CN103243161A - Product for performing assisted prediction on postoperative survival time length of esophageal squamous carcinoma patient - Google Patents

Abstract

The invention discloses a product for performing assisted prediction on postoperative survival time length of an esophageal squamous carcinoma patient. The product comprises substances for detecting 178 miRNA expression quantity substances comprising hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p and hsa-miR-205-5p, and records a carrier with the diagnostic criteria and functional expressions as follows: if 0.94dig is less than dip, the postoperative survival time of the esophageal squamous carcinoma patient to be tested is more than 5 years, and if the 0.94dig is more than or equal to dip, the postoperative survival time of the esophageal squamous carcinoma patient to be tested is less than 5 years. After the result of the postoperative survival time of the esophageal squamous carcinoma patient is predicted by using the product, more accurate and effective treatment is adopted, and the patient condition can be effectively improved. In addition, the medicine which influences the expression quantities of hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p and hsa-miR-205-5p can be used for treating the esophageal squamous carcinoma.

Description

Product for assisting in predicting postoperative survival time of esophageal squamous carcinoma patient

Technical Field

The invention relates to a medical diagnosis product, in particular to a product for assisting in predicting the postoperative survival time of an esophageal squamous cell carcinoma patient.

Background

Esophageal cancer is the eighth malignancy worldwide with mortality ranking sixth among all cancers. There are two pathological types of esophageal cancer: squamous cell carcinoma of adenocarcinoma. Currently, TNM staging provides an important basis for clinical prediction of survival of esophageal squamous cell carcinoma patients. However, clinicians have found that patient prognosis for the same clinical stage and similar treatment strategies can vary widely. This suggests that the current clinical staging, which is primarily based on anatomical features of the tumor, is not sufficiently accurate as a prognostic indicator. Studies over the last decade have revealed heterogeneity of tumors. Different alterations at the molecular and genetic levels are more important factors in determining the prognosis of cancer patients. Some studies have found mRNA and protein markers associated with the prognosis of patients with esophageal squamous cell carcinoma, but none have proven to be sufficiently reliable and stable for clinical use. Therefore, it is very necessary to find a new prognostic marker for esophageal squamous carcinoma.

microRNA (miRNA) is RNA of a large class of small non-coding proteins widely existing in animals and plants, has the length of 18-25 nucleotides, is well conserved in species evolution, has tissue specificity and time sequence specificity in expression, and has the function of negatively regulating gene expression so as to regulate basic physiological processes of metabolism, proliferation, differentiation, apoptosis and the like of cells. Thus, alterations in mirnas must lead to several serious pathological processes. Research has proved that miRNA plays the role of oncogene or cancer suppressor gene in the generation and development of tumor, the expression profile of miRNA can be used for the diagnosis, staging and prognosis judgment of some tumors, and has more superiority than mRNA in tumor classification.

Kong et al reported that low expression of miR-375 was associated with a later stage and a poor prognosis in patients with esophageal squamous cell carcinoma. Our past studies found that upregulation of miR-92a expression was significantly associated with poor prognosis in patients with esophageal squamous carcinoma. In addition, the low expression of miR-150 is reported to be related to the poor prognosis of patients with esophageal squamous carcinoma. The classifier composed of a plurality of markers is more advantageous than a single marker in the aspect of survival prediction, and the prediction value is more reliable and has more clinical popularization value due to the fact that the statistical method and the verification process used by the classifier are found. The effects of miRNA prognostic classifiers have been reported in a variety of tumors such as lung cancer, nasopharyngeal cancer, and leukemia. In non-small cell lung cancer patients, a prognostic classifier of 5 mirnas found in the training set of patients was validated in both the training and independent test sets of patients. Strict verification of the prognosis classifier ensures repeatability of the prediction effect. At present, no miRNA composition classifier capable of stably predicting prognosis of esophageal squamous carcinoma patients is found.

Disclosure of Invention

The invention aims to provide a product for predicting or assisting in predicting the postoperative survival time of an esophageal squamous carcinoma patient, which contains a carrier recording the following diagnostic standard and a functional formula:

if 0.94d_ig<d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is long; the postoperative survival time is longer than 5 years after the esophageal squamous cell carcinoma patient to be detected carries out esophageal squamous cell carcinoma resection;

if 0.94d_ig≥d_ipThen the operation of the esophageal squamous carcinoma patient is testedThe post-survival time is short; the postoperative survival time is as short as the survival time of the esophageal squamous cell carcinoma patient to be detected after esophageal squamous cell carcinoma excision is less than 5 years;

wherein, ${d_{\mathrm{ig}}}^2=\sqrt{\begin{array}{c}{(X1-5.33922)}^2+{(X2-11.16542)}^2\\ +{(X3-7.780801)}^2+{(X4-13.273)}^2\end{array}};$

${d_{\mathrm{ip}}}^2=\sqrt{\begin{array}{c}{(X1-5.820479)}^2+{(X2-10.83262)}^2\\ +{(X3-7.546922)}^2+{(X4-12.73359)}^2\end{array}};$

the X1 is the assignment of the ranking numbers of the expression quantity of hsa-miR-218-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X2 is the assignment of ranking numbers of the expression quantity of hsa-miR-142-3p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X3 is the assignment of the ranking numbers of the expression quantity of hsa-miR-150-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X4 is the assignment of ranking numbers of the expression quantity of hsa-miR-205-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the 178 miRNAs are RNAs shown in sequences 1-178 in a sequence table;

the hsa-miR-218-5p is RNA shown in a sequence 1 in a sequence table;

the hsa-miR-142-3p is RNA shown in a sequence 2 in a sequence table;

the hsa-miR-150-5p is RNA shown in a sequence 3 in a sequence table;

the hsa-miR-205-5p is RNA shown in a sequence 4 of a sequence table.

The product can also contain a substance for detecting the expression quantity of the 178 miRNAs.

In the above product, the substance for detecting the expression level of the 178 mirnas is a microarray chip on which probes including the 178 mirnas are immobilized.

The invention protects the application of the substance for detecting the expression quantity of 178 miRNAs in preparing products for diagnosing or assisting in diagnosing the postoperative survival time of esophageal squamous cell carcinoma patients.

In the above application, the product contains the vector describing the diagnostic standard and the functional formula.

The invention protects the application of four, any three, any two or any one of the following four medicaments in preparing a product for treating an esophageal squamous cell carcinoma patient: the medicine taking hsa-miR-218-5p as a target point, the medicine taking hsa-miR-142-3p as a target point, the medicine taking hsa-miR-150-5p as a target point and the medicine taking hsa-miR-205-5p as a target point.

The invention protects the application of four, any three, any two or any one of the following four medicaments in preparing a product for treating an esophageal squamous cell carcinoma patient: a drug targeting the target gene of hsa-miR-218-5p, a drug targeting the target gene of hsa-miR-142-3p, a drug targeting the target gene of hsa-miR-150-5p, and a drug targeting the target gene of hsa-miR-205-5 p.

In the product or the application, the substance for detecting the expression quantity of the 178 miRNAs can be a specific primer and a required reagent used for detecting the expression quantity of the miRNAs by a real-time fluorescent quantitative RT-PCR method, and can also be a chip, a probe and a required reagent used for detecting the expression quantity of the miRNAs by a miRNA microarray chip method; in the embodiment of the invention, the substance is specifically miRNA microarray chip "human miRNA V18.08X 60 k" produced by Agilent.

The invention obtains a classifier (or a model) which is composed of 4 miRNAs (namely miRNAs shown in sequences 1-4 of a sequence table) and can predict the postoperative survival time of an esophageal squamous cell carcinoma patient by analyzing the miRNA expression profiles and the survival time data of 119 esophageal squamous cell carcinoma and paracarcinoma normal tissues by random forest and minimum proximity algorithm. By substituting the 4 miRNA expression levels in the cancer tissues of 47 patients with esophageal squamous cell carcinoma with known survival time into the classifier (or model), the coincidence rate of the result of predicting the length of the survival time and the actually measured result is 63.8%. After the result of predicting the postoperative survival time of the esophageal squamous cell carcinoma patient is used, more accurate and effective treatment is adopted, and the condition of the patient can be effectively improved. In addition, the 4 miRNAs can also be target points of future medicines for treating esophageal squamous cell carcinoma, and medicines influencing the expression quantity or action strength of the 4 miRNAs can also be used for treating esophageal squamous cell carcinoma.

Drawings

FIG. 1 is a graph showing survival curves of the high-risk group and the low-risk group in the patients of the test group in example 1.

Detailed Description

The experimental procedures used in the following examples are all conventional procedures unless otherwise specified.

Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.

Example 1 establishment of the method of the invention

1. Acquisition of specimen and survival information

Taking cancer and paracarcinoma normal tissues (frozen by liquid nitrogen and then transferred to a refrigerator at minus 80 ℃ for storage) of 119 primary esophageal squamous carcinoma patients who have received esophageal squamous carcinoma resection at tumor research institute of Chinese academy of medical sciences as specimens; all patients did not receive radiotherapy and chemotherapy before operation; survival information for the patient was obtained by phone follow-up. Each patient received informed consent.

For each specimen, a portion was left to be paraffin-embedded, sectioned, and stained with conventional methods H & E for pathological examination. The pathological characteristics of each specimen were independently examined and agreed by two medical doctors, and the cancer cell ratio of all tumor specimens was over 60%. TNM staging of tumors was performed according to the handbook of tumor staging by the United states cancer Association (seventh edition).

The study was approved by the medical ethics committee of the institute of oncology, national academy of medical sciences.

2. Extraction and purification of total RNA

The cancer and paracancerous normal tissues of 119 patients obtained in step 1 were each subjected to total RNA extraction using Trizol reagent (Invitrogen) and purification using the mirVana miRNA Isolation Kit (Ambion, Austin, TX, USA). The purity and concentration of RNA were determined by the OD260/280 value of a spectrophotometer (NanoDrop ND-1000); the integrity of the RNA was determined by 1% formaldehyde denaturing gel electrophoresis. As a sample to be detected for chip detection.

3. Detection of miRNA expression level

Using a miRNA microarray chip "human miRNA V18.08 × 60 k" (probe for 1887 mature mirnas from miRBase R18.0 database (including 178 mirnas shown in table 2) and 121 mirnas related to personal viruses is fixed on the chip, and each miRNA is set to 30 repeats), according to the instructions of using the chip, detecting the expression level of each miRNA in the sample to be detected in step 2, specifically the following method:

the sample to be tested (100ng total RNA) is labeled with pCp-Cy3 after demethylation; purifying the marked RNA and hybridizing with a probe of miRNA on the chip; the hybridized images were scanned with an Agilent chip scanner, gridded and analyzed using Agilent feature extraction software version 10.10.

Compared with the miRNA expression result detected by real-time fluorescent quantitative PCR, the miRNA expression result detected by the chip has no obvious difference.

4. Data processing, analysis and modeling

1) Data normalization

The original data obtained in step 3 for the expression level of each miRNA in 119 patients were subjected to background subtraction and log-based 2 conversion, followed by excluding more than half of the miRNA that could not be detected in the cancer tissue, and the remaining 178 miRNA data (the names and sequences of which are shown in Table 2 in the sequence listing) were normalized by ranking (Bolstad BM, Irizary RA, amorphous M, Speed TP. A composition of biochemical methods for high density oligonucleotide array based on variable and biological information.2003; 19:185-93.Rudy J, valve F. expression of clinical diagnosis-platform biochemical expression data. BMB expression. CBb. 12: 4671, the results are shown in Table 1.

TABLE 1 data normalization ranking and assignment results

TABLE 2, 178 miRNAs and their sequence numbers in the sequence Listing

The miRNA expression data used in the following steps 2) -7) is obtained by ranking and normalizing 178 miRNA expression data of the same cancer tissue according to the method of step 1), and then determining the assignment of ranking numbers in table l as the miRNA expression of the cancer tissue.

2) Data classification

The 119 patients were divided into two cases according to survival time:

low risk group (good prognosis): the survival time after operation is long, namely the survival time after operation is more than 5 years, and the total number is 47;

high risk group (poor prognosis): the survival time after operation is short, namely the survival time after operation is less than 5 years, and the total number is 72.

119 patients were randomized into a training set (n 60) and a test set (n 59). In the training set, the prognosis was good for 24 patients and poor for 36 patients, and the ratio of the two in the test set was 23: 36.

3) Data screening

And selecting 9 miRNAs related to the post-operation survival time of the patient based on the 178 miRNA expression quantity and survival time length data in the step 1) of the training set by using a Random forest algorithm (document: Schwarz DF, Konig IR, Ziegler A. on safari t0 Random Jungle: a fast evaluation of Random forms for high-dimensional data. bioinformatics.2010:26: 1752-8).

4) Model building and determination

Listing all possible combinations (511 types in total) of 9 miRNAs related to the post-operation survival time of the patient in the step 3), establishing a model for predicting the survival time aiming at a data set of 60 patients of each miRNA combination in the training set of the step 2) by using a minimum proximity algorithm, and determining the model established by the miRNA combinations (hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p and hsa-miR-205-5p, the sequences of which are respectively sequences 1-4 in the sequence table) with the highest prediction accuracy (namely the average value of the accuracy of predicting the patient to be a high-risk group and a low-risk group is 80.5%) as a final model, wherein the model is specifically described as follows:

if 0.94d_ig<d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is long; the postoperative survival time is longer than 5 years after the esophageal squamous cell carcinoma patient to be detected carries out esophageal squamous cell carcinoma resection;

if 0.94d_ig≥d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is short; the postoperative survival time is as short as the survival time of the esophageal squamous cell carcinoma patient to be detected after esophageal squamous cell carcinoma excision is less than 5 years;

wherein, ${d_{\mathrm{ig}}}^2=\sqrt{\begin{array}{c}{(X1-5.33922)}^2+{(X2-11.16542)}^2\\ +{(X3-7.780801)}^2+{(X4-13.273)}^2\end{array}};$

${d_{\mathrm{ip}}}^2=\sqrt{\begin{array}{c}{(X1-5.820479)}^2+{(X2-10.83262)}^2\\ +{(X3-7.546922)}^2+{(X4-12.73359)}^2\end{array}};$

the X1 is the assignment of the ranking numbers of the expression quantity of hsa-miR-218-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X2 is the assignment of the ranking numbers of the expression quantity of the hsa-miR-142-3p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the table 1;

the X3 is the assignment of the ranking numbers of the expression quantity of hsa-miR-150-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

and the X4 is the assignment of the ranking numbers of the expression quantity of the hsa-miR-205-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the 178 miRNA expression quantities of the cancer tissue from small to large in Table 1.

5) Testing of the model

And (3) substituting the expression quantities of hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p and hsa-miR-205-5p in the cancer tissues of the test set (n =59) into the model in the step 4), so that the postoperative survival time of 16 patients is less than 5 years (namely a poor prognosis and high risk group), and the postoperative survival time of 43 patients is more than 5 years (namely a good prognosis and low risk group).

Drawing a survival curve according to the actual survival time of the high-risk group patients; according to the actual survival time of the patients in the low-risk group, a survival curve is drawn, and the result is shown in figure 1. In fig. 1, the abscissa represents the post-operation survival time, and the ordinate represents the survival rate (= number of survivors/total number of persons in the group) in the high-risk group or the low-risk group within a certain survival time. As can be seen from fig. 1, the median survival in the high-risk group was 19.0 months, the median survival in the low-risk group was 37.5 months, and the data differed significantly between the two groups (p = 0.025).

There were no significant differences in the clinical pathology and TNM staging results among patients in the test set (n = 59).

The results of example 1 show that the method of the present invention is more effective than the clinical pathology and TNM staging in predicting the length of post-operative survival of patients with esophageal squamous carcinoma.

Example 2 application of the method of the invention

Taking the cancer tissues of 47 other esophageal squamous carcinoma patients (patients to be detected) who receive esophageal squamous carcinoma resection at the institute of tumor research of Chinese academy of medical sciences, and predicting the postoperative survival time of each patient to be detected according to the following steps:

1. total RNA extraction and reverse transcription

Total RNA was extracted from each cancer tissue of the patients to be tested by the method of step 2 in example 1.

2. Detection of miRNA expression level

The expression levels of 178 miRNAs shown in Table 2 in the cancer tissues of the patients to be tested were detected according to the method of step 3 in example 1.

3. Data normalization processing

Ranking the 178 miRNA expression quantity data of each patient cancer tissue to be tested obtained in the step 2 from small to large to obtain ranking numbers, and then obtaining the expression quantities X1, X2, X3 and X4 of hsa-miR-218-5p, hsa-miR-142-3p, hsa-miR-150-5p and hsa-miR-205-5p according to the assignment of the corresponding ranking numbers in the table 1, wherein if the ranking numbers of the expression quantities of hsa-miR-218-5p in the cancer tissue of a certain patient to be tested in the 178 miRNA expression quantity data of the cancer tissue of the patient are 20 from small to large, then X1 is 2.95898.

4. Substitution model prediction

The results of X1, X2, X3, and X4 obtained in step 3 were respectively substituted into the model of step 3) in example 1, step 4, to obtain the predicted results for each patient, the results of prediction results for which the post-operative survival time was longer than 5 years were denoted as L, the results of prediction results for which the post-operative survival time was shorter than 5 years were denoted as S, and the results are shown in table 3.

5. The post-operative survival time of the patients was recorded from the last follow-up visit and the results are shown in table 3.

Table 3 prediction results and actual follow-up results of postoperative survival time of each patient to be tested

The results in table 3 show that 17 of the results (patient nos. 9, 12, 16, 17, 18, 22, 23, 24, 26, 27, 28, 29, 30, 31, 35, 41, 46) for predicting the length of postoperative survival of patients with esophageal squamous carcinoma using the model established in example l were different from the actual postoperative survival, with a concordance rate of 63.8%.

Claims (7)

1. A product for diagnosing or assisting in diagnosing the length of postoperative survival time of a patient with esophageal squamous carcinoma, which comprises a carrier recording the following diagnostic criteria and functional formulas:

if 0.94d_ig<d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is long; the postoperative survival time is longer than 5 years after the esophageal squamous cell carcinoma patient to be detected carries out esophageal squamous cell carcinoma resection;

if 0.94d_ig≥d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is short; the above-mentionedThe postoperative survival time is as short as the survival time of the patient with esophageal squamous cell carcinoma to be detected after esophageal squamous cell carcinoma excision is less than 5 years;

wherein, ${d_{\mathrm{ig}}}^2=\sqrt{\begin{array}{c}{(X1-5.33922)}^2+{(X2-11.16542)}^2\\ +{(X3-7.780801)}^2+{(X4-13.273)}^2\end{array}};$

${d_{\mathrm{ip}}}^2=\sqrt{\begin{array}{c}{(X1-5.820479)}^2+{(X2-10.83262)}^2\\ +{(X3-7.546922)}^2+{(X4-12.73359)}^2\end{array}};$

the X1 is the assignment of the ranking numbers of the expression quantity of hsa-miR-218-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X2 is the assignment of ranking numbers of the expression quantity of hsa-miR-142-3p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X3 is the assignment of the ranking numbers of the expression quantity of hsa-miR-150-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

the X4 is the assignment of ranking numbers of the expression quantity of hsa-miR-205-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in the 178 miRNA expression quantities in the cancer tissue in Table 1;

TABLE 1

The 178 miRNAs are RNAs shown in sequences 1-178 in a sequence table;

the hsa-miR-218-5p is RNA shown in a sequence 1 in a sequence table;

the hsa-miR-142-3p is RNA shown in a sequence 2 in a sequence table;

the hsa-miR-150-5p is RNA shown in a sequence 3 in a sequence table;

the hsa-miR-205-5p is RNA shown in a sequence 4 of a sequence table.

2. The product of claim 1, wherein: the product contains substances for detecting the expression quantity of the 178 miRNAs.

3. The product according to claim 1 or 2, characterized in that: the substance for detecting the expression quantity of the 178 miRNAs is a microarray chip fixed with probes comprising the 178 miRNAs.

4. And the application of the substance for detecting the expression quantity of the 178 miRNAs in preparing products for diagnosing or assisting in diagnosing the postoperative survival time of the esophageal squamous cell carcinoma patient.

5. Use according to claim 4, characterized in that: the product contains a vector which records the following diagnostic standard and functional formula:

if 0.94d_ig＜d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is long; the postoperative survival time is longer than 5 years after the esophageal squamous cell carcinoma patient to be detected carries out esophageal squamous cell carcinoma resection;

if 0.94d_ig≥d_ipThe postoperative survival time of the esophageal squamous carcinoma patient to be detected is short; the postoperative survival time is as short as the survival time of the esophageal squamous cell carcinoma patient to be detected after esophageal squamous cell carcinoma excision is less than 5 years;

wherein, ${d_{\mathrm{ig}}}^2=\sqrt{\begin{array}{c}{(X1-5.33922)}^2+{(X2-11.16542)}^2\\ +{(X3-7.780801)}^2+{(X4-13.273)}^2\end{array}};$

${d_{\mathrm{ip}}}^2=\sqrt{\begin{array}{c}{(X1-5.820479)}^2+{(X2-10.83262)}^2\\ +{(X3-7.546922)}^2+{(X4-12.73359)}^2\end{array}};$

the X1 is the assignment of ranking numbers of the expression quantity of hsa-miR-218-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in 178 miRNA expression quantities in the table 1;

the X2 is the assignment of ranking numbers of the expression quantity of hsa-miR-142-3p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in 178 miRNA expression quantities in the table 1;

the X3 is the assignment of ranking numbers of the expression quantity of hsa-miR-150-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in 178 miRNA expression quantities in the table 1;

the X4 is the assignment of ranking numbers of the expression quantity of hsa-miR-205-5p in the cancer tissue of the esophageal squamous carcinoma patient to be detected in the cancer tissue from small to large in 178 miRNA expression quantities in the table 1;

the 178 miRNAs are RNAs shown in sequences 1-178 in a sequence table;

the hsa-miR-218-5p is RNA shown in a sequence 1 in a sequence table;

the hsa-miR-142-3p is RNA shown in a sequence 2 in a sequence table;

the hsa-miR-150-5p is RNA shown in a sequence 3 in a sequence table;

the hsa-miR-205-5p is RNA shown in a sequence 4 of a sequence table.

6. The application of four, any three, any two or any one of the following four medicaments in preparing the medicament for treating the esophageal squamous carcinoma patient: the medicine taking hsa-miR-218-5p as a target point, the medicine taking hsa-miR-142-3p as a target point, the medicine taking hsa-miR-150-5p as a target point and the medicine taking hsa-miR-205-5p as a target point.

7. The application of four, any three, any two or any one of the following four medicaments in preparing the medicament for treating the esophageal squamous carcinoma patient: a drug targeting the target gene of hsa-miR-218-5p, a drug targeting the target gene of hsa-miR-142-3p, a drug targeting the target gene of hsa-miR-150-5p, and a drug targeting the target gene of hsa-miR-205-5 p.

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