CN115747331B - Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis - Google Patents

Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis Download PDF

Info

Publication number
CN115747331B
CN115747331B CN202211155709.XA CN202211155709A CN115747331B CN 115747331 B CN115747331 B CN 115747331B CN 202211155709 A CN202211155709 A CN 202211155709A CN 115747331 B CN115747331 B CN 115747331B
Authority
CN
China
Prior art keywords
nasopharyngeal carcinoma
hla
cxcl13
prognosis
marker
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202211155709.XA
Other languages
Chinese (zh)
Other versions
CN115747331A (en
Inventor
贝锦新
刘洋
何帅
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sun Yat Sen University Cancer Center
Original Assignee
Sun Yat Sen University Cancer Center
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sun Yat Sen University Cancer Center filed Critical Sun Yat Sen University Cancer Center
Priority to CN202211155709.XA priority Critical patent/CN115747331B/en
Priority to PCT/CN2022/124108 priority patent/WO2024060327A1/en
Publication of CN115747331A publication Critical patent/CN115747331A/en
Application granted granted Critical
Publication of CN115747331B publication Critical patent/CN115747331B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids

Abstract

The invention provides a tertiary lymphoid structure component marker for predicting nasopharyngeal carcinoma prognosis, which comprises one or more of germinal center B cell component markers, follicular auxiliary CD4+ T cell component markers, CXCL13+CD8+ T cell component markers and CXCL13+ fibroblast component markers. The invention also provides application of the tertiary lymphoid structure component marker and a system for predicting nasopharyngeal carcinoma prognosis. The invention can predict the clinical prognosis of the nasopharyngeal carcinoma patient by measuring the expression level of different components in the tertiary lymph structure of the nasopharyngeal carcinoma, is favorable for carrying out individual treatment, and finally brings survival benefit to the patient.

Description

Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis
Technical Field
The invention belongs to the field of biological medicine, and particularly relates to a three-level lymphoid structure component marker combination, a system and application for predicting nasopharyngeal carcinoma prognosis.
Background
Nasopharyngeal carcinoma is a unique tumor of the head and neck, closely related to infection by EB virus, and is well developed in the south-huashan area, also known as "guangdong tumor".
Nasopharyngeal carcinoma is caused in the nasopharynx, and is hidden, and is mostly diagnosed in middle and late stages. Due to the radiation sensitivity of nasopharyngeal carcinoma tumor cells, radiotherapy is a main treatment mode of nasopharyngeal carcinoma patients, and with the development of radiotherapy technology and the assistance of chemotherapy, the survival result of nasopharyngeal carcinoma patients is significantly improved, reaching a total survival rate of more than 85% for 5 years. Nevertheless, more than 10% of patients with nasopharyngeal carcinoma develop recurrent and metastatic nasopharyngeal carcinoma.
Different prognosis results can appear after the same clinical stage nasopharyngeal carcinoma patients are treated by the same method, and biological heterogeneity among tumors is reflected, so that understanding of the biological characteristics of nasopharyngeal carcinoma is one of the focus of current researches.
In addition to the high heterogeneity of tumor cells, the tumor tissue of nasopharyngeal carcinoma also includes infiltration immune cells of focus part, and these cell components together form tumor microenvironment, and the difference of different cell components in tumor microenvironment can influence the biological characteristics of tumor, and may further lead to different prognosis results.
Previous studies reported that the tertiary lymphoid structure, the region of immune cell aggregation within tumors, could predict the prognosis of patients. However, the three-level lymphoid structure area of the nasopharyngeal carcinoma is rarely studied at present, and no systematic report is available for predicting the prognosis of the nasopharyngeal carcinoma patient by the three-level lymphoid structure. The analysis of the three-level lymph structural components of the nasopharyngeal carcinoma is helpful for understanding the biological characteristics of the nasopharyngeal carcinoma, and can be used for predicting the clinical prognosis of the nasopharyngeal carcinoma patient, carrying out personalized treatment and finally bringing survival benefit to the patient. The tertiary lymphoid structure is dispersed in the tumor, and the existence of the tertiary lymphoid structure is only observed in the morphological level by the traditional technology, but the cell constitution and the molecular characteristics of the tertiary lymphoid structure are not known very much, and how to detail the cell constitution and the molecular characteristics of the tertiary lymphoid structure is still a challenging work.
Disclosure of Invention
Aiming at the technical problems to be solved, the invention aims to provide a tertiary lymphoid structure component marker for predicting nasopharyngeal carcinoma prognosis.
It is another object of the present invention to provide a system for predicting the prognosis of nasopharyngeal carcinoma.
It is a further object of the present invention to provide the use of the tertiary lymphoid structure component markers for predicting prognosis of nasopharyngeal carcinoma.
To achieve the above object, the present invention provides a tertiary lymphoid structure component marker combination for predicting nasopharyngeal carcinoma prognosis, wherein the tertiary lymphoid structure component markers include one or more of germinal center B cell component, follicular assist CD4+ T cell component, CXCL13+CD8+T cell component, CXCL13 +fibroblast component.
The four tertiary lymphoid structure components can be used for predicting the prognosis of the nasopharyngeal carcinoma independently or in any combination.
Preferably, the germinal center B cell component marker is one or more of the following characteristic genes or proteins: RGS13, MARGKSL 1, NEIL1, TCL1A, HMGN1, LRMP, ACTG1, SERPINA9, RP11-231C14.7, LPP, CD79B, ATP5L, SERF2, SUGCT, LTB, HMCES, BASP1, LMO2, RFTN1, SMIM14, BCL7A, DAAM1, AC023590.1, BIK, ARPC2, PARP1, GCHFR, UCP2, TCEA1, METAP2, CD40, GAPDH, CD22, BCAS4, SYNE2, LIMD2, VPREB3, CCDC144A, TKT, SLC A5, CORO1A, HMGA, IRF8, STAG3, EZR, CFL1, LCP1, ACTB, H3F3A, CD CCDC88A, GRHPR, SUSD3, VNN2, ACY3, TMEM123, KLHL6, PRPSAP2, PRDX6, ALOX5AP, GMDS, DHRS9, AC079767.4, PFN1, WDR66, AICDA, GGA2, BRK1, ARPC1B, CD53, ANP32B, MEF2B, ARPC5, DEF8, ACTR3, OAZ1, MYO1E, SWAP70, ARPC4, PKM, SMARCB1, HOPX, HLA-DMB, LCK, ARPC3, SRSF9, HTR3A, RRAS2, MBD4, SEC14L1, IL4R, DCAF12, LYPLA1, SNAP23, lamor 5, UBE2J1, CCDC69, HLA-DMA, RGS10, CDV3.
Preferably, the follicular helper cd4+ T cell component markers are one or more of the following signature genes or proteins: CXCL13, ITM2A, RP-1028K7.2, PDCD1, TOX2, CHI3L2, ICA1, SH2D1A, IGFBP4, PASK, PCAT29, NR3C1, RP11-455F5.5, SMCO4, CD200, NMB, TOX, PTPN, CXCR5, ZNF331, TCF7, TIGIT, FKBP5, RNF19A, LAT, MAGEH1, C9orf16, LIMS1, FABP5, PPP1CC, SRGN, THADA, CPM, IL ST, CORO1B, ST8SIA1, COTL1, IKZF3, SLC9A9, RGS2, IL6R, MAF, C1orf228, CXCR4, FYN, GNG4, ATC NF1, YPEL5 TBC1D4, JUNB, TRBC2, NUCB2, DUSP6, GZMM, LGMN, RNASET2, TC2N, TSHZ2, CD84, IL16, SFXN1, TRAC, SIRPG, FYB, LRMP, CD40LG, BTLA, RHOB, POU AF1, NR4A2, PPP2R5C, AHI1, SH3TC1, TRPS1, DENND2D, ASB2, KIAA1551, RAB27A, STOM, PTPRC, FAAH2, DUSP2, CD27, SIAH2, EVI2B, FAM A, TSPYL2, SEPTIN6, TNFSF8, ZBTB10, SESN3, PYHIN1, TIFA, PTPN2, SPCS1, CNIH1, TMEM2, SLC25A46, H2AFZ, PTPN7.
Preferably, the cxcl13+cd8+ T cell component marker is one or more of the following characteristic genes or proteins: CXCL13, TRBV6-5, TOX, CD27, FXYD6, RP5-1028K7.2, GZMK, CD74, TSHZ2, DUSP4, IGFBP4, SH2D1A, FOS, BCAT1, AP3S1, CHI3L2, CAV1, HLA-DPB1, ENC1, GEM, NR3C1, ITM2A, HLA-DPA1, HLA-DQA1, PASK, LANCL2, GZMM, FABP5, CRTAM, PMAIP1, DUSP1, ITM2C, VOPP, VIPR2, TCF7, CDHR1, RGS2, CD82, HLA-DRA, CLDND1, ZNF331, APLP2, FCRL3, JUNB, TUBA A, SEPTIN6, TIUNB, TIFA CHN1, TRAT1, AIG1, HLA-DRB1, TRAV3, HSPA1B, RHOB, TTN, CXCR5, DKK3, TIAM1, PCAT29, DNAJB1, CD200, B3GNT2, FAAH2, CDH1, LY9, EOMES, CD8A, SEPTIN9, PEBP1, SIRPG, ELMO1, HLA-a, pdlm 4, SMPDL3A, LAT, DTHD1, CXCR3, HLA-DRB5, HLA-B, PON2, IGFBP2, STAG3, BATF, GRINA, LYST, CIRBP, IL RA, AIF1, LPL, METTL8, HIF1A, CD28, PDE4DIP, SEMA4A, ZFAS1, L1CAM, lt3, NGFRAP1, TNFRSF9, HLA-DQB1.
Preferably, the cxcl13+ fibroblast component marker is one or more of the following characteristic genes or proteins: PTGDS, CCL19, MMP1, MMP3, CXCL14, CXCL1, CXCL13, CHI3L1, CCL11, C3, rares 2, CCL21, SOD2, TNFSF13B, C1S, TMEM176B, VCAM1, ABI3BP, HPGD, CP, ADH B, DPT, CD24, CCL2, CXCL6, TMEM176A, MT2A, RBP5, LUM, MFAP4, DCN, CYP1B1, FGF7, FTH1, CXCL12, C1R, DIO2, CTSK, LSAMP, PCOLCE, FDCSP, RND3, CTSS, CXCL9, NR2F1, APOE, rares 1, LOXL1, FMO2, PLEKHH2 OLFML3, CCDC80, TWIST2, STEAP1, CD82, SERPINF1, TNFAIP6, LTBP1, CRABP1, SOSTDC1, IL32, PRESP, IDO1, TIMP1, EMILIN1, PDPN, SELM, AKR C1, C7, AC090498.1, C2, IGFBP5, MMP9, TNC, G0S2, IFI27L2, PTGES, PDGFRA, UBD, S A13, CLU, ISOC1, FMOD, NDRG2, FRZB, TYMP, ADAMDEC1, TSPAN8, ITIH5, LGALS3BP, CLMP, IL, CFB, GEM, PPA, SQSTM1, CD63, TMEM98, CEBPB, DDR2.
On the other hand, the invention also provides application of the tertiary lymphoid structure component marker combination for predicting the prognosis of the nasopharyngeal carcinoma in preparing a reagent for determining the prognosis of the nasopharyngeal carcinoma.
In another aspect, the invention also provides the use of a reagent for quantifying the tertiary lymphoid structure component marker combination according to the invention in the preparation of a reagent for prognosis determination of nasopharyngeal carcinoma.
Preferably, the reagent for quantifying the tertiary lymphoid structure component marker combination according to the present invention is a reagent for quantifying the marker mRNA or protein. The reagent may be other reagents, chips or other methods that can react with the amount of expression of the marker mRNA or protein.
In another aspect, the invention also provides a system for predicting the prognosis of nasopharyngeal carcinoma, comprising:
tertiary lymphoid structure component marker quantification means for determining the expression level of tertiary lymphoid structure component marker combinations;
a data analysis device for determining the prognosis of nasopharyngeal carcinoma based on the expression level of the tertiary lymphoid structure component markers;
and a result output means for outputting the calculated prognosis result.
Preferably, the expression level can be the expression level determined by different methods, preferably the expression level after dimensionless treatment, so that the data analysis and treatment are convenient.
In some examples, the tertiary lymphoid structure component marker quantification device comprises a reagent, a chip, a detection device, a kit for quantitatively detecting the expression level of marker mRNA or protein.
In some examples, reagents for quantitative detection of marker mRNA at the gene level include, but are not limited to, expression chips, mRNA sequencing devices, qPCR gene detection devices, nanostring technology gene detection devices, and the like. Methods for quantifying marker proteins at the protein level include, but are not limited to, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (IRA), immunohistochemical staining, western blot, electrophoresis, liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS), and the like.
In some examples, the expression level of each component can be calculated by quantifying the mRNA or protein expression level of each component's characteristic gene and performing a single sample gene enrichment analysis (ssGSEA) on the mRNA expression level of all the characteristic genes of each component. mRNA or protein expression levels determined by different methods were normalized.
In some examples, the germinal center B cell component is expressed in an amount below 10.77 and is at high risk and above 10.77 is at low risk.
In some examples, the expression level of the follicular helper cd4+ T cell component is determined to be at high risk when it is below 9.09 and is determined to be at low risk when it is above 9.09.
In some examples, the cxcl13+cd8+ T cell component is expressed in an amount below 8.41 and is at high risk and above 8.41 is at low risk.
In some examples, the cxcl13+ fibroblast component is expressed in an amount below 8.58 and is at high risk and above 8.58 is at low risk.
In some examples, other known methods may also be employed to determine the specific risk threshold.
According to the invention, through calculating the expression quantity of the characteristic genes or proteins of the four immune cell components, the expression level of different components in the three-level lymph structure of the nasopharyngeal carcinoma can be predicted, clinical prognosis prediction can be carried out on a nasopharyngeal carcinoma patient, the individual treatment is facilitated, and finally survival benefit is brought to the patient.
Drawings
Figure 1 shows normalized average expression of TLS typical marker genes (columns) for different cell types (rows). The fill color from blue to red represents a normalized average expression level from low to high.
Figure 2 shows the characteristic scores of germinal center B cells, follicular helper cd4+ T cells, cxcl13+cd8+ T cells, cxcl13+ fibroblast components (rows) for 150 NPC samples (columns). The fill color from blue to red represents a low to high zoom expression level. The color bars at the top of the heat map represent information on the total and progression free survival of the samples. All samples can be divided into two groups based on the components with low or high tertiary lymphoid structure.
Figure 3 shows that NPC patients were divided into high and low groups according to tertiary lymphoid structure content, KM survival curve analysis demonstrated the difference between progression free survival (left panel) and total survival (right panel) for both groups of patients.
Figure 4 shows that the KM survival profile analysis demonstrates the differences in progression free survival (left panel) and overall survival (right panel) of two groups of patients, based on germinal center B cells, follicular helper cd4+ T cells, cxcl13+ cd8+ T cells, cxcl13+ fibroblast components, dividing NPC patients into high and low groups.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It will be apparent to those skilled in the art that the examples are merely to aid in understanding the invention and should not be construed as limiting the invention in any way; the sequencing and analysis methods used in the examples described below are conventional methods unless otherwise specified.
The invention will be further illustrated in connection with specific experiments, it being understood that the following is only illustrative of the invention and is not intended to limit the scope of the invention.
By using single cell mRNA sequencing technology to study, it was found that the tertiary lymphoid structure of nasopharyngeal carcinoma comprises four cellular components, including: the method comprises the steps of generating germinal center B cells, follicular auxiliary CD4+ T cells, CXCL13+CD8+ T cells and CXCL13+ fibroblasts, digging out characteristic genes corresponding to each component through systematic bioinformatics calculation, detecting mRNA expression amounts of the characteristic genes of each component in nasopharyngeal carcinoma tumor tissues, and carrying out single-sample gene enrichment analysis on the mRNA expression amounts of the characteristic genes of each component so as to predict the expression amounts of each component in the nasopharyngeal carcinoma tissues. Further, by performing survival analysis on the expression amounts of the components, it was found that the four components can predict the clinical prognosis of a patient with nasopharyngeal carcinoma.
The components of tertiary lymphoid structure and the corresponding characteristic genes of each component:
gene mRNA expression from a total of 349038 cells from 67 nasopharyngeal carcinoma patients (from the university of Zhongshan tumor control center) was detected by single cell mRNA sequencing technology, and nine large cell subsets were found by cluster analysis. And finally determining that the germinal center B cells, the follicular auxiliary CD4+ T cells, the CXCL13+ CD8+ T cells and the CXCL13+ fibroblasts are derived from the tertiary lymphoid structure by carrying out cluster analysis on each cell subset and combining the expression of the tertiary lymphoid structure markers.
As shown in fig. 1, normalized average expression of TLS typical marker genes (columns) for different cell types (rows) is shown. The fill color from blue to red represents a normalized average expression level from low to high. As can be seen from FIG. 1, the expression levels of four cells, germinal center B cells (RGS13+B cells), follicular helper CD4+T cells, CXCL13+CD8+T cells, CXCL 13+fibroblasts, were highest.
And then, performing differential gene analysis on the four cell components by using a rank sum test, and respectively selecting the first 100 genes with the most obvious fold difference as characteristic genes to form markers capable of predicting the four cell components.
Markers for the four cell components are shown in table 1 below.
TABLE 1 markers for four cellular components
The mRNA expression quantity of the characteristic genes of each component of the four cell components is subjected to single sample gene enrichment analysis, so that the expression quantity of each component in nasopharyngeal carcinoma tumor tissues can be predicted.
The clinical prognosis of a patient with nasopharyngeal carcinoma can be predicted by measuring the expression of four cellular components.
The invention further carries out survival analysis on the prognosis prediction effect of each component. For 150 nasopharyngeal carcinoma patients initially treated in the center of tumor prevention and treatment of Zhongshan university, nasopharyngeal carcinoma tumor tissue samples were obtained by means of nasopharyngeal mirror biopsy before treatment, and mRNA chip detection was performed on each sample to obtain gene expression profile of each sample.
Figure 2 shows the characteristic scores of germinal center B cells, follicular helper cd4+ T cells, cxcl13+cd8+ T cells, cxcl13+ fibroblast components (rows) for 150 NPC samples (columns). The fill color from blue to red represents a low to high zoom expression level. The color bars at the top of the heat map represent information on the total and progression free survival of the samples. All samples can be divided into two groups based on the components with low or high tertiary lymphoid structure.
The mRNA expression levels of the characteristic genes of the four cell components are subjected to single sample gene enrichment analysis, the respective expression levels of the four cell components can be calculated, the optimal solution of the expression levels of each component is searched for as a boundary value by utilizing a receiver operation characteristic (receiver operating characteristic, ROC) curve, each cell component is divided into a high expression group and a low expression group, survival analysis is carried out, and the conditions of no-progress survival (PFS) and total survival (OS) of the high expression group compared with the low expression group are explored.
Figure 3 shows that NPC patients were divided into high and low groups according to tertiary lymphoid structure content, KM survival curve analysis demonstrated the difference between progression free survival (left panel) and total survival (right panel) for both groups of patients.
As a result, as shown in FIG. 4, it was found that the prognosis of the nasopharyngeal carcinoma patient was better (P < 0.05) than that of the low expression group patient when the four cell components were highly expressed (FIG. 4).
Therefore, the invention can predict the expression level of different components in the three-level lymph structure of the nasopharyngeal carcinoma by calculating the expression level of the respective characteristic genes or proteins of the four immune cell components, can predict the clinical prognosis of the nasopharyngeal carcinoma patient, is favorable for carrying out individuation treatment, and finally brings survival benefit to the patient.
The following risk thresholds may be employed in deciding high and low risk: the expression level of germinal center B cell components was judged to be high risk when it was below 10.77, and low risk when it was above 10.77; the risk was judged to be high when the expression level of the follicle-assisted cd4+ T cell component was below 9.09, and the risk was judged to be low when it was above 9.09; the higher the expression level of CXCL13+CD8+ T cell components is below 8.41, the higher the risk is, the lower the risk is; the higher the expression level of CXCL13+ fibroblast components is below 8.58, the higher the risk is, the higher the risk is, the lower the risk is.
Other known methods may also be employed to determine the specific risk threshold.
The above embodiments are merely exemplary and do not limit the scope of the present invention in any way. It will be understood by those skilled in the art that various changes and substitutions of details and forms of the technical solution of the present invention may be made without departing from the spirit and scope of the present invention, but these changes and substitutions fall within the scope of the present invention.

Claims (5)

1. A tertiary lymphoid structure component marker combination for predicting nasopharyngeal carcinoma prognosis, wherein said tertiary lymphoid structure component markers comprise germinal center B cell component markers, follicular assist cd4+ T cell component markers, cxcl13+cd8+ T cell component markers, cxcl13+ fibroblast component markers;
the hair growth center B cell component marker is the following characteristic genes: RGS13, MARGKSL 1, NEIL1, TCL1A, HMGN1, LRMP, ACTG1, SERPINA9, RP11-231C14.7, LPP, CD79B, ATP5L, SERF2, SUGCT, LTB, HMCES, BASP1, LMO2, RFTN1, SMIM14, BCL7A, DAAM1, AC023590.1, BIK, ARPC2, PARP1, GCHFR, UCP2, TCEA1, METAP2, CD40, GAPDH, CD22, BCAS4, SYNE2, LIMD2, VPREB3, CCDC144A, TKT, SLC A5, CORO1A, HMGA, IRF8, STAG3, EZR, CFL1, LCP1, ACTB, H3F3A, CD CCDC88A, GRHPR, SUSD3, VNN2, ACY3, TMEM123, KLHL6, PRPSAP2, PRDX6, ALOX5AP, GMDS, DHRS9, AC079767.4, PFN1, WDR66, AICDA, GGA2, BRK1, ARPC1B, CD53, ANP32B, MEF2B, ARPC5, DEF8, ACTR3, OAZ1, MYO1E, SWAP70, ARPC4, PKM, SMARCB1, HOPX, HLA-DMB, LCK, ARPC3, SRSF9, HTR3A, RRAS2, MBD4, SEC14L1, IL4R, DCAF12, LYPLA1, SNAP23, lamor 5, UBE2J1, CCDC69, HLA-DMA, RGS10, CDV3;
the follicles assisted cd4+ T cell component markers are the following characteristic genes: CXCL13, ITM2A, RP-1028K7.2, PDCD1, TOX2, CHI3L2, ICA1, SH2D1A, IGFBP4, PASK, PCAT29, NR3C1, RP11-455F5.5, SMCO4, CD200, NMB, TOX, PTPN, CXCR5, ZNF331, TCF7, TIGIT, FKBP5, RNF19A, LAT, MAGEH1, C9orf16, LIMS1, FABP5, PPP1CC, SRGN, THADA, CPM, IL ST, CORO1B, ST8SIA1, COTL1, IKZF3, SLC9A9, RGS2, IL6R, MAF, C1orf228, CXCR4, FYN, GNG4, ATC NF1, YPEL5 TBC1D4, JUNB, TRBC2, NUCB2, DUSP6, GZMM, LGMN, RNASET2, TC2N, TSHZ2, CD84, IL16, SFXN1, TRAC, SIRPG, FYB, LRMP, CD40LG, BTLA, RHOB, POU AF1, NR4A2, PPP2R5C, AHI1, SH3TC1, TRPS1, DENND2D, ASB2, KIAA1551, RAB27A, STOM, PTPRC, FAAH2, DUSP2, CD27, SIAH2, EVI2B, FAM A, TSPYL2, SEPTIN6, TNFSF8, ZBTB10, SESN3, PYHIN1, TIFA, PTPN2, SPCS1, CNIH1, TMEM2, SLC25A46, H2AFZ, PTPN7;
the CXCL13+CD8+ T cell component markers are the following characteristic genes: CXCL13, TRBV6-5, TOX, CD27, FXYD6, RP5-1028K7.2, GZMK, CD74, TSHZ2, DUSP4, IGFBP4, SH2D1A, FOS, BCAT1, AP3S1, CHI3L2, CAV1, HLA-DPB1, ENC1, GEM, NR3C1, ITM2A, HLA-DPA1, HLA-DQA1, PASK, LANCL2, GZMM, FABP5, CRTAM, PMAIP1, DUSP1, ITM2C, VOPP, VIPR2, TCF7, CDHR1, RGS2, CD82, HLA-DRA, CLDND1, ZNF331, APLP2, FCRL3, JUNB, TUBA A, SEPTIN6, TIUNB, TIFA CHN1, TRAT1, AIG1, HLA-DRB1, TRAV3, HSPA1B, RHOB, TTN, CXCR5, DKK3, TIAM1, PCAT29, DNAJB1, CD200, B3GNT2, FAAH2, CDH1, LY9, EOMES, CD8A, SEPTIN9, PEBP1, SIRPG, ELMO1, HLA-a, pdl 4, SMPDL3A, LAT, DTHD1, CXCR3, HLA-DRB5, HLA-B, PON2, IGFBP2, STAG3, BATF, GRINA, LYST, CIRBP, IL RA, AIF1, LPL, METTL8, HIF1A, CD28, PDE4DIP, SEMA4A, ZFAS1, L1CAM, MLLT3, NGFRAP1, TNFRSF9, HLA-DQB1;
the CXCL13+ fibroblast component markers are the following characteristic genes: PTGDS, CCL19, MMP1, MMP3, CXCL14, CXCL1, CXCL13, CHI3L1, CCL11, C3, rares 2, CCL21, SOD2, TNFSF13B, C1S, TMEM176B, VCAM1, ABI3BP, HPGD, CP, ADH B, DPT, CD24, CCL2, CXCL6, TMEM176A, MT2A, RBP5, LUM, MFAP4, DCN, CYP1B1, FGF7, FTH1, CXCL12, C1R, DIO2, CTSK, LSAMP, PCOLCE, FDCSP, RND3, CTSS, CXCL9, NR2F1, APOE, rares 1, LOXL1, FMO2, PLEKHH2 OLFML3, CCDC80, TWIST2, STEAP1, CD82, SERPINF1, TNFAIP6, LTBP1, CRABP1, SOSTDC1, IL32, PRESP, IDO1, TIMP1, EMILIN1, PDPN, SELM, AKR C1, C7, AC090498.1, C2, IGFBP5, MMP9, TNC, G0S2, IFI27L2, PTGES, PDGFRA, UBD, S A13, CLU, ISOC1, FMOD, NDRG2, FRZB, TYMP, ADAMDEC1, TSPAN8, ITIH5, LGALS3BP, CLMP, IL, CFB, GEM, PPA, SQSTM1, CD63, TMEM98, CEBPB, DDR2.
2. Use of a reagent for quantifying the tertiary lymphoid structure component marker combination of claim 1 in the preparation of a nasopharyngeal carcinoma prognosis reagent.
3. The use according to claim 2, wherein the reagent for quantifying the tertiary lymphoid structural element marker combination is a reagent for quantifying marker mRNA.
4. A system for predicting a prognosis of nasopharyngeal carcinoma, comprising:
a tertiary lymphoid structure component marker quantification device for determining the expression level of the tertiary lymphoid structure component marker combination according to claim 1;
a data analysis device for determining the prognosis of nasopharyngeal carcinoma based on the expression level of the tertiary lymphoid structure component marker;
and a result output means for outputting the calculated prognosis result.
5. The system of claim 4, wherein the tertiary lymphoid structure component marker quantification device comprises reagents to quantitatively detect the amount of marker mRNA expression.
CN202211155709.XA 2022-09-22 2022-09-22 Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis Active CN115747331B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202211155709.XA CN115747331B (en) 2022-09-22 2022-09-22 Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis
PCT/CN2022/124108 WO2024060327A1 (en) 2022-09-22 2022-10-09 Tertiary lymphoid structure component marker combination and system for predicting prognosis of nasopharyngeal cancer, and use

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211155709.XA CN115747331B (en) 2022-09-22 2022-09-22 Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis

Publications (2)

Publication Number Publication Date
CN115747331A CN115747331A (en) 2023-03-07
CN115747331B true CN115747331B (en) 2023-08-25

Family

ID=85351808

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211155709.XA Active CN115747331B (en) 2022-09-22 2022-09-22 Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis

Country Status (2)

Country Link
CN (1) CN115747331B (en)
WO (1) WO2024060327A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117476097A (en) * 2023-10-25 2024-01-30 中山大学附属第六医院 Colorectal cancer prognosis and treatment response prediction model based on tertiary lymphoid structure characteristic genes, and construction method and application thereof

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110418651A (en) * 2016-08-02 2019-11-05 哈佛学院院长等 For adjusting the biomaterial of immune response
CN111910000A (en) * 2020-07-02 2020-11-10 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所） Tumor microenvironment component marker combination and system for predicting nasopharyngeal carcinoma prognosis

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100316996A1 (en) * 2009-06-15 2010-12-16 Lih-Chyang Chen Nasopharyngeal cancer malignancy biomarker and method thereof
CN109690314B (en) * 2016-05-09 2022-08-02 法国国家卫生及研究医学协会 Method for classifying patients with solid cancer
EP3652534B1 (en) * 2017-07-13 2024-03-27 Institut Gustave Roussy A radiomics-based imaging tool to monitor tumor-lymphocyte infiltration and survival of cancer patients treated with anti-pd-1/pd-l1
CN113462782A (en) * 2021-07-30 2021-10-01 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所） Nasopharyngeal carcinoma marker and application thereof

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110418651A (en) * 2016-08-02 2019-11-05 哈佛学院院长等 For adjusting the biomaterial of immune response
CN111910000A (en) * 2020-07-02 2020-11-10 中山大学肿瘤防治中心（中山大学附属肿瘤医院、中山大学肿瘤研究所） Tumor microenvironment component marker combination and system for predicting nasopharyngeal carcinoma prognosis

Also Published As

Publication number Publication date
CN115747331A (en) 2023-03-07
WO2024060327A1 (en) 2024-03-28

Similar Documents

Publication Publication Date Title
JP7241353B2 (en) Methods for Subtyping Lung Adenocarcinoma
Cao et al. Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis
Dieckgraefe et al. Analysis of mucosal gene expression in inflammatory bowel disease by parallel oligonucleotide arrays
US20190249260A1 (en) Method for Using Gene Expression to Determine Prognosis of Prostate Cancer
Sana et al. Microarray analysis of primary endothelial cells challenged with different inflammatory and immune cytokines
JP2024009859A (en) Variant based disease diagnostics and tracking
US20230366034A1 (en) Compositions and methods for diagnosing lung cancers using gene expression profiles
EP3458611B1 (en) Methods for subtyping of lung squamous cell carcinoma
US20200255898A1 (en) Diagnostic assay for source of inflammation
EP2909340B1 (en) Diagnostic method for predicting response to tnf alpha inhibitor
WO2010076322A1 (en) Prediction of response to taxane/anthracycline-containing chemotherapy in breast cancer
WO2012093821A2 (en) Gene for predicting the prognosis for early-stage breast cancer, and a method for predicting the prognosis for early-stage breast cancer by using the same
Albright et al. Microarray analysis of activated mixed glial (microglia) and monocyte-derived macrophage gene expression
CN108588230B (en) Marker for breast cancer diagnosis and screening method thereof
JP3469551B2 (en) Novel method for detection and monitoring of endometrial and uterine cancer
CN115747331B (en) Three-level lymphoid structure component marker combination, system and application for predicting nasopharyngeal carcinoma prognosis
Schmidt et al. Cancer diagnosis and microarrays
CN108866187B (en) Long-chain non-coding RNA marker related to lung cancer auxiliary diagnosis and application thereof
US20230111281A1 (en) Identification of the cellular function of an active nfkb pathway
WO2018103679A1 (en) Benign thyroid nodule-specific gene
CN108456730B (en) Application of recurrence risk gene group as marker in preparation of product for evaluating recurrence risk at distant place in breast cancer molecular typing
Akçay Integrated network analysis of the potential molecular biomarkers and key pathways in clear renal cell carcinoma (ccRCC)
WO2011152884A2 (en) 14 gene signature distinguishes between multiple myeloma subtypes
EP4134454A1 (en) Reagent combination and kit for detecting liver cancers, and use thereof
EP2708606A1 (en) Novel biomarkers for human cervical cancer and/or HPV infection

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant