A model for predicting the efficacy of chemotherapy combined with immunotherapy for cholangiocarcinoma and application thereof

Abstract

The present application relates to the technical field of medicine, in particular to a set of gene combination (PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A) in the preparation of reagent kit for predicting the efficacy of chemoimmunotherapy of cholangiocarcinoma. The present application proposes an expression and scoring model involving the gene combination by analyzing and screening the gene expression profile and treatment effect of cholangiocarcinoma patient tissue samples. According to the score, the effect of chemoimmunotherapy for patients can be predicted. Based on the above-mentioned model, the present application establishes a kit for detecting and scoring the expression level of the gene combination in tumor samples, which can effectively indicate the efficacy of chemoimmunotherapy for cholangiocarcinoma patients, help clinicians to accurately evaluate cholangiocarcinoma patients, and thus bring better survival benefits to patients. It has important value for the effective application of cholangiocarcinoma immunotherapy.

Description

Technical Field

[0001] This invention relates to the field of pharmaceutical technology, specifically to a set of methods and models for predicting the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma based on specific gene combinations (PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A), and their application in the preparation of kits for predicting the efficacy of chemotherapy combined with immunotherapy in cholangiocarcinoma. Background Technology

[0002] Bile tract cancer (BTC) is a general term for malignant tumors originating from the epithelial cells of the bile ducts. Depending on the location of origin, it is classified into intrahepatic cholangiocarcinoma, hilar cholangiocarcinoma, and distal cholangiocarcinoma, and is a type of primary liver cancer. Bile tract cancer is characterized by a long latency period, high malignancy, and poor prognosis. Radical surgery is the only curative treatment for BTC, but because the disease is often diagnosed at an advanced stage where surgery is not possible, only about 12% of BTC patients undergo radical resection (Brindley PJ, et al. Cholangiocarcinoma. Nat Rev Dis Primers, 2021, 9:65). Currently, BTC patients who are not eligible for surgery often receive systemic treatment, including chemotherapy combined with immune checkpoint inhibitors. Gemcitabine or gemcitabine combined with platinum is currently the main first-line standard treatment, which can significantly prolong progression-free survival and overall survival in some patients, but is still not satisfactory (Valle J, et al: Cisplatin plus gemcitabine versus gemcitabine for biliary tract cancer. N Engl J Med 2010, 362:1273-1281). With the rapid development of immunotherapy, especially the application of immune checkpoint inhibitors, new hope has been brought to the treatment of cholangiocarcinoma. Among them, programmed death factor-1 (PD-1) / programmed death factor ligand-1 (PD-L1) inhibitors have made breakthrough progress in the treatment of various tumors, changing the landscape of tumor treatment including melanoma and non-small cell lung cancer; however, research on their application in the treatment of cholangiocarcinoma started relatively late. The Keynote 028 cohort study found that pembrolizumab monotherapy achieved an objective response rate of 21.4% in patients with a specific type of cholangiocarcinoma; however, the Keynote 158 study found that only 5.8% of unselected cholangiocarcinoma patients benefited (Bang YJ, et al: Pembrolizumab (pembro) for advanced biliary adenocarcinoma: Results from the KEYNOTE-028 (KN028) and KEYNOTE-158 (KN158) basket studies. Journal of Clinical Oncology, 2019, 37(15_suppl):4079-4079). Subsequent studies have shown that PD-L1 inhibitors combined with standard gemcitabine chemotherapy as first-line treatment for cholangiocarcinoma improved the objective response rate by 8% and significantly prolonged overall survival by 1.3 months compared to traditional chemotherapy regimens, and it has now become another standard first-line treatment option for advanced cholangiocarcinoma.Therefore, immunotherapy combined with chemotherapy is currently considered an important approach to improve the prognosis of patients with cholangiocarcinoma. However, it should also be noted that approximately 30% of patients receiving chemotherapy combined with immunotherapy do not benefit, and some patients experience severe toxic side effects after receiving the combination therapy. Considering the rapid progression and extremely poor prognosis of cholangiocarcinoma, establishing a precise predictive indicator system to predict the efficacy of chemotherapy combined with immunotherapy in cholangiocarcinoma patients will help guide individualized medication and improve treatment outcomes.

[0003] Previous studies have shown that indicators such as PD-L1 expression, high microsatellite instability (MSI-H), and tumor mutational burden (TMB) in specific tumor types can indicate whether patients will benefit from immunotherapy (Razvan Cristescu1, Robin Mogg1, Mark Ayerset et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy. Science, 2018, 362:eaar3593). Compared to the application of single indicators in efficacy prediction, the role of multi-indicator combinations in guiding immunotherapy has received widespread attention. Interferon response gene combination scores and T-cell inflammation-related gene scores in tumor tissue have some guiding significance in predicting the efficacy of PD-1 / PD-L1 treatment for various tumors. However, our previous study found that these indicators are not effective in indicating the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma. Therefore, there is currently no good indicator model that can indicate the subgroup of bile duct cancer patients who can benefit from immunotherapy combined with chemotherapy. There is an urgent need to develop new indicator models and detection methods to guide personalized treatment for patients.

[0004] The efficacy of immunotherapy is considered closely related to the tumor immune microenvironment and the characteristics of the tumor itself; therefore, using tumor tissue samples as research subjects is more scientifically sound. Besides surgery, pathological biopsy, a key technique for assisting in the diagnosis of cholangiocarcinoma, can also provide tumor tissue from patients with advanced, inoperable disease. Compared to protein expression level detection, gene RNA expression level detection has advantages such as high sensitivity and specificity, accurate quantification, and ease of operation. It also has good sample compatibility and is suitable for testing small amounts of frozen and paraffin-embedded samples (such as pathological biopsy sections). It allows for the direct detection of tumor tissue-related indicators without increasing the risk of additional invasive testing for cholangiocarcinoma patients.

[0005] In summary, establishing a detection and scoring model based on the expression levels of specific gene combinations in tumor samples to predict the efficacy of chemotherapy combined with immunotherapy is of great significance for assisting in the precise clinical treatment and personalized medication of cholangiocarcinoma. Detection reagents or kits developed based on this model have potential applications. Summary of the Invention

[0006] The purpose of this invention is to provide a detection and scoring model that can be used to accurately predict the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma; another purpose of this invention is to provide reagents or kits based on this model that can detect the expression levels of relevant genes and be applied to the prediction of the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma.

[0007] In a first aspect, the present invention provides a method for constructing a model to predict the efficacy and prognosis of patients with cholangiocarcinoma receiving chemotherapy combined with immune checkpoint therapy, specifically comprising the following steps:

[0008] (1) Collect pre-treatment tumor samples and clinical treatment efficacy data of patients with cholangiocarcinoma who received chemotherapy combined with immunotherapy;

[0009] (2) Detect the transcriptome data of tumor samples and conduct correlation analysis with indicators such as objective response rate and progression-free survival of patients to obtain genes that are significantly related to the treatment effect;

[0010] (3) By scoring the selected genes in specific combinations, a model is constructed to predict the efficacy of chemotherapy combined with immunotherapy for cholangiocarcinoma.

[0011] Furthermore, the genes identified in step (2) that predict the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma are PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A.

[0012] Furthermore, the aforementioned cholangiocarcinoma includes intrahepatic cholangiocarcinoma, hilar cholangiocarcinoma, and extrahepatic cholangiocarcinoma.

[0013] Furthermore, the samples mentioned are tumor samples from patients with cholangiocarcinoma before they receive chemotherapy combined with immunotherapy, including tumor biopsy samples and surgical samples.

[0014] Furthermore, the construction method also includes a step of validating the model.

[0015] In a second aspect, the present invention provides a model for predicting the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma. The model is constructed by the method described above. The model uses the arithmetic mean of the standardized expression levels of six genes, PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A, as a score, and predicts the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma based on the score.

[0016] Furthermore, the calculation method of the model is as follows: detect the RNA expression levels of PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A genes in tumor tissue, perform standardized transformation, and use the arithmetic mean of the six genes as the score. Based on the score, predict the efficacy of chemotherapy combined with immune checkpoint therapy for patients with cholangiocarcinoma.

[0017] Furthermore, the model includes an optimal cutoff point. The model calculates the optimal cutoff point for gene combination scores using methods such as R.

[0018] Furthermore, the methods for detecting the RNA expression level of the gene include, but are not limited to, probes, gene chips, and PCR primers.

[0019] In a preferred embodiment of the present invention, a risk score is calculated based on the expression of relevant gene RNA in cholangiocarcinoma tissue. The score is compared with the model cutoff point to distinguish which patients have high objective response rates and survival. Scores higher than the cutoff point indicate better therapeutic efficacy; otherwise, the benefit may be small. Specifically, in this invention, RNA is extracted from paraffin-embedded samples after cholangiocarcinoma biopsy. RNA detection probes that specifically identify target genes are co-incubated with RNA from tumor tissue samples for hybridization. Subsequently, fluorescently labeled probes are used to identify the detection probes. Digital detection signals are acquired using the NanoString nCounter platform, and after data standardization, the score of the gene combination is calculated. According to statistical software, the cutoff point of this model is 8.21.

[0020] The present invention also provides the application of the model described above in the preparation of a kit for predicting the efficacy of chemotherapy combined with immune checkpoint therapy in patients with cholangiocarcinoma.

[0021] Furthermore, the model can be used to guide medication use in patients with cholangiocarcinoma.

[0022] A third aspect of the present invention provides the application of a gene combination in the preparation of a kit for predicting the efficacy of chemotherapy combined with immune checkpoint therapy in patients with cholangiocarcinoma; said gene combination consists of genes PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A.

[0023] Furthermore, the kit contains reagents specifically for detecting the RNA expression levels of the PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A genes in tumor tissue.

[0024] Furthermore, the reagents are selected from probes, gene chips, or PCR primers that have detection specificity for the PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A genes, respectively.

[0025] The present invention also provides the application of reagents for detecting the expression levels of PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A genes in tumor tissue in the preparation of a kit for predicting the efficacy of chemotherapy combined with immune checkpoint therapy in patients with cholangiocarcinoma.

[0026] In a fourth aspect, the present invention provides a kit for predicting the efficacy of chemotherapy combined with immune checkpoint therapy in patients with cholangiocarcinoma, the kit comprising reagents for detecting the expression levels of PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A genes in tumor tissue.

[0027] Furthermore, the kit comprehensively scores the expression levels of gene combinations and predicts the efficacy of chemotherapy combined with immune checkpoint therapy based on the score.

[0028] Furthermore, the kit uses the arithmetic mean of the expression levels of six genes—PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A—as a score to predict the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma.

[0029] Furthermore, the kit detects the RNA expression levels of PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A genes in tumor tissue and converts them into logarithmic values ​​of expression levels. The average of the logarithmic values ​​of the six gene expression levels is used as a score, and the efficacy of chemotherapy combined with immune checkpoint therapy is predicted based on the score.

[0030] In a preferred embodiment of the present invention, pathological slide samples are collected from patients with cholangiocarcinoma after biopsy. A nucleic acid probe specifically recognizing the target gene RNA is used. After denaturation-annealing-renaturation steps, a hybrid of the target nucleic acid and the nucleic acid probe is formed. The detection probe is fluorescently labeled, and quantitative RNA data of the target gene is obtained through a digital pathological image analysis platform. After standardization conversion, a gene combination score is calculated, and the cutoff point for this method is 8.00. When the score of the test sample is greater than the cutoff point, it indicates that the patient can benefit from a chemotherapy combined with immunotherapy regimen.

[0031] Furthermore, there are various methods for detecting gene RNA expression levels, including but not limited to probes, gene chips, and PCR primers. The region for detecting specific gene RNA can include the transcript of the gene, including the open reading frame (ORF) and the upstream and downstream sequences of the ORF.

[0032] Furthermore, the kit may also include subsequent detection signal amplification or easily detectable systems, which may include: secondary systems carrying amplified primary detection signals (including fluorescent, bioluminescent, reagents containing specific tag sequences, etc.), blocking solutions, retrieval solutions, buffer solutions, etc. Those skilled in the art can select appropriate systems based on the type and characteristics of the detectable signal molecules used.

[0033] Based on the novel findings of this invention, various nucleic acid detection methods can be used to detect the RNA expression levels of the aforementioned six genes in a sample, and a comprehensive score can be given for the expression levels of these six genes. These methods are all included in this invention.

[0034] Furthermore, the aforementioned cholangiocarcinoma includes intrahepatic cholangiocarcinoma, hilar cholangiocarcinoma, and extrahepatic cholangiocarcinoma.

[0035] Furthermore, the bile duct cancer patients mentioned are those who are preparing to receive chemotherapy and immune checkpoint therapy. The chemotherapy regimen is gemcitabine or gemcitabine combined with platinum (including cisplatin or oxaliplatin, etc.), and the immune checkpoint therapy regimen is an inhibitor targeting PD-1 / PD-L1 (including antibodies, peptides, etc.).

[0036] Furthermore, the test targets of the kit are: ex vivo bile duct cancer tissue obtained by surgical resection, biopsy puncture, bile duct brushing, etc., including fresh tissue, frozen tissue and paraffin-embedded tissue.

[0037] Furthermore, the method for using the aforementioned kit to predict the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma is as follows:

[0038] (1) Detect the expression levels of six genes, PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A, in the isolated bile duct cancer tissue of the subjects;

[0039] (2) Calculate the comprehensive score of the expression levels of the above 6 genes;

[0040] If the score is higher than the cutoff point of the kit, the subject is suitable for chemotherapy combined with immunotherapy.

[0041] In a preferred embodiment of the present invention, the test results are quantitatively standardized, and the mean is taken as a score. A score higher than 8.0 is considered high expression, indicating that chemotherapy combined with immunotherapy is effective and the treatment regimen is acceptable. A score less than or equal to 8.0 is considered low, indicating that the patient will not benefit from chemotherapy combined with immunotherapy, and further active examination and treatment are recommended, along with trying other treatment options for cholangiocarcinoma.

[0042] The advantages of this invention are:

[0043] 1. This invention provides a model and method for predicting the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma. Through analysis and screening of gene expression profiles and treatment effects in tissue samples from cholangiocarcinoma patients, an expression and scoring model involving a set of gene combinations (PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A) is proposed. Based on the score, the efficacy of chemotherapy combined with immunotherapy can be predicted. Using the predictive model of this invention, information from tumor tissue samples before the patient receives chemotherapy combined with immunotherapy can be used to comprehensively score the expression levels of six specific genes, thus predicting the patient's therapeutic benefit from this treatment.

[0044] 2. Based on the above model, this invention establishes a kit for detecting and scoring the expression levels of the gene combinations mentioned above in tumor samples. This kit can effectively indicate the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma. It can assist clinicians in conducting accurate individualized assessments of cholangiocarcinoma patients when enrolling in chemotherapy combined with immunotherapy. It is simple and intuitive, easy to promote and apply, thereby bringing better survival benefits to patients. It has important value for the effective application of immunotherapy for cholangiocarcinoma. Attached Figure Description

[0045] Figure 1 The following are the efficacy results of chemotherapy combined with immunotherapy as a first-line treatment for 12 patients with cholangiocarcinoma in a clinical study: A is a waterfall plot of the best efficacy in the response group and the non-response group; B is the survival curve of progression-free survival in the response group and the non-response group.

[0046] Figure 2 The transcriptome differences between the response and non-response groups of the above-mentioned cholangiocarcinoma cohort tumor samples are as follows: A represents differentially expressed genes in the transcriptomes of the response and non-response groups; B represents key signaling pathways and core gene combinations enriched in the response group, including six genes: PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A.

[0047] Figure 3 This describes the expression levels of the above six genes between the response and non-response groups in the cholangiocarcinoma cohort.

[0048] Figure 4The following is an analysis of the scoring model based on the expression levels of six genes and its effect on predicting the efficacy of chemotherapy combined with immunotherapy in cholangiocarcinoma: A shows the distribution of the scoring model scores based on the six gene combinations in the response and non-response groups of a cohort of 12 cholangiocarcinoma patients; B shows the predictive ability of the six gene-based scoring model for progression-free survival in a cohort of 26 independent cholangiocarcinoma patients; C shows the distribution of the scoring model scores in the response and non-response groups of the 26 independent cholangiocarcinoma patients; D shows the ROC curves used to evaluate the specificity and sensitivity of the model.

[0049] Figure 5 The ability of predictive indicators of immunotherapy efficacy found in other tumors to predict the efficacy of cholangiocarcinoma: A is the predictive ability of tumor mutational burden; B is the predictive ability of cytotoxic T cell score in tumor tissue; C is the predictive ability of cell killing score.

[0050] Figure 6 This study describes the use of a reagent based on a 6-gene expression scoring model to detect the expression of relevant genes in cholangiocarcinoma tissue samples. Detailed Implementation

[0051] The specific implementation methods provided by the present invention will be described in detail below with reference to the embodiments.

[0052] Example 1: Construction of a predictive model for the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma

[0053] Twelve patients were selected from the clinical trial cohort (ChiCTR2000036652) that had been included in the study investigating the efficacy of gemcitabine-based chemotherapy combined with PD-1 inhibitors as first-line treatment for advanced cholangiocarcinoma. These patients were pathologically diagnosed with cholangiocarcinoma and excluded those with high microsatellite instability who were previously treatment-naïve. Patient basic information is shown in Table 1.

[0054] Table 1. Clinical characteristics of patients

[0055]

[0056] (1) Obtain the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma and tumor samples before treatment.

[0057] The patient was treated with sintilimab combined with chemotherapy (sintilimab: 200mg IV drip D1 + gemcitabine: 1000mg / m²). 2 Intravenous infusion of D1,8 + cisplatin: 25 mg / m 2Treatment was administered intravenously on days 1 and 8 every three weeks. Treatment was discontinued in the following three cases: (a) confirmed disease progression; (b) intolerable adverse reactions; (c) at the patient's request. After completing 8 cycles of combination therapy, patients received sintilimab (200 mg intravenously every three weeks) maintenance therapy until withdrawal from the trial as required by the study. Liver biopsies were performed on each patient prior to treatment to obtain tumor samples for pathological diagnosis. Samples were formalin-fixed and paraffin-embedded. All patient sample use was reviewed and approved by the hospital ethics committee, and all patients signed informed consent forms.

[0058] After receiving chemotherapy combined with immunotherapy, patients' treatment outcomes were assessed according to the RECIST 1.1 criteria for evaluating the efficacy of treatment in solid tumors, including efficacy evaluation of the target lesion, overall survival, progression-free survival, objective response rate, and duration of disease. Patients were divided into a response group and a non-response group based on their treatment efficacy: 8 patients experienced tumor shrinkage from baseline after treatment (response group); 4 patients experienced tumor enlargement from baseline (non-response group). In the response group, 5 patients achieved a tumor shrinkage of more than 30%, reaching a partial response (PR). The overall objective response rate was 41.7% (5 / 12). The progression-free survival was 13.2 months in the response group and 3.45 months in the non-response group, with a statistically significant difference (p = 0.0448, HR: 0.25, 95% CI: 0.04-1.38). Figure 1 ).

[0059] (2) Screening for gene combinations that are significantly correlated with treatment efficacy

[0060] Transcriptome data analysis of tumor samples: Tissue from paraffin sections containing at least 30% tumor tissue was transferred to microcentrifuge tubes. Total cellular RNA was extracted from the sections using a paraffin-embedded RNA extraction kit, and the total RNA content was quantified using a spectrophotometer. Sequencing was performed using the FDA-approved NanoString (NanoString Technologies, WA) platform. At least 300 ng of RNA was added to the probe pair reagent and hybridized overnight at 65°C. After the liquid-phase hybridization reaction, the reaction system was transferred to the sample channel of the sample loading stage. After a series of elution processes, non-target nucleic acids and free probes were removed, purifying the target mRNA and probe pair hybridization complex. Through the interaction of biotin and avidin, the hybridization complex was immobilized and spread on the sample loading stage. The sample loading stage was transferred to a scanner for signal acquisition and counting. Gene expression data were generated using an nCounter™ digital analyzer, and expression levels were normalized using the platform software. The reagents we used can detect the expression levels of 289 genes in the samples, covering different pathways such as tumor, tumor microenvironment composition, and immune response.

[0061] Screening for differentially expressed genes related to patient treatment efficacy: Statistical methods such as DESeq2, Limma, and NanoString differential analysis were used to screen for genes with significant expression differences between tumor samples from the responding and non-responding groups. Cox regression analysis was then performed on these genes in relation to patient survival time to identify those with prognostic differential expression. Subsequently, GSEA pathway enrichment analysis was performed on the sample transcriptomes, revealing the top three significantly different signaling pathways: the biostimulation response pathway (p = 0.002), the innate immune response regulation pathway (p = 0.009), and the T-cell migration-related pathway (p = 0.022). We then analyzed and compared core genes with overlap in these three pathways as potential candidate gene combinations, ultimately selecting six genes: PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A.

[0062] (3) Constructing a predictive model for the efficacy of chemotherapy combined with immunotherapy for cholangiocarcinoma

[0063] The mRNA expression information of the above 6 genes (PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A) in the tumor sample was selected, and the optimal cutoff point was calculated by taking the arithmetic mean of the logarithmic values ​​of the expression levels of the 6 genes.

[0064] Example 2: Validation and Comparison of Predictive Models

[0065] We examined the model's predictive ability in the aforementioned cohort of 12 patients and found that the model's score was significantly higher in the response group than in the non-response group. Figure 4 A, p = 0.008).

[0066] To validate the predictive power of the model, we retrospectively collected data from 26 patients with cholangiocarcinoma at our center. All patients received first-line treatment with PD-1 monoclonal antibody combined with gemcitabine-based chemotherapy. We used the NanoString platform to detect the expression levels of six genes in pre-treatment tumor biopsy samples and calculated a score for each patient based on these six genes. The optimal cutoff point was 8.21. The results showed that our scoring model could still significantly differentiate patient efficacy in the 26 independent cohorts: compared to patients with low scores, patients with high scores had longer progression-free survival; the progression-free survival was 9.9 months in the high-scoring group and only 4.1 months in the low-scoring group, a significant difference. Figure 4 B, p = 0.0379, HR: 0.34, 95% CI: 0.1231–0.9415). Based on treatment responsiveness, we found that the mean scores in the responding and non-responding groups were 8.982 and 7.818, respectively, with a statistically significant difference. Figure 4C, p = 0.0044). The ROC curve also demonstrated the model's good predictive performance, with an area under the curve of 0.831 (95% CI: 0.666–0.997), a sensitivity of 90%, and a specificity of 81.2%. Figure 4 D).

[0067] We then compared the model's predictive performance on treatment efficacy with that of other reported indicators. Tumor mutational burden (TMB) has been reported to be associated with prognosis of immunotherapy in certain tumors, such as non-small cell lung cancer. We found that TP53 mutations (41.7%) and KRAS mutations (33.3%) were still the most common in 12 patients with cholangiocarcinoma, but there was no significant difference in their distribution between the treatment-responsive and non-responsive groups. The median TMB was 3.195 Muts / Mb (0.71–25.74 Muts / Mb). Dividing patients into two groups using the median, the results showed no significant difference in efficacy between the two groups (p = 1.000). Tumor-killing T-cell levels (CTL levels) and cytotoxic T-cell scores (CYT score) also predict the efficacy of immunotherapy in tumors such as melanoma; however, in our cholangiocarcinoma cohort, these indicators could not distinguish whether patients benefited (CTL level, p = 0.93; CYT score, p = 1.00).

[0068] Compared to the models reported above, our model is significantly superior in terms of predictive performance, ease of operation, and other aspects, and has better clinical application value.

[0069] Example 3: Establishing reagents or kits to help predict the efficacy of chemotherapy combined with immunotherapy in patients with cholangiocarcinoma.

[0070] Based on the above-mentioned detection and scoring model based on six gene combinations in tissues, this invention establishes a reagent or kit for detecting the expression levels of six genes in cholangiocarcinoma samples.

[0071] Various methods exist for detecting gene RNA expression levels, including but not limited to probes, gene chips, and PCR primers. The region for detecting specific gene RNA may include the gene's transcript, including the open reading frame (ORF) and the upstream and downstream sequences of the ORF. Furthermore, the reagent or kit may include subsequent signal amplification or easily detectable systems, such as secondary systems carrying amplified primary detection signals (including fluorescence, bioluminescence, reagents containing specific tag sequences, etc.), blocking solutions, retrieval solutions, buffers, etc. Those skilled in the art can select appropriate systems based on the type and characteristics of the detectable signal molecules used.

[0072] Based on the novel findings of this invention, various nucleic acid detection methods can be used to detect the RNA expression levels of the aforementioned six genes in a sample, and a comprehensive score can be calculated for the expression levels of these six genes. These methods are all included in this invention. In one embodiment, the method includes the steps of: detecting the expression levels of the six genes in an isolated cholangiocarcinoma sample using this reagent or kit and calculating a comprehensive score; based on the score results, predicting whether cholangiocarcinoma patients can benefit from chemotherapy combined with immunotherapy, and guiding individualized medication regimens for cholangiocarcinoma patients.

[0073] Example 4:

[0074] Paraffin-embedded tissue samples were collected from four patients with clinically advanced cholangiocarcinoma via biopsy, and tissue sections were prepared. Fluorescent RNA probes for detecting six genes were prepared; the probe sequences are as follows:

[0075] PSMB10:

[0076] CCATCGCGGGCCTGGTGTTCCAAGACGGGGTCATTCTGGGCGCCGATACGCGAGCCACTAACGATTCGGTCGTGGCGGACAAGAGCTGCGAGAAGATCCA(SEQ ID NO.1)

[0077] PSMB9:

[0078] TCAGGTATATGGAACCCTGGGAGGAATGCTGACTCGACAGCCTTTTGCCATTGGTGGCTCCGGCAGCACCTTTATCTATGGTTATGTGGATGCAGCATAT(SEQ ID NO.2)

[0079] LAG3:

[0080] TTTTGGTGACTGGAGCCTTTGGCTTTCACCTTTGGAGAAGACAGTGGCGACCAAGACGATTTTCTGCCTTAGAGCAAGGGATTCACCCTCCGCAGGCTCA(SEQ ID NO.3)

[0081] CCL5:

[0082] CCAAGTGTGTGCCAACCCAGAGAAGAAATGGGTTCGGGAGTACATCAACTCTTTGGAGATGAGCTAGGATGGAGAGTCCTTGAACCTGAACTTACACAAA(SEQ ID NO.4)

[0083] IFI35:

[0084] TGCCCTCTGCTTGCGGGCTCTGCTCTGATCACCTTTGATGACCCCAAAGTGGCTGAGCAGGTGCTGCAACAAAAGGAGCACACGATCAACATGGAGGAGT(SEQ ID NO.5)

[0085] SH2D1A:

[0086] GCTGTATCACGGTTACATTTATACATACCGAGTGTCCCAGACAGAAACAGGTTCTTGGAGTGCTGAGACAGCACCTGGGGTACATAAAAGATATTTCCGG(SEQ ID NO.6)

[0087] Nucleic acid hybridization was performed, and the results were quantified and averaged to obtain a score. A score higher than 8.0 was considered high expression, and a score less than or equal to 8.0 was considered low expression.

[0088] Based on the scoring results, the study predicted whether patients would benefit from chemotherapy combined with immunotherapy. The results are as follows:

[0089] Two patients scored above 8.0, indicating that chemotherapy combined with immunotherapy was effective and that this treatment regimen was acceptable.

[0090] Two patients scored below 8.0, indicating they would not benefit from chemotherapy combined with immunotherapy. It was recommended that they undergo further active examination and treatment, and try other treatment options for bile duct cancer.

[0091] The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. The application of a gene combination in the preparation of a kit for predicting the efficacy of chemotherapy combined with immune checkpoint therapy in patients with cholangiocarcinoma, characterized in that, The gene combination consists of genes PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A. The kit detects the RNA expression levels of PSMB10, PSMB9, LAG3, CCL5, IFI35, and SH2D1A genes in tumor tissue. After standardization, the arithmetic mean is used as a score, and the score is used to predict the efficacy of chemotherapy combined with immune checkpoint therapy in cholangiocarcinoma patients. The cholangiocarcinoma patients are those who are preparing to receive chemotherapy combined with immune checkpoint therapy, wherein the chemotherapy regimen is gemcitabine-based, and the immune checkpoint therapy regimen is an inhibitor targeting PD-1 / PD-L1.

2. The application according to claim 1, characterized in that, The kit contains reagents that specifically detect the expression levels of PSMB10, PSMB9, LAG3, CCL5, IFI35 and SH2D1A genes in tumor tissue.

3. The application according to claim 1, characterized in that, The cholangiocarcinoma mentioned includes intrahepatic cholangiocarcinoma, hilar cholangiocarcinoma, and extrahepatic cholangiocarcinoma.

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