WO2023284789A1 - Molecular marker group of human esophageal squamous cell carcinoma and application of molecular marker group - Google Patents

Abstract

Provided are a molecular marker group of a human esophageal squamous cell carcinoma and an application of the molecular marker group. The molecular marker group is: a molecular marker group for the esophageal squamous cell carcinoma to be divided into a differentiated type, an immunogenic type, a metabolic type, and a stemness type: the differentiated type: LCE3D, CDSN, KLK5, SPRR2G, and DSG1; the immunogenic type: MS4A1, CD79A, CXCL9, MZB1, and IDO1; the metabolic type: GSTA1, ADH7, UGT1A3, and ALDH3A1; and the stemness type: WFDC2, PEG10, SFRP1, LGR6, and VWA2; and an NK cell surface molecular marker group for the esophageal squamous cell carcinoma to be divided into poor prognosis and drug insensitive subtypes.

Description

Molecular marker panel and its application in human esophageal squamous cell carcinoma technical field

The invention belongs to the technical field of medicine and biology, and specifically relates to a molecular marker group of human esophageal squamous cell carcinoma and its application.

Background technique

Esophageal cancer (EC) is a serious and rapidly progressive neoplastic disease. As of 2018, it is one of the tumors with the highest mortality rate (509,000 cases per year) and highest incidence rate (572,000 new cases per year) in the world (Bray et al., 2018). Global morbidity and mortality from EC are projected to continue to increase in the coming decades (Bray et al., 2018; Malhotra et al., 2017). The highest prevalence of EC occurs in Asia and Africa, where the most common subtype is esophageal squamous cell carcinoma (ESCC), while adenocarcinoma is more common in North America and Western Europe (Bray et al, 2018).

Despite some progress in treatment options, including novel targeted therapies and cancer immunotherapies, the prognosis of ESCC remains poor, with a five-year survival rate of <15% (Abnet et al., 2018; Smyth et al., 2017). The main challenge in ESCC treatment is the invasion and late diagnosis of tumor cells. Therefore, studying the molecular characteristics of ESCC to identify biomarkers for early diagnosis and key molecular markers affecting disease prognosis is crucial for early intervention and improved treatment strategies.

Several major international studies have made important progress in identifying the molecular landscape of ESCC and understanding the molecular mechanisms (Cui et al., 2020; Frankell et al., 2019; Sawada et al., 2016; Song et al., 2014; Wu et al., 2014; Yan et al. , 2019). They highlighted common dysregulation of RTK/RAS/PI3K and WNT/Notch pathways, cell cycle regulation, frequently mutated genes such as TP53, FAT1, NOTCH1, KMT2D, NFE2L2, and ZNF750, and epigenetic alterations in ESCC (Cao et al., 2020) . However, the genetic events associated with the heterogeneous behavior of ESCC are still poorly understood, resulting in the lack of reliable biomarkers for predicting prognosis or designing effective targeted therapy regimens for clinical regimen selection. Furthermore, the precise immune evasion mechanisms of ESCC have not been fully revealed, and no effective immunotherapy options are available for ESCC, even though immunotherapeutic drugs will be incorporated into standard systemic treatment options for ESCC in the near future (Kojima et al., 2020).

Therefore, comprehensive multi-omics studies of ESCC are needed to decipher the molecular and immune heterogeneity to thoroughly understand the pathogenesis of the disease and to discover molecular changes that are strongly associated with the prognosis of esophageal cancer, especially for patients from regions with the highest incidence of ESCC. patient.

[references]

1Bray,F.et al.Global cancer statistics 2018:GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J Clin 68,394-424,doi:10.3322/caac.21492(2018).

2 Malhotra, G.K. et al. Global trends in esophageal cancer. J Surg Oncol 115, 564-579, doi: 10.1002/jso.24592 (2017).

3Cui,Y.et al.Whole-genome sequencing of 508 patients identifies key molecular features associated with poor prognosis in esophageal squamous cell carcinoma.Cell Res,doi:10.1038/s41422-020-0333-6(2020)

4 Frankell, A.M. et al. The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic. Nat Genet 51, 506-516, doi: 10.1038/s41588-018-0331-5 (2019).

5 Sawada, G. et al. Genomic Landscape of Esophageal Squamous Cell Carcinoma in a Japanese Population. Gastroenterology 150, 1171-1182, doi:10.1053/j.gastro.2016.01.035(2016).

6 Song, Y. et al. Identification of genomic alterations in oesophageal squamous cell cancer. Nature 509, 91-95, doi: 10.1038/nature13176 (2014).

7Wu,C.et al.Joint analysis of three genome-wide association studies of esophageal squamous cell carcinoma in Chinese populations.Nat Genet 46,1001-1006,doi:10.1038/ng.3064(2014).

8Yan,T.et al.Multi-region sequencing unveils novel actionable targets and spatial heterogeneity in esophageal squamous cell carcinoma.Nat Commun 10,1670,doi:10.1038/s41467-019-09255-1(2019).

9Cao,W.et al.Multi-faceted epigenetic dysregulation of gene expression promotes esophageal squamous cell carcinoma.Nat Commun 11,3675,doi:10.1038/s41467-020-17227-z(2020).

10 Kojima, T. et al. Randomized Phase III KEYNOTE-181 Study of Pembrolizumab Versus Chemotherapy in Advanced Esophageal Cancer. J Clin Oncol, JCO2001888, doi: 10.1200/JCO.20.01888 (2020).

Contents of the invention

The present invention firstly relates to the application of a group of molecular markers in the preparation of diagnostic kits, characterized in that,

The diagnostic kit divides esophageal squamous cell carcinoma (ESCC) into four molecular types: differentiated, immunogenic, metabolic, and stemness;

The relationship between the molecular markers and the molecular typing of the ESCC is as follows:

Differentiated: High expression of LCE3D, CDSN, KLK5, SPRR2G and DSG1;

Immunogenic: high expression of MS4A1, CD79A, CXCL9, MZB1 and IDO1;

Metabolic: high expression of GSTA1, ADH7, UGT1A3 and ALDH3A1;

Stemness: High expression of WFDC2, PEG10, SFRP1, LGR6 and VWA2.

The present invention also relates to the application of a group of molecular markers in the preparation of diagnostic kits, characterized in that,

The diagnostic kit is used to identify poor prognosis and/or drug-insensitive subtypes of esophageal squamous cell carcinoma (ESCC);

The molecular markers are: NK cell surface markers or stem cell markers;

Preferably, the molecular marker is any combination of the following genes: XCL1, XCL2, CD160 and LGR6;

The identification is: detecting the high expression of the molecular marker.

The present invention also relates to a detection kit for identifying the stemness subtype of esophageal squamous cell carcinoma (ESCC), the kit includes detection of gene expression levels of WFDC2, SFRP1, LGR6, VWA2 and XCL1 Reagent, described detection reagent is preferably qRT-PCR, and the primers of each gene are respectively:

WFDC2

SEQ ID NO.1: Upstream primer: 5'-CTGCCCAATGATAAGGAGGGT-3'

SEQ ID NO.2: Downstream primer: 5'-TTGCGGCAGCATTTCATCTG-3'

VWA2

SEQ ID NO.3: Upstream primer: 5'-CTGCACACTGTCCCCTTCTACA-3'

SEQ ID NO.4: Downstream primer: 5'-GGTAGCCGTCCAGTCCTTCT-3'

SFRP1

SEQ ID NO.5: Upstream primer: 5'-TGGCCCGAGATGCTTAAGTG-3'

SEQ ID NO.6: Downstream primer: 5'-CCTCAGTGCAAACTCGCTGG-3'

LGR6

SEQ ID NO.7: Upstream primer: 5'-TGGGAAGACCAAGGTTGACAC-3'

SEQ ID NO.8: Downstream primer: 5'-AGAGAGACGCAGCTCCTCCAA-3'

XCL1

SEQ ID NO.9: Upstream primer: 5'-TGCTCTCTCACTGCATACATTG-3'

SEQ ID NO.10: Downstream primer: 5'-TGGTGTAGGTCTTGATTCTGCT-3'.

The present invention also relates to a medicine for treating esophageal squamous cell carcinoma (ESCC),

The subtype of esophageal squamous cell carcinoma (ESCC) is a subtype with high expression of NK cell surface markers;

The drug is a drug that blocks XCL1, XCL2, and CD160; preferably, the drug is LCL-161, and its structure is shown in the following formula:

Preferably, the medicine also includes: necessary pharmaceutical excipients.

The beneficial effect of the present invention is that,

(1) We performed a comprehensive genomic and deep transcriptomic analysis of tumors matched to normal tissues in untreated ESCC patients who were followed up for more than four years after surgical resection.

(2) We explored transcriptome subtypes and distinct immune microenvironments, and discovered novel tumor-intrinsic immune escape mechanisms. These data were subsequently combined to provide a robust set of prognostic biomarkers.

(3) Our study broadens the knowledge of the molecular and histological diversity of ESCC and provides new potential therapeutic targets for the treatment of ESCC.

Description of drawings

Figure 1. Transcriptome typing and identification of ESCC,

1A, NMF clustering and typing results of genome-wide expression data of 120 cases of esophageal squamous cell carcinoma;

1B, each typed sample has different cytological characteristics;

1C. Survival analysis results of each subtype;

1D. The groups with high expression of stem-type characteristic genes had poor survival.

Figure 2. Immune cell marker typing and association analysis of ESCC,

2A. Immunoassay typing results;

The expression levels of XCL1 and XCL2 genes in samples of 2B and C3 types were significantly higher than those of the other two types;

2C, High levels of B cells and NK cells are associated with poor prognosis in esophageal cancer;

2D, local sample set (China) and TCGA sample set, the prognosis of ESCC patients distinguished by NK cell markers showed significant differences;

Among the 2E and C3 immune types, the Stemness transcriptome genotype accounted for the highest proportion;

In samples from patients with 2F and C3 immune types, the expression of NK cell marker genes such as XCL1, XCL2 and CD160 and the representative gene LGR6 of cell stem type showed a significant positive correlation;

2G. Immunohistochemical analysis of the co-expression of LGR6, XCL1 and CD160 was performed on the tumor samples.

Figure 3. XCL1 gene expression and drug sensitivity analysis of esophageal squamous cell carcinoma

3A. The median value of XCL1 expression can divide esophageal squamous cell lines into two categories;

3B. Cell lines with high XCL1 expression are not sensitive to 5-fluorouracil;

3C. After overexpressing XCL1 in XCL1 low-expressing cell lines, the sensitivity to 5-fluorouracil is significantly reduced;

3D. Results of drug activity screening on XCL1 high-expression cell lines.

detailed description

Example 1. Whole-transcriptome analysis and typing, prognosis analysis and verification of esophageal squamous cell carcinoma (ESCC)

Collect 120 surgical specimens of esophageal squamous cell carcinoma (ethics review number of the Ethics Committee of the First Affiliated Hospital of Zhengzhou University: 2019-KY-51), and perform whole-transcriptome sequencing to ensure that each sample produces more than 5Gb of data (number of bases) ), the sequencing data was processed using Salmon software to repost the transcript data of version 37 of the human genome and count and quantify each gene.

The gene quantitative data of each sample was combined into a matrix, and only the 1,500 genes with the largest average absolute deviation among individuals were retained, and non-negative matrix factorization (NMF) cluster analysis was performed. The optimal cluster analysis results were determined by the maximum state Correlation coefficients and validation conditions in the three datasets were determined. The selection of characteristic genes compares the current typing with other samples, and uses limma software for differential gene analysis to find out highly expressed genes in the typing, requiring the multiple of difference to be more than 1. Gene enrichment analysis (GSEA) was performed on the differential genes of each subtype to obtain the most relevant (p<0.001) gene set for the subtype.

The results are shown in Figure 1A. The whole genome expression data of 120 cases of esophageal squamous cell carcinoma were classified into four subtypes by NMF clustering. According to the gene enrichment analysis of each subtype, the related gene sets were divided into four subtypes. Named respectively:

Differentiated (Differentiated), representative genes are LCE3D, CDSN, KLK5, SPRR2G and DSG1, etc.;

Immunogenic, representative genes are MS4A1, CD79A, CXCL9, MZB1 and IDO1, etc.;

Metabolic, representative genes are GSTA1, ADH7, UGT1A3 and ALDH3A1, etc.; and

Cell stemness, representative genes are WFDC2, PEG10, SFRP1, LGR6, and VWA2.

Hematoxylin-eosin (HE) stained slides showed that each typed sample had different cytological characteristics (Fig. 1B).

In order to investigate the prognostic value between different subtypes, 120 patients were followed up, and finally the follow-up information of 109 patients was obtained, and Kaplan-Meier curve analysis was performed combining clinicopathological characteristics such as age, gender, smoking, alcohol consumption, tumor stage and grade and COX multivariate analysis to determine whether there were differences in survival among the individual analyses. The results of the survival analysis are shown in Figure 1C. The results showed that there were significant differences in the prognosis among the various subtypes, especially the patients with the stem type had the shortest long-term survival.

In order to verify the prognostic value of stemness subtypes, four representative genes WFDC2, VWA2, SFRP1 and LGR6 and GAPDH were selected as reference genes to design qRTPCR primers (sequence structure of primers). Quantification of gene expression was performed on 65 samples of another sample set , and three PCR reactions were performed for each gene in each sample, and the gene CT value was the average value of the three experiments (see Table 2 for the original CT data of qRTPCR results). Calculate the difference between each gene and the GAPDH expression CT value - delta CT value is used as the expression level of each gene, and the expression levels of the four genes are summed to represent the cell stem type value of a sample, according to the cell stem type value The samples were divided into high and low groups, and Kaplan-Meier curve analysis and COX multivariate survival analysis were performed to determine its relationship with survival.

Table 1. Q-PCR expression data of representative genes of cell stem type typing and primer list of control genes

Gene	upstream primer sequence	downstream primer sequence
WFDC2	5'-CTGCCCAATGATAAGGAGGGT-3'	5'-TTGCGGCAGCATTTCATCTG-3'
VWA2	5'-CTGCACACTGTCCCTTCTACA-3'	5'-GGTAGCCGTCCAGTCCTTCT-3'
SFRP1	5'-TGGCCCGAGATGCTTAAGTG-3'	5'-CCTCAGTGCAAACTCGCTGG-3'
LGR6	5'-TGGGAAGACCAAGGTTGACAC-3'	5'-AGAGAGACGCAGCTCCTCCAA-3'
GAPDH	5'-GACTGTGGATGGCCCCTCCGG-3'	5'-AGGTGGAGGAGTGGGTGTCGC-3'

We performed RTPCR quantitative analysis of the expression of cell stemness characteristic genes in different sample sets to analyze their prognostic correlations, and found that groups with high cell stemness gene expression had poor survival (Figure 1D), with significant statistical differences.

Table 2, Q-PCR expression data of representative genes of stem type typing of 65 samples

Example 2. Immunotyping and Analysis of Esophageal Squamous Cell Carcinoma (ESCC)

Many different gene signatures are used to analyze the tumor microenvironment and immune cells, but their performance is very different. We selected 6 different gene signatures, including Timer, MCP-count, Danaher, xCell, Davoli, and Rooney. Methods to assess the immune microenvironment of the esophageal squamous cell carcinoma cohort (120 samples) also from embodiment 1, determine the immune cell type of esophageal squamous cell carcinoma by correlation analysis with immunohistochemical results, and then use the consensus clustering method to analyze the immune microenvironment of the esophagus The immune microenvironment clustering was carried out for squamous cell carcinoma, and the relevant parameters were set as aggregation hierarchical clustering and Pearson correlation distance and 50 times of resampling. After a comprehensive comparison of the prediction capabilities of various software for esophageal squamous cell carcinoma immune cells, we determined the prediction and analysis method of CD4+ T cells based on Danaher combined with Davoli, and finally determined 13 related immune cell types. Using these three types of immune cells to perform cluster analysis on esophageal squamous cell carcinoma, 120 local samples of esophageal squamous cell carcinoma can be divided into three immune subtypes: C1 (hot immune type), C2 (immune intermediate type) and C3 (cold immune type). ), the results of immunoassay typing are shown in Figure 2A. The best cluster typing results are jointly determined by the consensus matrix and the cluster tracking plot (based on transcriptome data). Immune cell clustering was determined using Pearson correlation and mean clustering. The immunophenotyping results were also verified using MCP-counter immune cell feature analysis.

XCL1 and XCL2 are the marker genes of NK cells. Through the Wilcox rank-sum test (Wilcoxon Rank-sum test), we compared the distribution of XCL1 and XCL2 among the three identified immune subtypes to determine whether they are clustered with immune subtypes. Class results are consistent. The results are shown in FIG. 2B . It can be seen that the expression levels of XCL1 and XCL2 genes in the samples of C3 type are significantly higher than those of the other two types. This suggests that we can further analyze the prognosis of ESCC patients with the level of immune cell markers.

For the prognostic value of each immune cell, we used Kaplan-Meier curve analysis and COX multivariate analysis to determine whether there is a survival difference between each analysis. The hazard ratio, 95% confidence interval and P value of each cell were statistically analyzed and Cells are sorted from small to large hazard ratios. The results are shown in Figure 2C. High levels of B cells and NK cells are associated with poor prognosis of esophageal cancer. The higher the level of CD8+T cells, the better the prognosis of patients with esophageal cancer. Further, the level of NK cells higher than 2.02 is associated with poor prognosis of esophageal cancer. Prognostic markers.

In order to clarify whether NK cells are verified in different data sets, we used the same method to analyze the immune cell markers in the 120 local samples from Example 1 and the data from TCGA (90 cases) (for In the processing of TCGA data, the level of NK cells was divided into high and low groups according to the cut-off value of 0.658), and then Kaplan-Meier curve analysis was used to carry out its survival prediction value, the results are shown in Figure 2D, the results show that in the implementation Both the local sample set (China) and the TCGA sample set of Example 1 showed significant differences in the prognosis of ESCC patients differentiated by NK cell markers.

In order to investigate whether there is a correlation between typing based on gene expression characteristics and immune typing, we put the two typing results together for comparison, and examined the differentiation type, immune type, metabolic type and The distribution of the stem-type samples was analyzed statistically. It was concluded that among the C3 immune types, the Stemness transcriptome genotype accounted for the highest proportion (Figure 2E).

LGR6 is the representative gene of the cell stem type determined in Example 1. We calculated the Pearson correlation between its expression level and the expression of NK cell characteristic genes and performed a fitting linear plot. The results are shown in Figure 2F. It can be seen that in C3 immune In samples from patients with type 2, the expression of NK cell marker genes such as XCL1, XCL2, and CD160 and the representative gene LGR6 of cell stem type showed a significant positive correlation.

Finally, the co-expression of LGR6, XCL1 and CD160 was further analyzed by serial sections for immunohistochemical analysis of tumor samples. CD160 has a certain expression distribution in immune cells and tumor cells.

The above results show that the immunotypes of ESCC patients with stem cells are relatively consistent, and they all belong to the immune type with high expression of NK cell markers (C3 subtype), and the prognosis analysis results also show that the two types also have poor Prognostic outcome.

Example 3, Differences in Drug Sensitivity of Different Types of ESCC Subtypes

The RNA-seq gene expression data of 22 cell lines of esophageal squamous cell carcinoma were downloaded from the CCLE database, and the expression levels of XCL1 were grouped according to the median value for differential gene analysis, and the expression levels of the stem-type esophageal squamous cell carcinoma markers LGR6 and XCL1 were analyzed Perform correlation analysis. The results showed that according to the median value of XCL1 expression, esophageal squamous cell carcinoma cell lines could be divided into 11 low-expression group cell lines and 11 high-expression group cell lines (Figure 3A), and the expression levels were significantly different (t test p value less than 0.05) There are 97 genes in total, and the results of differential hierarchical clustering using these 97 differential genes show that XCL1 high-expression cell lines and low-expression cell lines can be perfectly aggregated into two subgroups by using the 97 differences, and Pearson correlation analysis It indicated that the expression level of XCL1 was significantly positively correlated with LGR6 (r:0.59) (Fig. 3B).

The XCL1 high expression cell lines KYSE-30, KYSE-140, KYSE-510, KYSE-520 and XCL1 low expression cell lines KYSE-180, KYSE-270, KYSE450, KYSE-70, KYSE-150, A total of 10 cell lines of KYSE410 were tested for killing by 5-fluorouracil drug. The specific experimental process is as follows:

(1) Cell preparation: Digest logarithmic phase cells with trypsin, resuspend in 10% DMD, the final concentration is 4.4x104cells/ml, add to 96-well plate according to the concentration of 4000 cells per well, add to the upper, right and lower wells Add 100μl PBS to the left well and add 10% DMEM as blank control.

(2) After culturing for 24 hours, dilute the drug with 10% DMEM to a concentration of 10×, add 10 μl of the drug into the 96-well plate according to the drug concentration from high to low, and the rightmost cell well is a negative control without adding drug.

(3) Cultivate for 72 hours in a 37°C incubator with 5% CO ₂ concentration. Under dark conditions, mix MTS and PMS at a ratio of 20:1, then add 20 μl to all wells except PBS, and place in a CO ₂ incubator at 37°C for 3 hours;

(4) MTS and PMS form a stable solution within the reaction time, and read the OD value of each well at a wavelength of 490 nm with a microplate reader;

(5) According to the cell viability, use Graphpad Prism 5 to calculate the half-inhibitory concentration (IC50).

Further, we used the XCL1 low expression cell line KYSE-150 to construct an XCL1 overexpression cell line and then performed the same drug killing experiment. The overexpression cell line construction process is as follows:

(1) Use GENEWIZ to synthesize human XCL1 cDNA and clone it into lentiviral vector;

( ² ) Add 1x105 cells to a 24-well plate, use MOI (multiplicity of infection) = 50 to infect cloned XCL1 lentivirus or uncloned XCL1 lentivirus, and use puromycin (puromycin) to perform cell selection after culturing for 72 hours. The expression level of XCL1 was quantitatively determined by qRTPCR, and the primers were designed as follows:

Upstream primer: 5'-TGCTCTCTCACTGCATACATTG-3'

Downstream primer: 5'-TGGTGTAGGTCTTGATTCTGCT-3'

After obtaining the KYSE-150 cell line overexpressing XCL1, the above killing experiment was repeated.

The results showed that the 5-fluorouracil drug sensitivity test results showed that the XCL1 high-expression cell line was not sensitive to 5-fluorouracil (Figure 3C), and the same conclusion was also verified in the KYSE-150 cell line overexpressing XCL1 (Figure 3D) .

Finally, we further conducted a comparative analysis of the XCL1 high expression and low expression groups on the 367 drug killing sensitivities of GDSC (Genomics of Drug Sensitivity in Cancer, https://www.cancerrxgene.org), and some of the activities with large differences The drug activity screening results are shown in FIG. 3E , which indicates that esophageal squamous cell carcinoma with high expression of XCL1 is more sensitive to LCL-161 (the structural formula is shown below).

Finally, it should be noted that the above embodiments are only for those skilled in the art to understand the essence of the present invention, and are not intended to limit the protection scope of the present invention.

Claims (6)

1. The application of a group of molecular markers in the preparation of diagnostic kits is characterized in that,

   The diagnostic kit divides esophageal squamous cell carcinoma (ESCC) into four molecular types: differentiated, immunogenic, metabolic, and stemness;

   The relationship between the molecular markers and the molecular typing of the ESCC is as follows:

   Differentiated: High expression of LCE3D, CDSN, KLK5, SPRR2G and DSG1;

   Immunogenic: high expression of MS4A1, CD79A, CXCL9, MZB1 and IDO1;

   Metabolic: high expression of GSTA1, ADH7, UGT1A3 and ALDH3A1;

   Stemness: High expression of WFDC2, PEG10, SFRP1, LGR6 and VWA2.
2. The application of a group of molecular markers in the preparation of diagnostic kits is characterized in that,

   The diagnostic kit is used to identify poor prognosis and/or drug-insensitive subtypes of esophageal squamous cell carcinoma (ESCC);

   The molecular markers are: NK cell surface markers;

   The identification is: detecting the high expression of the molecular marker.
3. The application according to claim 2, wherein the molecular marker is any combination of the following genes: XCL1, XCL2, CD160 and LGR6.
4. A detection kit for identifying the cell stem subtype of esophageal squamous cell carcinoma (ESCC), characterized in that the kit includes detection reagents for detecting the expression of WFDC2, XCL1, SFRP1, LGR6 and VWA2 genes;

   Preferably, the detection reagents are qRTPCR primers, and the primers are respectively:

   WFDC2

   SEQ ID NO.1: Upstream primer: 5'-CTGCCCAATGATAAGGAGGGT-3'

   SEQ ID NO.2: Downstream primer: 5'-TTGCGGCAGCATTTCATCTG-3'

   VWA2

   SEQ ID NO.3: Upstream primer: 5'-CTGCACACTGTCCCCTTCTACA-3'

   SEQ ID NO.4: Downstream primer: 5'-GGTAGCCGTCCAGTCCTTCT-3'

   SFRP1

   SEQ ID NO.5: Upstream primer: 5'-TGGCCCGAGATGCTTAAGTG-3'

   SEQ ID NO.6: Downstream primer: 5'-CCTCAGTGCAAACTCGCTGG-3'

   LGR6

   SEQ ID NO.7: Upstream primer: 5'-TGGGAAGACCAAGGTTGACAC-3'

   SEQ ID NO.8: Downstream primer: 5'-AGAGAGACGCAGCTCCTCCAA-3'

   XCL1

   SEQ ID NO.9: Upstream primer: 5'-TGCTCTCTCACTGCATACATTG-3'

   SEQ ID NO.10: Downstream primer: 5'-TGGTGTAGGTCTTGATTCTGCT-3'.
5. A kind of medicine that is used for the treatment of esophageal squamous cell carcinoma (ESCC), it is characterized in that, the subtype of described esophageal squamous cell carcinoma (ESCC) is the high expression subtype of NK cell surface marker; Described medicine is For the medicine of blocking XCL1, XCL2, CD160, preferably, described medicine is LCL-161, and its structure is shown in the following formula:

   
6. A kind of medicine for the treatment of esophageal squamous cell carcinoma (ESCC), is characterized in that, the subtype of described esophageal squamous cell carcinoma (ESCC) is the high expression subtype of NK cell surface marker; Described medicine also includes treatment Effective amount of compound LCL-161 and necessary pharmaceutical auxiliary materials.

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