Model for judging responsiveness of platinum chemotherapeutic drugs and application thereof

Abstract

The invention discloses a model for judging platinum chemotherapeutic drug responsiveness of an ovarian cancer patient, which is characterized in that a homologous recombination repair defect score of a sample is firstly obtained, and a homologous recombination repair defect state of the sample is judged based on a positive threshold value of the homologous recombination repair defect score; and judging the platinum chemotherapeutic drug responsiveness of the ovarian cancer patient in combination with the expression level of the to-be-detected sample gene. When the model is used for judging the responsiveness of the platinum chemotherapeutic drugs of the ovarian cancer patient to be detected, the accuracy is higher than 80%, and compared with the mode that the homologous recombination repair defect state is judged only through the homologous recombination repair defect score, and then the responsiveness of the platinum chemotherapeutic drugs of the ovarian cancer patient is judged, the accuracy is improved by about 11%; the model provided by the invention can be used for accurately judging the responsiveness of the platinum chemotherapeutic drugs of the to-be-detected ovarian cancer patient, so that guidance is provided for clinical use of platinum drugs.

Description

Technical Field

[0001] This invention relates to the field of molecular biology, and more specifically, to a model for determining the responsiveness of platinum-based chemotherapy drugs and its application. Background Technology

[0002] Ovarian cancer (OV) is a common malignant tumor of the female reproductive system, and there is currently no cure. The classic treatment regimen is surgery combined with platinum-based chemotherapy, with an average 5-year survival rate of approximately 30%. Homologous Recombination Deficiency (HRD) status is a classic biological indicator used to predict and evaluate the efficacy of platinum-based chemotherapy. It can, to some extent, segment patients, expanding the proportion of ovarian cancer patients who benefit from the treatment from 20% to 50%.

[0003] Homologous recombination repair (HRR) is an intracellular DNA double-strand break (DSB) repair pathway based on complementary strand repair. Due to its high fidelity, it is also the preferred repair method in cells. When an HRD state occurs in the cell, HRR cannot be used normally, and DSBs will rely on alternative non-homologous end joining (NHEJ), microhomology-mediated end joining (MMEJ), and single-strand annealing (SSA) for repair. These methods do not completely depend on the template strand, which can easily lead to new gene mutations, ultimately resulting in genomic instability and cell death.

[0004] Platinum-based chemotherapy drugs (such as cisplatin, carboplatin, and oxaliplatin) induce DNA double-strand breaks (DSBs) and inhibit tumor cell proliferation by binding to DNA and forming complex structures that are detrimental to cellular transcription and replication. When ovarian cancer cells are unable to effectively repair themselves using HRR due to HRD (higher risk factor), the DSBs induced by these drugs force cancer cells to rely on low-fidelity repair pathways, further increasing genomic instability. Because these pathways are not precise enough, errors in the repair process lead to the accumulation of more mutations, thereby activating intracellular stress responses and programmed cell death pathways (such as apoptosis), ultimately leading to cancer cell death. Platinum-based chemotherapy drugs can exert their killing effect more effectively when tumor cells are in an HRD state; therefore, assessing a patient's HRD state is considered an important biological marker for predicting the efficacy of platinum-based chemotherapy drugs.

[0005] Currently, HRD status is primarily assessed by calculating one or more of the following: the number of loss of heterozygosity (LOH), the number of telomere allelic imbalances (TAI), and the number of large-scale state transitions (LST), using unweighted or weighted evaluation (HRD score). For example, the FDA-approved test product Myriad myChoice® CDx (Myriad Genetic Laboratories, Inc.) defines HRD positivity as the presence of BRCA1 / 2 somatic or germline pathogenic mutations in tumor cells and / or an HRD score ≥ 42. This threshold is based on the fifth quartile in BRCA-deficient ovarian and breast cancer samples. Another FDA-approved test product, Foundation Focus® CDx BRCALOH (Foundation Medicine, Inc.), defines HRD positivity as the presence of BRCA1 / 2 somatic or germline pathogenic mutations in tumor cells and / or a LOH score ≥ 16%.

[0006] These detection indicators have been validated in large-scale clinical studies, but they cannot fully reflect the effects of platinum-based chemotherapy in the real world. Therefore, the accuracy of their judgment on the HRD status of ovarian cancer patient samples needs to be improved. The main reasons include the following two points: (1) The assessment method only considers the HRD status, but does not consider other factors such as the tumor microenvironment, drug transport and efflux, upstream and downstream supplementation or abnormal activation of repair pathways; (2) It does not fully consider the expression of genes involved in the effects of platinum-based chemotherapy. The status of these genes may not be reflected in exome sequencing or HRD status.

[0007] Therefore, there is a current need for a method that can more accurately determine the HRD status of ovarian cancer patient samples, thereby guiding the use of platinum-based chemotherapy drugs. Summary of the Invention

[0008] The purpose of this invention is to overcome the above-mentioned shortcomings of the prior art and to provide a model for judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs and its application.

[0009] The first objective of this invention is to provide a detection reagent for use in the preparation of a product for assessing the responsiveness of platinum-based chemotherapy drugs in patients with ovarian cancer who are positive for homologous recombination repair defects.

[0010] A second objective of this invention is to provide a detection reagent used in the preparation of a product for assessing the responsiveness of platinum-based chemotherapy drugs in patients with homologous recombination repair-deficient ovarian cancer.

[0011] A third objective of this invention is to provide a detection reagent for use in the preparation of products for assessing the responsiveness to platinum-based chemotherapy drugs.

[0012] A fourth objective of this invention is to provide a product for assessing the responsiveness to platinum-based chemotherapy drugs.

[0013] The fifth objective of this invention is to provide a model for assessing the response of platinum-based chemotherapy drugs in ovarian cancer patients with positive homologous recombination repair defects.

[0014] The sixth objective of this invention is to provide a model for assessing the responsiveness of platinum-based chemotherapy drugs in ovarian cancer patients with negative homologous recombination repair defects.

[0015] The seventh objective of this invention is to provide a model for determining the responsiveness of platinum-based chemotherapy drugs.

[0016] To achieve the above objectives, the present invention is implemented through the following solution: The use of a detection reagent in the preparation of a product for assessing the response of platinum-based chemotherapy drugs in patients with homologous recombination repair deficiency-positive ovarian cancer; the detection reagent is a reagent for detecting gene expression levels, wherein the genes are ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR.

[0017] Preferably, the positive threshold for homologous recombination repair deficiency score in the homologous recombination repair deficiency-negative ovarian cancer patient sample is 38-45.

[0018] More preferably, the positive threshold for the homologous recombination repair defect score is 38, 39, 44 or 45.

[0019] More preferably, the positive threshold for the homologous recombination repair defect score is 45.

[0020] Preferably, the platinum-based drug is cisplatin, carboplatin, oxaplatin, nedaplatin, and / or ethylpropionate platinum.

[0021] The present invention also claims the use of a detection reagent in the preparation of a product for assessing the responsiveness of platinum-based chemotherapy drugs in samples from patients with homologous recombination repair deficiency-negative ovarian cancer, wherein the detection reagent is a reagent for detecting gene expression levels; the genes are AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B.

[0022] Preferably, the positive threshold for homologous recombination repair deficiency score in the homologous recombination repair deficiency-negative ovarian cancer patient sample is 38-45.

[0023] More preferably, the positive threshold for the homologous recombination repair defect score is 38, 39, 44 or 45.

[0024] More preferably, the positive threshold for the homologous recombination repair defect score is 45.

[0025] Preferably, the platinum-based drug is cisplatin, carboplatin, oxaplatin, nedaplatin, and / or ethylpropionate platinum.

[0026] The present invention also claims protection for the use of a detection reagent in the preparation of a product for assessing the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs, wherein the detection reagent is a reagent for detecting gene expression levels; wherein the genes are AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B.

[0027] The present invention also claims protection for a product for assessing the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs, characterized in that it contains a detection reagent for detecting the expression levels of each gene in a gene combination, said gene combination including ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR.

[0028] Preferably, the gene combination includes AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B.

[0029] The present invention also claims protection for a model for determining the responsiveness of platinum-based chemotherapy drugs in patients with homologous recombination repair deficiency-positive ovarian cancer, including a determination module and a result output module; The judgment module determines the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs based on the expression levels of the following genes in samples of ovarian cancer patients with homologous recombination repair deficiency. The genes include ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR genes; The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

[0030] Preferably, the platinum-based drug is cisplatin, carboplatin, oxaplatin, nedaplatin, and / or ethylpropionate platinum.

[0031] The present invention also claims protection for a model for determining the responsiveness of platinum-based chemotherapy drugs in samples of patients with homologous recombination repair deficiency-negative ovarian cancer, including a determination module and a result output module; The judgment module determines the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs based on the expression levels of the following genes in samples of ovarian cancer patients with homologous recombination repair deficiency. The genes include AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B genes. The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

[0032] Preferably, the platinum-based drug is cisplatin, carboplatin, oxaplatin, nedaplatin, and / or ethylpropionate platinum.

[0033] This invention also claims protection for a model for determining the responsiveness of platinum-based chemotherapy drugs, including a data acquisition module, a judgment module, and a result output module; The data acquisition module is used to acquire homologous recombination repair defect scores of ovarian cancer patient samples and to determine the homologous recombination repair defect status of ovarian cancer patients based on the positive threshold of the homologous recombination repair defect score. The judgment module assesses the platinum-based chemotherapy response of ovarian cancer patients by combining the expression levels of ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR genes in ovarian cancer patient samples that are positive for homologous recombination repair defects obtained by the data acquisition module. For ovarian cancer patient samples with a negative homologous recombination repair deficiency status obtained from the data acquisition module, the expression levels of the AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR and TMEM30B genes in the samples were used to determine the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs. The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

[0034] Preferably, the sample is a sample from an ovarian cancer patient.

[0035] Furthermore, the samples were selected from patients with advanced serous ovarian cancer.

[0036] More preferably, the sample is a sample from a patient with advanced plasma ovarian cancer who has received platinum-based therapy.

[0037] Preferably, the homologous recombination repair defect score in the data acquisition module is an unweighted sum of the heterozygous deletion score (LOH score), the telomere genotype imbalance score (TAI score), and the large-scale structural transfer score (LST score).

[0038] More preferably, the homologous recombination repair defect score is calculated using the scarHRD software.

[0039] Preferably, the positive threshold for homologous recombination repair defect scoring in the data acquisition module is 38-45.

[0040] More preferably, the positive threshold for the homologous recombination repair defect score is 38, 39, 44 or 45.

[0041] More preferably, the positive threshold for the homologous recombination repair defect score is 45.

[0042] Preferably, in the judgment module, for ovarian cancer patient samples with a positive homologous recombination repair defect status obtained by the data acquisition module, the platinum-based drug responsiveness of ovarian cancer patients is judged using Formula I; Formula I: F1 = A0 - A1 × ANXA4 + A2 × CD27 - A3 × GRB7 + A4 × GSTZ1 + A5 × SHMT2 - A6 × TCF15 - A7 × WARS - A8 × GALNT6 + A9 × ZFR; where A0 to A9 are obtained through LASSO regression analysis; ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6 and ZFR in Formula I represent the expression levels of the corresponding genes in ovarian cancer patient samples.

[0043] More preferably, A0 to A9 are obtained through a LASSO regression analysis model, wherein the regularization parameter λ1 of the LASSO regression analysis model is 0.01629.

[0044] More preferably, when A0 to A9 are obtained through the LASSO regression analysis model, LASSO regression analysis is performed by combining the expression levels of ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR genes in sample set 1 with the platinum-based chemotherapy response of ovarian cancer patients in sample set 1; the samples in sample set 1 are homologous recombination repair defect-positive samples from 196 patients with advanced plasma ovarian cancer who have detailed records of their post-platinum-based drug use, as described in the paper (PMID: 21720365).

[0045] More preferably, the samples in sample set 1 are samples with a homologous recombination repair deficiency score >45 from 196 patients with advanced plasma ovarian cancer who have detailed records of their post-platinum drug use, as described in the paper (PMID: 21720365).

[0046] More preferably, Formula I is: F1=0.256309071612022-0.0194163477558527×ANXA4+0.669038155514554×CD27-0.232859065953763×GRB7+0.178899693365171×GSTZ1+0 .623906367787577×SHMT2-0.368400667169836×TCF15-0.280938533614944×WARS-0.221539503346267×GALNT6+0.672754144414643×ZFR.

[0047] More preferably, in Formula I, ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR are the expression levels of the corresponding genes in the sample. After Z-score standardization, they are divided into upper and lower quartiles. Genes located in the upper quartile are assigned a value of 2, genes located in the lower quartile are assigned a value of 0, and genes located in the middle quartile are assigned a value of 1.

[0048] More preferably, the Z-score normalization is based on the expression level of the corresponding gene in the background sample set, which is the tumor sample set of 196 patients with advanced plasma ovarian cancer described in the paper (PMID: 21720365) with detailed records of their post-treatment status with platinum-based drugs.

[0049] All 196 patients with advanced plasma ovarian cancer in the background sample set underwent whole exome sequencing and transcriptome sequencing, and the sequencing data are described in the paper (PMID: 21720365).

[0050] More preferably, for ovarian cancer patient samples with a positive homologous recombination repair defect status obtained by the data acquisition module, if the F1 calculated using Formula I is ≥0.5, the sample is a sample of ovarian cancer patients sensitive to platinum-based chemotherapy drugs; otherwise, it is a sample of ovarian cancer patients resistant to platinum-based chemotherapy drugs.

[0051] Preferably, in the judgment module, for samples with a negative homologous recombination repair defect status obtained by the data acquisition module, the platinum-based chemotherapy response of ovarian cancer patients is judged using Formula II; Formula II: F2 = B0 + B1 × AADAC + B2 × ADA - B3 × ANXA4 - B4 × CD27 + B5 × GJB1 + B6 × GRB7 + B7 × GSTZ1 + B8 × SHMT2 - B9 × TCF15 + B 10 ×WARS-B 11 ×TNFSF11-B 12 ×UBD-B 13 ×GALNT6-B 14 ×PHF20+B 15 ×ZFR-B 16 ×TMEM30B; where B0~B 16 The results were obtained through LASSO regression analysis model; AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR and TMEM30B in Formula II represent the expression levels of the corresponding genes in the samples.

[0052] More preferably, B0~B 16 The regularization parameter λ2 of the LASSO regression analysis model was obtained as 0.008965.

[0053] More preferably, B0 to B1 are obtained through a LASSO regression analysis model. 16 At the same time, LASSO regression analysis was performed on the expression levels of AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR and TMEM30B genes in sample set 2 and their response to platinum-based chemotherapy drugs. The samples in sample set 2 were homologous recombination repair defect-negative samples from 196 patients with advanced plasma ovarian cancer who had detailed records of their post-treatment status with platinum-based drugs, as described in the paper (PMID: 21720365).

[0054] More preferably, the samples in sample set 2 are samples with a homologous recombination repair deficiency score ≤45 from 196 patients with advanced plasma ovarian cancer who have detailed records of their post-platinum drug use, as described in the paper (PMID: 21720365).

[0055] More preferably, Formula II is: F2 = 2.63480181408828 + 1.75414711832022 × AADAC + 1.61744050879368 × ADA - 0.335529411791532 × ANXA4 - 2.85124109729058 × CD27 + 0.855056380659892 × GJB1 + 2.55634098439207 × GRB7 + 0.280308617354185 × GSTZ1 + 0.239486972 628679×SHMT2-1.96629329833821×TCF15+0.109161478982231×WARS-1.82019288788304×TNFSF11-0.108601110679264×UBD-0.0338767735048593×GALNT6-3.78049656515552×PHF20+1.36369711583015×ZFR-0.536490390878037×TMEM30B.

[0056] More preferably, in Formula II, AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B are the expression levels of the corresponding genes in the sample, which are Z-score standardized and then divided into upper and lower quartiles. Genes located in the upper quartile are assigned a value of 2, genes located in the lower quartile are assigned a value of 0, and genes located in the middle quartile are assigned a value of 1.

[0057] More preferably, the Z-score normalization is based on the expression level of the corresponding gene in the background sample set, which is the tumor sample set of 196 patients with advanced plasma ovarian cancer described in the paper (PMID: 21720365) with detailed records of their post-treatment status with platinum-based drugs.

[0058] More preferably, for samples with a negative homologous recombination repair defect status obtained by the data acquisition module, if F2 < 0.5 calculated using Formula II, the sample is a sample from a platinum-resistant ovarian cancer patient; otherwise, it is a sample from a platinum-sensitive ovarian cancer patient.

[0059] Preferably, the sample in any of the above methods is a test sample, and the test sample is an ovarian cancer patient sample.

[0060] This invention also claims protection for the use of any of the methods described above in determining the responsiveness to platinum-based chemotherapy drugs.

[0061] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a model for assessing the responsiveness to platinum-based chemotherapy drugs. It first obtains the homologous recombination repair deficiency score of a sample and then determines the homologous recombination repair deficiency status based on a positive threshold for the score. For ovarian cancer patient samples with a positive homologous recombination repair deficiency status, the responsiveness to platinum-based chemotherapy drugs is assessed by combining the expression levels of the ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR genes. For samples with a negative homologous recombination repair deficiency status, the responsiveness to platinum-based chemotherapy drugs is assessed by combining the expression levels of the AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B genes. When using the model described in this invention to determine the responsiveness of samples to platinum-based chemotherapy drugs, the accuracy is higher than 80%, which is about 11% more accurate than using the homologous recombination repair deficiency score to determine the homologous recombination repair deficiency status and thus determine the responsiveness of platinum-based chemotherapy drugs. The model described in this invention can accurately determine the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs, thereby providing guidance for the clinical use of platinum-based drugs. Attached Figure Description

[0062] Figure 1 This is a graph showing the accuracy results of judging platinum drug sensitivity under each HRD score threshold in Example 1; Figure 2 This is a forest plot of the Cox proportional hazards regression model in Example 1; Figure 3 The following are ROC results for assessing the responsiveness of ovarian cancer patients to platinum-based chemotherapy in Example 2: a) ROC results for assessing the responsiveness of ovarian cancer patients in training set 1 to platinum-based chemotherapy in Example 2 using Formula I; b) ROC results for assessing the responsiveness of ovarian cancer patients in validation set 1 to platinum-based chemotherapy in Example 2 using Formula I; c) ROC results for assessing the responsiveness of ovarian cancer patients in training set 2 to platinum-based chemotherapy in Example 2 using Formula II; d) ROC results for assessing the responsiveness of ovarian cancer patients in validation set 2 to platinum-based chemotherapy in Example 2 using Formula II. Figure 4The first figure shows the ROC results for assessing the responsiveness to platinum-based chemotherapy in Example 3; the second figure shows the ROC results for assessing the responsiveness to platinum-based chemotherapy in training set 3 ovarian cancer patients in Example 3; the third figure shows the ROC results for assessing the responsiveness to platinum-based chemotherapy in validation set 3 ovarian cancer patients in Example 3; and the fourth figure shows the ROC results for assessing the responsiveness to platinum-based chemotherapy in control group 1 of Example 3. Figure 5 This is the ROC result graph for determining the responsiveness of ovarian cancer patients in the test set in Example 3. Detailed Implementation

[0063] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. These embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Unless otherwise specified, the experimental methods used in the following embodiments are conventional methods; the materials and reagents used, unless otherwise specified, are commercially available.

[0064] The clinical samples used in the test set of this embodiment came from the applicant's institution, and the patients were informed and their consent was obtained before the clinical samples were tested.

[0065] Example 1: Determination of HRD score threshold and platinum-based drug responsiveness-related genes I. Experimental Methods 1. Determining the HRD scoring threshold (1) Calculation of HRD score The sample set was selected from the open-source paper (PMID: 21720365) which contained detailed records of patients with high-grade serous ovarian cancer after platinum-based chemotherapy (tumor samples from 196 patients with high-grade serous ovarian cancer) and adjacent normal tissue samples as control samples. All 196 ovarian cancer patients in this sample set had received platinum-based chemotherapy and their post-treatment status (clinical platinum-based chemotherapy resistance) was recorded in detail. Records of efficacy with platinum-based chemotherapy were classified as platinum-based chemotherapy sensitivity, while records of poor or no efficacy with platinum-based chemotherapy were classified as platinum-based chemotherapy tolerance. All 196 ovarian cancer patients in this sample set underwent whole-exome sequencing and transcriptome sequencing, and the sequencing data were all recorded in the paper (PMID: 21720365).

[0066] Based on the whole-exome sequencing results of each ovarian cancer patient in the sample set, the scarHRD software was used to calculate the loss of heterozygosity (LOH), telomere genotype imbalance (TAI), and extensive structural metastasis (LST) scores for each ovarian cancer patient. The LOH, TAI, and LST scores were then summed unweighted to obtain the homologous recombination repair deficiency score (HRD score) for each ovarian cancer patient.

[0067] (2) Screening of HRD scoring thresholds The HRD score positive threshold was set to each integer value between 30 and 55. When the HRD score of an ovarian cancer patient was ≤ the HRD score positive threshold, the patient was considered to be resistant to platinum-based chemotherapy. When the HRD score of an ovarian cancer patient was > the HRD score positive threshold, the patient was considered to be sensitive to platinum-based chemotherapy.

[0068] Using an exhaustive method, based on the platinum-based drug sensitivity of ovarian cancer patients' clinical records, the accuracy (ACC) for judging the platinum-based drug sensitivity of ovarian cancer patients at each HRD score positive threshold was calculated. ACC = Number of ovarian cancer patients whose sensitivity to platinum-based drugs was accurately determined / Total number of ovarian cancer patients in the sample set.

[0069] 2. Identification of platinum-based drug response-related genes Based on transcriptome sequencing data from 196 ovarian cancer patients in the sample set, the expression levels of each gene in each ovarian cancer patient were obtained. The expression levels of each gene were then normalized by Z-score based on the expression levels of the same gene in each ovarian cancer patient to obtain the normalized expression level of each gene. The normalized expression levels of each gene were divided into upper and lower quartiles. Genes with normalized expression levels in the upper quartile were designated as high-expression genes, genes with normalized expression levels in the lower quartile were designated as low-expression genes, and the rest were designated as medium-expression genes. This yielded transcriptome expression level data from 196 ovarian cancer patients in the sample set.

[0070] Using the Cox proportional hazards regression model, the transcriptome expression levels of 196 ovarian cancer patients in the sample set were analyzed in relation to the disease-free survival of ovarian cancer patients (including calculation of Wald test significance, statistical significance P-value, and relative hazard ratio HR). P-value < 0.05 was considered statistically significant, and genes that significantly affect the disease-free survival of ovarian cancer patients were identified.

[0071] II. Experimental Results 1. Determination of HRD scoring thresholds The accuracy results for assessing platinum-based drug sensitivity at each HRD score positive threshold are as follows: Figure 1 As shown, the results indicate that the ACC for judging platinum-based drug sensitivity differs when the HRD score positivity threshold is between 38 and 45. Furthermore, when the HRD score positivity threshold is set to 38, 39, 44, or 45, the ACC for judging platinum-based drug sensitivity reaches 74.0%, 74.0%, 72.5%, and 73.5%, respectively, all of which are higher than the ACC (71.9%) when the HRD threshold is 42.

[0072] Furthermore, when the HRD score positivity threshold was 38, the area under the ROC curve (AUC) for assessing platinum drug sensitivity was 0.609; when the HRD score positivity threshold was 39, the AUC was 0.613; when the HRD score positivity threshold was 44, the AUC was 0.629; and when the HRD score positivity threshold was 45, the AUC was 0.650.

[0073] Therefore, by combining the ACC result value and the corresponding ROC curve area under the curve (AUC), it was determined that the optimal positive threshold for the HRD score used to determine the sensitivity of platinum drugs is 45.

[0074] 2. Results of HRD-related gene identification Using a Cox proportional hazards regression model, the analysis of transcriptomic expression levels and disease-free survival of ovarian cancer patients showed that the expression levels of AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, HLA.DOA, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, SASH1, PHF20, ZFR, and TMEM30B genes were correlated with disease-free survival expectations in ovarian cancer patients (P-value < 0.05).

[0075] The forest plot of the above genes in the Cox proportional hazards regression model is shown below. Figure 2 As shown, the forest plot includes Wald test significance, statistical significance P-value, and relative hazard ratio (HR).

[0076] Example 2: A method for assessing the responsiveness of platinum-based chemotherapy drugs for non-diagnostic purposes I. Experimental Methods 1. Determination of corrective genes in ovarian cancer patients with HRD > 45 (1) Determination of the formula for calculating corrective genes and risk factors Of the 196 ovarian cancer patients in the sample set of Example 1, 153 ovarian cancer patients with HRD scores > 45 were divided into training set: validation set = 7:3. 108 of these ovarian cancer patients were randomly selected as training set 1, and the remaining 45 ovarian cancer patients were selected as validation set 1.

[0077] Using the transcriptome expression level of ovarian cancer patients in training set 1 as a feature and the responsiveness to platinum-based chemotherapy drugs in ovarian cancer patients in training set 1 as a predictor, the regularization parameter λ1=0.01629 was set for LASSO regression analysis. Through LASSO regression analysis, the genes associated with responsiveness to platinum-based chemotherapy drugs in ovarian cancer patients with HRD scores >45 and the related weight coefficients of the genes were obtained, and the risk calculation formula I was derived.

[0078] (2) Validation of the formula for correcting genes and risk calculation Based on the risk calculation formula I obtained in step (1), the responsiveness of ovarian cancer patients in training set 1 to platinum-based chemotherapy drugs is determined, specifically as follows: The expression values ​​of each characteristic gene from ovarian cancer patients in training set 1 are substituted into risk calculation formula I to obtain the final predicted value F. HRD＞45 And rounded to the nearest whole number, F HRD＞45 ≥0.5 is denoted as 1, F HRD＞45 <0.5 is recorded as 0.

[0079] F in ovarian cancer patients in training set 1 HRD＞45 A value of 1 indicates that the ovarian cancer patient is sensitive to platinum-based chemotherapy drugs; the F value of ovarian cancer patients in training set 1 HRD＞45 A value of 0 indicates that the ovarian cancer patient is resistant to platinum-based chemotherapy drugs.

[0080] The AUC value of ovarian cancer patients in training set 1 was determined by combining clinical platinum-based chemotherapy resistance with risk calculation formula I.

[0081] Following the method described above, training set 1 is replaced with validation set 1 to obtain the AUC value when judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs in validation set 1 using risk calculation formula I.

[0082] Simultaneously, based on the risk calculation formula I obtained in step (1), the responsiveness of platinum-based chemotherapy drugs in 153 ovarian cancer patients with HRD scores > 45 among the 196 ovarian cancer patients in the sample set of Example 1 was judged, the results were recorded, and the ACC value was calculated.

[0083] 2. Determination of corrective genes in ovarian cancer patients with HRD ≤ 45 (1) Determination of corrective genes and risk calculation formula Of the 196 ovarian cancer patients in Example 1, 43 ovarian cancer patients with an HRD score ≤ 45 were divided into training set and validation set, with a ratio of 7:3. 31 patients were randomly selected as training set 2, and the remaining 12 ovarian cancer patients were selected as validation set 2.

[0084] Using the transcriptome expression level of ovarian cancer patients in training set 2 as a feature and the platinum-based chemotherapy response of ovarian cancer patients in training set 2 as a predictor, the regularization parameter λ2=0.008965 was set for LASSO regression analysis. Through LASSO regression analysis, the genes related to platinum-based chemotherapy response and their related weight coefficients in samples with HRD scores ≤45 were obtained, and the risk calculation formula II was derived.

[0085] (2) Validation of the formula for correcting genes and risk calculation Based on the risk calculation formula II obtained in step (1), the responsiveness of ovarian cancer patients in training set 2 to platinum-based chemotherapy drugs is determined, specifically as follows: Substituting the expression values ​​of each characteristic gene from ovarian cancer patients in training set 2 into risk calculation formula II, the final predicted value F is calculated. HRD≤45 And rounded to the nearest whole number, F HRD≤45 ≥0.5 is denoted as 1, F HRD≤45 <0.5 is recorded as 0.

[0086] F in ovarian cancer patients in training set 2 HRD≤45 A value of 1 indicates that the ovarian cancer patient is sensitive to platinum-based chemotherapy drugs; the F value of ovarian cancer patients in training set 2... HRD≤45 A value of 0 indicates that the ovarian cancer patient is resistant to platinum-based chemotherapy drugs.

[0087] The AUC value of ovarian cancer patients in training set 2 was determined by combining clinical platinum-based chemotherapy resistance with risk calculation formula II.

[0088] Following the method described above, training set 2 is replaced with validation set 2 to obtain the AUC value when judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs in validation set 2 using risk calculation formula II.

[0089] Simultaneously, using the risk calculation formula II obtained in step (1), the responsiveness of platinum-based chemotherapy drugs in 43 ovarian cancer patients with HRD scores ≤45 among the 196 ovarian cancer patients in the sample set of Example 1 was judged, the results were recorded, and the ACC value was calculated.

[0090] 3. A method for assessing platinum-based drug sensitivity in ovarian cancer patients for non-diagnostic purposes. (1) A method for assessing the sensitivity of a patient with ovarian cancer to platinum-based drugs for non-diagnostic purposes, comprising the following steps: S1. Whole exome sequencing with a sequencing depth of 150× was performed on the ovarian cancer patients to be tested. The loss of heterozygosity score (LOH), telomere genotype imbalance score (TAI), and extensive structural metastasis score (LST) of the ovarian cancer patients to be tested were calculated using scarHRD software. The LOH, TAI and LST were then summed unweighted to obtain the homologous recombination repair deficiency score (HRD score) of the ovarian cancer patients to be tested. The positive threshold of HRD score was set at 45. S2. In step S1, when the homology repeat repair defect score of the ovarian cancer patient to be tested is >45, F is calculated using risk calculation formula I. HRD＞45 F HRD＞45 ≥0.5 indicates that the ovarian cancer patient being tested is a platinum-sensitive ovarian cancer patient; otherwise, the patient is a platinum-resistant ovarian cancer patient. In step S1, when the homologous recombination repair deficiency score of the ovarian cancer patient to be tested is ≤45, F is calculated using risk calculation formula II. HRD≤45 F HRD≤45 ≥0.5 indicates that the ovarian cancer patient being tested is a platinum-sensitive ovarian cancer patient; otherwise, the patient is a platinum-resistant ovarian cancer patient.

[0091] II. Experimental Results 1. Results of corrective gene determination in ovarian cancer patients with HRD > 45 For ovarian cancer patients with an HRD score >45, LASSO regression analysis identified genes associated with patients' response to platinum-based chemotherapy, including ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR. The risk calculation formula is shown in Formula I.

[0092] Formula I: F HRD>45 =0.256309071612022-0.0194163477558527×ANXA4+0.669038155514554×CD27-0.232859065953763×GRB7+0.178899693365171×GSTZ1+0.623906367787577×SHMT2-0.368400667169836×TCF15-0.280938533614944×WARS-0.221539503346267×GALNT6+0.672754144414643×ZFR; In Formula I, ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR represent the expression levels of corresponding genes in ovarian cancer patients. After Z-score standardization, the expression levels of the same genes in each ovarian cancer patient in the sample of Example 1 are divided into upper quartiles and lower quartiles. Genes located in the upper quartile are assigned a value of 2, genes located in the lower quartile are assigned a value of 0, and genes located in the middle quartile are assigned a value of 1.

[0093] The ROC results for judging the response of ovarian cancer patients to platinum-based chemotherapy drugs in training set 1 using Formula I are as follows: Figure 3 As shown in Figure a, the ROC results for judging the response of ovarian cancer patients to platinum-based chemotherapy drugs in validation set 1, combined with Formula I, are as follows: Figure 3 As shown in b; the results of judging the responsiveness of platinum-based chemotherapy drugs in 153 ovarian cancer patients with HRD scores > 45 among the 196 ovarian cancer patients in the sample set of Example 1, based on Formula I, are shown in Table 1.

[0094] Table 1. Results of assessing the response of ovarian cancer patients with HRD scores > 45 to platinum-based chemotherapy.

[0095] The ACC for assessing the response of ovarian cancer patients with HRD scores > 45 to platinum-based chemotherapy was (109 + 13) / (109 + 22 + 9 + 13) × 100% = 79.7%.

[0096] 2. Results of corrective gene determination in ovarian cancer patients with HRD≤45 For ovarian cancer patients with an HRD score ≤45, LASSO regression analysis identified genes associated with patients' response to platinum-based chemotherapy, including AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B. The risk calculation formula II is shown in Formula II.

[0097] Formula II: F HRD≤45=2.63480181408828+1.75414711832022×AADAC+1.61744050879368×ADA-0.335529411791532×ANXA4-2.85124109729058×CD27+0.855056380659892×GJB1+2.55634098439207×GRB7+0.280308617354185×GSTZ1+0.239486972628679× SHMT2-1.96629329833821×TCF15+0.109161478982231×WARS-1.82019288788304×TNFSF11-0.108601110679264×UB D-0.0338767735048593×GALNT6-3.78049656515552×PHF20+1.36369711583015×ZFR-0.536490390878037×TMEM30B; In Formula II, AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B represent the expression levels of corresponding genes in ovarian cancer patients. After Z-score standardization with the expression levels of the same genes in each ovarian cancer patient in the sample of Example 1, the genes are divided into upper and lower quartiles. Genes located in the upper quartile are assigned a value of 2, genes located in the lower quartile are assigned a value of 0, and genes located in the middle quartile are assigned a value of 1.

[0098] Combined with Formula II, the ROC results for judging the response of ovarian cancer patients to platinum-based chemotherapy drugs in training set 2 are as follows: Figure 3 As shown in c, the ROC results for judging the response of ovarian cancer patients to platinum-based chemotherapy drugs in validation set 2, combined with Formula II, are as follows: Figure 3 As shown in d; the results of judging the responsiveness of platinum-based chemotherapy drugs in 43 ovarian cancer patients with HRD scores ≤45 among the 196 ovarian cancer patients in the sample set of Example 1, combined with Formula II, are shown in Table 2.

[0099] Table 2. Results of assessing the response of platinum-based chemotherapy in 43 ovarian cancer patients with HRD scores ≤45.

[0100] The ACC for assessing the response of ovarian cancer patients with HRD scores ≤45 to platinum-based chemotherapy was (13+22) / (13+4+4+22)×100%=81.4%.

[0101] Example 3: Validation of a method for assessing the responsiveness of platinum-based chemotherapy drugs for non-diagnostic purposes I. Experimental Methods (1) Validation using database samples Using the 196 ovarian cancer patients in Example 1 as the sample set, the ovarian cancer patients in Training Set 1 and Training Set 2 in Example 2 were combined to form Training Set 3 (containing 139 ovarian cancer patients), and the ovarian cancer patients in Validation Set 1 and Validation Set 2 were combined to form Validation Set 3 (containing 57 ovarian cancer patients).

[0102] Following the method described in Example 2 for determining the homologous recombination repair deficiency status of ovarian cancer patients for non-diagnostic purposes, the responsiveness of ovarian cancer patients in training set 3 and validation set 3 to platinum-based chemotherapy drugs was determined, and the AUC values ​​for determining the responsiveness of ovarian cancer patients in training set 3 and validation set 3 to platinum-based chemotherapy drugs were calculated based on the clinical platinum-based chemotherapy resistance of ovarian cancer patients in training set 3 and validation set 3, respectively.

[0103] An experimental group, control group 1, and control group 2 were set up. The experimental group consisted of 196 ovarian cancer patients in the sample set whose platinum drug sensitivity was assessed using the non-diagnostic method for assessing ovarian cancer patients as shown in Example 2.

[0104] Control group 1: Based on the HRD scores of 196 ovarian cancer patients in the sample set, the positive threshold for HRD score was set to 42. Ovarian cancer patients with HRD scores > 42 were judged as HRD positive (HRD exists, platinum-sensitive), and ovarian cancer patients with HRD scores ≤ 42 were judged as HRD negative (no HRD, platinum-resistant). The AUC results when the positive threshold for HRD score was 42 were calculated.

[0105] Control group 2 consisted of 196 ovarian cancer patients in the sample set whose HRD scores were used to set a positive threshold of 45. Ovarian cancer patients with an HRD score > 45 were judged as HRD positive (having HRD and sensitive to platinum-based chemotherapy), while ovarian cancer patients with an HRD score ≤ 45 were judged as HRD negative (not having HRD and resistant to platinum-based chemotherapy).

[0106] (2) Validation using clinical samples The test set consisted of 50 ovarian cancer patients. All ovarian cancer patients in the test set had undergone whole exome sequencing and transcriptome sequencing in accordance with the methods shown in the prior art (PMID: 21720365). All 50 ovarian cancer patients had received clinical platinum-based chemotherapy and their clinical response to platinum-based chemotherapy was recorded.

[0107] The homologous recombination repair deficiency score (HRD score) of each ovarian cancer patient in the test set was calculated as shown in Example 1. The ovarian cancer patients in the test set were divided into ovarian cancer patients with HRD score > 45 (33 ovarian cancer patients) and ovarian cancer patients with HRD score ≤ 45 (17 ovarian cancer patients).

[0108] Following the method for assessing platinum-based chemotherapy responsiveness for non-diagnostic purposes as shown in Example 2, the responsiveness of ovarian cancer patients in the test set to platinum-based chemotherapy was assessed, and the AUC value for assessing the responsiveness of ovarian cancer patients in the test set using the method shown in Example 2 was calculated based on the clinical platinum-based chemotherapy response of each ovarian cancer patient in the test set.

[0109] II. Experimental Results (1) Database sample validation results The ROC results for assessing the platinum-based chemotherapy responsiveness of ovarian cancer patients in training set 3 using the method described in Example 2 for non-diagnostic purposes are as follows: Figure 4 As shown in Figure a, the ROC results for assessing the platinum-based chemotherapy response of ovarian cancer patients in validation set 3, according to the method for non-diagnostic assessment of platinum-based chemotherapy response in ovarian cancer patients as described in Example 2, are as follows: Figure 4 As shown in b, the ROC results for assessing the response of ovarian cancer patients to platinum-based chemotherapy drugs in control group 1 are as follows: Figure 4 As shown in c.

[0110] The results of assessing the sensitivity of ovarian cancer patients in the sample set to platinum-based drugs in the experimental group, control group 1, and control group 2 are shown in Table 3.

[0111] Table 3. Results of assessing platinum-based drug sensitivity in ovarian cancer patients in the sample set (experimental group, control group 1, and control group 2).

[0112] The results showed that: when judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs according to control group 1, ACC=141 / 196×100%=71.9%<80%; when judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs according to control group 2, ACC=144 / 196×100%=73.5%<80%; when judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs according to the experimental group (i.e., the method for judging the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs for non-diagnostic purposes as shown in Example 2), ACC=157 / 196×100%=80.1%>80%.

[0113] (2) Clinical sample validation results The ROC results for assessing the responsiveness of platinum-based chemotherapy drugs in the test set of ovarian cancer patients using the method for non-diagnostic purposes as shown in Example 2 are illustrated in the figure below. Figure 5 As shown, the area under the ROC curve (AUC) when using this method to judge each patient in the test set is 0.796.

[0114] Table 4 shows the results of using Formula I to determine the responsiveness of ovarian cancer patients with HRD scores > 45 in the test set to platinum-based chemotherapy drugs, and Table 5 shows the results of using Formula II to determine the responsiveness of ovarian cancer patients with HRD scores ≤ 45 in the test set to platinum-based chemotherapy drugs.

[0115] Table 4. Results of assessing platinum-based chemotherapy response in ovarian cancer patients with HRD scores > 45 in the test set.

[0116] Table 5. Results of assessing platinum-based chemotherapy response in ovarian cancer patients with HRD scores ≤45 in the test set.

[0117] The ACC for judging the responsiveness of ovarian cancer patients with HRD > 45 in the test set was (8+19) / (8+1+5+19)×100%=81.8%; the ACC for judging the responsiveness of ovarian cancer patients with HRD ≤ 45 in the test set was (9+2) / (9+2+2+4)×100%=76.5%.

[0118] Results show that the method for assessing the responsiveness of platinum-based chemotherapy drugs for non-diagnostic purposes, as described in Example 2, can effectively improve the accuracy of assessing the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs, whether for ovarian cancer samples recorded in the database or actual clinical ovarian cancer samples. This allows for a more accurate assessment of whether ovarian cancer patients are sensitive to platinum-based chemotherapy, providing guidance for precision medicine in clinical practice.

[0119] Example 4: A model for determining the responsiveness to platinum-based chemotherapy drugs A model for determining the responsiveness of borax chemotherapy drugs includes a data acquisition module, a judgment module, and a result output module; The data acquisition module is used to acquire whole exome sequencing data of ovarian cancer patients to be tested and to use scarHRD software to calculate the loss of heterozygosity score (LOH), telomere genotype imbalance score (TAI), and extensive structural metastasis score (LST) of ovarian cancer patients to be tested. The LOH, TAI and LST are then summed unweighted to obtain the homologous recombination repair deficiency score (HRD score) of ovarian cancer patients to be tested. The positive threshold of HRD score is set to 45 to obtain the homologous recombination repair deficiency status of ovarian cancer patients to be tested. For ovarian cancer patients whose homologous repeat repair defect status is positive as obtained by the data acquisition module, the judgment module calculates F using the risk calculation formula shown in Formula I. HRD＞45 F HRD＞45 ≥0.5 indicates that the ovarian cancer patient being tested is a platinum-sensitive ovarian cancer patient; otherwise, the patient is a platinum-resistant ovarian cancer patient. Formula I: F HRD>45 =0.256309071612022-0.0194163477558527×ANXA4+0.669038155514554×CD27-0.232859065953763×GRB7+0.178899693365171×GSTZ1+0.623906367787577×SHMT2-0.368400667169836×TCF15-0.280938533614944×WARS-0.221539503346267×GALNT6+0.672754144414643×ZFR; In Formula I, ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR represent the expression levels of corresponding genes in ovarian cancer patients. After Z-score standardization, the expression levels of the same genes in each ovarian cancer patient in the sample of Example 1 are divided into upper quartiles and lower quartiles. Genes located in the upper quartile are assigned a value of 2, genes located in the lower quartile are assigned a value of 0, and genes located in the middle quartile are assigned a value of 1. For ovarian cancer patients whose homologous repeat repair defect status is negative as obtained by the data acquisition module, the judgment module calculates F using risk calculation formula II shown in formula II. HRD≤45 F HRD≤45≥0.5 indicates that the ovarian cancer patient being tested is a platinum-sensitive ovarian cancer patient; otherwise, the patient is a platinum-resistant ovarian cancer patient. Formula II: F HRD≤45 =2.63480181408828+1.75414711832022×AADAC+1.61744050879368×ADA-0.335529411791532×ANXA4-2.85124109729058×CD27+0.855056380659892×GJB1+2.55634098439207×GRB7+0.280308617354185×GSTZ1+0.239486972628679× SHMT2-1.96629329833821×TCF15+0.109161478982231×WARS-1.82019288788304×TNFSF11-0.108601110679264×UB D-0.0338767735048593×GALNT6-3.78049656515552×PHF20+1.36369711583015×ZFR-0.536490390878037×TMEM30B; In Formula II, AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B represent the expression levels of corresponding genes in ovarian cancer patients. After Z-score standardization, the expression levels of the same genes in each ovarian cancer patient in the sample of Example 1 are divided into upper quartiles and lower quartiles. Genes located in the upper quartile are assigned a value of 2, genes located in the lower quartile are assigned a value of 0, and genes located in the middle quartile are assigned a value of 1. The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

[0120] Comparative Example 1: A method for determining the state of homologous recombination repair defects in a test sample for non-diagnostic purposes. I. Experimental Methods Based on Example 1, the 18 genes that were associated with disease-free survival expectation in ovarian cancer patients (P-value < 0.05) are: AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, HLA.DOA, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, SASH1, PHF20, ZFR, and TMEM30B.

[0121] Using 196 ovarian cancer patients from the sample set of Example 1 as the ovarian cancer samples to be tested, the regularization parameters λ1 and λ2 were adjusted according to the method shown in Example 2 to obtain the genes related to the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs and the related weight coefficients of the genes. Using the 196 ovarian cancer patients from Example 1 as the sample set, the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs was determined and the ACC was calculated.

[0122] II. Experimental Results After adjusting the regularization parameters λ1 and λ2, the gene information related to the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs and the results of judging the accuracy of platinum-based chemotherapy drug responsiveness are shown in Table 6.

[0123] Table 6. Genetic Information and Accuracy Results

[0124] The results showed that ACC > 0.8 only when the gene combination shown in Combination 1 (i.e., the method shown in Example 2) was used to assess the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention. For those skilled in the art, other variations or modifications can be made based on the above description and ideas, and it is neither necessary nor possible to exhaustively describe all implementation methods here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. The use of a detection reagent in the preparation of a product for determining the response of platinum-based chemotherapy drugs in patients with homologous recombination repair deficiency-positive ovarian cancer, wherein the detection reagent is a reagent for detecting gene expression levels, and the genes are ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR.

2. The use of a detection reagent in the preparation of a product for assessing the response of platinum-based chemotherapy drugs in patients with homologous recombination repair deficiency-negative ovarian cancer, wherein the detection reagent is a reagent for detecting gene expression levels; wherein the genes are AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B.

3. The use of a detection reagent in the preparation of a product for assessing the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs, wherein the detection reagent is a reagent for detecting gene expression levels; wherein the genes are AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B.

4. The application according to any one of claims 1 to 3, characterized in that, The platinum-based drugs mentioned are cisplatin, carboplatin, oxaliplatin, nedaplatin, and / or ethylproplatin.

5. A product for assessing responsiveness to platinum-based chemotherapy drugs, characterized in that, The assay contains a reagent for detecting the expression levels of each gene in a gene combination, which includes ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR.

6. A model for assessing the response to platinum-based chemotherapy in ovarian cancer patients with homologous recombination repair deficiency, characterized in that, Includes a judgment module and a result output module; The judgment module determines the responsiveness to platinum-based chemotherapy drugs based on the expression levels of the following genes in ovarian cancer patient samples with homologous recombination repair deficiency. The genes include ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR genes; The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

7. A model for assessing the response to platinum-based chemotherapy in patients with homologous recombination repair-deficient ovarian cancer, characterized in that, Includes a judgment module and a result output module; The judgment module determines the responsiveness to platinum-based chemotherapy drugs based on the expression levels of the following genes in patients with homologous recombination repair-deficient negative ovarian cancer. The genes include AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR, and TMEM30B genes. The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

8. A model for determining the responsiveness to platinum-based chemotherapy drugs, characterized in that, It includes a data acquisition module, a judgment module, and a result output module; The data acquisition module is used to acquire homologous recombination repair defect scores of ovarian cancer patients and to determine the homologous recombination repair defect status of ovarian cancer patients based on the positive threshold of the homologous recombination repair defect score. The judgment module assesses the platinum-based chemotherapy response of ovarian cancer patients by combining the expression levels of ANXA4, CD27, GRB7, GSTZ1, SHMT2, TCF15, WARS, GALNT6, and ZFR genes in ovarian cancer patient samples that are positive for homologous recombination repair defects obtained by the data acquisition module. For ovarian cancer patient samples with a negative homologous recombination repair deficiency status obtained from the data acquisition module, the responsiveness of ovarian cancer patients to platinum-based chemotherapy drugs was assessed by combining the expression levels of the AADAC, ADA, ANXA4, CD27, GJB1, GRB7, GSTZ1, SHMT2, TCF15, WARS, TNFSF11, UBD, GALNT6, PHF20, ZFR and TMEM30B genes in the samples. The result output module is used to output the platinum-based chemotherapy drug responsiveness results obtained by the judgment module.

9. The model according to claim 8, characterized in that, The positive threshold for homologous recombination repair defect scoring in the data acquisition module is 38-45.

10. The model according to claim 9, characterized in that, The positive threshold for the homologous recombination repair defect score is 38, 39, 44 or 45.

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