An endometrial carcinoma prognosis evaluation model based on DUSP1, BUB1 and MCM7 and application thereof

Abstract

This invention discloses a prognostic assessment model for endometrial cancer based on DUSP1, BUB1, and MCM7, and its application. The prognostic assessment model includes an endometrial cancer prognostic risk scoring model and an endometrial cancer overall prognostic scoring model. The endometrial cancer prognostic risk scoring model includes a recurrence-free survival risk scoring model and an overall survival risk scoring model; the overall prognostic scoring model includes a recurrence-free survival overall score model and an overall survival overall score model. Experiments have demonstrated that the prognostic assessment models for endometrial cancer based on this invention can effectively predict the recurrence-free survival rate and overall survival rate of endometrial cancer patients. The prognostic assessment models for endometrial cancer provided by this invention facilitate stratified management of endometrial cancer patients, reduce overtreatment, accurately predict recurrence, and provide theoretical and clinical basis for guiding individualized clinical treatment of endometrial cancer patients.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, specifically to a prognostic assessment model for endometrial cancer based on DUSP1, BUB1, and MCM7 and its application. Background Technology

[0002] Endometrioid adenocarcinoma is the most common pathological type of endometrial cancer (EC), and its prognosis is closely related to traditional clinicopathological factors such as FIGO staging and histological grade. Clinical practice has shown that patients with endometrioid adenocarcinoma at the same FIGO stage or histological grade exhibit significant differences in prognosis; some early-stage patients experience rapid recurrence and death, while some late-stage patients achieve long-term survival. Clinically, EC patients with the same histological type and stage, receiving the same treatment regimen, often show significant differences in treatment response and prognosis. These findings suggest that endometrial cancer may have different subtypes, and the traditional EC classification (Type I / II) has failed to accurately classify EC and predict patient prognosis. This classification model has also led to overtreatment in some patients and undertreatment in others. Traditional pathological morphology diagnosis is no longer adequate for the needs of modern medical oncology diagnosis and treatment.

[0003] Genetic molecular characteristics play a crucial role in endometrioid adenocarcinoma (EC). In 2013, the Cancer Genome Atlas Research Network (TCGA) released a molecular classification of EC based on next-generation sequencing. Although the TCGA molecular classification divides EC into four types, explaining the heterogeneity of EC prognosis from a molecular perspective and having significant implications for EC diagnosis, prognosis, and personalized treatment, it cannot completely and accurately predict the prognosis of EC patients. Furthermore, the direct clinical application of the TCGA molecular classification is difficult. Scientists and clinicians are continuously attempting to simplify the TCGA method to predict the prognosis of endometrial cancer and develop new, more clinically feasible, and prognostic molecular classification systems based on TCGA.

[0004] The assessment and stratification of endometrial cancer patients should not rely solely on traditional indicators such as clinical stage and pathological grade, but should also incorporate their molecular characteristics. Early assessment of endometrial cancer patients combining clinicopathological and molecular features can better guide individualized treatment and prognostic monitoring. Summary of the Invention

[0005] The technical problem to be solved by this invention is how to assess the prognosis of patients with endometrial cancer.

[0006] To address the aforementioned technical problems, this invention first provides a novel use for a substance that detects the expression levels of BUB1, DUSP1, and MCM7.

[0007] This invention provides the application of a substance for detecting the expression levels of BUB1, DUSP1, and MCM7 in any of the following A1)-A3):

[0008] A1) Prepare products for prognostic assessment of patients with endometrial cancer; A2) To develop products for assessing the prognostic recurrence-free survival rate of patients with endometrial cancer; A3) Prepare products for assessing overall survival in patients with endometrial cancer.

[0009] To address the aforementioned technical problems, this invention provides new uses for substances that detect the expression levels of BUB1, DUSP1, and MCM7, and for media loaded with endometrial cancer prognostic scoring model formulas.

[0010] This invention provides the use of substances for detecting the expression levels of BUB1, DUSP1, and MCM7, and media loaded with endometrial cancer prognostic scoring model formulas, in any of the following A1)-A3): A1) To develop products for prognostic risk assessment in patients with endometrial cancer; A2) To develop products for assessing the prognostic recurrence-free survival rate of patients with endometrial cancer; A3) Prepare products for assessing overall survival in patients with endometrial cancer; The endometrial cancer prognostic scoring model includes an endometrial cancer prognostic risk scoring model and an endometrial cancer overall prognostic scoring model. The prognostic risk scoring model for endometrial cancer includes a recurrence-free survival risk scoring model and an overall survival risk scoring model. The overall prognostic scoring model for endometrial cancer includes a recurrence-free survival scoring model and an overall survival scoring model. The formula for the relapse-free survival risk scoring model is as follows: Relapse-free survival risk score = (BUB1 × 0.117) - (DUSP1 × 2.135) + (MCM7 × 1.163) Equation I; where, if BUB1 is highly expressed, then BUB1 takes the value of 1, if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, if MCM7 is poorly expressed, then MCM7 takes the value of 0. The total survival risk score model formula is as follows: Total Survival Risk Score = (BUB1 × 0.681) - (DUSP1 × 1.503) + (MCM7 × 1.049) Equation II; where, if BUB1 is highly expressed, then BUB1 takes the value of 1, and if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, and if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, and if MCM7 is poorly expressed, then MCM7 takes the value of 0. The formula for the relapse-free survival total score model is as follows: Relapse-free survival total score = exp(RFS linear predictive value) Equation III; where, RFS linear predictive value = 0.0915 × geneSignature = 2 + 17.6706 × geneSignature = 3 + 18.198 × geneSignature = 4 + 19.1022 × geneSignature = 5 + 19.9294 × geneSignature = 6 + 20.4149 × geneSignature = 7 + 21.0384 × geneSignature = 8 + 2.2812 × stage = stage II - IV; If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is low expressed, BUB1 is high expressed, and MCM7 is high expressed, then geneSignature=2 is 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; GeneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is lowly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. Conversely, if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is lowly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, and geneSignature=8 are all set to 0. =6, geneSignature=8 are both set to 0; if DUSP1, BUB1, and MCM7 are all low expressed, then geneSignature=8 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=7 are all set to 0; if the tumor stage is stage II-IV (including II, III, and IV), then stage=stageII-IV is set to 1, and if the tumor stage is not stage II-IV (including II, III, and IV), then stage=stageII-IV is set to 0. The overall survival score model formula is as follows: Overall Survival Score = exp(OS linear predictive value) Equation IV; where, OS linear predictive value = (-0.4204) × geneSignature = 2 + 18.9083 × geneSignature = 3 + 19.7752 × geneSignature = 4 + (-0.1956) × geneSignature = 5 + (-1.1338) × geneSignature = 6 + 21.2686 × geneSignature = 7 + 20.1785 × geneSignature = 8 + (-15.4608) × stage = stageII-IV + (-0.1256) × grade = 2 + 1.0165 × grade = 3; If DUSP1, BUB1, and MCM7 are all highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0; If DUSP1 is lowly expressed, BUB1, and MCM7 are all highly expressed, then geneSignature=2 will be 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0. All values ​​are set to 0; if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=3 is set to 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0; if DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is poorly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is poorly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, geneSignature=8 are all set to 0. If ignature=5, geneSignature=6, and geneSignature=8 are all set to 0; if DUSP1, BUB1, and MCM7 are all lowly expressed, then geneSignature=8 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=7 are all set to 0; if the tumor stage is stage II-IV (including II, III, and IV), then stage=stageII-IV is set to 1; if the tumor stage is not stage II-IV (including II, III, and IV), then stage=stageII-IV is set to 0; if the tumor grade is G2, then grade=2 is set to 1, and grade=3 is set to 0; if the tumor grade is G3, then grade=3 is set to 1, and grade=2 is set to 0; if the tumor grade is G1, then grade=2 and grade=3 are both set to 0.

[0011] In practical applications, the recurrence-free survival or overall survival of endometrial cancer patients can be directly assessed by the expression levels of DUSP1, BUB1, and MCM7. The specific method is as follows: the recurrence-free survival or overall survival of endometrial cancer patients with low DUSP1 expression, high BUB1 expression, and high MCM7 expression is lower than or candidate lower than that of endometrial cancer patients with low DUSP1 expression, high BUB1 expression, and low MCM7 expression; endometrial cancer patients with low DUSP1 expression, low BUB1 expression, and high MCM7 expression; endometrial cancer patients with high DUSP1 expression, low BUB1 expression, and low MCM7 expression; endometrial cancer patients with high DUSP1 expression, low BUB1 expression, and high MCM7 expression; endometrial cancer patients with high DUSP1 expression, high BUB1 expression, and high MCM7 expression; and endometrial cancer patients with high DUSP1 expression, high BUB1 expression, and low MCM7 expression.

[0012] In practical applications, the recurrence-free survival or overall survival of endometrial cancer patients can also be assessed by substituting the expression level data of DUSP1, BUB1, and MCM7 into the risk scoring model formula mentioned above to calculate the risk score of endometrial cancer patients. The specific method may include the following steps: taking a test group consisting of several endometrial cancer patients as the test sample, calculating the risk score of each test sample using the risk scoring model formula mentioned above, and then arranging the test group in ascending order of risk score and dividing it into two equal parts. The half of the test group with the lowest risk score is designated as the low group, and the other half is designated as the high group. The recurrence-free survival or overall survival of endometrial cancer patients from the test group is predicted according to the following criteria: the recurrence-free survival or overall survival of endometrial cancer patients from the high group is lower or candidate lower than that of endometrial cancer patients from the low group.

[0013] In practical applications, the recurrence-free survival or overall survival of endometrial cancer patients can also be assessed by substituting DUSP1, BUB1, and MCM7 expression level data, tumor staging data, and / or tumor grade data into the above-mentioned total scoring model formula. A specific method may include the following steps: using a test population consisting of several endometrial cancer patients as the test sample, calculating the total score for each test sample using the above-mentioned total scoring model formula, then arranging the test population in ascending order of total score and dividing it into two equal parts. The half of the test population with the lowest total score is designated as the low group, and the remaining half is designated as the high group. The recurrence-free survival or overall survival of endometrial cancer patients from the test population is predicted according to the following criteria: the recurrence-free survival or overall survival of endometrial cancer patients from the high group is lower than or candidate lower than that of endometrial cancer patients from the low group.

[0014] In the above applications, the medium also includes the following predictive model formula for recurrence-free survival of endometrial cancer patients: h(t) = h0(t)exp(RFS total score Equation V), where h(t) represents the recurrence-free survival rate at time t; h0(t) represents the baseline survival rate at time t; and the RFS total score is the total score calculated according to the above recurrence-free survival total score model formula. In one embodiment of the present invention, the baseline survival rate is shown in Table 3 below. The recurrence-free survival rate includes the 3-year recurrence-free survival rate, the 5-year recurrence-free survival rate, and the 7-year recurrence-free survival rate. In practical applications, when calculating the 3-year recurrence-free survival rate of endometrial cancer patients, the baseline survival rate value (0.99999999999285) corresponding to the closest time to 3 years but less than 3 years (1064.583 days) can be found through Table 3 below. Then, the baseline survival rate value and the RFS total score are substituted into Equation V to calculate the 3-year recurrence-free survival rate of the endometrial cancer patient.

[0015] In the above applications, the medium also includes the following predictive model formula for the overall survival of endometrial cancer patients: h(t) = h0(t)exp(OS total score formula VI), where h(t) represents the overall survival rate at time t; h0(t) represents the baseline survival rate at time t; and the OS total score is the total score calculated according to the above overall survival score model formula. In one embodiment of the present invention, the baseline survival rate is shown in Table 4 below. The overall survival rate includes the 3-year overall survival rate, the 5-year overall survival rate, and the 7-year overall survival rate. In practical applications, when calculating the 3-year overall survival rate of endometrial cancer patients, the baseline survival rate value (0.999999999944411) corresponding to the closest time to 3 years but less than 3 years (913 days) can be found through Table 4 below. Then, the baseline survival rate value and the OS total score are substituted into formula VI to calculate the 3-year overall survival rate of the endometrial cancer patient.

[0016] The present invention solves the above-mentioned technical problems, and the present invention also provides a kit for assessing the prognosis of endometrial cancer.

[0017] The kit for assessing the prognosis of endometrial cancer provided by the present invention includes the substances described above for detecting the expression levels of BUB1, DUSP1 and MCM7, and a medium loaded with the above-described endometrial cancer prognostic scoring model formula.

[0018] Furthermore, the kit also includes reagents and / or devices for detecting the stage of endometrial cancer tumors.

[0019] Furthermore, the kit also includes reagents and / or devices for detecting the grade of endometrial cancer tumors.

[0020] Furthermore, the medium also includes the above-mentioned predictive model formula (Formula V) for recurrence-free survival of endometrial cancer patients and the above-mentioned predictive model formula (Formula VI) for overall survival of endometrial cancer patients.

[0021] The expression levels mentioned above include protein expression levels and mRNA expression levels.

[0022] In some embodiments, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the expression levels of BUB1, DUSP1, and MCM7 proteins.

[0023] In some implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the expression levels of BUB1, DUSP1, and MCM7 mRNA.

[0024] The substance described above for detecting the expression levels of BUB1, DUSP1, and MCM7 is used to detect the levels of BUB1, DUSP1, and MCM7 expression.

[0025] In some implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the level of expression of BUB1, DUSP1, and MCM7 proteins (high or low expression).

[0026] In some implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the level of BUB1, DUSP1, and MCM7 mRNA expression (high or low expression).

[0027] The substance described above for detecting the expression levels of BUB1, DUSP1, and MCM7 is the substance for detecting the expression levels of BUB1, DUSP1, and MCM7 in endometrial cancer tissue.

[0028] In some implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the expression levels of BUB1, DUSP1, and MCM7 proteins in endometrial cancer tissue, such as antibodies used to detect the expression levels of BUB1, DUSP1, and MCM7 proteins in endometrial cancer tissue by methods such as immunohistochemistry, immunoblotting, and enzyme-linked immunosorbent assay.

[0029] In some specific implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 proteins in endometrial cancer tissue is a substance used to detect the expression levels of BUB1, DUSP1, and MCM7 proteins in endometrial cancer tissue using immunohistochemistry. The method for determining the expression level can be based on immunohistochemical scoring standards known to those skilled in the art (such as H-score, Allred score, or Allred score), or the percentage of positive cells, or staining intensity (e.g., DUSP1 IRS > 3 indicates high expression, DUSP1 IRS ≤ 3 indicates low expression; BUB1 positive cell percentage ≥ 10% indicates high expression, BUB1 positive cell percentage < 10% indicates low expression; MCM7 positive cell percentage ≥ 25% indicates high expression, MCM7 positive cell percentage < 25% indicates low MCM7 expression).

[0030] In some implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the expression levels of BUB1, DUSP1, and MCM7 mRNA in endometrial cancer tissue. This could be a probe, chip, or primer used to detect the expression levels of BUB1, DUSP1, and MCM7 mRNA in endometrial cancer tissue using methods such as in situ hybridization, RNA-seq, or qPCR.

[0031] In some specific implementations, the substance used to detect the expression levels of BUB1, DUSP1, and MCM7 is a substance used to detect the mRNA expression levels of BUB1, DUSP1, and MCM7 in endometrial cancer tissue using RNA-seq. The mRNA expression level can be determined by using the average gene expression level determined after standardizing and analyzing sequencing data (such as sequencing data in a database) as a standard (e.g., below the average gene expression level is considered low expression, and above the average gene expression level is considered high expression).

[0032] To address the aforementioned technical problems, the present invention also provides a data processing device for assessing the prognosis of endometrial cancer.

[0033] The data processing device for assessing the prognosis of endometrial cancer provided by this invention is data processing device A, data processing device B, data processing device C, or data processing device D.

[0034] The data processing device A includes a memory, a processor, and a computer program stored in the memory, characterized in that: the processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data of endometrial cancer patients; substituting the data into a recurrence-free survival risk scoring model formula to calculate a recurrence-free survival risk score for endometrial cancer patients; and assessing the recurrence-free survival rate of endometrial cancer patients based on the recurrence-free survival risk score. The data processing device B includes a memory, a processor, and a computer program stored in the memory, characterized in that: the processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data of endometrial cancer patients; substituting the data into an overall survival risk scoring model to calculate an overall survival risk score for endometrial cancer patients; and assessing the overall survival rate of endometrial cancer patients based on the overall survival score. The data processing device C includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data and tumor staging data from endometrial cancer patients; substituting the data into a recurrence-free survival total score model to calculate the recurrence-free survival total score for endometrial cancer patients; and assessing the recurrence-free survival rate of endometrial cancer patients based on the recurrence-free survival total score. The data processing device D includes a memory, a processor, and a computer program stored in the memory, characterized in that: the processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data, tumor stage data, and tumor grade data of endometrial cancer patients; substituting the data into an overall survival score model to calculate the overall survival score of endometrial cancer patients; and assessing the overall survival rate of endometrial cancer patients based on the overall survival score.

[0035] In some embodiments, the data processing apparatus for assessing the prognosis of endometrial cancer further includes data processing device E and data processing device F.

[0036] The data processing device E includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data and tumor staging data from endometrial cancer patients; substituting the data into a recurrence-free survival total score model to calculate the recurrence-free survival total score for endometrial cancer patients; and substituting the recurrence-free survival total score and the baseline survival rate (Table 3) corresponding to a certain time point into a prediction model (Equation V) for the recurrence-free survival rate of endometrial cancer patients to calculate the recurrence-free survival rate of endometrial cancer patients at that time point.

[0037] The data processing device F includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data, tumor stage data, and tumor grade data from endometrial cancer patients; substituting the data into an overall survival score model to calculate the overall survival score for endometrial cancer patients; and substituting the overall survival score and the baseline survival rate (Table 4) at a certain time point into a prediction model (Equation VI) for the overall survival rate of endometrial cancer patients to calculate the overall survival rate at that time point.

[0038] To address the aforementioned technical problems, the present invention also provides a method for assessing the prognosis of endometrial cancer.

[0039] The method for assessing the prognosis of endometrial cancer provided by this invention is method A, method B, method C, or method D.

[0040] Method A includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 in patients with endometrial cancer to obtain BUB1, DUSP1, and MCM7 expression level data; substituting the data into a recurrence-free survival risk scoring model to calculate a recurrence-free survival risk score for patients with endometrial cancer; and assessing the recurrence-free survival rate of patients with endometrial cancer based on the recurrence-free survival risk score. Method B includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 in patients with endometrial cancer to obtain BUB1, DUSP1, and MCM7 expression level data; substituting the data into an overall survival risk scoring model to calculate an overall survival risk score for patients with endometrial cancer; and assessing the overall survival rate of patients with endometrial cancer based on the overall survival risk score. Method C includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 and the tumor stage of endometrial cancer patients to obtain BUB1, DUSP1, and MCM7 expression level data and tumor stage data; substituting the data into a recurrence-free survival total score model to calculate the recurrence-free survival total score of endometrial cancer patients; and assessing the recurrence-free survival rate of endometrial cancer patients based on the recurrence-free survival total score. Method D includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7, tumor stage, and tumor grade in the tissues of endometrial cancer patients to obtain the expression levels of BUB1, DUSP1, and MCM7, tumor stage, and tumor grade; substituting the data into the overall survival score model to calculate the overall survival score of endometrial cancer patients; and assessing the overall survival rate of endometrial cancer patients based on the overall survival score.

[0041] In some implementations, the method further includes method E and method F.

[0042] Method E includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 and the tumor stage of endometrial cancer patients to obtain BUB1, DUSP1, and MCM7 expression level data and tumor stage data; substituting the data into the recurrence-free survival total score model to calculate the recurrence-free survival total score of endometrial cancer patients; substituting the recurrence-free survival total score and the baseline survival rate corresponding to a certain time point (Table 3) into the prediction model of recurrence-free survival rate of endometrial cancer patients (Equation V) to calculate the recurrence-free survival rate of endometrial cancer patients at that time point.

[0043] Method F includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7, tumor stage, and tumor grade of endometrial cancer patients to obtain BUB1, DUSP1, and MCM7 expression level data, tumor stage data, and tumor grade data; substituting the data into the overall survival score model to calculate the overall survival score of endometrial cancer patients; and substituting the overall survival score and the baseline survival rate at a certain time point (Table 4) into the prediction model (Equation VI) for the overall survival of endometrial cancer patients to calculate the overall survival rate of endometrial cancer patients at that time point.

[0044] To address the aforementioned technical problems, the present invention also provides a computer program product.

[0045] The computer program product provided by this invention implements the steps of the above method when executed by a processor.

[0046] To address the aforementioned technical problems, the present invention also provides a computer-readable storage medium.

[0047] The computer-readable storage medium provided by this invention enables a computer to perform the steps of the above-described method.

[0048] The medium mentioned above refers to a data storage carrier, which may be magnetic tape, disk, floppy disk, optical disk, magneto-optical disk, ROM, PROM, VCD, DVD, hard disk, flash memory, USB flash drive, CF card, SD card, MMC card, SM card, Memory Stick, or xD card, etc.

[0049] The endometrial cancer mentioned above is endometrioid adenocarcinoma.

[0050] The amino acid sequence of any of the DUSP1 proteins described above is shown in Sequence 1.

[0051] The amino acid sequence of any of the above-mentioned BUB1 proteins is shown in Sequence 2.

[0052] The amino acid sequence of any of the MCM7 proteins described above is shown in Sequence 3.

[0053] This invention provides a prognostic assessment model for endometrial cancer based on DUSP1, BUB1, and MCM7. The endometrial cancer prognostic assessment model includes an endometrial cancer prognostic risk scoring model and an endometrial cancer overall prognostic scoring model. The endometrial cancer prognostic risk scoring model includes a recurrence-free survival risk scoring model and an overall survival risk scoring model; the endometrial cancer overall prognostic scoring model includes a recurrence-free survival overall score model and an overall survival overall score model. Experiments have demonstrated that the various endometrial cancer prognostic assessment models based on this invention can effectively predict the recurrence-free survival rate and overall survival rate of endometrial cancer patients. The endometrial cancer prognostic assessment model provided by this invention facilitates stratified management of endometrial cancer patients, reduces overtreatment, accurately predicts recurrence, and provides theoretical and clinical basis for guiding individualized clinical treatment of endometrial cancer patients. Attached Figure Description

[0054] Figure 1 Methods for reading and scoring immunohistochemical examination slides of DUSP1, BUB1, NDC80 and MCM7.

[0055] Figure 2Immunohistochemical staining results of three proteins DUSP1, BUB1 and MCM7 in endometrial cancer tissue.

[0056] Figure 3 This study analyzed the correlation between the expression of DUSP1, BUB1, and MCM7 and the clinicopathological features of endometrial cancer. A represents the distribution of tumor stage in the low- and high-expression groups of BUB1. B represents the distribution of tumor grade in the low- and high-expression groups of BUB1. C represents the distribution of tumor myometrial invasion in the low- and high-expression groups of BUB1. D represents the distribution of tumor stage in the low- and high-expression groups of DUSP1. E represents the distribution of tumor grade in the low- and high-expression groups of DUSP1. F represents the distribution of tumor myometrial invasion in the low- and high-expression groups of DUSP1. G represents the distribution of tumor stage in the low- and high-expression groups of MCM7. H represents the distribution of tumor grade in the low- and high-expression groups of MCM7. I represents the distribution of tumor myometrial invasion in the low- and high-expression groups of MCM7.

[0057] Figure 4 The relationship between the individual use of DUSP1, BUB1, and MCM7 and the prognosis of endometrial cancer. A: Relationship between BUB1 expression level and recurrence-free survival. B: Relationship between DUSP1 expression level and recurrence-free survival. C: Relationship between MCM7 expression level and recurrence-free survival. D: Relationship between BUB1 expression level and overall survival. E: Relationship between DUSP1 expression level and overall survival. F: Relationship between MCM7 expression level and overall survival.

[0058] Figure 5 The relationship between the combined use of DUSP1, BUB1, and MCM7 and the prognosis of endometrial cancer is shown in the following sections: A) Relationship between the 3-gene model of DUSP1, BUB1, and MCM7 and overall survival; B) Relationship between the 3-gene model of DUSP1, BUB1, and MCM7 and recurrence-free survival; C) Relationship between the 2-gene model of DUSP1 and MCM7 and overall survival; D) Relationship between the 2-gene model of DUSP1 and MCM7 and recurrence-free survival; E) Relationship between the 2-gene model of DUSP1 and BUB1 and overall survival; F) Relationship between the 2-gene model of DUSP1 and BUB1 and recurrence-free survival; G) Relationship between the 2-gene model of BUB1 and MCM7 and overall survival; H) Relationship between the 2-gene model of BUB1 and MCM7 and recurrence-free survival.

[0059] Figure 6The following are independent risk factors for recurrence-free survival and overall survival in patients with endometrial cancer. A: Univariate Cox regression analysis of recurrence-free survival showed that ascites tumor, FIGO stage, presence of distant metastasis, and risk score were important risk factors for recurrence-free survival. B: Univariate Cox regression analysis of overall survival showed that ascites tumor, FIGO stage, presence of distant metastasis, and risk score were important risk factors for overall survival. C: Multivariate Cox analysis of recurrence-free survival showed that tumor grade and risk score were two independent risk factors for recurrence-free survival. D: Multivariate Cox analysis of overall survival showed that FIGO stage, tumor grade, and risk score were three independent risk factors for overall survival.

[0060] Figure 7 This section describes the establishment and validation of nomograms (nomographs). A) Integrating risk score and tumor stage features into the nomogram to predict recurrence-free survival in endometrial cancer patients. B) Integrating risk score, tumor stage, and tumor grade features into the nomogram to predict overall survival in endometrial cancer patients. C) Calculating the total score for patients based on the recurrence-free survival total score model and dividing patients into low and high groups based on the median total score. Survival analysis showed that the recurrence-free survival rate was lower in the high group than in the low group. D) Calculating the total score for patients based on the overall survival total score model and dividing patients into low and high groups based on the median total score. Survival analysis showed that the overall survival rate was lower in the high group than in the low group. E) Using ROC curve analysis, the power of tumor grade, risk score, and total score in predicting recurrence-free survival is shown. The AUC for predicting recurrence-free survival by tumor grade was 0.815 (sensitivity 0.796, specificity 0.813), the AUC for predicting recurrence-free survival by risk score was 0.853 (sensitivity 0.820, specificity 0.771), and the AUC for predicting recurrence-free survival by total score was 0.923 (sensitivity 0.889, specificity 0.847). F represents the ROC curve analysis of the power of tumor grade, tumor stage, risk score, and total score in predicting overall survival. Among them, the AUC for predicting overall survival by tumor stage was 0.726 (sensitivity 0.669, specificity 0.691), the AUC for predicting overall survival by tumor grade was 0.873 (sensitivity 0.768, specificity 0.773), the AUC for predicting overall survival by risk score was 0.817 (sensitivity 0.801, specificity 0.825), and the AUC for predicting overall survival by total score was 0.963 (sensitivity 0.906, specificity 0.918).

[0061] Figure 8This study validates the expression patterns of DUSP1, BUB1, and MCM7, as well as the risk scoring model, in the TCGA cohort. A represents the expression level of BUB1 in patients with different tumor stages in the TCGA cohort. B represents the expression level of BUB1 in patients with different tumor grades in the TCGA cohort. C represents the expression level of BUB1 in patients with different lymph node metastasis states in the TCGA cohort. D represents the expression level of DUSP1 in patients with different tumor stages in the TCGA cohort. E represents the expression level of DUSP1 in patients with different tumor grades in the TCGA cohort. F represents the expression level of DUSP1 in patients with different lymph node metastasis states in the TCGA cohort. G represents the expression level of MCM7 in patients with different tumor stages in the TCGA cohort. H represents the expression level of MCM7 in patients with different tumor grades in the TCGA cohort. I represents the expression level of MCM7 in patients with different lymph node metastasis states in the TCGA cohort. J represents the expression levels of the three genes in normal tissues and endometrial cancer tissues. K and L represent the validation of the relationship between risk score and recurrence-free survival and overall survival in the TCGA cohort. Results showed that the KM curve analysis of the low DUSP1 and high BUB1 / MCM7 subgroups was worse than other subgroups, consistent with the results of the cohort of 152 cases. M represents the power of ROC curve analysis in the TCGA cohort to predict 3-year, 5-year, and 7-year recurrence-free survival. Specifically, the AUC for predicting 3-year recurrence-free survival was 0.709 (sensitivity 0.674, specificity 0.685), the AUC for predicting 5-year recurrence-free survival was 0.739 (sensitivity 0.715, specificity 0.718), and the AUC for predicting 7-year recurrence-free survival was 0.723 (sensitivity 0.695, specificity 0.702). N represents the power of ROC curve analysis in the TCGA cohort to predict 3-year, 5-year, and 7-year overall survival rates using risk scores. The AUC for predicting 3-year overall survival was 0.728 (sensitivity 0.685, specificity 0.693), the AUC for predicting 5-year overall survival was 0.757 (sensitivity 0.724, specificity 0.731), and the AUC for predicting 7-year overall survival was 0.752 (sensitivity 0.719, specificity 0.728).

[0062] Figure 9 This study aimed to assess the efficacy of ROC curve analysis in predicting recurrence-free survival using tumor grade, risk score, and total score in the TCGA cohort. Here, DUSP1+MCM7+BUB1 represents the risk score, clinical stage represents the clinical tumor stage, and Allfactors represents the total score.

[0063] Figure 10The power of ROC curve analysis in the TCGA cohort to predict overall survival based on tumor grade, tumor stage, risk score, and total score was determined. Here, DUSP1+MCM7+BUB1 represents the risk score, clinical stage+grade represents the clinical tumor stage and grade, and All 5 factors represent the total score.

[0064] Figure 11 This paper examines the concordance of the endometrioid adenocarcinoma patient recurrence-free survival prediction model (Equation V) of this invention with the 3-year recurrence-free survival of endometrial cancer. The X-axis represents the probability of 3-year recurrence-free survival predicted by the prediction model, the Y-axis represents the actual 3-year recurrence-free survival rate, Ideal represents the ideal standard line; Apparent represents the original calibration line; and Bias-corrected represents the bias correction standard line.

[0065] Figure 12 This paper examines the concordance of the endometrioid adenocarcinoma patient recurrence-free survival prediction model (Equation V) of this invention with the 5-year recurrence-free survival of endometrial cancer. The X-axis represents the probability of 5-year recurrence-free survival predicted by the prediction model, the Y-axis represents the actual 3-year recurrence-free survival rate, Ideal represents the ideal standard line; Apparent represents the original calibration line; and Bias-corrected represents the bias correction standard line.

[0066] Figure 13 This paper examines the concordance of the endometrioid adenocarcinoma patient recurrence-free survival prediction model (Equation V) of this invention with the 7-year recurrence-free survival of endometrial cancer. The X-axis represents the probability of 7-year recurrence-free survival predicted by the prediction model, the Y-axis represents the actual 7-year recurrence-free survival rate, Ideal represents the ideal standard line; Apparent represents the original calibration line; and Bias-corrected represents the bias correction standard line.

[0067] Figure 14 This invention serves as a test of the concordance of the overall survival prediction model (VI) for endometrioid adenocarcinoma patients in assessing the 3-year overall survival of endometrial cancer. The X-axis represents the probability of 3-year overall survival predicted by the model, the Y-axis represents the actual 3-year overall survival rate, Ideal represents the ideal standard line, Apparent represents the original calibration line, and Bias-corrected represents the bias-corrected standard line.

[0068] Figure 15 This invention serves as a test of the concordance of the overall survival prediction model (VI) for endometrioid adenocarcinoma patients in assessing 5-year overall survival in endometrial cancer. The X-axis represents the probability of 5-year overall survival predicted by the model, the Y-axis represents the actual 5-year overall survival rate, Ideal represents the ideal standard line, Apparent represents the original calibration line, and Bias-corrected represents the bias-corrected standard line.

[0069] Figure 16 This invention provides a test of the concordance of the overall survival prediction model (VI) for endometrioid adenocarcinoma patients with 7-year overall survival in endometrial cancer. The X-axis represents the probability of 7-year overall survival predicted by the model, the Y-axis represents the actual 7-year overall survival rate, Ideal represents the ideal standard line, Apparent represents the original calibration line, and Bias-corrected represents the bias correction standard line. Detailed Implementation

[0070] The present invention will now be described in further detail with reference to specific embodiments. The given embodiments are merely illustrative of the invention and not intended to limit its scope. The embodiments provided below can serve as a guide for further improvements by those skilled in the art and do not constitute a limitation on the invention in any way.

[0071] Unless otherwise specified, the experimental methods used in the following examples are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

[0072] The definitions of the technical terms used in the following examples are as follows: Relapse-free survival rate: refers to the percentage of patients who survived without relapse during the follow-up period compared to the total number of patients in the study.

[0073] Relapse-free survival: refers to the period from the start of treatment until a relapse of the disease is observed or death occurs from any cause.

[0074] In this article, relapse-free survival and disease progression-free survival have the same meaning.

[0075] Overall survival rate: refers to the percentage of patients who survived during the follow-up period compared to the total number of patients in the study.

[0076] 3-year survival rate: refers to the percentage of patients who survived during the three-year follow-up period compared to the total number of patients in the study.

[0077] 5-year survival rate: refers to the percentage of patients who survived during the five-year follow-up period compared to the total number of patients in the study.

[0078] 7-year survival rate: refers to the percentage of patients who survived during the seven-year follow-up period compared to the total number of patients in the study.

[0079] Overall survival: This refers to the time from randomization to death from any cause. For subjects lost to follow-up before death, the time of last follow-up is usually calculated as the time of death. Deaths caused by non-tumor factors are also included in the statistics; for example, if a subject dies in a car accident within the statistical period, their survival data are also considered valid.

[0080] FIGO staging for endometrial cancer: This refers to the clinical staging of endometrial cancer established by the International Federation of Gynecology and Obstetrics (FIGO). It is divided into stages I, II, III, and IV based on the location of tumor invasion.

[0081] Endometrial cancer tumor grading: refers to pathological grading, which is based on the degree of differentiation of tumor cells as seen on pathological sections, and is divided into high (G3), medium (G2), and low (G1).

[0082] Example 1: Establishment and Validation of a Prognostic Model for Endometrial Cancer I. Screening for genes related to the prognosis of endometrial cancer 1. The applicant previously conducted a preliminary study on the molecular characteristics of endometrial cancer. 492 genes reported in the literature and associated with prognosis were screened from the NCBI (National Center for Biotechnology Information) and CNKI (China National Knowledge Infrastructure) databases, and a high-throughput transcriptome chip was designed. Then, 32 endometrial cancer samples were used as the research subjects, divided into two groups according to clinicopathological characteristics and patient prognostic outcomes. High-throughput gene chips were used to screen for differentially expressed genes between the two groups. The results showed that the following 21 differentially expressed genes were identified: RFC4, BARD1, CCNE1, NDC80, MCM6, MCM7, PRC1, CCNB2, BUB1, NUSAP1, PCNA, TYMS, CCNE2, ESM1, CDK6, PIWIL2, DUSP1, FOS, NR4A1, SERPINA1, and CCL20.

[0083] 2. Subsequently, the applicant conducted transcriptome sequencing and analysis on the primary lesions of 13 cases of non-recurrent endometrial cancer and 8 cases of recurrent endometrial cancer. A total of 2106 differentially expressed genes were identified. Based on the criteria of P < 0.05 and |log2FC| ≥ 1, compared with the primary lesion group of non-recurrent patients (PE) and the primary lesion group of recurrent patients (RRE), 1231 differentially expressed genes were upregulated and 875 differentially expressed genes were downregulated. The mRNA expression levels of KCNS2, LSP1, NDC80, BUB1, KRT17P2, MCM7, and TTK were significantly upregulated, while the mRNA expression levels of KRT83, IGSF8, MMP20, DBH, and DUSP1 were significantly downregulated.

[0084] 3. The intersection of the differentially expressed genes obtained in step 2 and the differentially expressed genes obtained in step 1 was used to finally screen out the following four important differentially expressed genes that may be related to the prognosis of endometrial cancer patients: DUSP1, BUB1, NDC80 and MCM7.

[0085] II. The Relationship Between Four Genes and the Prognosis of Endometrial Cancer Study subjects: 152 patients with endometrioid adenocarcinoma from the Department of Gynecology, Peking University People's Hospital, who had postoperative follow-up data, from January 2006 to December 2011. The clinicopathological characteristics of these 152 patients with endometrioid adenocarcinoma are shown in Table 1.

[0086] Table 1. Clinicopathological characteristics of 152 patients with endometrioid adenocarcinoma

[0087] Experimental Methods: Immunohistochemical staining for DUSP1, BUB1, NDC80, and MCM7 was performed on endometrioid adenocarcinoma tissues and normal tissues from 152 patients with endometrioid adenocarcinoma. The protein expression levels of DUSP1, BUB1, NDC80, and MCM7 were also detected. The antibodies used and their information for immunohistochemical staining are shown in Table 2. Based on long-term follow-up results, the relationship between the different expression states of the four genes and the prognosis of endometrioid adenocarcinoma was analyzed using the Log-rank test.

[0088] Table 2. Information on DUSP1, BUB1, NDC80, and MCM7 antibodies.

[0089] The specific methods for slide reading and scoring in immunohistochemical examinations of DUSP1, BUB1, NDC80, and MCM7 are as follows: DUSP1: DUSP1 primarily stains the cytoplasm, and the staining results are determined using the Immunohistoactive Score (IRS). The score is based on the intensity of the cytoplasmic staining: 0 points: no staining; 1 point: weak staining, pale yellow; 2 points: moderate staining, brownish-yellow; 3 points: strong staining, brownish-red. Then, the score is based on the percentage of positive cells: 0 points: no positive cells; 1 point: positive cell percentage ≤10%; 2 points: positive cell percentage 11%-50%; 3 points: positive cell percentage 51%-75%; 4 points: positive cell percentage >75%. The IRS is then calculated using the following formula: IRS = Staining Intensity Score × Positive Cell Percentage Score. Finally, the expression level of DUSP1 is determined based on the IRS: IRS > 3 indicates high DUSP1 expression, and IRS ≤ 3 indicates low DUSP1 expression.

[0090] BUB1: BUB1 is mainly a staining agent for cell nuclei. Therefore, the expression level of BUB1 is determined by the percentage of positive cells: a percentage of positive cells ≥10% indicates high expression of BUB1, and a percentage of positive cells <10% indicates low expression of BUB1.

[0091] NDC80: NDC80 is mainly a cytoplasmic stain. NDC80 expression is determined by IRS: IRS > 3 indicates high NDC80 expression, and IRS ≤ 3 indicates low NDC80 expression. The specific calculation method for IRS is the same as DUSP1.

[0092] MCM7: MCM7 is mainly a staining cell nucleus, so the expression level of MCM7 is determined by the percentage of positive cells: a percentage of positive cells ≥25% indicates high expression of MCM7, and a percentage of positive cells <25% indicates low expression of MCM7.

[0093] Immunohistochemical detection, slide reading, and scoring methods for high and low expression of DUSP1, BUB1, NDC80, and MCM7 are as follows: Figure 1 As shown.

[0094] The results showed that DUSP1, BUB1, and MCM7 were expressed to varying degrees in 152 patients with endometrioid adenocarcinoma. Specifically, 34 patients had low DUSP1 expression, and 118 had high DUSP1 expression; 104 patients had low BUB1 expression, and 48 had high BUB1 expression; 73 patients had low MCM7 expression, and 79 had high MCM7 expression. However, NCD80 expression did not show significant differences between endometrioid adenocarcinoma and normal tissues.

[0095] Immunohistochemical staining results of three proteins DUSP1, BUB1 and MCM7 in endometrial cancer tissue are as follows: Figure 2 As shown.

[0096] III. Relationship between the expression of DUSP1, BUB1, and MCM7 and clinicopathological features The expression of DUSP1, BUB1, and MCM7 in the tissues of 152 patients with endometrioid adenocarcinoma, as determined by immunohistochemical staining, was analyzed in relation to the clinicopathological characteristics of these patients.

[0097] The results showed that the expression level of BUB1 differed significantly among stage I, II, and III-IV endometrial cancer tissues. Figure 3 A). The tumor grade distribution between the BUB1 low expression group and the BUB1 high expression group was also significant. Figure 3 B). Upregulation of BUB1 can also lead to myometrial infiltration (B). Figure 3 C). DUSP1 expression in different clinicopathological features is exactly the opposite of BUB1 expression. Patients with high-stage and deep muscle layer infiltration typically express lower levels of DUSP1. Furthermore, the proportions of patients with low DUSP1 expression in FIGO stages I-II and III-IV were 27 / 130 and 7 / 22, respectively. Significant differences in DUSP1 expression exist among patients with different FIGO stages. Figure 3 DF). MCM7 and BUB1 have similar expression patterns; however, the proportion of cases with low MCM7 expression is relatively low in high-stage, poorly differentiated, and deep muscle-invasive EC tissues. Figure 3 These results indicate that BUB1, DUSP1, and MCM7 play important roles in the progression of endometrial cancer.

[0098] IV. Relationship between the use of DUSP1, BUB1, and MCM7, alone or in combination, and prognosis 1. Relationship between the individual application of DUSP1, BUB1, and MCM7 and prognosis Kaplan-Meier survival curves showed that patients with endometrioid adenocarcinoma who expressed high levels of BUB1 had relatively low recurrence-free survival, but the difference was not statistically significant. Figure 4 A). Survival analysis showed that patients with endometrioid adenocarcinoma exhibiting low DUSP1 expression and high MCM7 expression had significantly reduced recurrence-free survival. Figure 4 BC). Analysis of overall survival revealed no statistically significant difference between high and low BUB1 expression. Figure 4 D). Higher DUSP1 expression was associated with better overall survival (P<0.05), while lower MCM7 expression also showed a better prognosis, but the difference was not significant. Figure 4 EF).

[0099] 2. Relationship between combined use of DUSP1, BUB1, and MCM7 and prognosis Given that predicting recurrence-free survival and overall survival of patients with endometrioid adenocarcinoma based on a single gene DUSP1, BUB1, or MCM7 has limited significance, this invention combines the expression of two or three of BUB1, DUSP1, and MCM7 to predict the survival rate of patients with endometrioid adenocarcinoma.

[0100] Kaplan-Meier survival curves showed that endometrioid adenocarcinoma patients with low DUSP1 expression, high BUB1 expression, and high MCM7 expression had the worst recurrence-free survival and overall survival. Figure 5 ).

[0101] V. Prognostic Risk Scoring Model for Endometrial Cancer To further illustrate the importance of the three genes (DUSP1, BUB1, and MCM7), this invention constructed a relapse-free survival risk scoring model (RFS risk scoring model) and an overall survival risk scoring model (OS risk scoring model) through multivariate analysis, as follows: The RFS risk scoring model formula is as follows: RFS Risk Score = (BUB1 × 0.117) - (DUSP1 × 2.135) + (MCM7 × 1.163) Equation I, where, if BUB1 is highly expressed, then BUB1 takes the value of 1, if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, if MCM7 is poorly expressed, then MCM7 takes the value of 0.

[0102] The OS risk scoring model formula is as follows: OS Risk Score = (BUB1 × 0.681) - (DUSP1 × 1.503) + (MCM7 × 1.049) Equation II, where, if BUB1 is highly expressed, then BUB1 takes the value of 1, and if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, and if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, and if MCM7 is poorly expressed, then MCM7 takes the value of 0.

[0103] The expression levels of BUB1, DUSP1, and MCM7 in the EC tissues of each patient with endometrioid adenocarcinoma were detected by immunohistochemistry. Then, the RFS risk score and OS risk score for each patient were calculated using the RFS risk scoring model and OS risk scoring model, respectively. Univariate Cox regression analysis and multivariate Cox regression analysis were performed on the risk scores and clinical indicators of patients with endometrioid adenocarcinoma.

[0104] Univariate Cox regression analysis showed that the RFS risk score was an important risk factor for relapse-free survival. Figure 6 A), OS risk score is an important risk factor for overall survival ( Figure 6 B). Multivariate Cox regression analysis showed that tumor stage and RFS risk score were two independent risk factors for recurrence-free survival. Figure 6 C), tumor stage, tumor grade, and OS risk score are three independent risk factors for overall survival. Figure 6 D).

[0105] VI. Overall Prognostic Scoring Model for Endometrial Cancer 1. Establishment of RFS total score and OS total score models Based on the Cox regression analysis results, this invention constructs a relapse-free survival total score model (RFS total score model). The formula for the RFS total score model is as follows: RFS total score = exp(RFS linear predictive value), RFS linear predictive value = 0.0915 × geneSignature = 2 + 17.6706 × geneSignature = 3 + 18.198 × geneSignature = 4 + 19.1022 × geneSignature = 5 + 19.9294 × geneSignature = 6 + 20.4149 × geneSignature = 7 + 21.0384 × geneSignature = 8 + 2.2812 × stage = stageII-IV. Specifically, if DUSP1, BUB1, and MCM7 are all highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0; if DUSP1 is lowly expressed, BUB1 is highly expressed, and MCM7 is highly expressed, then geneSignature=2 is set to 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=3 takes the value of 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 all take the value of 0; if DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 takes the value of 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 all take the value of 0.If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is poorly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is poorly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=8 is set to 0. For each of the following gene signatures: ignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=8, the value is 0. If DUSP1, BUB1, and MCM7 are all lowly expressed, then geneSignature=8 is 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=7 are all 0. If the tumor stage is stage II-IV (including II, III, and IV), then stage=stageII-IV is 1; if the tumor stage is not stage II-IV (including II, III, and IV), then stage=stageII-IV is 0.

[0106] The expression levels of BUB1, DUSP1, and MCM7 in the EC tissues of each patient with endometrioid adenocarcinoma were detected by immunohistochemistry. The total RFS score for each patient was then calculated using the RFS total score model, and patients were divided into low- or high-risk groups based on the median score. Kaplan-Meier survival analysis was used to analyze the difference in recurrence-free survival between the high- and low-risk groups. Survival analysis showed that the recurrence-free survival rate was lower in the high-risk group than in the low-risk group. Figure 7 C).

[0107] Based on the Cox regression analysis results, this invention also constructs an overall survival score model (OS total score model). The formula for the OS total score model is as follows: OS total score = exp(OS linear predictive value) Equation IV, the linear predictive value of OS = (-0.4204) × geneSignature = 2 + 18.9083 × geneSignature = 3 + 19.7752 × geneSignature = 4 + (-0.1956) × geneSignature = 5 + (-1.1338) × geneSignature = 6 + 21.2686 × geneSignature = 7 + 20.1785 × geneSignature = 8 + (-15.4608) × stage = stageII-IV + (-0.1256) × grade = 2 + 1.0165 × grade = 3. Specifically, if DUSP1, BUB1, and MCM7 are all highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0; if DUSP1 is lowly expressed, BUB1 is highly expressed, and MCM7 is highly expressed, then geneSignature=2 is set to 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=3 takes the value of 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 all take the value of 0; if DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 takes the value of 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 all take the value of 0.If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is poorly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is poorly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. For `nature=5`, `geneSignature=6`, and `geneSignature=8`, the value is 0. If DUSP1, BUB1, and MCM7 are all lowly expressed, then `geneSignature=8` is 1, and `geneSignature=2`, `geneSignature=3`, `geneSignature=4`, `geneSignature=5`, `geneSignature=6`, and `geneSignature=7` are all 0. If the tumor stage is stage II-IV (including II, III, and IV), then `stage=stageII-IV` is 1; if the tumor stage is not stage II-IV (including II, III, and IV), then `stage=stageII-IV` is 0. If the tumor grade is G2, then `grade=2` is 1, and `grade=3` is 0. If the tumor grade is G3, then `grade=3` is 1, and `grade=2` is 0. If the tumor grade is G1, then both `grade=2` and `grade=3` are 0.

[0108] The expression levels of BUB1, DUSP1, and MCM7 in the EC tissues of each patient with endometrioid adenocarcinoma were detected by immunohistochemistry. The total OS score was then calculated for each patient based on an OS total score model, and patients were divided into low- or high-risk groups according to the median score. Kaplan-Meier survival analysis was used to analyze the difference in overall survival between the high- and low-risk groups. The survival analysis showed that the overall survival rate of the high-risk group was lower than that of the low-risk group. Figure 7D).

[0109] 2. Establishment of nomograms to predict relapse-free survival and overall survival. This invention designs a nomogram (normative plot) to predict recurrence-free survival in patients with endometrioid adenocarcinoma. The recurrence-free survival nomogram integrates two features (tumor stage and RFS risk score). Figure 7 A). The formula for predicting recurrence-free survival in patients with endometrioid adenocarcinoma is as follows: h(t) = h0(t)exp(RFS total score, formula V). Where h(t) represents the recurrence-free survival rate at time t; h0(t) represents the baseline survival rate at time t, as shown in Table 3; the RFS total score is calculated according to the above formula.

[0110] Table 3

[0111] The recurrence-free survival rate for each patient with endometrioid adenocarcinoma was calculated according to Equation V above. The bootstrap method was used, with 1000 repeated samplings for concordance verification. The corrected curve for 3-year recurrence-free survival is shown below. Figure 11 As shown, the adjusted curve for 5-year relapse-free survival is as follows: Figure 12 As shown, the adjusted curve for 7-year recurrence-free survival is as follows: Figure 13 As shown in the figure. This result indicates that the predictive model for recurrence-free survival in patients with endometrioid adenocarcinoma of this invention has good agreement.

[0112] This invention also designed a nomogram (nomograph) to predict the overall survival of patients with endometrioid adenocarcinoma. The overall survival nomogram integrates three features (tumor stage, tumor grade, and OS risk score). Figure 7 B). The formula for predicting overall survival in patients with endometrioid adenocarcinoma is as follows: h(t) = h0(t)exp(OS total score formula VI). Where h(t) represents the recurrence-free survival rate at time t; h0(t) represents the baseline survival rate at time t, as shown in Table 4; the OS total score is calculated according to the above OS total score model formula.

[0113] Table 4

[0114] The overall survival rate for each patient with endometrioid adenocarcinoma was calculated using Equation VI above. The bootstrap method was employed, with 1000 repeated samplings for consistency verification. The corrected curve for the 3-year overall survival rate is shown below. Figure 14 As shown, the corrected curve for the 5-year overall survival rate is as follows: Figure 15 As shown, the corrected curve for the 7-year overall survival rate is as follows: Figure 16 As shown. This result indicates that the predictive model for overall survival in patients with endometrioid adenocarcinoma of the present invention has good agreement.

[0115] VII. Predictive Power of Prognostic Risk Scoring and Total Score Models for Endometrial Cancer To evaluate the predictive power of the prognostic risk scoring model and total score model for endometrial cancer of the present invention, the risk score and total score of patients with endometrioid adenocarcinoma were calculated according to the risk scoring model and the total score model, respectively. Patients with endometrioid adenocarcinoma were divided into low-risk group and high-risk group according to the median values ​​of the risk score and total score. Then, the predictive power of the risk score or total score for recurrence-free survival and overall survival was analyzed by ROC curve analysis.

[0116] ROC curve analysis showed that the areas under the ROC curves (AUCs) for predicting recurrence-free survival and overall survival using the endometrial cancer prognostic risk scoring model of this invention were 0.853 and 0.817, respectively, while the areas under the ROC curves (AUCs) for predicting recurrence-free survival and overall survival using the endometrial cancer prognostic overall scoring model of this invention were 0.923 and 0.963, respectively. Both were significantly higher than the areas under the ROC curves (AUCs) for predicting recurrence-free survival and overall survival based on tumor grade and stage. Figure 7 EF).

[0117] 8. Validate the predictive power of the endometrial cancer prognostic model in a test cohort. The predictive power of the above endometrial cancer prognostic model was validated using 532 patients with endometrioid adenocarcinoma from the TCGA human cancer database as a test cohort (TCGA cohort).

[0118] 1. Analyze the expression patterns of DUSP1, BUB1, and MCM7 in the TCGA cohort and the relationship between their combined application and prognosis. The results showed that the expression levels of BUB1 and MCM7 were relatively elevated in patients with higher stage, higher grade, and more aggressive disease. Meanwhile, the expression pattern of DUSP1 was opposite to that of the other two genes. Figure 8 AI). Furthermore, BUB1 and MCM7 expression was also higher in EC tissues than in normal tissues (AI). Figure 8 J). Kaplan-Meier curve analysis showed that, compared with other subgroups in the TCGA cohort, the low DUSP1 and high BUB1 / MCM7 subgroups (low DUSP1 expression, high BUB1 expression, and high MCM7 expression) had poorer prognoses in terms of recurrence-free survival and overall survival. Figure 8 KL), consistent with the results of the cohort of 152 samples mentioned above.

[0119] 2. Validate the predictive power of the prognostic risk score and total score model for endometrial cancer in the TCGA cohort. A risk scoring model was introduced into the TCGA cohort to calculate the risk score for each individual. Patients with endometrioid adenocarcinoma in the test cohort were then divided into high-risk and low-risk groups based on the median score. ROC curve analysis was then used to analyze the power of the risk score in predicting recurrence-free survival and overall survival. Results showed that the AUCs of the risk scoring model in the TCGA cohort for predicting 3-year recurrence-free survival and 3-year overall survival were 0.709 and 0.728, respectively; the AUCs for 5-year recurrence-free survival and 5-year overall survival were 0.739 and 0.757, respectively; and the AUCs for 7-year recurrence-free survival and 7-year overall survival were 0.723 and 0.752, respectively. Figure 8 (MN). This demonstrates that the endometrial cancer prognostic risk scoring model of the present invention performed excellently in the test cohort.

[0120] Risk scores and total scores were calculated for patients in the test cohort based on the risk scoring model and the total score model. Patients with endometrioid adenocarcinoma were then divided into low-risk and high-risk groups according to the median values ​​of their risk and total scores. ROC curve analysis was then used to analyze the predictive power of the risk and total scores for recurrence-free survival and overall survival. ROC curve analysis showed that the areas under the ROC curve (AUC) for the endometrial cancer prognostic risk scoring model of this invention in predicting recurrence-free survival and overall survival were 0.577 and 0.662, respectively, and the areas under the ROC curve (AUC) for the endometrial cancer prognostic total score model of this invention in predicting recurrence-free survival and overall survival were 0.669 and 0.784, respectively. Figure 9 and Figure 10 ).

[0121] In summary, the various prognostic models for endometrioid adenocarcinoma constructed in this invention can accurately and comprehensively predict the recurrence and survival outcomes of endometrial cancer patients. They can be used for stratified management of endometrial cancer patients, reduce overtreatment, and accurately predict recurrence.

[0122] The present invention has been described in detail above. For those skilled in the art, the invention can be practiced in a wide range of ways with equivalent parameters, concentrations, and conditions without departing from its spirit and scope, and without requiring unnecessary experiments. Although specific embodiments have been given, it should be understood that further modifications can be made to the invention. In summary, according to the principles of the invention, this application is intended to include any changes, uses, or improvements to the invention, including changes made using conventional techniques known in the art that depart from the scope disclosed herein. Some of the essential features can be applied within the scope of the following appended claims.

Claims

1. Application of substances used to detect the expression levels of BUB1, DUSP1, and MCM7 in any of the following A1)-A3): A1) Prepare products for prognostic assessment of patients with endometrial cancer; A2) To develop products for assessing the prognostic recurrence-free survival rate of patients with endometrial cancer; A3) Prepare products for assessing overall survival in patients with endometrial cancer.

2. The application of substances for detecting the expression levels of BUB1, DUSP1, and MCM7, and media loaded with the prognostic scoring model formula for endometrial cancer, in any of the following A1)-A3): A1) Prepare products for prognostic assessment of patients with endometrial cancer; A2) To develop products for assessing the prognostic recurrence-free survival rate of patients with endometrial cancer; A3) Prepare products for assessing overall survival in patients with endometrial cancer; The endometrial cancer prognostic scoring model includes an endometrial cancer prognostic risk scoring model and an endometrial cancer overall prognostic scoring model. The prognostic risk scoring model for endometrial cancer includes a recurrence-free survival risk scoring model and an overall survival risk scoring model. The overall prognostic scoring model for endometrial cancer includes a recurrence-free survival scoring model and an overall survival scoring model. The formula for the relapse-free survival risk scoring model is as follows: Relapse-free survival risk score = (BUB1 × 0.117) - (DUSP1 × 2.135) + (MCM7 × 1.163) Equation I; where, If BUB1 is highly expressed, then BUB1 is 1; if BUB1 is poorly expressed, then BUB1 is 0. If DUSP1 is highly expressed, then DUSP1 is 1; if DUSP1 is poorly expressed, then DUSP1 is 0. If MCM7 is highly expressed, then MCM7 is 1; if MCM7 is poorly expressed, then MCM7 is 0. The total survival risk score model formula is as follows: Total Survival Risk Score = (BUB1 × 0.681) - (DUSP1 × 1.503) + (MCM7 × 1.049) Equation II; where, if BUB1 is highly expressed, then BUB1 takes the value of 1, and if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, and if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, and if MCM7 is poorly expressed, then MCM7 takes the value of 0. The formula for the relapse-free survival total score model is as follows: Relapse-free survival total score = exp(RFS linear predictive value) Equation III; where, RFS linear predictive value = 0.0915 × geneSignature = 2 + 17.6706 × geneSignature = 3 + 18.198 × geneSignature = 4 + 19.1022 × geneSignature = 5 + 19.9294 × geneSignature = 6 + 20.4149 × geneSignature = 7 + 21.0384 × geneSignature = 8 + 2.2812 × stage = stage II - IV; If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is low expressed, BUB1 is high expressed, and MCM7 is high expressed, then geneSignature=2 is 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; GeneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is lowly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. Conversely, if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is lowly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, and geneSignature=8 are all set to 0. For neSignature=6 and geneSignature=8, the value is 0. If DUSP1, BUB1, and MCM7 are all lowly expressed, then geneSignature=8 is 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=7 are all 0. If the tumor stage is stage II-IV, then stage=stageII-IV is 1; if the tumor stage is not stage II-IV, then stage=stageII-IV is 0. The overall survival score model formula is as follows: Overall Survival Score = exp(OS linear predictive value) Equation IV; where, OS linear predictive value = (-0.4204) × geneSignature = 2 + 18.9083 × geneSignature = 3 + 19.7752 × geneSignature = 4 + (-0.1956) × geneSignature = 5 + (-1.1338) × geneSignature = 6 + 21.2686 × geneSignature = 7 + 20.1785 × geneSignature = 8 + (-15.4608) × stage = stageII-IV + (-0.1256) × grade = 2 + 1.0165 × grade = 3; If DUSP1, BUB1, and MCM7 are all highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0; If DUSP1 is lowly expressed, BUB1, and MCM7 are all highly expressed, then geneSignature=2 will be 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0. All values ​​are set to 0; if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=3 is set to 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0; if DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is poorly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is poorly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, geneSignature=8 are all set to 0. For tumors with low expression levels of DUSP1, BUB1, and MCM7, the values ​​for geneSignature=8, ure=4, geneSignature=5, geneSignature=6, and geneSignature=8 are all 0. For tumors with low expression levels of stage II-IV, the value for stage=stageII-IV is 1; for tumors with a stage other than stage II-IV, the value for stage=stageII-IV is 0. For tumors with a grade of G2, the value for grade=2 is 1, and the value for grade=3 is 0. For tumors with a grade of G3, the value for grade=3 is 1, and the value for grade=2 is 0. For tumors with a grade of G1, the values ​​for grade=2 and grade=3 are both 0.

3. The application according to claim 1 or 2, characterized in that: The endometrial cancer mentioned is endometrioid adenocarcinoma.

4. A kit for assessing the prognosis of endometrial cancer, comprising a substance for detecting the expression levels of BUB1, DUSP1 and MCM7 and a medium loading the endometrial cancer prognostic scoring model formula as described in claim 2.

5. The kit of claim 4, wherein: The endometrial cancer mentioned is endometrioid adenocarcinoma.

6. A data processing device for assessing the prognosis of endometrial cancer, wherein the data processing device is data processing device A, data processing device B, data processing device C or data processing device D; The data processing device A includes a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data from endometrial cancer patients; substituting the data into a recurrence-free survival risk scoring model formula to calculate a recurrence-free survival risk score for endometrial cancer patients; and assessing the recurrence-free survival rate of endometrial cancer patients based on the recurrence-free survival risk score. The data processing device B includes a memory, a processor, and a computer program stored in the memory, characterized in that: the processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data of endometrial cancer patients; substituting the data into an overall survival risk scoring model to calculate an overall survival risk score for endometrial cancer patients; and assessing the overall survival rate of endometrial cancer patients based on the overall survival score. The data processing device C includes a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data and tumor staging data from endometrial cancer patients; substituting the data into a recurrence-free survival total score model to calculate the recurrence-free survival total score for endometrial cancer patients; and assessing the recurrence-free survival rate of endometrial cancer patients based on the recurrence-free survival total score. The data processing device D includes a memory, a processor, and a computer program stored in the memory, characterized in that: the processor executes the computer program to perform the following steps: receiving BUB1, DUSP1, and MCM7 expression level data, tumor stage data, and tumor grade data of endometrial cancer patients; substituting the data into an overall survival score model to calculate the overall survival score of endometrial cancer patients; and assessing the overall survival rate of endometrial cancer patients based on the overall survival score. The formula for the relapse-free survival risk scoring model is as follows: Relapse-free survival risk score = (BUB1 × 0.117) - (DUSP1 × 2.135) + (MCM7 × 1.163) Equation I; where, if BUB1 is highly expressed, then BUB1 takes the value of 1, if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, if MCM7 is poorly expressed, then MCM7 takes the value of 0. The total survival risk score model formula is as follows: Total Survival Risk Score = (BUB1 × 0.681) - (DUSP1 × 1.503) + (MCM7 × 1.049) Equation II; where, if BUB1 is highly expressed, then BUB1 takes the value of 1, and if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, and if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, and if MCM7 is poorly expressed, then MCM7 takes the value of 0. The formula for the relapse-free survival total score model is as follows: Relapse-free survival total score = exp(RFS linear predictive value) Equation III; where, RFS linear predictive value = 0.0915 × geneSignature = 2 + 17.6706 × geneSignature = 3 + 18.198 × geneSignature = 4 + 19.1022 × geneSignature = 5 + 19.9294 × geneSignature = 6 + 20.4149 × geneSignature = 7 + 21.0384 × geneSignature = 8 + 2.2812 × stage = stage II - IV; If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is low expressed, BUB1 is high expressed, and MCM7 is high expressed, then geneSignature=2 is 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; GeneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is lowly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. Conversely, if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is lowly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, and geneSignature=8 are all set to 0. For neSignature=6 and geneSignature=8, the value is 0. If DUSP1, BUB1, and MCM7 are all lowly expressed, then geneSignature=8 is 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=7 are all 0. If the tumor stage is stage II-IV, then stage=stageII-IV is 1; if the tumor stage is not stage II-IV, then stage=stageII-IV is 0. The overall survival score model formula is as follows: Overall Survival Score = exp(OS linear predictive value) Equation IV; where, OS linear predictive value = (-0.4204) × geneSignature = 2 + 18.9083 × geneSignature = 3 + 19.7752 × geneSignature = 4 + (-0.1956) × geneSignature = 5 + (-1.1338) × geneSignature = 6 + 21.2686 × geneSignature = 7 + 20.1785 × geneSignature = 8 + (-15.4608) × stage = stageII-IV + (-0.1256) × grade = 2 + 1.0165 × grade = 3; If DUSP1, BUB1, and MCM7 are all highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0; If DUSP1 is lowly expressed, BUB1, and MCM7 are all highly expressed, then geneSignature=2 will be 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0. All values ​​are set to 0; if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=3 is set to 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0; if DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is poorly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is poorly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, geneSignature=8 are all set to 0. For tumors with low expression levels of DUSP1, BUB1, and MCM7, the values ​​for geneSignature=8, ure=4, geneSignature=5, geneSignature=6, and geneSignature=8 are all 0. For tumors with low expression levels of stage II-IV, the value for stage=stageII-IV is 1; for tumors with a stage other than stage II-IV, the value for stage=stageII-IV is 0. For tumors with a grade of G2, the value for grade=2 is 1, and the value for grade=3 is 0. For tumors with a grade of G3, the value for grade=3 is 1, and the value for grade=2 is 0. For tumors with a grade of G1, the values ​​for grade=2 and grade=3 are both 0.

7. A method for assessing the prognosis of endometrial cancer, said method being method A, method B, method C, or method D; Method A includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 in patients with endometrial cancer to obtain BUB1, DUSP1, and MCM7 expression level data; substituting the data into a recurrence-free survival risk scoring model to calculate a recurrence-free survival risk score for patients with endometrial cancer; and assessing the recurrence-free survival rate of patients with endometrial cancer based on the recurrence-free survival risk score. Method B includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 in patients with endometrial cancer to obtain BUB1, DUSP1, and MCM7 expression level data; substituting the data into an overall survival risk scoring model to calculate an overall survival risk score for patients with endometrial cancer; and assessing the overall survival rate of patients with endometrial cancer based on the overall survival risk score. Method C includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7 and the tumor stage of endometrial cancer patients to obtain BUB1, DUSP1, and MCM7 expression level data and tumor stage data; substituting the data into a recurrence-free survival total score model to calculate the recurrence-free survival total score of endometrial cancer patients; and assessing the recurrence-free survival rate of endometrial cancer patients based on the recurrence-free survival total score. Method D includes the following steps: detecting the expression levels of BUB1, DUSP1, and MCM7, tumor stage, and tumor grade in the tissues of endometrial cancer patients to obtain the expression levels of BUB1, DUSP1, and MCM7, tumor stage, and tumor grade; substituting the data into an overall survival score model to calculate the overall survival score of endometrial cancer patients; and assessing the overall survival rate of endometrial cancer patients based on the overall survival score. The formula for the relapse-free survival risk scoring model is as follows: Relapse-free survival risk score = (BUB1 × 0.117) - (DUSP1 × 2.135) + (MCM7 × 1.163) Equation I; where, If BUB1 is highly expressed, then BUB1 is 1; if BUB1 is poorly expressed, then BUB1 is 0. If DUSP1 is highly expressed, then DUSP1 is 1; if DUSP1 is poorly expressed, then DUSP1 is 0. If MCM7 is highly expressed, then MCM7 is 1; if MCM7 is poorly expressed, then MCM7 is 0. The total survival risk score model formula is as follows: Total Survival Risk Score = (BUB1 × 0.681) - (DUSP1 × 1.503) + (MCM7 × 1.049) Equation II; where, if BUB1 is highly expressed, then BUB1 takes the value of 1, and if BUB1 is poorly expressed, then BUB1 takes the value of 0; if DUSP1 is highly expressed, then DUSP1 takes the value of 1, and if DUSP1 is poorly expressed, then DUSP1 takes the value of 0; if MCM7 is highly expressed, then MCM7 takes the value of 1, and if MCM7 is poorly expressed, then MCM7 takes the value of 0. The formula for the relapse-free survival total score model is as follows: Relapse-free survival total score = exp(RFS linear predictive value) Equation III; where, RFS linear predictive value = 0.0915 × geneSignature = 2 + 17.6706 × geneSignature = 3 + 18.198 × geneSignature = 4 + 19.1022 × geneSignature = 5 + 19.9294 × geneSignature = 6 + 20.4149 × geneSignature = 7 + 21.0384 × geneSignature = 8 + 2.2812 × stage = stage II - IV; If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is low expressed, BUB1 is high expressed, and MCM7 is high expressed, then geneSignature=2 is 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; If DUSP1 is high expressed, BUB1 is low expressed, and MCM7 is high expressed, then geneSignature=3 is 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all 0; GeneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is lowly expressed, BUB1 is highly expressed, and MCM7 is lowly expressed, then geneSignature=6 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. Conversely, if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is lowly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, and geneSignature=8 are all set to 0. For neSignature=6 and geneSignature=8, the value is 0. If DUSP1, BUB1, and MCM7 are all lowly expressed, then geneSignature=8 is 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, and geneSignature=7 are all 0. If the tumor stage is stage II-IV, then stage=stageII-IV is 1; if the tumor stage is not stage II-IV, then stage=stageII-IV is 0. The overall survival score model formula is as follows: Overall Survival Score = exp(OS linear predictive value) Equation IV; where, OS linear predictive value = (-0.4204) × geneSignature = 2 + 18.9083 × geneSignature = 3 + 19.7752 × geneSignature = 4 + (-0.1956) × geneSignature = 5 + (-1.1338) × geneSignature = 6 + 21.2686 × geneSignature = 7 + 20.1785 × geneSignature = 8 + (-15.4608) × stage = stageII-IV + (-0.1256) × grade = 2 + 1.0165 × grade = 3; If DUSP1, BUB1, and MCM7 are all highly expressed, then geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0; If DUSP1 is lowly expressed, BUB1, and MCM7 are all highly expressed, then geneSignature=2 will be 1, and geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 will all be 0. All values ​​are set to 0; if DUSP1 is highly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=3 is set to 1, and geneSignature=2, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0; if DUSP1 is lowly expressed, BUB1 is lowly expressed, and MCM7 is highly expressed, then geneSignature=4 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=5, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0.If DUSP1 is highly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=5 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=6, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is poorly expressed, BUB1 is highly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=7, and geneSignature=8 are all set to 0. If DUSP1 is highly expressed, BUB1 is poorly expressed, and MCM7 is poorly expressed, then geneSignature=7 is set to 1, and geneSignature=2, geneSignature=3, geneSignature=4, geneSignature=5, geneSignature=6, geneSignature=7, geneSignature=8 are all set to 0. For tumors with low expression levels of DUSP1, BUB1, and MCM7, the values ​​for geneSignature=8, ure=4, geneSignature=5, geneSignature=6, and geneSignature=8 are all 0. For tumors with low expression levels of stage II-IV, the value for stage=stageII-IV is 1; for tumors with a stage other than stage II-IV, the value for stage=stageII-IV is 0. For tumors with a grade of G2, the value for grade=2 is 1, and the value for grade=3 is 0. For tumors with a grade of G3, the value for grade=3 is 1, and the value for grade=2 is 0. For tumors with a grade of G1, the values ​​for grade=2 and grade=3 are both 0.

8. The data processing apparatus according to claim 6 or the method according to claim 7, characterized in that: The endometrial cancer mentioned is endometrioid adenocarcinoma.

9. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor, it implements the steps of the method described in claim 7 or 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium enables a computer to perform the steps of the method of claim 7 or 8.

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