non-water-soluble components are collected separately and prepared into nano or microparticles, and the non-water-soluble components are dissolved using a dissolution solution containing a dissolving agent; or a dissolution solution containing a dissolving agent can be directly used to lyse cancer cells or tumor tissue and dissolve the whole cell components and prepare nano or microparticles, and the non-water-soluble components are dissolved by the dissolution solution containing a dissolving agent.

[0031] When the antigen component according to the present application is a tumor tissue / cancer cell whole cell lysate component, the preparation method is: (1) first lyse the cancer cells / tumor tissue, then prepare water-soluble components and non-water-soluble components separately, and then dissolve the non-water-soluble components using a specific dissolution solution containing a dissolving agent; (2) lyse the cells using a dissolution solution containing a dissolving agent, and then dissolve the whole cell components after lysis using a dissolution solution containing a dissolving agent.

[0032] The preparation method of the nano / microparticles loaded with whole cell antigens in the present application can refer to the preparation methods in the submitted inventions ZL202010223563.2, ZL202011146241.9, 202310600906.6, 202310814634X, 202311600143.1, 202311600664.7.

[0033] The tumor whole cell antigen according to the present application is obtained by whole cell lysis of one or more cancer cells and / or tumor tissues, or is obtained by processing after whole cell lysis of one or more cancer cells and / or tumor tissues, or is obtained by lysis after processing of one or more cancer cells and / or tumor tissues, preferably at least one of the cancer cells or tumor tissues is the same as the target disease type; or the antigen component is composed of a part of components in one or more cancer cells and / or tumor tissues, and the part of components contains protein / polypeptide components and / or mRNA components in the lysis solution;

[0034] The biomarker and detection technology thereof are characterized in that, when the tumor whole cell antigen is part of the whole cell lysis component containing tumor tissue and / or cancer cells, the preparation method is: (1) first prepare the lysis solution of tumor tissue / cancer cells, then prepare the water-soluble component and the non-water-soluble component respectively, then dissolve the non-water-soluble component using a specific dissolution solution containing a dissolving agent, then use it, then separate and extract the protein and polypeptide components in the water-soluble component using an appropriate method, then use the separated and extracted protein and polypeptide components in the water-soluble component together with all the non-water-soluble components as the antigen component; (2) first prepare the lysis solution of tumor tissue / cancer cells, then prepare the water-soluble component and the non-water-soluble component respectively, then dissolve the non-water-soluble component using a specific dissolution solution containing a dissolving agent, then use it, then separate and extract the protein and polypeptide components in the water-soluble component using an appropriate method, then use the separated and extracted protein and polypeptide components in the non-water-soluble component together with all the water-soluble components as the antigen component; (3) first prepare the lysis solution of tumor tissue / cancer cells, then prepare the water-soluble component and the non-water-soluble component respectively, then dissolve the non-water-soluble component using a specific dissolution solution containing a dissolving agent, then use it, then separate and extract the protein and polypeptide components in the water-soluble component and the non-water-soluble component using an appropriate method respectively, then use the separated and extracted protein and polypeptide components in the water-soluble component and the non-water-soluble component together as the antigen component; (4) or the cell or tissue can also be directly lysed using a dissolution solution containing a dissolving agent to dissolve the whole cell component, then the protein / polypeptide component is prepared by an appropriate method and used as the antigen component. The above preparation method can also add the step of separating and extracting whole cell mRNA, and the whole cell mRNA is used as part of the antigen component. The appropriate treatment method includes but is not limited to salting-out, heating and enzymatic hydrolysis, etc. The non-water-soluble component or the precipitate produced after salting-out, heating and enzymatic hydrolysis, etc. is dissolved using a dissolution solution containing a dissolving agent.

[0035] The whole cell antigen component contains the protein and polypeptide components and / or mRNA components in the whole cell lysis component.

[0036] The tumor whole cell antigen of the present application is obtained by lysing one or more cancer cells and / or tumor tissues, or by processing one or more cancer cells and / or tumor tissues after lysis, or by processing one or more cancer cells and / or tumor tissues after lysis, preferably at least one of the cancer cells or tumor tissues is the same as the target disease type; or the antigen component is composed of one or more cancer cells and / or tumor tissues, and a part of the components contains protein / polypeptide components and / or mRNA components in the lysis solution.

[0037] The antigen component of the present application can be: (1) a cancer cell / tumor tissue whole cell lysate component; (2) or a part of the whole cell component containing protein and polypeptide components in the cancer cell / tumor tissue whole cell lysate component; (3) or protein and polypeptide components in the cancer cell / tumor tissue whole cell component plus mRNA components.

[0038] In the preferred technical solution of the present application, the tumor whole cell antigen is a cell lysate component of tumor tissue and / or cancer cells, containing one or both of the water-soluble components and the water-insoluble components produced after lysis of the tumor tissue and / or cancer cells, and the water-soluble components and the water-insoluble components are collected separately and prepared into nano or microparticles; or a solubilizing solution containing a solubilizing agent can be used to directly lyse the cancer cells or tumor tissues and dissolve the whole cell components and prepare nano or microparticles, and the water-insoluble components are dissolved by a dissolving solution containing a dissolving agent. Or it can also be the protein and polypeptide components obtained after appropriate treatment of the above lysis solution components, or the protein and polypeptide components plus mRNA components.

[0039] The preparation method of the antigen component in the whole cell lysate component (containing protein and polypeptide components in the whole cell component of cancer cells) is as follows: (1) the cancer cells / tumor tissues are first lysed, and then water-soluble components and non-water-soluble components are prepared respectively, the non-water-soluble components are dissolved using a specific dissolution solution containing a dissolving agent, and then the protein and polypeptide components in the water-soluble components are separated and extracted using a suitable method, and then the separated and extracted protein and polypeptide components in the water-soluble components are used together with all the non-water-soluble components as the antigen component; (2) the cancer cells / tumor tissues are first lysed, and then water-soluble components and non-water-soluble components are prepared respectively, the non-water-soluble components are dissolved using a specific dissolution solution containing a dissolving agent, and then the protein and polypeptide components in the water-soluble components are separated and extracted using a suitable method, and then the separated and extracted protein and polypeptide components in the non-water-soluble components are used together with all the water-soluble components as the antigen component; (3) the cancer cells / tumor tissues are first lysed, and then water-soluble components and non-water-soluble components are prepared respectively, the non-water-soluble components are dissolved using a specific dissolution solution containing a dissolving agent, and then the protein and polypeptide components in the water-soluble components and the non-water-soluble components are separated and extracted using a suitable method respectively, and then the separated and extracted protein and polypeptide components in the water-soluble components and the non-water-soluble components are used together as the antigen component; (4) the cells are lysed using a dissolution solution containing a dissolving agent, and then the lysed whole cell components are dissolved using a dissolution solution containing a dissolving agent, and then the protein and polypeptide components are separated and extracted using a suitable method. In the above preparation methods, a step of separating and extracting whole cell mRNA can also be added, and the whole cell mRNA is used as part of the antigen component.

[0040] The suitable method for separating and extracting the protein and polypeptide components includes but is not limited to salting-out, heating, and enzymatic hydrolysis. After the separation and extraction of the protein and polypeptide components, the components are re-dissolved in a dissolution solution containing a dissolving agent.

[0041] The whole cell component in the present application can be prepared into nanoparticles or microparticles after being inactivated or denatured, solidified, biomineralized, ionized, chemically modified, and treated with a nuclease before or after lysis, or can be directly prepared without any inactivation or denaturation, solidification, biomineralization, ionization, chemical modification, and nuclease treatment before or after lysis.

[0042] In the preferred technical solution of the present application, the tumor tissue cells are inactivated or denatured before lysis, or can be inactivated or denatured after lysis, or can be inactivated or denatured before and after lysis.

[0043] The inactivation or denaturation treatment method of the cells before or (and) after lysis includes any one or combination of ultraviolet irradiation, high temperature heating, radiation irradiation, high pressure, solidification, biomineralization, ionization, chemical modification, nuclease treatment, collagenase treatment, freeze-drying.

[0044] The mixed co-incubation of the application is selected from any one of the following three ways: (a) direct mixing of the three for a certain period of time; (b) co-incubation of microparticles and / or nanoparticles with antigen-presenting cells for a period of time, and then adding T cells for co-incubation; (c) co-incubation of microparticles and / or nanoparticles with antigen-presenting cells for a period of time, and then sorting out the incubated antigen-presenting cells and co-incubating the antigen-presenting cells with T cells.

[0045] Before the cells are co-incubated with nanoparticles / microparticles and antigen-presenting cells, the T cells can be separately rested for a period of time, or appropriately sorted; or before the T cells are co-incubated with the activated antigen-presenting cells, the T cells can be separately rested for a period of time, or appropriately sorted.

[0046] In the preferred technical solution of the application, the culture conditions of the mixed co-incubation are co-incubation at 30-38℃, 1-10% CO2 for 1-168h.

[0047] In the preferred technical solution of the application, the nanoparticles and / or microparticles for activating cancer-specific T cells can co-load one and / or multiple components of tumor tissues and / or cancer cells together with immunoadjuvants on the nanoparticles or microparticles.

[0048] In the preferred technical solution of the application, both the water-soluble part and the non-water-soluble part can be dissolved in a solubilizing aqueous solution containing a solubilizing agent or an organic solvent. The solubilizing agent is at least one of the solubilizing agents that can increase the solubility of proteins or polypeptides in an aqueous solution; the organic solvent is an organic solvent that can dissolve proteins or polypeptides.

[0049] In the preferred technical solution of the application, the original non-water-soluble part is changed from insoluble in pure water to soluble in an aqueous solution containing a solubilizing agent / dissolving agent or an organic solvent by using an appropriate solubilization method; the solubilizing agent / dissolving agent used is selected from one or more of the following: a compound containing the structure of structural formula 1, a deoxycholate, a dodecyl sulfate, glycerol, a protein-degrading enzyme, albumin, lecithin, a polypeptide, an amino acid, a glycoside, and choline; wherein the structural formula 1 is as follows:

[0050] R1 is C, N, S, or O, and R2-R5 are independently selected from at least one of hydrogen, alkyl, amino, carboxyl, and substituted or unsubstituted guanidino.

[0051] The compound containing structural formula 1 includes, but is not limited to, metformin hydrochloride, metformin sulfate, metformin sulfonate, metformin salt, metformin, polyhexamethylene guanidine hydrochloride, guanidylbutylamine sulfate, methylguanidine hydrochloride, tetramethylguanidine hydrochloride, urea, guanidine hydrochloride, guanidine sulfate, guanidine sulfonate, guanidine salt, other guanidine group or urea containing compounds, guanidine carbonate, arginine, guanidyl acetic acid, guanidyl phosphoric acid, guanidine sulfamic acid, guanidyl succinic acid, aminourea hydrochloride, carbamoyl urea, acetyl urea, sulfonyl urea compounds (glibenclamide, gliclazide, gliquidone, glimepiride, etc.), thiourea compounds (sulfonylureas, imidazoles, etc.), nitrosoureas containing structural formula 1 compounds.

[0052] In the preferred technical solution of the present application, the cell components loaded on the nanoparticles or microparticles are derived from one or more cancer cells and / or one or more tumor tissue whole cells, and the non-water-soluble components are loaded on the delivery particles, so that the nanoparticles or microparticles contain more antigens, and more preferably, the water-soluble components and the non-water-soluble components are simultaneously loaded on the delivery particles, so that the delivery particles are loaded with whole cell component antigens.

[0053] In the preferred technical solution of the present application, the preparation material of the nanoparticles and / or microparticles is an organic synthetic polymer material, a natural polymer material, or an inorganic material.

[0054] In the preferred technical solution of the present application, the organic synthetic polymer material is a biocompatible or biodegradable polymer material, including any one of PLGA, PLA, PGA, PLGA-PEG, PLA-PEG, PGA-PEG, PEG, PCL, Poloxamer, PVA, PVP, PEI, PTMC, polyanhydride, PDON, PPDO, PMMA, synthetic amino acid, synthetic polypeptide, synthetic lipid, or a combination thereof.

[0055] In the preferred technical solution of the present application, the natural polymer material is a biocompatible or biodegradable polymer material, including any one of lecithin, cholesterol, sodium alginate, albumin, collagen, gelatin, cell membrane components, starch, sugar, polypeptide, or a combination thereof.

[0056] In the preferred technical solution of the present application, the inorganic material is a material with no obvious biological toxicity, including but not limited to diiron trioxide, ferric oxide, calcium carbonate, calcium phosphate, etc.

[0057] The biomarker and its detection technology of the present application, after the biomarker on the cell surface or inside of T cell and / or B cell is labeled by a specific signal probe, the content of T cell and / or B cell labeled by the signal probe is detected by flow cytometry, mass spectrometry flow, mass spectrometry, magnetic bead method and other methods, the signal probe is combined with antibody or other chemical molecules that can combine with the biomarker; the signal probe includes but is not limited to fluorescence, phosphorescence, radioactive substance, isotope, chemiluminescence substance, chromogenic substance, DNA sequencing technology, RNA sequencing technology, single cell sequencing technology and the like.

[0058] The method for detecting the biomarker of the present application includes but is not limited to any one or combination of flow cytometry, mass spectrometry flow, magnetic bead method, chemiluminescence method, substrate precipitation method. One biomarker inside T cell and / or B cell can be detected or more than one different marker combination can be detected at the same time.

[0059] The biomarker and its detection technology of the present application, the tumor is selected from solid tumor, blood tumor and lymphoma. Including but not limited to lung cancer, ovarian cancer, colon cancer, rectal cancer, melanoma, kidney cancer, bladder cancer, breast cancer, liver cancer, lymphoma, malignant blood tumor such as leukemia, brain tumor, head and neck cancer, glioma, gastric cancer, nasopharyngeal carcinoma, laryngeal carcinoma, cervical carcinoma, uterine body tumor, osteosarcoma, bone cancer, pancreatic cancer, skin cancer, prostate cancer, uterine cancer, anal cancer, testicular cancer, fallopian tube cancer, endometrial cancer, vaginal cancer, vulva cancer, Hodgkin's disease, non-Hodgkin's lymphoma, esophageal cancer, small intestine cancer, endocrine system cancer, thyroid cancer, parathyroid cancer, adrenal cancer, soft tissue sarcoma, urethral cancer, penile cancer, chronic or acute leukemia, pediatric solid tumor, lymphocytic lymphoma, bladder cancer, kidney or ureter cancer, renal pelvis cancer, central nervous system (CNS) tumor, primary CNS lymphoma, tumor angiogenesis, spinal tumor, brain stem neuroglioma, pituitary adenoma, Kaposi's sarcoma, epidermoid carcinoma, squamous cell carcinoma, T cell lymphoma, environment-induced cancer, metastatic cancer, circulating tumor cell.

[0060] Compared with the prior art, the present application has the following beneficial technical effects:

[0061] 1. The biomarker of the present application is obviously contrasted in the treatment of cured body and the treatment of uncured body, and can effectively distinguish individuals who have response to treatment and individuals who have no response to treatment after treatment.

[0062] 2. The biomarker and its detection method of the present application can predict or evaluate the therapeutic effect.

[0063] 3. The biomarker and its detection method of the present application have the advantages of simple operation, controllable quality and suitability for industrialized detection. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 is the subpopulation distribution of each subpopulation after the primary clustering analysis of single cell sequencing;

[0065] Figure 2 is the content of different subpopulation cells in each group of peripheral blood;

[0066] Figure 3 is the content of different subpopulation cells in each group of spleen cells;

[0067] Figure 4 is the CD8 + T cell subpopulation distribution after the secondary subclustering analysis of T cells;

[0068] Figure 5 is the CD4 + T cell subpopulation distribution after the secondary subclustering analysis of T cells;

[0069] Figure 6 is the content of CD8 + T cell subpopulation cells in each group of peripheral blood samples;

[0070] Figure 7 is the content of CD8 + T cell subpopulation cells in each group of spleen cell samples;

[0071] Figure 8 is the content of CD4 + T cell subpopulation cells in each group of peripheral blood samples;

[0072] Figure 9 is the content of CD4 + T cell subpopulation cells in each group of spleen cell samples;

[0073] Figure 10 is the result of detecting T cell biomarkers in cured mice and uncured mice after immunotherapy in Example 2 using flow cytometry;

[0074] Figure 11 is the result of detecting T cell biomarkers in cured mice and uncured mice after immunotherapy in Example 3 using flow cytometry;

[0075] Figure 12 is the result of detecting T cell and B cell biomarkers in cured mice and uncured mice after radiotherapy in Example 4 using flow cytometry;

[0076] Figure 13 is the result of verifying the peripheral blood markers of non-small cell lung cancer patients for predicting the effect of combined treatment of chemotherapy and radiotherapy in Example 5. DETAILED DESCRIPTION

[0077] The present application will be further described below in conjunction with the drawings and specific examples, so that those skilled in the art can better understand the present application and implement it. The examples are not intended to limit the present application.

[0078] The materials and preparation methods involved in the present application are as follows:

[0079] If the nanoparticles / microparticles loaded with whole cell antigens are co-incubated with immune cells containing T cells in the present application, the preparation method of the nanoparticles / microparticles loaded with whole cell antigens refers to the preparation methods in the submitted inventions ZL202010223563.2, ZL202011146241.9, 202310600906.6, 202310814634X, 202311600143.1, 202311600664.7.

[0080] Example 1 The cured and uncured groups of tumor-bearing mice after immunotherapy have different T cell and B cell biomarkers

[0081] (1) Preparation of antigen component and nanoparticles

[0082] In this example, mice melanoma is used as a cancer model to obtain cured and uncured mice after cancer immunotherapy. After lysing B16F10 melanoma tumor tissue, 8M urea is used for solubilization to obtain solubilized whole cell lysate component, then organic polymer material PLGA (30-36KDa) is used as nanoparticle scaffold material, Polyinosinic-polycytidylic acid (poly(I:C)), CpG2395 and CpG1018 are used as immunoadjuvants, and solvent evaporation method is used to prepare nanoparticles loaded with tumor tissue whole cell antigens, then the nanoparticles are used to treat melanoma mice.

[0083] Specifically:

[0084] Each C57BL / 6 mouse was subcutaneously inoculated with 1.5×10 5 B16F10 cells on the back, and the mice were sacrificed and the tumor tissue was removed when the tumor volume reached about 1000mm 3 After the tumor tissue was cut and ground, a tumor tissue single cell suspension (containing cancer cells) was prepared by passing through a cell filter. Then, an appropriate amount of pure water was added to the tumor tissue single cell suspension and repeated freeze-thawing was performed 5 times, which can be accompanied by ultrasonic treatment to destroy the lysed cells. After cell lysis, the lysate was centrifuged at 12000RPM for 10 minutes, and the supernatant was obtained as the water-soluble component; 8M urea aqueous solution was added to the obtained precipitate to dissolve the non-water-soluble component that was not dissolved in pure water, so that it can be converted to be soluble in 8M urea aqueous solution. The above is the antigen component for preparing nanoparticles.

[0085] The nanoparticles in this example were prepared by the double emulsion method in solvent evaporation method. The molecular weight of the PLGA used in the preparation of the nanoparticles was 30-36 KDa. The immunoadjuvants used were poly (I:C), CpG 2395 and CpG 1018. The preparation method was as previously described. During the preparation process, the antigen component and the adjuvant were first loaded into the nanoparticles using the double emulsion method, then 100 mg of the nanoparticles were centrifuged at 12,000 g for 30 minutes, resuspended in 10 mL of ultrapure water containing 4% trehalose, and freeze-dried for 48 h. The average particle size of the nanoparticles was about 280 nm, and each 1 mg of the PLGA nanoparticles loaded about 200 μg of the protein or polypeptide component.

[0086] (2) Treatment of cancer using nanoparticles loaded with whole cell antigens

[0087] Six to eight-week-old female C57BL / 6 mice were selected as model mice to prepare melanoma tumor-bearing mice. On day 0, 1.5 x 10 5 B16F10 cells were subcutaneously inoculated on the right lower back of each recipient mouse, and on day 3, day 6, day 9, day 14, day 19 and day 25, 2 mg of nanoparticles loaded with whole cell antigens or PBS were subcutaneously injected into each mouse. The size of the tumor volume of the mice was recorded every 3 days from day 0, and whether the tumor-bearing mice recovered after treatment with the nanoparticles was recorded. The tumor growth rate of the PBS control group mice was the fastest, and the survival period of the mice was very short. About half of the tumor-bearing mice recovered after immunotherapy. The mice that recovered and did not recover after immunotherapy were used for subsequent experiments, respectively.

[0088] (3) Preparation of mouse spleen cell single cell suspension and peripheral blood mononuclear cells (PBMC)

[0089] The C57BL / 6 mice in each group were sacrificed after treatment or a certain period of recovery, and the spleens of 4 mice in each group (C57BL / 6 healthy mice, 21-day-killed tumor-bearing mice treated with PBS, 30-day-killed tumor-bearing mice treated with immunotherapy but not recovered after treatment, 30-day-killed tumor-bearing mice recovered after immunotherapy, 4-month-killed tumor-bearing mice recovered 3 months after immunotherapy, and 8-month-killed tumor-bearing mice recovered more than 6 months after immunotherapy) were collected, respectively. Then the spleens were cut into small pieces and prepared into spleen cell single cell suspensions by passing through a 70 μm cell filter. The mice recovered 3 months and more than 6 months after treatment were injected with 2 mg of nanoparticles to stimulate and activate the corresponding immune cells 3 days before being sacrificed.

[0090] C57BL / 6 mice in each group were sacrificed 21 days after inoculation of cancer cells or a certain time after treatment recovery, and fresh blood was collected from 4 mice in each group (C57BL / 6 healthy mice, 21-day-killed tumor mice treated with PBS, 30-day-killed tumor mice treated with immunotherapy but not recovered after treatment, 30-day-killed tumor mice treated with immunotherapy and just recovered, 4-month-killed tumor mice treated with immunotherapy and recovered for 3 months, 8-month-killed tumor mice treated with immunotherapy and recovered for more than 6 months). Fresh blood samples were collected in EDTA anticoagulant tubes and immediately subjected to peripheral blood mononuclear cell (PBMC) isolation using standard density gradient centrifugation. After washing with PBS containing 0.04% BSA, the cell particles were resuspended in PBS containing 0.04% bovine serum albumin and refiltered through a 35-μm cell filter. The isolated single cells were then stained with Calcein-AM (Thermo Fisher Scientific) and Draq7 (BD Biosciences) for viability assessment.

[0091] (4) Single-cell RNA sequencing

[0092] The BD Rhapsody system was used to capture the transcriptome information of single cells. Single-cell capture was achieved by randomly distributing single-cell suspensions in >200,000 microwells through a limited dilution method. Oligonucleotide barcode-containing beads were added to saturation, allowing the beads to pair with the cells in the microwells. The cells were lysed in the microwells, and the messenger ribonucleic acid molecules were hybridized to the barcode capture oligos on the beads. The beads were collected into a single tube for cDNA synthesis and library construction. Gene expression libraries and V(D)J libraries were prepared using the Whole Transcript Analysis Amplification Kit and the TCR / BCR Amplification Kit, respectively. The libraries were analyzed using a High Sensitivity DNA chip (Agilent) and a Qubit High Sensitivity DNA assay (Thermo Fisher Scientific), and then sequenced using a Novaseq6000 (Illumina, San Diego, CA).

[0093] (5) Single-cell RNA statistical analysis

[0094] The scRNA-seq data analysis was performed by NovelBio-Bio-Pharm Technology Co., Ltd. using the NovelBrain cloud analysis platform. BD Rhapsody TMThe sequence analysis pipeline was applied to single-cell transcriptome analysis and V(D)J analysis together with mouse genome mm10 (Ensembl 100). Cells containing more than 200 expressed genes and cells with mitochondrial UMI rates lower than 20% were filtered by cell quality and mitochondrial genes were removed in the expression table. Seurat package (version: 4.0.3, https: / / satijalab.org / seurat / ) was used for cell normalization and regression. PCA was constructed based on the quantification table with the top 2000 high variable genes, and the top 10 principal components were used for tSNE construction and UMAP construction. With the graph-based clustering method (resolution = 0.8), we obtained the cell clustering results based on the PCA top 10 principle, and used the wilcox rank sum test algorithm to calculate the marker genes through the FindAllMarkers function, and the standards for calculation were as follows: 1, Log2FC > 0.25; 2, p value < 0.05; 3, minimum pressure > 0.1. In order to identify the cell types in detail, the clusters of the same cell types were selected for sub-clustering analysis.

[0095] (6) Preliminary clustering analysis results

[0096] The preliminary clustering analysis results (Figure 1) show that there are 28 cell subgroups in the PBMC and spleen cell single cell suspensions, among which: 0 subgroup, 1 subgroup, 3 subgroup, 4 subgroup, 8 subgroup, 11 subgroup, 13 subgroup, 23 subgroup and 25 subgroup are B cell subgroups; 2 subgroup, 5 subgroup, 6 subgroup, 7 subgroup, 9 subgroup, 10 subgroup, 15 subgroup, 17 subgroup and 21 subgroup are T cell subgroups; 12 subgroup is a proliferating T / B cell subgroup; 14 subgroup, 16 subgroup, 18 subgroup, 19 subgroup, 20 subgroup, 22 subgroup, 24 subgroup, 26 subgroup and 27 subgroup are other cell subgroups. Figure 2 and Figure 3 respectively list the cell contents of different subgroups in each group of mice in PBMC and spleen cells. By comparing the healthy mouse group, the PBS treatment group, the cured group after using the vaccine (just cured, cured for a period of time and cured for a very long time) and the group using the vaccine but not cured, it can be found that: the contents of 2 subgroup, 3 subgroup, 4 subgroup, 8 subgroup, 10 subgroup, 17 subgroup in the cured group and the healthy mice are obviously higher than those in the uncured group; the cell contents of 11 subgroup, 13 subgroup, 15 subgroup and 21 subgroup in the uncured group are obviously higher than those in the cured group after treatment and the healthy mouse group. Therefore, the characteristic cell markers unique to 2 subgroup, 3 subgroup, 4 subgroup, 8 subgroup, 10 subgroup, 17 subgroup, 11 subgroup, 13 subgroup, 15 subgroup and 21 subgroup can be used as markers to distinguish the cured group and the uncured group. Through analysis of the single cell sequencing preliminary subgrouping result data, it can be known that the cell markers unique to 2 subgroup (T cell) are PDE4D, DUSP10, EMB, endoplasmic reticulum stress kinase PERK (EIF2AK3), NR4A3, RAMP3, PLCXD2, RNF19A, DBF4, PJA1, RAMP3, TIPRL, SATB1. The main characteristic markers of 3 subgroup are: endoplasmic reticulum stress kinase PERK (EIF2AK3), BLK, POU2afl, MEF2C, BMP2K, SNX30, FCRLA, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, CD22 (3, 4, 8 and 17 subgroups are unique) and LITAF. The main characteristic markers of 8 subgroup (B cell) are: CD22, CD79b, FCRL1, H2-Oa, SWAp70, CiiTa (8 and 17 subgroups are unique), PXDC1, Pold4, SNN, CXCR5 (8 and 17 subgroups are unique) and zfp318. The unique FOXP3, ICOS, IL2RA (CD25), CTLA4, LKZF2, RORA, TNFRSF4, CISH in 10 subgroup T cell.17 CD79b, CD22, CD24a, CD55 (decay-accelerating factor, DAF), CD72, CD38, CllTa, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, FCRL1, GGA2, H2-Oa, BLK, SNN, PAX5, Ly6D, SCD1, PML, ZFP38, PJA1, TECPR, GALNT6, EXT1, EXT1 (exostosin glycosyltransferase 1), GM20186, CXCR5. S100A8, S100A9, RETnLG, Lyz2, Camk2d are the characteristic markers of 11, 13, 15 and 21 subgroups. CXCL2 is the marker specific to 11 and 15 subgroups. NGP, Ltf, Chil3 are the markers specific to 13 and 21 subgroups. IL1b is the marker specific to 11, 13 and 15 subgroups. LCN2 is the marker specific to 13, 15 and 21 subgroups. According to the results shown in Figures 2 and 3, the above-mentioned genes and the proteins encoded thereby can be used as biomarkers for evaluating the therapeutic effect after treatment.

[0097] (7) T cell sub-cluster analysis results

[0098] Further sub-cluster analysis of all T cells can be performed by first classifying T cells into CD8 + T cells and CD4 + T cells, and then performing further sub-cluster analysis on CD8 + T cells and CD4 + T cells, respectively. Ten CD8 + T cell subgroups (Figure 4) and 11 CD4 + T cell subgroups (Figure 5) can be obtained.

[0099] Further analysis of the 10 CD8 + T cell subgroups in peripheral blood and spleen cell single-cell suspensions shows that in peripheral blood (Figure 6), the contents of 0, 1, 2, 4, 5 and 7 subgroups increase in healthy and cured mice; the contents of 8 and 9 subgroups significantly increase in uncured mice. In spleen cells (Figure 7), the contents of 0, 1, 2, 4 and 6 subgroups increase in healthy and cured mice; the contents of 8 and 9 subgroups significantly increase in uncured mice. Therefore, the above-mentioned subgroups in peripheral blood PBMC and spleen cells can be used to evaluate the therapeutic effect. The contents of 8 CD8 +The characteristic markers of T cells mainly include S100A4, KLRG1, CX3CR1, S1PR5, KLRK1, itgax, fgl2, S100A8, S100A9, CCL3, KLRC1.9 subgroup CD8 +Characteristic markers of T cells are: Ki67, CDCA8, CDK1, UHRF1, CX3CR1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8.8 and 9 subgroups CD8 +T cell specific: KLRA7, KLRA1, KLRE1, Myb, EOMES, PTMS, SLAMF7, ITGB1, CCL5, CTLA2a, CCR5, CD44. Subgroups 7 and 9 contain CTLA4, Myb (subgroups 7 and 9 contain). Subgroup 5 CD8 + The characteristic markers of T cells are: EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1. According to the results shown in Figures 6 and 7, the above-listed genes and the proteins encoded thereby can be used as biomarkers for distinguishing the therapeutic efficacy after treatment.

[0100] The 11 CD4 + Further analysis of T cell subgroups in peripheral blood and spleen cell single cell suspensions found that in peripheral blood (Figure 8), the contents of 0 subgroup, 1 subgroup, 3 subgroup and 4 subgroup in healthy group and cured group mice increased, and almost no 10 subgroup; in uncured group, the contents of 2 subgroup, 5 subgroup, 6 subgroup, 7 subgroup, 9 subgroup and 10 subgroup increased significantly. In peripheral immune cell spleen cells, the contents of 0 subgroup, 1 subgroup, 2 subgroup, 3 subgroup, 4 subgroup and 6 subgroup in healthy group and cured group mice increased; in uncured group, the contents of 5 subgroup, 7 subgroup, 8 subgroup, 9 subgroup and 10 subgroup increased significantly. 10 subgroup CD4 + T cell markers: Ki67, TOP2a, PCLAF, BIRC5, CCNA2, UBE2C, RRM2, CENPF, CENPE, TPX2, NUSAP1, KIF11, CCNB2. Subgroups 5, 8, 9, 10 CD4 + T cell markers: lkzf2, CTLA4, IL2rb, CD44, ICOS, IL2ra, FOXP3. Subgroups 7, 9 and 10 CD4 + T cell markers: CXCR3, CCR2. Subgroups 7, 8, 9, 10 CD4 + T cell markers: S100A4, S100A6, S100A11, S100A13, CXCR3. Subgroups 7 and 10 CD4 + T cell markers: CXCR6. Subgroups 8 and 10 CD4 + T cell markers: CXCR5. Subgroups 0, 1, 2, 3, 4, 6 CD4 +Markers of T cells: IFNGr2, DUSP10, eif2ak3, PDE4d, Nr4a3. According to the results shown in FIG. 8 and FIG. 9, the above-listed genes and the proteins encoded thereby can all be used as biomarkers for distinguishing the therapeutic efficacy of the treatment.

[0101] Example 2: Detection of T cell biomarkers in cured and uncured mice after immunotherapy using flow cytometry

[0102] (1) Treatment of cancer with aPDl antibody

[0103] Six to eight-week-old female C57BL / 6 mice were selected as model mice to prepare lung cancer tumor-bearing mice. On day 0, each recipient mouse was subcutaneously inoculated with 1.5 x 10 6 LLC lung cancer cells on the right lower back, and on day 7, day 10, day 13, day 16, and day 19, each mouse was intraperitoneally injected with aPDl antibody (10 mg / kg) and carboplatin (20 mg / kg), respectively. The size of the tumor volume of the mice was recorded every 3 days from day 0, and whether the tumor-bearing mice were cured after treatment with aPDl antibody + carboplatin was recorded. The tumor growth rate of the PBS control group mice was the fastest. About 20% of the tumor-bearing mice were cured after immunotherapy. The cured and uncured mice after immunotherapy described above were used for subsequent experiments, respectively.

[0104] (2) Preparation of mouse peripheral blood mononuclear cells (PBMCs)

[0105] On day 21 after tumor inoculation, C57BL / 6 mice in each group were sacrificed, and fresh blood was collected from each group of mice (C57BL / 6 healthy mice, tumor-bearing PBS-treated control mice, tumor-bearing mice treated with immunotherapy but not cured after treatment, and tumor-bearing mice cured after immunotherapy). The fresh blood samples were collected in heparin sodium anticoagulant tubes and immediately separated using standard density gradient centrifugation to isolate PBMCs from the blood.

[0106] (3) Preparation of nanoparticles loaded with whole cell antigens

[0107] First, LLC lung cancer tumor tissue was collected from mice, and then the LLC tumor tissue was lysed using an 8M aqueous urea solution, and the lysed product was dissolved using 8M urea to obtain a tumor tissue whole cell lysate after solubilization. The tumor tissue whole cell lysate described above was loaded into PLGA nanoparticles using a double emulsion method, thereby obtaining nanoparticles loaded with whole cell antigens. The nanoparticles had a particle size of 250 nm, a surface charge of -18 mV, and a protein / polypeptide loading capacity of 0.05 mg / mg PLGA.

[0108] (4) Detection of specific T cell subsets in mouse PBMCs after nanoparticle stimulation using flow cytometry

[0109] PBMCs from each group of mice were incubated with a certain amount of lung cancer cell whole cell antigen-loaded nanoparticles (0.8 mg / mL) in DMEM complete medium for 48 hours (37°C, 5% CO2), and the cell concentration during co-incubation was 1.0 x 10 6 PBMCs were incubated alone in DMEM complete medium for 48 hours (37°C, 5% CO2), and the cell concentration during co-incubation was 1.0 x 10 6 Then, BrefeldinA Solution (BFA) (1000x diluted into cell culture medium) was added to the culture medium, and co-incubation was performed for 4 hours. After collecting the suspended cells in the culture medium using a pipette, the sample cells were centrifuged at 400-500 g for 5 minutes, and the supernatant was discarded after collecting the cells. After collecting the cells, the sample cells were resuspended in 1 mL of PBS. Then, the cells were labeled with Zombie dyes and Fc block, and then labeled with various flow cytometry antibodies for extracellular markers and intracellular markers. The cells were directly co-incubated with the corresponding antibodies with fluorescent probes using flow cytometry antibodies for extracellular markers. When using flow cytometry antibodies to label intracellular markers, the cells were first fixed with paraformaldehyde for more than 40 minutes, then co-acted with a membrane-breaking agent for a certain period of time, and then labeled with the corresponding antibodies modified with fluorescent probes for intracellular markers. After labeling with various flow cytometry antibodies, the cells were detected using a flow cytometer (FACS Aria TMIII, BD), and the content of T cells or B cells positive for the corresponding cell markers was analyzed using Flowjo software. One panel was used, and the proteins corresponding to the flow cytometry antibodies in the panel were as follows: CD3, CD4, CD8, CXCR3, and IKZF2.

[0110] (5) Experimental results

[0111] As shown in Figure 10, the healthy mice without nano-particle stimulation control (Healthy (No NP stimulating)), the PBS group without nano-particle stimulation control (PBS (No NP stimulating)), the group of not cured after immunotherapy and without nano-particle stimulation (Not cured (No NP stimulating)), the group of cured after immunotherapy and without nano-particle stimulation (Cured (No NP stimulating)), the healthy mice with nano-particle stimulation (Healthy (NP stimulated)), the PBS group with nano-particle stimulation (PBS (NP stimulated)), the group of cured after immunotherapy and with nano-particle stimulation (Cured (NP stimulated)) were compared in terms of the content of CXCR3 in CD4 T cells + In CD4 T cells + T cells and the content of IKZF2 in CD4 T cells + In CD4 T cells + T cells and the content of IKZF2 in CD4 T cells + In CD4 T cells + T cells and the content of IKZF2 in CD4 T cells + In CD4 T cells + T cells were significantly increased. It is proved that the detection of the above indexes after the stimulation of nano-particles loaded with whole cell antigens can be used to evaluate the efficacy of immunotherapy.

[0112] Example 3 Detection of T cell biomarkers in cured and not cured mice after immunotherapy by flow cytometry

[0113] (1) αPD1 antibody treatment of cancer

[0114] 6-8 week old female C57BL / 6 mice were selected as model mice to prepare breast cancer tumor-bearing mice. On day 0, 1.0 x 10 6 EO771 breast cancer cells were subcutaneously inoculated into the right lower back of each recipient mouse, and 200 μg of αPD1 antibody was intraperitoneally injected into each mouse on days 5, 7, 9, 11, 13, 15, 17 and 19. The size of the tumor volume of the mice was recorded every 3 days from day 0, and whether the tumor-bearing mice were cured after αPD1 antibody treatment was recorded. The tumor growth rate of the PBS control group of mice was the fastest. About 10% of the tumor-bearing mice were cured after immunotherapy. The cured and not cured mice after immunotherapy were used for subsequent experiments.

[0115] (2) Preparation of mouse PBMC

[0116] C57BL / 6 mice in each group were sacrificed on day 21 after tumor inoculation, and fresh blood was collected from each group of mice (C57BL / 6 healthy mice, tumor-bearing control mice treated with PBS, tumor-bearing mice treated with immunotherapy but not recovered after treatment, and tumor-bearing mice treated with immunotherapy and just recovered). The fresh blood samples were collected in heparin sodium anticoagulation tubes and immediately separated PBMCs from the blood using standard density gradient centrifugation.

[0117] (3) Preparation of nanoparticles loaded with whole cell antigens

[0118] First, mouse EO771 breast tumor tissue was collected, then the tumor tissue was lysed using 8M aqueous urea solution, and the lysed product was dissolved using 8M urea to obtain a tumor tissue whole cell lysate after solubilization. The tumor tissue whole cell lysate was loaded into PLGA nanoparticles using the double emulsion method, and nanoparticles loaded with whole cell antigens were obtained. The particle size of the nanoparticles was 350 nm, the surface charge was -19 mV, and the protein / polypeptide loading capacity was 1.0 mg / mg PLGA.

[0119] (4) Detection of specific T cell subtypes in mouse PBMCs using flow cytometry

[0120] A certain amount of PBMCs from each group of mice was incubated with a certain amount of nanoparticles loaded with whole cell antigens (0.8 mg / mL) in DMEM complete medium for 48 hours (37°C, 5% CO2). The cell concentration during co-incubation was 1.0 x 10 6 After that, BrefeldinA Solution (BFA) was added to the culture medium (1000x diluted into the cell culture medium), and co-incubation was performed for 4 hours. Then, the suspended cells in the culture medium were collected by pipetting, and the sample cells were centrifuged at 400-500 g for 5 minutes after collection. After discarding the supernatant, the cells were collected. After collecting the cells, the sample cells were resuspended in 1 mL of PBS. Then, the cells were labeled with Zombie dyes and Fc block, and then the cell membrane markers were labeled with various flow antibodies. After labeling with various flow antibodies, the cells were detected using a flow cytometer (FACS Aria TMIII, BD), and the content of T cells or B cells positive for the corresponding cell markers was analyzed using Flowjo software. One panel was used, and the proteins corresponding to the flow antibodies in the panel were as follows: CD3, CD4, CD8, KLRG1, IL2Ra, and CX3CR1.

[0121] (5) Experimental results

[0122] As shown in Figure 11, there was no significant difference in the content of KLRG1 in CD8 T cells, IL2Ra in CD4 T cells, and CX3CR1 in CD8 T cells among the healthy mice using nanoparticle stimulation group (Healthy (NP stimulated)), the PBS group using nanoparticle stimulation (PBS (NP stimulated)), and the group cured after immunotherapy and using nanoparticle stimulation group (Cured (NP stimulated)). + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups. + In CD8 T cells, the content of IL2Ra in CD4 T cells, and the content of CX3CR1 in CD8 T cells were significantly increased in the group not cured after immunotherapy and using nanoparticle stimulation (Not Cured (NP stimulated)) compared with the above groups.

[0123] Example 4: Detection of T cell and B cell biomarkers in cured and uncured mice after radiotherapy using flow cytometry

[0124] (1) Radiotherapy of cancer

[0125] Female C57BL / 6 mice of 6-8 weeks were selected as model mice to prepare liver cancer tumor-bearing mice. On day 0, 1.5x10 6 Hepa1-6 liver cancer cells were inoculated subcutaneously on the right lower back of each recipient mouse, and each mouse in the radiotherapy group was given a radiation dose of 7 Gy on days 7, 10, 13, 16, and 19. The size of the tumor volume of the mice was recorded every 3 days from day 0, and whether the tumor-bearing mice were cured after radiotherapy was recorded. The tumor growth rate of the PBS control group mice was the fastest, and the mouse survival time was very short. About 10% of the tumor-bearing mice were cured after immunotherapy. The above cured and uncured mice after immunotherapy were used for subsequent experiments.

[0126] (2) Preparation of mouse PBMC

[0127] C57BL / 6 mice in each group were sacrificed on day 21 after tumor inoculation, and fresh blood was collected from each group of mice (C57BL / 6 healthy mice, tumor-bearing mice treated with PBS, tumor-bearing mice treated but not recovered after treatment, and tumor-bearing mice just recovered after treatment), respectively. The fresh blood samples were collected in heparin sodium anticoagulation tubes and immediately subjected to peripheral blood mononuclear cell (PBMC) isolation using standard density gradient centrifugation.

[0128] (3) Preparation of nanoparticles loaded with whole cell antigens

[0129] First, mouse Hepa1-6 hepatoma tumor tissues were collected, and then the tumor tissues were lysed using an 8M aqueous urea solution, and the lysed products were dissolved using 8M urea to obtain a tumor tissue whole cell lysate after solubilization. The tumor tissue whole cell lysate was loaded into PLGA nanoparticles using a multiple emulsion method, i.e., nanoparticles loaded with whole cell antigens were obtained. The particle size of the nanoparticles was 300 nm, the surface charge was -20 mV, and the protein / polypeptide loading capacity was 0.5 mg / mg PLGA.

[0130] (4) Detection of specific T cell subtypes in mouse PBMC using flow cytometry

[0131] An amount of PBMC from each group of mice was incubated with an amount of nanoparticles loaded with hepatoma cell whole cell antigens in DMEM complete medium for 36 hours (37°C, 5% CO2). The cell concentration during co-incubation was 2x10 6cells / mL, nanoparticle concentration is 0.6 mg / mL. Then, Brefeldin A Solution (BFA) (1000x dilution to cell culture medium) is added to the culture medium, and co-incubation is performed for 4 hours. Then, the suspended cells in the culture medium are collected by pipette blowing, and after the cells are collected, the sample cells are centrifuged at 400-500 g for 5 minutes, and the supernatant is discarded to collect the cells. After the cells are collected, the sample cells are resuspended in 1 mL of PBS. Then, the cells are labeled with Zombie dyes, Fc block, and then labeled with various flow antibodies for extracellular markers and intracellular markers in sequence. The cells are directly co-incubated with the corresponding antibodies with fluorescent probes using flow antibody extracellular markers. When using flow antibodies to label intracellular markers, the cells are first fixed with paraformaldehyde for more than 40 minutes, then co-acted with a membrane breaker for a certain period of time, and then labeled with the corresponding antibodies modified by fluorescent probes for intracellular markers. After labeling with various flow antibodies, the cells are detected by flow cytometry (FACS Aria TMIII, BD), and then the content of T cells positive for the corresponding cell markers is analyzed by Flowjo software. One panel is used, and the flow antibodies in the panel bind to the following proteins, respectively: (1) CD3, CD4, CD8, S1PR5, DUSP10, EIF2AK3.

[0132] (5) Experimental results

[0133] As shown in FIG. 12, the healthy mouse using nanoparticle stimulation group (Healthy (NP stimulated)), and the cured mouse using nanoparticle stimulation group (Cured (NP stimulated)) after immunotherapy have no significant difference in the content of S1PR5 + in CD8 + T cells, the content of DUSP10 + in B cells, and the content of EIF2AK3 + in B cells. Compared with the above groups, the not cured mouse using nanoparticle stimulation group (Not Cured (NP stimulated)) after immunotherapy has a significant increase in the content of S1PR5 + in CD8 + T cells, a significant decrease in the content of DUSP10 + in B cells, and a significant decrease in the content of EIF2AK3 + in B cells. Compared with the healthy group, the PBS group using nanoparticle stimulation (PBS (NP stimulated)) has a significant increase in the content of EIF2AK3 +Significant decrease in the content in B cells, and no significant difference in other cells. It is proved that the detection of the above markers after stimulation using nanoparticles loaded with whole cell antigens can be used to evaluate the efficacy of immunotherapy.

[0134] Example 5 Verification experiment of peripheral blood markers of non-small cell lung cancer patients for predicting the effect of chemotherapy combined with immunotherapy

[0135] (1) Treatment effect of non-small cell lung cancer patients

[0136] Two non-small cell lung cancer patients were selected respectively, both were male and had a history of smoking, and both had undergone PD-1 antibody immunotherapy combined with platinum chemotherapy. Among them, patient A had good treatment effect and was cured (Responder) after treatment, while patient B had poor treatment effect and progressed very quickly (Non-responder) after treatment.

[0137] (2) Preparation of nanoparticles

[0138] The following lung cancer cell lines were cultured respectively and then mixed according to the cell number ratio of 1:1: A549, H1299, H1650, PC9, H226, H520, and SK-MES-1. Then, the mixed cell lines were lysed using an 8M aqueous urea solution, and the lysed products were dissolved using an 8M urea solution to obtain the mixed cell lysate after solubilization. The mixed cell lysate was loaded into PLGA nanoparticles using a double emulsion method, and the nanoparticles loaded with whole cell antigens were obtained. The particle size of the nanoparticles was 200 nm, the surface charge was -19 mV, and the protein / polypeptide loading capacity was 0.3 mg / mg PLGA.

[0139] (3) Preparation of PBMC

[0140] Before immunotherapy and on the 42nd day after starting immunotherapy, 5 mL of peripheral blood was collected from each of the two lung cancer patients (collected in a heparin sodium anticoagulation tube), and PBMC was isolated and extracted from each sample using density gradient centrifugation.

[0141] (4) Detection of specific T cells and B cells in PBMC of lung cancer patients using flow cytometry

[0142] A certain amount of PBMC was incubated with a certain amount of nanoparticles loaded with whole cell antigens of lung cancer cells in DMEM complete culture medium for 36 hours (37°C, 5% CO2). The cell concentration during co-incubation was 1x10 6cells / mL, nanoparticle concentration is 0.75 mg / mL. Then, Brefeldin A Solution (BFA) (1000x dilution into cell culture medium) is added into the culture medium, and co-incubation is performed for 4 hours. Then, the suspended cells in the culture medium are collected by pipette blowing, and after the cells are collected, the sample cells are centrifuged at 400-500 g for 5 minutes, and the supernatant is discarded to collect the cells. After the cells are collected, the sample cells are resuspended in 1 mL of PBS. Then, the cells are labeled with Zombie dyes, Fc block, and then labeled with various flow antibodies for extracellular membrane markers and intracellular cell markers in sequence. The cells are directly co-incubated with corresponding antibodies with fluorescent probes using flow antibody membrane markers. When using flow antibodies to label intracellular markers, the cells are first fixed with paraformaldehyde for more than 40 minutes, then co-acted with a membrane breaker for a certain period of time, and then labeled with corresponding antibodies modified by fluorescent probes for intracellular markers. After labeling with various flow antibodies, the cells are detected by flow cytometry (FACS Aria TMIII, BD), and then the content of T cells with positive corresponding cell markers is analyzed by Flowjo software. Two panels are used, and the flow antibodies of the first panel are combined with the following proteins: (1) CD3, CD4, CD8, KLRG1, CXCR3; and the flow antibodies of the second panel are combined with the following proteins: CD3, CD4, CD8, CD9, CX3CR1, S100A8.

[0143] (5) Test results

[0144] As shown in FIG. 13, the sample of Responder prior-therapy (NP stimulated) of patient A with good treatment effect and the sample of Responder prior-therapy (NP stimulated) of patient A after treatment have no significant difference in the content of CX3CR1 + in CD8 + T cells; and the sample of Non-responder prior-therapy (NP stimulated) of patient B with poor treatment effect and the sample of Non-responder post-therapy (NP stimulated) of patient B after treatment have no significant difference in the content of CX3CR1 + in CD8 +CD8 T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + T cells / CD4 + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In CD8 + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In CD4 + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + T cells / CD4 + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In CD8 + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In CD4 + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In + T cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In B cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells. + In B cells. Non-responder prior-therapy (NP stimulated) and Non-responder post-therapy (NP stimulated) showed a significant increase in the percentage of CD8 T cells / CD4 T cells and a significant increase in the percentage of KLRG1 T cells.

[0145] In some embodiments, the immune cells after immunotherapy are directly detected; in some embodiments, the nanoparticles / microparticles are co-incubated with immune cells containing antigen-presenting cells and / or T cells, and then the detection of relevant cell markers is performed. In practical applications, whether to use nanoparticles / microparticles to co-incubate with the immune cells to be detected can be selected as needed.

[0146] Due to the limited length, only several cell markers such as CD22, A100A8, DUSP10, EIF2AK3, granzyme B, S100A4, IKZF2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra in T cells or B cells are listed and used as the markers of T cell subtype or B cell subtype to evaluate the therapeutic efficacy in the embodiments of the present application, and any other cell markers that can be used to distinguish the T cell subtype and / or B cell subtype for evaluating the therapeutic efficacy can be used in actual application, and the molecules of the cell markers that can be used to distinguish the therapeutic efficacy include but are not limited to: CD22, CTLA4, CD55, RAMP3, Nr4A3, DUSP10, PDE4d, Ciita, CXCR5, CXCR3, CD72, CD38, S100A2, S100A3, S100A8, S100A9, S100A4, S100A5, S100A6, S100A7, S100A10, Eif2ak3, granzyme A (GZMA), granzyme B (GZMB), granzyme C (GZMC), granzyme D (GZMD), granzyme E (GZME), granzyme F (GZMF), granzyme G (GZMG), granzyme G (GZMG), granzyme H (GZMH), granzyme I (GZMI), granzyme J (GZMJ), granzyme K (GZMK), granzyme L (GZML), granzyme M (GZMM), Ikzf2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra, NGP, CXCL2, IL1b, KLRK1, itgax, fgl2, CCL3, GZMK, FASL, KLRC1, KLRA7, KLRA1, KLRE1, RETnLG, Lyz2, LCN2, Ltf, Chil3, Mki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a,PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8, EMB, PLCXD2, RNF19A, DBF4, PJA1, RAMP3, TIPRL, SATB1, EIF2AK3, BLK, POU2af1, MEF2C, BMP2K, SNX30, FCRLA, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, LITAF, FCRL1, H2-Oa, SWAp70, PXDC1, Pold4, SNN, CXCR5, zfp318, ICOS, IL2RA (CD25), LKZF2, RORA, TNFRSF4, CISH, CD72, CD24a, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, FCRL1, GGA2, H2-Oa, BLK, SNN, PAX5, Ly6D, SCD1, PML, ZFP38, PJA1, TECPR, GALNT6, EXT1, GM20186, camk2d, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1,Any one or any combination of LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1, etc., or one or more proteins expressed by the above genes. Any one of the above can represent a T cell / B cell marker or a component of more than one cell marker is also within the scope of the present application.

[0147] In the embodiments of the present application, flow cytometry, single cell sequencing are used to detect cell biomarkers. In practical applications, mass spectrometry flow, magnetic bead method, mass spectrometry, magnetic bead method, chemiluminescence method, enzyme-linked immunospot method, enzyme-linked immunosorbent assay method, substrate precipitation method, DNA sequencing technology, RNA sequencing technology, etc. Any other method that can quantitatively detect and analyze the listed biomarkers can be used. Using any of the above methods to detect cell markers, the method of analyzing cell subtype content and predicting and evaluating the efficacy of treatment of the specific cell markers described in the present application is also within the scope of the present application.

[0148] Obviously, the above embodiments are only examples for the sake of clarity, and are not limiting. For those skilled in the art, other different forms of changes or variations can be made on the basis of the above description. Here, it is not necessary and impossible to exhaust all the embodiments. The obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. Use of a composition for detecting a biomarker in the manufacture of a product for predicting or assessing the efficacy of a therapeutic method on a patient with a tumor, characterized in that, The product predicts or evaluates the therapeutic effect by detecting the content of specific B cell subtype and / or T cell subtype in immune cells in peripheral blood, peripheral immune organs or tumor tissues of healthy individuals or before treatment, and the content of specific B cell subtype and / or T cell subtype in immune cells in peripheral blood, peripheral immune organs or tumor tissues after treatment at least once, The composition contains: (a) a sample to be tested, (b) stimulating particles for activating biomarkers in the sample to be tested, (c) reagents necessary for detecting biomarkers in the method; The biomarkers include: (I) biomarkers for identifying B cells and / or T cells, (II) biomarkers for evaluating therapeutic effect; The sample to be tested is a blood sample, which is obtained from the body after treatment by the treatment method; The stimulating particles are nano-particles or micro-particles loaded with tumor whole cell antigens, The product is used to detect the content of specific B cell subtype and / or T cell subtype containing the biomarkers for evaluating therapeutic effect, The specific B cell subtype and / or T cell subtype for evaluating therapeutic effect are: (1) one or more of S100A8, S100A9, RETnLG, Lyz2, CXCL2, CAMK2D, NGP, Ltf, Chil3, IL1b, LCN2 or the proteins encoded thereby expressed in B cells, (2) one or more of DUSP10, FCRL1, H2-Oa, SWAP70, Ciita, PXDC1, POLD4, SNN, CXCR5, ZFP318, Eif2ak3, BLK, POU2af1, MEF2C, BMP2K, SNX30, FCRLA, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, CD22, LITAF or the proteins encoded thereby expressed in B cells, (3) CD22, CTLA4, CD55, RAMP3, Nr4A3, DUSP10, PDE4d, Ciita, CXCR5, CD72, CD38, S100A2, S100A3, S100A8, S100A9, S100A4, S100A5, S100A6, S100A7, S100A10, Granzyme A, Granzyme B, Granzyme C, Granzyme D, Granzyme E, Granzyme F, Granzyme G, Granzyme G, Granzyme H, Granzyme I, Granzyme J, Granzyme K, Granzyme L, Granzyme M, Ikzf2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra, NGP, CXCL2, IL1b, KLRK1, itgax, fgl2, CCL3, GZMK, FASL, KLRC1, KLRA7, KLRA1, KLRE1, RETnLG, Lyz2, LCN2, Ltf, Chil3, Mki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5,CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, one or more of PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa, RBBp8, EMB, PLCXD2, RNF19A, DBF4, PJA1, TIPRL, SATB1, EIF2AK3, BLK, POU2afl, MEF2C, BMP2K, SNX30, DMXL1, TNFRSF1, FCMR, LGHD, FCER2A, H2-DMB2, CD79b, CD24a, MS4A1, LITAF, FCRL1, PXDC1, Pold4, SNN, zfp318, ICOS, LKZF2, RORA, TNFRSF4, CISH, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, GGA2, H2-Oa, PAX5, Ly6D, SCD1, PML, ZFP38, TECPR, GALNT6, EXT1, GM20186, camk2d, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1, or a protein encoded thereby, wherein: a B cell containing biomarker (1) is passed if it is not higher than in the individual before treatment, and is not passed otherwise, or is passed if it is higher than in a healthy individual, and is not passed otherwise; or a B cell containing biomarker (2) is passed if it is not lower than in the individual before treatment, and is not passed otherwise, or is passed if it is lower than in a healthy individual, and is not passed otherwise; or a T cell containing biomarker (3) is passed if it is not higher or lower than in the individual before treatment or in a healthy individual, and is not passed otherwise.

2. Use according to claim 1, wherein (31) one or more of PDE4D, DUSP10, EMB, EIF2AK3, NR4A3, RAMP3, PLCXD2, RNF19A, DBF4, TIPRL, SATB1, CD79b, CD22, CD24a, CD55, CD72, CD38, CiiTa, BANK1, CR2, TNFRSF13C, SWAP70, BC11a, SPiB, FCRLA, FCRL1, GGA2, H2-Oa, BLK, SNN, PAX5, Ly6D, SCD1, PML, ZFP38, PJA1, TECPR, GALNT6, EXT1, GM20186, CXCR5, or a protein encoded thereby, is expressed in a T cell. (32) T cells expressing one or more of S100A8, S100A9, RETnLG, Lyz2, Camk2d, CXCL2, NGP, Ltf, Chil3, IL1b, LCN2, or one or more of the proteins encoded thereby, When the T cells containing the biomarker (31) are not lower than the content in the individual before treatment, then pass, otherwise fail, or when the T cells containing the biomarker (31) are lower than the content in the healthy individual, then fail, otherwise pass; or When the T cells containing the biomarker (32) are not higher than the content in the individual before treatment, then pass, otherwise fail, or when the T cells containing the biomarker (32) are higher than the content in the healthy individual, then fail, otherwise pass.

3. The use according to claim 1, wherein the tumor antigen is a tumor whole cell antigen. (33) CD4 + S100A4, S100A8, S100A9, Ikzf2, CCR2, KLRG1, CX3CR1, S1PR5, CXCR3, IL2Ra, CTLA4, IL2Rb, CD44, FOXP3, CCR2, S100A6, S100A11, S100A13, CXCR5, CXCR6, or a protein encoded thereby, expressed in a T cell, (34) CD4 + one or more of EMB, RAMP3, PLCXD2, RNF19A, DBF4, PJA1, TIPRL, SATB1, IFNGr2, DUSP10, eif2ak3, PDE4d, Nr4a3, or a protein encoded thereby, expressed in T cells, When the CD4 + T cells are not higher than the level in the individual prior to treatment, then pass, otherwise then not passed, or when the CD4 + T cells are higher than the levels in healthy individuals, then not passed, and vice versa; or When the CD4+ T cells contain the biomarker (34) at a level that is not less than the level in the individual prior to treatment, then the individual passes, otherwise the individual fails, or when the CD4+ T cells contain the biomarker (34) at a level that is less than the level in a healthy individual, then the individual fails, otherwise the individual passes. + T cells not less than the level in the individual prior to treatment, then the individual passes, otherwise the individual fails, or when the CD4+ T cells contain the biomarker (34) at a level that is less than the level in a healthy individual, then the individual fails, otherwise the individual passes. + T cells not less than 4. The use according to claim 1, wherein the tumor antigen is a tumor whole cell antigen. (35) CD8 + GZMA, GZMB, S100A4, KLRG1, CXCR3, CX3CR1, S1PR5, IL2Ra, KLRK1, itgax, fgl2, S100A8, S100A9, CCL3, GZMK, FASL, KLRC1, Ki67, CDCA8, CDK1, UHRF1, KIF11, RRM1, KIF5, CCNB2, TACC3, UBE2C, SMC2, RRM2, TPX2, NCAPD2, CKS1b, CCNA2, CENPE, NCAPG, MCM5, SPC24, CENPF, NUSAP1, TYMS, NSD2, NCAPH, MAD2L1, ASF1b, CKAP2L, MCM7, NRM, H2AX, DUT, PRC1, CBX5, HMMR, KIF23, BUB1, KNL1, CDCA3, FBXO5, CLSPN, KIF22, DLGAP5, GMNN, NDC80, MIS18NP1, NUF2, RAD51, KIF4, AURKb, TK1, PRIM1, CIT, LOCKD, CHAF1A, TFDP1, CIP2a, CDC20, NCAPG2, ARHGAP11a, PIK1, HELLS, ASPM, CEP55, CKAP2, KIF20A, RFC5, TCF19, DIAPH3, BUB1b, ESCO2, GM10282, CIP2a, CENPH, KNSTRN, ATAD5, CDCA2, DTL, POLA1, NEK2, SGO1, CENPW, MXD3, SPAG5, PSAT1, CCDC34, ORC6, SGO2a, SHCBP1, KIF2C, CDK2, RFC4, DHFR, STIL, FOXM1, CCNB1, ESPL1, PRR11, TIPIN, MCM10, PPIL1, FIGNL1, E2F8, RAD51AP1, DEPDC1a, Hirip3, RFC3, CDCA7, KIF18b, POLe, CDCa5, CENPM, CDKN2c, RCC1, CHAF1b, H1F5, CENPL, CENPN, KPNA2, ANLN, H3C3, H2aC8, KIF14, KNTC1, HMGB3, TRIP13, MELK, BARD1, ARHGAP19, SPDL1, CDC6, BRCA1, CISD1, PBDC1, BRCA2, PBK, CDKN3, GPSM2, CDC7, SKA1, RMI2, CCNF, CHEK1, CENPI, PIF1, CHTF18, PCLAF, Birc5, PLP2, EZH2, Lig1, CDK2a, CENPa,RBBp8, CTLA4, Myb, EOMES, PTMS, SLAMF7, ITGB1, GZMK, CCL5, CTLA2a, CCR5, CD44 or one or more of the proteins encoded thereby, (36) CD8 + DUSP10, EIF2AK2, DDX60, RSAD2, LFIT3b, OAS2, GBP10, OASL1, ZBP1, Gbp6, LFIT1, LFIT3, RTP4, LSG15, LIGP1, OASL2, USP18, LSG20, CMPK2, LFIH1, or one or more of the proteins encoded thereby, expressed in T cells, When the CD8+ T cells contain the biomarker (35) at a level that is not higher than the level in the individual prior to treatment, the individual passes, and otherwise fails, or when the CD8+ T cells contain the biomarker (35) at a level that is higher than the level in a healthy individual, the individual fails, and otherwise passes. + T cells not higher than the level in the individual prior to treatment, the individual passes, and otherwise fails, or when the CD8+ T cells contain the biomarker (35) at a level that is higher than the level in a healthy individual, the individual fails, and otherwise passes. + T cells not higher than the level in the individual prior to treatment, the When the CD8 + T cells contain the biomarker (36) at a level that is not less than the level in the individual prior to treatment, then the individual passes, otherwise the individual fails, or when the CD8 + T cells contain the biomarker (36) at a level that is less than the level in a healthy individual, then the individual fails, otherwise the individual passes.

5. The use according to claim 1, characterized in that, The biomarker for identifying B cells and / or T cells comprises at least one of CD3, CD4, CD8, CD19, and B220.

6. Use according to claim 1, characterized in that, The method for detecting the biomarker comprises flow cytometry, single-cell sequencing, mass cytometry, magnetic bead method, mass spectrometry, chemiluminescence method, enzyme-linked immunospot method, enzyme-linked immunosorbent assay, substrate precipitation method, DNA sequencing method, or RNA sequencing method.

7. Use according to claim 1, characterized in that, In the detection, the immune cells in the sample to be tested are separated, the immune cells are co-incubated with stimulating particles, after the incubation, the biomarker is detected, and the T cell subtype and / or B cell subtype containing the specific cell marker are quantified.

8. The use according to claim 7, wherein the tumor antigen is a tumor whole cell antigen. Preferably, the immune cells are co-incubated with the stimulating particles for 1-168 hours. Preferably, the concentration of the immune cells is (0.01-100) x 10 7 cells / ml. Preferably, the concentration of the stimulating particles is 0.01-10 mg / mL.

9. The use according to claim 1, characterized in that, The tumor whole cell antigen is a cell lysate component of tumor tissue and / or cancer cells, comprising water-soluble components and non-water-soluble components produced after cell lysis of tumor tissue and / or cancer cells; and the preparation method of the tumor whole cell antigen is: The cancer cells and / or tumor tissue are first lysed to prepare water-soluble components and non-water-soluble components, and then the non-water-soluble components are dissolved using a dissolution solution containing a dissolving agent; or The cells are lysed using a dissolution solution containing a dissolving agent, and then the whole cell components after lysis are dissolved using a dissolution solution containing a dissolving agent.

10. Use according to claim 9, characterized in that, In the preparation of the water-soluble components and non-water-soluble components, a treatment step is included, and the treatment method comprises salting-out, heating, or enzymolysis, wherein the precipitate produced after treatment of the non-water-soluble components is dissolved using a dissolution solution containing a dissolving agent.

11. Use according to claim 1, characterized in that, After labeling the biomarkers on the cell surface or in the cells of T cells and / or B cells using specific signal probes, the content of the T cells and / or B cells labeled by the signal probes is detected using one of the methods comprising flow cytometry, mass cytometry, mass spectrometry, magnetic bead method, chemiluminescence method, substrate precipitation method, DNA sequencing method, RNA sequencing method, and single-cell sequencing. The signal probe is combined with a chemical molecule that can bind to the biomarker. Preferably, the signal probe comprises at least one of a fluorescent, phosphorescent, radioactive, isotope, chemiluminescent, chromogenic substance, Preferably, the chemical molecule capable of binding a biomarker comprises an antibody.

12. The use according to claim 1, characterized in that, The tumor is selected from one of a solid tumor, a blood tumor and a lymphoma; Preferably, the tumor is any one of lung cancer, ovarian cancer, colon cancer, rectal cancer, melanoma, renal cancer, bladder cancer, breast cancer, liver cancer, lymphoma, a malignant blood tumor such as leukemia, brain tumor, head and neck cancer, glioma, stomach cancer, nasopharyngeal cancer, laryngeal cancer, cervical cancer, uterine body tumor, osteosarcoma, bone cancer, pancreatic cancer, skin cancer, prostate cancer, uterine cancer, anal cancer, testicular cancer, fallopian tube cancer, endometrial cancer, vaginal cancer, vulvar cancer, Hodgkin's disease, non-Hodgkin's lymphoma, esophageal cancer, small bowel cancer, endocrine system cancer, thyroid cancer, parathyroid cancer, adrenal cancer, soft tissue sarcoma, urethral cancer, penile cancer, chronic or acute leukemia, pediatric solid tumor, lymphocytic lymphoma, bladder cancer, kidney or ureter cancer, renal pelvis cancer, central nervous system tumor, primary CNS lymphoma, tumor angiogenesis, spinal column tumor, brain stem neuroglioma, pituitary adenoma, Kaposi's sarcoma, epidermoid carcinoma, squamous cell carcinoma, T-cell lymphoma, environmentally induced cancer, metastatic cancer, circulating tumor cell or a combination thereof.

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