CN111910000B - Tumor microenvironment component marker combination and system for predicting nasopharyngeal carcinoma prognosis - Google Patents
Tumor microenvironment component marker combination and system for predicting nasopharyngeal carcinoma prognosis Download PDFInfo
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Abstract
The invention discloses a tumor microenvironment component marker combination and a system for predicting nasopharyngeal carcinoma prognosis, which comprises a cell cycle proliferation component and at least one of macrophage, plasmacytoid dendritic cell, CLEC9A + dendritic cell, natural killer cell and plasmacytoid cell. According to some embodiments of the invention, the expression levels of different components in the nasopharyngeal carcinoma tumor microenvironment can be predicted by calculating the expression levels of the characteristic genes of one tumor cell component and five immune cell components, and the clinical prognosis prediction can be performed on a nasopharyngeal carcinoma patient, so that the individual treatment can be facilitated, and finally, the survival benefit can be brought to the patient.
Description
Technical Field
The invention relates to the field of biology, in particular to a tumor microenvironment component marker combination and a system for predicting nasopharyngeal carcinoma prognosis.
Background
Nasopharyngeal carcinoma is the most common head and neck tumor in China, particularly is better to be developed in south China and is also called as Guangdong tumor. According to different clinical stages, the current treatment modes of nasopharyngeal carcinoma are different, and radiotherapy and chemotherapy are mainly used as the core, and targeted therapy, immunotherapy and other multidisciplinary comprehensive treatments are used as the auxiliary. With the innovation of treatment modes and the push of standardized treatment, the survival rate and the quality of life of patients with early nasopharyngeal carcinoma are improved, but the prognosis of patients with middle and late stages is still poor, and patients with the same clinical stage can have different prognosis results after the same treatment, reflecting the biological heterogeneity among tumors, so that the understanding of the biological characteristics of the nasopharyngeal carcinoma is deepened to become one of the focuses of the current research. The tumor tissue of nasopharyngeal carcinoma contains not only tumor cells with high heterogeneity, but also infiltration immune cells at the focus part, and the cell components jointly form a tumor microenvironment, and the difference of different cell components in the tumor microenvironment can influence the biological characteristics of the tumor, thereby possibly leading to different prognosis results. Therefore, by deeply analyzing the constituent components of the nasopharyngeal carcinoma tumor microenvironment, the method is helpful for understanding the biological characteristics of the nasopharyngeal carcinoma, can be used for predicting the clinical prognosis of patients with the nasopharyngeal carcinoma, carries out individualized treatment and finally brings survival benefit to the patients.
There are many factors associated with nasopharyngeal carcinoma and many mRNA expressed differentially, and there are many reported markers associated with NPC prognosis in the literature, however, it is still a challenging task to screen many markers to obtain a combination of markers that can be used to determine NPC prognosis.
Disclosure of Invention
The invention aims to overcome at least one defect of the prior art and provides a tumor microenvironment component marker combination and a system for predicting nasopharyngeal carcinoma prognosis.
The technical scheme adopted by the invention is as follows:
in a first aspect of the present invention, there is provided:
a set of tumor microenvironment component markers for predicting nasopharyngeal carcinoma prognosis, comprising a cell cycle proliferation component and at least one of five immune cell components, wherein:
the characteristic genes of the cell cycle proliferation component are DEPDC1, DLGAP5, HJURP, PBK, TOP2A, GTSE1, ASPM, CDC20, CEP55, CKAP2L, HMMR, NEK2, BIRC5, CCNA2, MKI67, FAM64A, KIF4A, KIF2C, CENPF, AURKB, KIF14, NUF2, ESCO2, NUSAP1, NCAPG, CDCA3, CDCA5, CENPE, KIF20A and CENPA;
the five immune cell components are macrophage component, plasmacytoid dendritic cell component, CLEC9A + dendritic cell component, natural killer cell component and plasmacytoid cell component respectively,
the characteristic gene of the macrophage component is APOE, APOC1, RNASE1, CTSL, C1QA, C1QB, C1QC, CTSD, ADAMTC 1, SPP1, FTL, NUPR1, GPNMB, FCGR3A, CCL8, PLD3, LGMN, GLUL, CTSC, CD163, PSAP, CTSB, CCL3, HES1, MMP9, MS4A4A, IFIT1, ACP5, PLA2G7, CD68, MAFB 14, IFI6, TREM2, MS4A7, PRDX1, LS1, LGAAH 3, CCL4, IFI27, MARCKS, CREG1, CD81, CCL 40A1, CTSS, FCER1 SLC 1G, CXER 9;
the characteristic genes of the plasmacytoid dendritic cell component are PTGDS, GZMB, IGJ, TCL1A, LILRA4, PLAC8, ITM2C, IRF7, PPP1R14B, TCF4, TSPAN13, CLIC3, SELL, PLD4, UGCG, CCDC50, C12orf75, BCL11A, MZB1, PTCRA, SPIB, LRRC26, SMPD3, MAP1A, ALOX5AP, SCT, PTPRS, IL3RA, APP, CYB561a3, SEC61B, SPCS1, CLEC4C, SLC15A4, HIGD1A, NUCB2, MPEG1, LTB, GAPT, IDH3A, 5, trac 10orf118, TRAF4, and of 1;
the CLEC9A + dendritic cell component is characterized by RGCC, CPVL, CLEC9A, CPNE3, C1orf54, DNASE1L3, SNX3, CCND1, IRF8, LGALS2, CLNK, CST3, NAAA, SERPINB1, PPT1 and XCR 1;
the characteristic genes of the natural killer cell component are GNLY, TYROBP, KLRC1, FCER1G, XCL1, XCL2, KLRD1, CTSW, IFITM3, HOPX, KLRF1, KLRC2, and PRF 1;
the characteristic gene of the plasma cell component is IGJ, XBP, MZB, SSR, DERL, FKBP, HSP90B, ITM2, SEC11, PRDX, FKBP, HERPUD, JUN, SSR, VIMP, SDF2L, SELK, SPCS, MANF, C19orf, SPCS, HSPA, IFI, PPIB, RRBP, SEC61, DNAJB, PIM, SPCS, CD, PDIA, ERLEC, NUCB, TNFRSF, SEC61, LMAN, JSRRP, TMEM258, TMEM, RPN, RABAC, SDC, LGALS, KDELR, CRELD, IFI, SUB, PSAP, GSTP, CD, NPC, TMTXR, ARF, NEAT, KRTCAP, TMED, SELM, PDIA, SLAMF, HM, P4, SRGN, TMED, CD, KDELR, TIBIED, TMTMTMTMTMTMM, and HLA.
The 6 tumor microenvironment components can be used for predicting the prognosis of the nasopharyngeal carcinoma independently, and can also be combined randomly for predicting the prognosis of the nasopharyngeal carcinoma.
In a second aspect of the present invention, there is provided:
use of a reagent for quantifying a marker of a tumor microenvironment component as described in the first aspect of the invention in the preparation of a nasopharyngeal carcinoma prognosis determining reagent.
The expression quantity can be determined by different methods, preferably is subjected to dimensionless processing, and is convenient for data analysis and processing.
In some examples, the agent that quantifies a marker of a component of the tumor microenvironment is an agent that quantifies marker mRNA. The reagent may be other reagent, chip or other method capable of responding to the expression level of marker mRNA.
In some examples, the expression level of each component can be calculated by quantifying the mRNA expression level of the characteristic Gene of each component and performing single-sample Gene Enrichment Analysis (ssGSEA) on the mRNA expression levels of all the characteristic genes of each component. The mRNA expression levels thus determined by the different methods were normalized.
In some examples, the prognosis of nasopharyngeal carcinoma is determined by the expression level of each component.
In a third aspect of the present invention, there is provided:
a system for predicting nasopharyngeal carcinoma prognosis, comprising:
a tumor microenvironment component marker quantifying device for determining the expression level of a tumor microenvironment component marker, wherein the tumor microenvironment component marker is as defined in the first aspect of the present invention;
the data analysis device is used for calculating and determining the prognosis of the nasopharyngeal carcinoma based on the expression quantity of the tumor microenvironment component markers; and
and a result output device for outputting the calculated prognosis result.
In some examples, the quantitative device includes, but is not limited to, conventional mRNA quantitative devices such as an expression chip for quantifying a marker mRNA, an mRNA sequencing device, a qPCR gene detection device, and a Nanostring technology gene detection device.
In some examples, the expression level of each component can be calculated by quantifying the mRNA expression level of the characteristic gene of each component and performing ssGSEA on the mRNA expression levels of all the characteristic genes of each component.
In some examples, the data analysis device computationally determines the prognosis of nasopharyngeal carcinoma based on the amount of expression of components of the tumor microenvironment.
In some examples, the cell cycle proliferative component is at high risk when the expression level is above-1826 and at low risk when below-1826;
the expression level of the macrophage component is higher than 7481 and is judged to be low risk, and the expression level is lower than 7481 and is judged to be high risk;
the expression level of the plasmacytoid dendritic cell component is judged to be low risk when being higher than 4028, and is judged to be high risk when being lower than 4028;
the expression level of CLEC9A + dendritic cell component is determined as low risk when higher than 4286 and high risk when lower than 4286;
the natural killer cell component expression level is judged to be low risk when being higher than 2961 and high risk when being lower than 2961;
the expression level of the plasma cell component is above 7799 and judged as low risk, and below 7799 and judged as high risk.
Other known methods may also be used to determine the specific risk threshold.
The invention has the beneficial effects that:
according to some embodiments of the invention, the expression levels of different components in the nasopharyngeal carcinoma tumor microenvironment can be predicted by calculating the expression levels of the characteristic genes of one tumor cell component and five immune cell components, and the clinical prognosis prediction can be performed on a nasopharyngeal carcinoma patient, so that the individual treatment can be facilitated, and finally, the survival benefit can be brought to the patient.
Drawings
FIG. 1 is a schematic representation of tSNE (T distribution and random neighbor insertion) from 48,584 cells in total from 16 nasopharyngeal carcinoma samples, which can be classified into tumor cells and three major classes of immune cells (myeloid cells, T cells, B cells);
FIG. 2 shows that tumor cells are clustered and grouped by Non-negative matrix factorization (Non-negative matrix factorization) clustering method, and after correlation analysis, the tumor cells are found to be divided into five main components: epithelial differentiation 1, epithelial differentiation 2, epithelial differentiation 3, cell cycle proliferation, cell secretion.
FIG. 3 is a graph showing that the clustering of three main types of immune cells (myeloid cells, T cells, B cells) based on Principal component analysis (Principal component analysis) can differentiate each of the myeloid cells, T cells, and B cells into different components;
FIG. 4 is a graph showing that the expression levels of the respective tumor cell components are obtained by single-sample Gene Set expression Analysis (ssGSEA), the median of the expression levels of each component is taken as a threshold value, each component is divided into a high expression group and a low expression group, the progression-free survival (progression-free survival) of the high expression group compared to the low expression group is analyzed in a cohort of 113 nasopharyngeal carcinoma samples (cohort A), when the risk ratio is greater than 1, the prognosis of the high expression group patient is worse than that of the low expression group patient, when the risk ratio is less than 1, the prognosis of the high expression group patient is better than that of the low expression group patient, and when the square is red, the statistical difference is achieved (P < 0.05).
FIG. 5 shows that the expression levels of the respective immune cell components were obtained by single-sample Gene Set expression Analysis (ssGSEA), and the median of the expression levels of each component was taken as a threshold value, and each component was divided into a high-expression group and a low-expression group, and the progression-free survival (progression-free survival) of the high-expression group compared to the low-expression group was analyzed in a cohort of 113 nasopharyngeal carcinoma samples (cohort A), wherein a case where the risk ratio was greater than 1 means that the prognosis of the high-expression group patients was worse than that of the low-expression group patients, a case where the risk ratio was less than 1 means that the prognosis of the high-expression group patients was better than that of the low-expression group patients, and a case where the square color red means that the statistical difference was achieved (P < 0.05).
FIG. 6 is a graph showing the expression levels of tumor cell components and immune cell components obtained by single-sample Gene Enrichment Analysis (ssGSEA) in an independent cohort of 128 nasopharyngeal carcinoma samples (cohort B), which was divided into a high-expression group and a low-expression group according to the boundary values of the components obtained from cohort A, and analyzed for progression-free survival (progression-free survival) of the high-expression group compared to the low-expression group, in which case a risk ratio greater than 1 means a worse prognosis of the high-expression group compared to the low-expression group, and a risk ratio less than 1 means a better prognosis of the high-expression group compared to the low-expression group, and a red color means a statistically significant difference (P < 0.05).
Detailed Description
The inventor discovers that the tumor microenvironment of the nasopharyngeal darcinoma comprises five tumor cell components and 17 immune cell components by adopting a single-cell mRNA sequencing technology, digs out a characteristic Gene corresponding to each component by systematic bioinformatics calculation, and can predict the expression level of each component in the nasopharyngeal darcinoma tissue by detecting the mRNA expression level of the characteristic Gene of each component and carrying out single-sample Gene Enrichment Analysis (ssGSEA) on the mRNA expression level of the characteristic Gene of each component. Further, the inventor discovers six tumor microenvironment components capable of predicting the clinical prognosis of patients with nasopharyngeal carcinoma by performing survival analysis on the expression level of each component, wherein the six tumor microenvironment components comprise: cell cycle proliferation, macrophages, plasmacytoid dendritic cells, CLEC9A+Dendritic cells, natural killer cells and plasma cells.
The invention will be further illustrated in connection with specific experiments, it being understood that the following is only intended to illustrate the invention and is not intended to limit the scope of the invention.
Component constitution of nasopharyngeal carcinoma tumor microenvironment and characteristic genes corresponding to each component
The expression of gene mRNA from 48,584 cells in 16 nasopharyngeal carcinoma samples was detected by single cell mRNA sequencing and further clustered, and was found to be divided into tumor cell components and immune cell components, wherein the immune cell components include myeloid cells, T-cells and B-cells (FIG. 1). The inventor further carries out clustering and subgroup division on the tumor cell components by a Non-negative matrix factorization (Non-negative matrix factorization) clustering method, and finds that the tumor cells can be divided into five main components after correlation analysis is carried out: epithelial differentiation 1, epithelial differentiation 2, epithelial differentiation 3, cell cycle proliferation, cell secretion (fig. 2). The inventor takes the first 30 genes with the most significant expression difference as characteristic genes for the five tumor cell components respectively, namely, a marker combination capable of predicting the five tumor cell components is formed, as shown in table 1:
TABLE 1 five tumor cell components and their corresponding characteristic genes
For immune cells, the inventors clustered three major classes of immune cells (myeloid cells, T cells, B cells) each based on Principal component analysis (Principal component analysis), and could differentiate each of the myeloid cells, T cells, and B cells into different components (fig. 3). Further, the inventors characterized genes for each immune cell component according to the following principles: the average expression amount of mRNA of the gene in the component needs to be at least 2.5 times larger than that of mRNA in all other components; the gene needs to be expressed in more than 25% of the cells in this fraction, i.e. mRNA expression > 0; the average expression level of mRNA in the component of the gene needs to be larger than the average expression level of mRNA in any other component. Based on the above screening method, a marker combination that can predict these 17 immune cell components was formed, as shown in table 2:
TABLE 2.17 immune cell components and their corresponding characteristic genes
ssGSEA is carried out on the mRNA expression quantity of the characteristic genes of the five tumor cell components and the 17 immune cell components, so that the expression quantity of each component in the tumor tissue of the nasopharyngeal carcinoma can be predicted.
Six nasopharyngeal carcinoma tumor microenvironment components can predict the clinical prognosis of nasopharyngeal carcinoma patients
The inventors analyzed the mRNA expression levels of all the characteristic genes of each component by ssGSEA, and calculated the expression levels of 5 tumor cell components, and the inventors divided each of the 5 tumor cell components into a high expression group and a low expression group by taking the median of the expression levels of each component as a threshold.
The inventor further performs survival analysis on the prognosis prediction effect of each component, firstly, the inventor takes nasopharyngeal carcinoma tumor tissue samples of 113 nasopharyngeal carcinoma patients treated primarily in the center of tumor prevention and treatment of Zhongshan university through nasopharyngeal mirror biopsy before treatment, forms a queue A of the 113 nasopharyngeal carcinoma samples, and performs general mRNA sequencing on each sample to obtain a gene expression profile of each sample. Then, the expression level of each tumor component was calculated according to the above calculation formula, and then, the median was divided into two groups of high and low, and survival analysis was performed to search for the progression-free survival (progression-free survival) of the high expression group compared to the low expression group, and it was found that when the cell cycle proliferative component was highly expressed, the prognosis of the nasopharyngeal carcinoma patients was worse (P <0.05) than that of the low expression group (fig. 4).
The inventors also calculated the expression levels of the 17 immune cell components using ssGSEA, and divided each of the components into high expression and low expression groups using the median of the expression levels of each component as a cut-off.
The inventors performed survival analysis of 17 immune cell components in cohort a consisting of 113 nasopharyngeal carcinoma samples. The inventor calculates the calculation according to the above calculation formulaThe expression level of each immune component was then divided into two groups of high and low by taking the median, and survival analysis was performed to find the progression-free survival (progression-free survival) of the high expression group compared with the low expression group, and macrophages, plasmacytoid dendritic cells, and CLEC9A were found+When the dendritic cell, natural killer cell and plasma cell components are highly expressed, the prognosis of nasopharyngeal carcinoma patients is better than that of patients in the low expression group (P)<0.05) (fig. 5). Meanwhile, the inventor finds MKI67+When B cell components are highly expressed, the prognosis for patients with nasopharyngeal carcinoma is worse than for patients with low expression (P)<0.05) (fig. 5).
To verify the above conclusions, the inventors obtained nasopharyngeal carcinoma tumor tissue samples from 128 additional nasopharyngeal carcinoma patients who were treated first in the center of cancer prevention and treatment of Zhongshan university by nasopharyngeal mirror biopsy before treatment, and formed an independent queue B from the 128 nasopharyngeal carcinoma samples, and performed mRNA chip detection on them to obtain their gene expression profiles. The present inventors also obtained the expression levels of five tumor cell components and 17 immune cell components by ssGSEA method, and performed survival analysis by dividing the expression levels into two groups, i.e., high and low groups, based on the cut-off values of the components obtained from cohort a (fig. 6). The inventors found that there were a total of six components, cell cycle proliferation, macrophages, plasmacytoid dendritic cells, CLEC9A+Dendritic cells, natural killer cells and plasma cells can predict the situation of progression-free survival (progression-free survival) of the nasopharyngeal carcinoma patients in the cohort A and the cohort B, and finally, the six components can effectively predict the clinical prognosis of the nasopharyngeal carcinoma patients.
Claims (4)
1. A tumor microenvironment component marker combination for predicting nasopharyngeal carcinoma prognosis, selected from at least one of a cell cycle proliferative component and five immune cell components, wherein:
the characteristic genes of the cell cycle proliferation component are DEPDC1, DLGAP5, HJURP, PBK, TOP2A, GTSE1, ASPM, CDC20, CEP55, CKAP2L, HMMR, NEK2, BIRC5, CCNA2, MKI67, FAM64A, KIF4A, KIF2C, CENPF, AURKB, KIF14, NUF2, ESCO2, NUSAP1, NCAPG, CDCA3, CDCA5, CENPE, KIF20A and CENPA; when the cell cycle proliferation component is highly expressed, the prognosis of the nasopharyngeal carcinoma patient is worse compared with the nasopharyngeal carcinoma patient in a low expression group;
the five immune cell components are macrophage component, plasmacytoid dendritic cell component, CLEC9A + dendritic cell component, natural killer cell component and plasmacytoid cell component respectively,
the characteristic gene of the macrophage component is APOE, APOC1, RNASE1, CTSL, C1QA, C1QB, C1QC, CTSD, ADAMTC 1, SPP1, FTL, NUPR1, GPNMB, FCGR3A, CCL8, PLD3, LGMN, GLUL, CTSC, CD163, PSAP, CTSB, CCL3, HES1, MMP9, MS4A4A, IFIT1, ACP5, PLA2G7, CD68, MAFB 14, IFI6, TREM2, MS4A7, PRDX1, LS1, LGAAH 3, CCL4, IFI27, MARCKS, CREG1, CD81, CCL 40A1, CTSS, FCER1 SLC 1G, CXER 9; when the macrophage component is highly expressed, the prognosis of the nasopharyngeal carcinoma patient is better compared with that of the patient in a low expression group;
the characteristic genes of the plasmacytoid dendritic cell component are PTGDS, GZMB, IGJ, TCL1A, LILRA4, PLAC8, ITM2C, IRF7, PPP1R14B, TCF4, TSPAN13, CLIC3, SELL, PLD4, UGCG, CCDC50, C12orf75, BCL11A, MZB1, PTCRA, SPIB, LRRC26, SMPD3, MAP1A, ALOX5AP, SCT, PTPRS, IL3RA, APP, CYB561a3, SEC61B, SPCS1, CLEC4C, SLC15A4, HIGD1A, NUCB2, MPEG1, LTB, GAPT, IDH3A, 5, C10orf118, oftraf 4 and LAMP 1; when the plasmacytoid dendritic cell component is highly expressed, the prognosis of the nasopharyngeal carcinoma patient is better compared with that of the patient in a low expression group;
the CLEC9A + dendritic cell component is characterized by RGCC, CPVL, CLEC9A, CPNE3, C1orf54, DNASE1L3, SNX3, CCND1, IRF8, LGALS2, CLNK, CST3, NAAA, SERPINB1, PPT1 and XCR 1; the CLEC9A+When the dendritic cell component is highly expressed, the prognosis of patients with nasopharyngeal carcinoma is better than that of patients in a low expression group;
the characteristic genes of the natural killer cell component are GNLY, TYROBP, KLRC1, FCER1G, XCL1, XCL2, KLRD1, CTSW, IFITM3, HOPX, KLRF1, KLRC2, and PRF 1; when the natural killer cell component is highly expressed, the prognosis of the nasopharyngeal carcinoma patient is better than that of the patient in a low expression group;
the characteristic gene of the plasma cell component is IGJ, XBP, MZB, SSR, DERL, FKBP, HSP90B, ITM2, SEC11, PRDX, FKBP, HERPUD, JUN, SSR, VIMP, SDF2L, SELK, SPCS, MANF, C19orf, SPCS, HSPA, IFI, PPIB, RRBP, SEC61, DNAJB, SPCS, CD, PDIA, ERLEC, NUCB, TNFRSF, SEC61, LMAN, JSRP, TMEM258, TMEM, RPN, RABAC, SDC, LGALS, KDELR, CRELD, IFI, PSAP, GSTP, CD, NPC, TMPIM, TMARF, NEAT, KRTCAP, TMED, SELM, PDIA, SLAMF, HM, P, SRGN, TMED, CD, KDELR, TRAMP, HLA, TIBIM, TMTXED, and TMTXED; when the plasma cell component is highly expressed, the prognosis of patients with nasopharyngeal carcinoma is better than that of patients in the low expression group.
2. The application of the reagent for quantifying the mRNA expression quantity of the tumor microenvironment component marker combination in the preparation of the nasopharyngeal carcinoma prognosis determination reagent is characterized in that: the tumor microenvironment component marker combination of claim 1.
3. Use according to claim 2, characterized in that: the expression level of each component can be calculated by quantifying the mRNA expression level of the characteristic gene of each component and performing single-sample gene enrichment analysis on the mRNA expression level of all the characteristic genes of each component.
4. Use according to claim 3, characterized in that: determining the prognosis of nasopharyngeal carcinoma according to the expression quantity of each component.
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