WO2023185985A1 - Biomarker, system, method, and kit for assessing efficacy of tumor ibc therapy - Google Patents

Abstract

Provided are a biomarker, a system, a method, and a kit for assessing the efficacy of tumor IBC therapy. The biomarker comprises circ-TMTC3 and/or circ-FAM117B. The biomarker, on the basis of circRNA development, has more stable tissue-specific expression and evolutionary conservation than linear mRNA, thus being stronger in specificity and higher in stability for assessing the efficacy of the tumor IBC therapy.

Description

Biomarkers, systems, methods and kits for evaluating the efficacy of tumor IBC therapy

Related application cross-references

This patent application claims priority to the Chinese patent application submitted on April 2, 2022, with the application number 2022103443947 and the invention title "Biomarkers, systems, methods and kits for evaluating the efficacy of tumor IBC therapy" , the entire text of the above application is incorporated herein by reference.

Technical field

The present invention relates to the field of biomedicine, and in particular to biomarkers, systems, methods and kits for evaluating the efficacy of tumor IBC therapy.

Background technique

Melanoma is the most common histological subtype and is responsible for approximately 75% of skin cancer-related deaths worldwide, with 15-25 deaths per 100,000 people. The median survival time for metastatic melanoma is 6-12 months. Immune checkpoint blockade (ICB) targeting programmed cell death receptor 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA-4) is a revolutionary breakthrough in oncology. Unfortunately, only a small proportion of patients derive lasting clinical benefit from immunotherapy. There is an urgent need to identify biomarkers that predict ICB to guide precision tumor immunotherapy.

CircRNA is a type of single-stranded non-coding RNA characterized by a covalently closed circular structure, which is produced by back-splicing precursor mRNA through the downstream 5' splice site to the upstream 3' splice site. circRNA participates in a variety of biological and cellular functions by binding to miRNA or proteins, such as tumorigenesis and epithelial-mesenchymal transition (EMT). Notably, recent studies have shown that circRNAs are involved in regulating various anti-tumor immune responses and immune cells. For example, hsa_circ_0020397 can bind and inhibit the expression of miR-138, thereby promoting the expression of the target protein PD-L1 of miR-138, leading to immune evasion of colorectal cancer. circRNA can also interact with proteins. For example, circFoxo3 can induce p53 degradation by binding to MDM2, thereby re-regulating immune responses. Tumor cells may produce aberrant circRNAs and transport them to immune cells via exosomes and extracellular vesicles, suggesting the potential role of circRNAs in intercellular communication. Furthermore, there is evidence of correlation between circRNA and immune cell infiltration in some cancers. These studies indicate that circRNA plays a role in the tumor microenvironment plays an important role in predicting the response to immunotherapy. Although circRNA has an increasing role in the immune system, there is still no expression map of circRNA in cancer immunotherapy. So far, there are multiple biomarkers related to ICB response in melanoma, such as PD-L1 and CD8, tumor mutation burden (TMB) and neoantigens, interferon (IFN)-γ signaling pathway, gene expression markers substances, and tumor immune microenvironment, etc.

The inventor found that there are at least the following problems in the prior art: the expression of PD-L1 protein on tumor cells or immune cells is currently a commonly used biomarker for predicting immune checkpoint blockade therapy, but it does not have the ability to predict ICB response. universality. Furthermore, PD-L1 expression is dynamic and can change with exposure to previous treatments and tumor-infiltrating immune cells, with spatial and temporal heterogeneity. These may limit its ability to distinguish whether patients respond to immunotherapy, resulting in poor specificity and low stability in the evaluation of tumor IBC treatment effects.

Contents of the invention

The purpose of the present invention is to provide a more specific and stable biomarker based on circRNA for evaluating the therapeutic effect of tumor IBC.

Another object of the present invention is to provide a kit for evaluating the therapeutic effect of tumor IBC.

Another object of the present invention is to provide a system and method for evaluating the therapeutic effect of tumor IBC.

In order to solve the above technical problems, the first aspect of the present invention provides a set of biomarkers for evaluating the efficacy of tumor IBC therapy, and the biomarkers include circ-TMTC3 and/or circ-FAM117B.

In some preferred scenarios, the assessment is a pre-assessment.

In some preferred solutions, the biomarkers include circ-TMTC3 and circ-FAM117B; wherein at least part of the nucleic acid sequence of circ-TMTC3 is identical to SEQ ID NO: 1; the nucleic acid sequence of circ-FAM117B At least part of it is the same as SEQ ID NO:2.

In some preferred embodiments, the tumor is melanoma.

A second aspect of the present invention provides a kit for evaluating the efficacy of tumor IBC therapy, the kit comprising:

A primer pair set and a probe, the primer pair set includes a first primer pair and a second primer pair;

A first primer pair, the first primer pair includes a forward primer with a sequence shown in SEQ ID NO:3, and a reverse primer with a sequence shown in SEQ ID NO:4;

A second primer pair, the second primer pair includes a forward primer of the sequence shown in SEQ ID NO:5, and a reverse primer of the sequence shown in SEQ ID NO:6.

In some preferred solutions, the probe includes:

The first probe specifically targets circ-TMTC3, and the sequence of the first probe is as shown in SEQ ID NO: 7; and

The second probe specifically targets circ-FAM117B, and the sequence of the second probe is shown in SEQ ID NO: 8.

The third aspect of the present invention provides the use of circ-TMTC3 and circ-FAM117B detection reagents for preparing a kit for evaluating the efficacy of tumor IBC therapy.

In another preferred embodiment, the detection reagent is a nucleic acid detection reagent (such as a PCR detection reagent that specifically detects circ-TMTC3, a PCR detection reagent that specifically detects circ-FAM117B), or an immunological detection reagent (such as a specific detection reagent that detects circ-FAM117B). Antibodies to circ-TMTC3, antibodies specifically detecting circ-FAM117B).

In another preferred example, the PCR detection reagent for specifically detecting circ-TMTC3 includes:

It includes a forward primer with a sequence shown in SEQ ID NO:3, and a reverse primer with a sequence shown in SEQ ID NO:4; preferably, it also includes a probe with a sequence shown in SEQ ID NO:7.

In another preferred example, the PCR detection reagent for specifically detecting circ-FAM117B includes:

It includes a forward primer with a sequence shown in SEQ ID NO:5, and a reverse primer with a sequence shown in SEQ ID NO:6; preferably, it also includes a probe with a sequence shown in SEQ ID NO:8.

A fourth aspect of the present invention provides a system for evaluating the efficacy of tumor IBC therapy, the system comprising:

a biomarker detection unit configured to determine the expression level of the biomarker in the patient's tumor tissue; and

a data processing unit configured to compare the patient's tumor tissue Expression levels and thresholds of biomarkers to evaluate the efficacy of tumor IBC therapy in the patient;

Wherein, the biomarkers include: circ-TMTC3 and/or circ-FAM117B.

In some preferred embodiments, the biomarker includes circ-TMTC3 or circ-FAM117B.

In some preferred solutions, the system includes:

A biomarker detection unit, the biomarker detection unit is configured to measure the expression level E1 of circ-TMTC3 in the patient's tumor tissue;

A data processing unit, the data processing unit is configured to compare E1 and the threshold E1' to determine the efficacy of the tumor IBC therapy on the patient;

When E1 is less than E1', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the system includes:

A biomarker detection unit, the biomarker detection unit is configured to measure the expression level E2 of circ-FAM117B in the patient's tumor tissue;

A data processing unit, the data processing unit is configured to compare E2 and the threshold E2' to determine the efficacy of the tumor IBC therapy on the patient;

When E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the biomarkers include: circ-TMTC3 and circ-FAM117B.

In some preferred solutions, the system includes:

a biomarker detection unit configured to determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue; and

A data processing unit, the data processing unit is configured to compare E1 with the threshold value E1', and compare E2 with the threshold value E2', to determine the efficacy of the tumor IBC therapy on the patient;

When E1 is less than E1', and E2 is less than E2', it is determined that the tumor IBC therapy is effective for the patient, otherwise it is determined that the tumor IBC therapy is ineffective for the patient.

In some preferred solutions, the system includes:

A biomarker detection unit, the biomarker detection unit is configured to measure the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

A data processing unit configured to:

Calculate the ICBcirSig score R according to E1 and E2,

Calculate the ICBcirSig score value R’ according to the thresholds E1’ and E2’;

Evaluate the efficacy of tumor IBC therapy in the patient by comparing the magnitudes of R and R';

Among them, the ICBcirSig score is obtained by weighting multivariate Cox regression coefficients of circ-TMTC3 and circ-FAM117B.

In some preferred solutions, the value of the ICBcirSig score is calculated by Formula I;

ICBcirSig=1.001×expression level of circ-TMTC3+1.048×expression level of circ-FAM117B, (Formula I).

In some preferred solutions, the detection method used to measure the expression level in the biomarker detection unit is selected from any one of RNA sequencing, hybridization and nucleic acid amplification.

In some preferred solutions, the assay method for measuring the expression level in the biomarker detection unit is selected from: HPLC/UV-Vis spectroscopy, enzymatic analysis, mass spectrometry, NMR, immunoassay, ELISA or any of them combination.

In some preferred solutions, the biomarker detection unit includes PCR amplification equipment.

In some preferred solutions, the biomarker detection unit uses the kit described in the second aspect of the present invention for detection.

In some preferred solutions, the method for measuring the expression level in the biomarker detection unit is a qRT-PCR method, and the threshold E1' is 0.4 to 0.6; the threshold E1' is 0.4 to 0.6.

The fifth aspect of the present invention provides a method for evaluating the efficacy of tumor IBC therapy, the method includes the steps:

Determine the expression levels of biomarkers in patient tumor tissues;

Evaluate the efficacy of tumor IBC therapy on the patient by comparing the expression level of the biomarker in the patient's tumor tissue with the threshold E1';

Wherein, the biomarkers include: circ-TMTC3 and/or circ-FAM117B.

In some preferred embodiments, the biomarker includes circ-TMTC3 or circ-FAM117B.

In some preferred solutions, the method includes the steps:

Determine the expression level E1 of circ-TMTC3 in patient tumor tissues;

Determine the efficacy of the tumor IBC therapy on the patient by comparing E1 with the threshold E1';

When E1 is less than E1', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the method includes the steps:

Determine the expression level E2 of circ-FAM117B in patient tumor tissues;

Determine the efficacy of the tumor IBC therapy on the patient by comparing E2 with the threshold E2';

When E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the biomarkers include: circ-TMTC3 and circ-FAM117B.

In some preferred solutions, the method includes the steps:

Determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

By comparing E1 with the threshold E1’, and

Determine the efficacy of the tumor IBC therapy on the patient by comparing E2 with the threshold E2';

When E1 is less than E1', and E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the method includes the steps:

Determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

By comparing the value of E1 with the threshold E1’, and

Determine the efficacy of the tumor IBC therapy on the patient by comparing the values of E2 and the threshold E2';

When E1 is less than E1', and E2 is less than E2', it is determined that the tumor IBC therapy is effective for the patient. The patient is sensitive (effective), otherwise it is determined that the tumor IBC therapy is tolerable (ineffective) to the patient.

In some preferred solutions, the method includes the steps:

Determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

Calculate the ICBcirSig score R according to E1 and E2;

Calculate the ICBcirSig score value R’ according to the thresholds E1’ and E2’;

Evaluate the efficacy of tumor IBC therapy in the patient by comparing the magnitudes of R and R';

Among them, the ICBcirSig score is obtained by weighting multivariate Cox regression coefficients of circ-TMTC3 and circ-FAM117B.

In some preferred solutions, the value of the ICBcirSig score is calculated by Formula I;

ICBcirSig=1.001×expression level of circ-TMTC3+1.048×expression level of circ-FAM117B, (Formula I).

In some preferred embodiments, the method for measuring the expression level is selected from any one of RNA sequencing, hybridization and nucleic acid amplification.

In some preferred embodiments, the method for measuring the expression level is selected from any one of RNA sequencing, hybridization and nucleic acid amplification.

In some preferred embodiments, the expression level is determined by HPLC/UV-Vis spectroscopy, enzymatic analysis, mass spectrometry, NMR, immunoassay, ELISA, or any combination thereof.

In some preferred solutions, the method for measuring the expression level in the biomarker detection unit is a qRT-PCR method, and the threshold E1' is 0.4 to 0.6; the threshold E1' is 0.4 to 0.6.

Compared with the prior art, the present invention has at least the following advantages:

(1) The biomarkers provided by the present invention are developed based on circRNA. They have tissue-specific expression, evolutionary conservation, and are more stable than linear mRNA. Therefore, they are more specific and stable for evaluating the therapeutic effect of tumor IBC;

(2) The method for evaluating the therapeutic effect of tumor IBC provided in some embodiments of the present invention uses two circRNAs, circ-TMTC3 and circ-FAM117B, to construct a model, which has better stability and accuracy in predicting the therapeutic effect of tumor IBC in patients. higher.

It should be understood that within the scope of the present invention, the above-mentioned technical features of the present invention and the technical features specifically described below (such as embodiments) can be combined with each other to form new or preferred technical solutions. Due to space limitations, they will not be described one by one here.

Description of drawings

One or more embodiments are exemplified by the pictures in the corresponding drawings, and these exemplary illustrations do not constitute limitations to the embodiments.

Figure 1 shows the number of circRNAs identified by each tool in independent melanoma patient cohort 1 and cohort 2 according to the embodiment of the present invention;

Figure 2 shows the number of circRNAs in each sample of cohort 1 and cohort 2 according to the embodiment of the present invention;

Figure 3 is a volcano plot of up-regulation (red) and down-regulation (blue) of circRNA in non-benefit and benefit melanoma samples according to an embodiment of the present invention (PRE before treatment; A), (EDT during treatment; B) (P-value <0.05, |log2(fold change)|≥0.5; see methods);

Figure 4 is a Venn diagram of the overlap of up-regulated circRNAs found in PRE (A) and EDT (B) samples according to the embodiment of the present invention (81 common circRNAs, 80 common circRNAs in MiOncoCirc, 74 host genes);

Figure 5 is an ICB-related circular circRNA-miRNA-mRNA axis (above, see Methods) and a network of all circRNA-miRNA-mRNA interaction pairs (below) according to an embodiment of the present invention. “+” indicates that the expression of circRNAs is positively correlated with mRNA;

Figure 6 is the Encyclopedia of Genes and Genomes (KEGG) and GO biological process enrichment (p value <0.05) of mRNA in the ICB-related circRNA-miRNA-mRNA axis in an embodiment of the present invention;

Figure 7 is a partial likelihood deviation diagram of LASSO Cox regression used to select candidate circRNAs in an embodiment of the present invention;

Figure 8 is a LASSO coefficient distribution diagram of candidate circRNA according to the embodiment of the present invention (the vertical dotted line is the optimal value under the minimum criterion);

Figure 9 is a forest plot of hazard ratios (HRs) of the multivariable Cox model of 4 circRNAs under progression-free survival (PFS) in an embodiment of the present invention;

Figure 10 is a Kaplan-Meier survival curve showing ICBcircSig according to the embodiment of the present invention. Schematic diagram of the correlation between circ-TMTC3 and PFS;

Figure 11 is a schematic diagram showing the correlation between circ-FAM117B and PFS in ICBcircSig according to the Kaplan-Meier survival curve in the embodiment of the present invention;

Figure 12 is an expression diagram of circ-TMTC3 in the PD group, CR/PR and SD groups according to the embodiment of the present invention;

Figure 13 is an expression diagram of circ-FAM117B in the PD group, CR/PR and SD groups according to the embodiment of the present invention;

Figure 14 is a Kaplan-Meier survival curve chart of PFS of high- and low-risk patients stratified using the optimal cutoff value ICBcircSig score in an embodiment of the present invention;

Figure 15 is a ROC curve chart of ICBcircSig score at 12 months and 24 months PFS according to the embodiment of the present invention;

Figure 16 is a box plot of ICBcircSig scores in the CR/PR group, SD group and PD group according to the embodiment of the present invention;

Figure 17 is an HR forest plot of the multivariable Cox model of ICBcircSig score and clinicopathological variables in an embodiment of the present invention (CR/PR, complete remission/partial remission; SD, stable disease; PD, progressive disease; ROC (affected by Receiver operating characteristic curve); HR, hazard ratio);

Figure 18 is the Kaplan-Meier survival curve of PFS of high- and low-risk patients stratified by circ-TMTC3 using the optimal threshold method in the embodiment of the present invention;

Figure 19 is a Kaplan-Meier survival curve of PFS of high- and low-risk patients stratified by circ-FAM117B using the optimal threshold method in an embodiment of the present invention;

Figure 20 is the expression of circ-TMTC3 in ICBcircSig in CR, PR, SD and PD groups according to the embodiment of the present invention;

Figure 21 is the expression of circ-FAM117B in ICBcircSig in CR, PR, SD and PD groups according to the embodiment of the present invention;

Figure 22 is a Kaplan-Meier survival curve of PFS for patients with high ICBcircSig score and low ICBcircSig score according to the embodiment of the present invention;

Figure 23 is a time-dependent ROC curve of ICBcircSig score at PFS 12 months and 24 months according to the embodiment of the present invention. ;

Figure 24 is the ICBcircSig score between CR, PR, SD and PD groups according to the embodiment of the present invention. Boxplots of distributions;

Figure 25 is a multivariable Cox model HR forest plot according to the ICBcircSig score and clinicopathological variables in the embodiment of the present invention (PFS: progression-free survival; CR, complete remission; PR, local response; SD, stable disease; PD, progressive Disease; ROC (receiver operating characteristic curve); HR, hazard ratio; AUC, area under the curve);

Figure 26 is a schematic diagram showing the expression of circ-TMTC3 verified by qRT-PCR and Sanger sequencing in the embodiment of the present invention;

Figure 27 is a schematic diagram of the generation of circ-TMTC3 in patient samples before anti-PD-1 treatment using qRT-PCR in an embodiment of the present invention;

Figure 28 is a schematic diagram showing the expression of circ-FAM117B verified by qRT-PCR and Sanger sequencing in the embodiment of the present invention;

Figure 29 is a schematic diagram of the generation of circ-FAM117B in patient samples before anti-PD-1 treatment using qRT-PCR in an embodiment of the present invention.

Detailed ways

The ability of biomarkers commonly used in the prior art to predict ICB response is extremely unstable. After detailed and thorough experiments, the inventors developed a circRNA-based biomarker effect that can evaluate the therapeutic effect of IBC therapy in tumor patients. , the biomarkers are more stable, have tissue-specific expression and evolutionary conservation, which greatly improves the accuracy of predicting ICB response. Some embodiments of the present invention provide a set of biomarkers for evaluating the efficacy of tumor IBC therapy, the biomarkers including circ-TMTC3 and/or circ-FAM117B.

In some preferred scenarios, the assessment is a pre-assessment. For example: predicting the efficacy of IBC therapy in melanoma patients.

In some preferred solutions, the biomarkers include circ-TMTC3 and circ-FAM117B; wherein at least part of the nucleic acid sequence of circ-TMTC3 is identical to SEQ ID NO: 1; the nucleic acid sequence of circ-FAM117B At least part of it is the same as SEQ ID NO:2.

The tumor described in the present invention refers to neogrowth formed by the proliferation of local tissue cells in the body under the action of various tumorigenic factors. It usually includes benign and malignant tumors, but preferably, the tumor is a malignant tumor. The malignant tumors referred to in this article refer to those that rapidly proliferate locally, destroy adjacent tissues, and move to other parts to continue growing, causing serious harm to the body. Tumors, which may include: skin cancer, gastric cancer, lung cancer, liver cancer, esophageal cancer, colorectal cancer, leukemia, malignant lymphoma, cervical cancer, nasopharyngeal cancer, breast cancer, etc. As a preferred example, the malignant tumor is Melanoma (malignant).

The inventor has experimentally verified that both circ-TMTC3 and circ-FAM117B can be used as biomarkers to evaluate the efficacy of tumor IBC therapy. By measuring the expression level of one or two circRNAs in patient tissues, it can be well predicted. Evaluate the effectiveness of IBC therapies in individual patients. In some embodiments of the present invention, a method for evaluating the efficacy of tumor IBC therapy is provided, the method comprising the steps:

Determine the expression levels of biomarkers in patient tumor tissues;

Evaluate the efficacy of tumor IBC therapy on the patient by comparing the expression levels and thresholds of biomarkers in the patient's tumor tissue;

Wherein, the biomarkers include: circ-TMTC3 and/or circ-FAM117B.

The two biomarkers provided in the present invention can be used alone or in combination to evaluate the efficacy of tumor IBC therapy. In some preferred embodiments of the invention, the biomarker includes circ-TMTC3 or circ-FAM117B.

When a single circRNA is selected as a biomarker, the method used to evaluate the efficacy of tumor IBC therapy can be in the following two ways:

【method one】

The method includes steps:

Determine the expression level E1 of circ-TMTC3 in patient tumor tissues;

Determine the efficacy of the tumor IBC therapy on the patient by comparing E1 and the y threshold E1';

When E1' is less than E1, it is determined that the tumor IBC therapy is effective for the patient, otherwise it is determined that the tumor IBC therapy is ineffective for the patient.

【Method 2】

In some preferred solutions, the method includes the steps:

Determine the expression level E2 of circ-FAM117B in patient tumor tissues;

Determine the efficacy of the tumor IBC therapy on the patient by comparing E2 with the threshold E2';

When E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, Otherwise, the tumor IBC therapy is judged to be tolerated (ineffective) by the patient.

The inventors found in further studies that the accuracy of assessment prediction was better when the combination of circ-TMTC3 and circ-FAM117B was selected as a biomarker. Therefore, in some more preferred embodiments of the invention, the biomarkers include: circ-TMTC3 and circ-FAM117B.

When the combination of circ-TMTC3 and circ-FAM117B is selected as a biomarker, the method for evaluating the efficacy of tumor IBC therapy may be as follows:

【Method 3】

The method includes steps:

Determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

By comparing E1 with the threshold E1’, and

Determine the efficacy of the tumor IBC therapy on the patient by comparing E2 with the threshold E2';

When E1 is less than E1', and E2 is less than E2', it is determined that the tumor IBC therapy is effective for the patient, otherwise it is determined that the tumor IBC therapy is ineffective for the patient.

Furthermore, the inventor used an integrated machine learning algorithm to construct a linear mixed effects model for accurately evaluating the efficacy of IBC therapy for melanoma, obtained the weight of each variable through multivariable Cox regression coefficient weighting, and linearly combined them. The optimized model can correct differences between individuals and ensure more reliable differentially expressed circRNAs. In some more preferred embodiments of the invention, the method includes the steps:

Determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

Calculate the ICBcirSig score R according to E1 and E2;

Calculate the ICBcirSig score R’ according to the threshold E1’ and the expression level E2’ of circ-FAM117B;

Evaluate the efficacy of tumor IBC therapy in the patient by comparing the magnitudes of R and R';

Among them, the ICBcirSig score is obtained by weighting multivariate Cox regression coefficients of circ-TMTC3 and circ-FAM117B.

In some preferred solutions, the value of the ICBcirSig score is calculated by Formula I. have to;

ICBcirSig=1.001×expression level of circ-TMTC3+1.048×expression level of circ-FAM117B, (Formula I).

As a method for measuring the expression level of biomarkers in the present invention, any one may be selected from RNA sequencing, hybridization (for example, tissue in situ hybridization (ISH)), and nucleic acid amplification.

In some preferred embodiments, the expression level is determined by HPLC/UV-Vis spectroscopy, enzymatic analysis, mass spectrometry, NMR, immunoassay, ELISA, or any combination thereof.

The inventor has also developed a kit for measuring the expression levels of circ-TMTC3 and circ-FAM117B biomarkers based on nucleic acid amplification. The kit has high sensitivity and accuracy, and has strong anti-interference ability, and can easily realize circ -Simultaneous determination of two biomarkers, TMTC3 and circ-FAM117B. In some embodiments of the present invention, a kit for evaluating the efficacy of tumor IBC therapy is also provided, and the kit includes:

A primer pair set, the primer pair set includes a first primer pair and a second primer pair;

A first primer pair, the first primer pair includes a forward primer with a sequence shown in SEQ ID NO:3, and a reverse primer with a sequence shown in SEQ ID NO:4;

A second primer pair, the second primer pair includes a forward primer of the sequence shown in SEQ ID NO:5, and a reverse primer of the sequence shown in SEQ ID NO:6.

Some embodiments of the present invention also provide a system for evaluating the efficacy of tumor IBC therapy, the system includes:

a biomarker detection unit configured to determine the expression level of the biomarker in the patient's tumor tissue; and

a data processing unit configured to compare the expression levels and thresholds of biomarkers in the patient's tumor tissue to evaluate the efficacy of tumor IBC therapy on the patient;

Wherein, the biomarkers include: circ-TMTC3 and/or circ-FAM117B.

In some preferred embodiments, the biomarker includes circ-TMTC3 or circ-FAM117B.

In some preferred solutions, the system includes:

Biomarker detection unit, the biomarker detection unit is configured to measure the patient's The expression level of circ-TMTC3 in tumor tissue E1;

A data processing unit, the data processing unit is configured to compare E1 and the threshold E1' to determine the efficacy of the tumor IBC therapy on the patient;

When E1 is less than E1', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the system includes:

A biomarker detection unit, the biomarker detection unit is configured to measure the expression level E2 of circ-FAM117B in the patient's tumor tissue;

A data processing unit, the data processing unit is configured to compare the values of E2 and the threshold E2' to determine the efficacy of the tumor IBC therapy on the patient;

When E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the biomarkers include: circ-TMTC3 and circ-FAM117B.

In some preferred solutions, the system includes:

a biomarker detection unit configured to determine the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue; and

a data processing unit, the data processing unit being configured to use a threshold E1' and compare E2 with the threshold E2' to determine the efficacy of the tumor IBC therapy on the patient;

When E1 is less than E1', and E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.

In some preferred solutions, the system includes:

A biomarker detection unit, the biomarker detection unit is configured to measure the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

A data processing unit configured to:

Calculate the ICBcirSig score R according to E1 and E2,

Calculate the ICBcirSig score value R’ according to the thresholds E1’ and E2’;

Evaluate the efficacy of tumor IBC therapy in the patient by comparing the magnitudes of R and R';

Among them, the ICBcirSig score is based on circ-TMTC3 and circ-FAM117B. The variable Cox regression coefficient is obtained by weighting.

In some preferred solutions, the value of the ICBcirSig score is calculated by Formula I;

ICBcirSig=1.001×expression level of circ-TMTC3+1.048×expression level of circ-FAM117B, (Formula I).

In some preferred solutions, the detection method used to measure the expression level in the biomarker detection unit is selected from any one of RNA sequencing, hybridization and nucleic acid amplification.

In some preferred solutions, the assay method for measuring the expression level in the biomarker detection unit is selected from: HPLC/UV-Vis spectroscopy, enzymatic analysis, mass spectrometry, NMR, immunoassay, ELISA or any of them combination.

In some preferred solutions, the biomarker detection unit includes PCR amplification equipment.

In some preferred solutions, the biomarker detection unit uses the kit described in the second aspect of the present invention for detection.

In some preferred solutions, the biomarker detection unit includes a detection reagent, the detection reagent includes a primer pair set, and the primer pair set includes a first primer pair and a second primer pair;

A first primer pair, the first primer pair includes a forward primer with a sequence shown in SEQ ID NO:3, and a reverse primer with a sequence shown in SEQ ID NO:4;

A second primer pair, the second primer pair includes a forward primer of the sequence shown in SEQ ID NO:5, and a reverse primer of the sequence shown in SEQ ID NO:6.

In some preferred solutions, the method for measuring the expression level in the biomarker detection unit is a qRT-PCR method, and the threshold E1' is 0.4 to 0.6; the threshold E1' is 0.4 to 0.6.

the term

Unless otherwise defined, the following terms may have the meanings assigned to them below. However, it should be understood that other meanings known or understood by those skilled in the art are also possible and within the scope of the present invention.

As used herein, the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. All technical and scientific terms used in this article have the same meaning righteous.

Unless specifically stated otherwise or apparent from context, as used herein, the term "about" shall be understood to mean within normal tolerances in the art, such as within 2 standard deviations of the mean. Approximately may be understood as being at 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05% or 0.01 of the stated value %Inside. Unless the context indicates otherwise, all numerical values provided herein may be modified by the term approximately.

As used herein, the term "amplification" refers to any known in vitro process for obtaining multiple copies ("amplicons") of a target nucleic acid sequence or its complement or fragment thereof. In vitro amplification refers to the generation of amplified nucleic acids that may contain less than the complete target region sequence or its complement. Known in vitro amplification methods include, for example, transcription-mediated amplification, replicase-mediated amplification, polymerase chain reaction (PCR) amplification, ligase chain reaction (LCR) amplification, and strand substitution amplification. Amplification (SDA), including multi-stranded substitution amplification (MSDA). Replicase-mediated amplification uses self-replicating RNA molecules and replicase (e.g., Q-beta-replicate) (e.g., Kramer et al., U.S. Patent No. 4,786,600) .PCR amplification is well known and uses DNA polymerase, primers

and thermal cycling to synthesize multiple copies of two complementary strands of DNA or cDNA (eg, Mullis et al., U.S. Patent Nos. 4,683,195, 4,683,202, and 4,800,159). LCR amplification uses at least four separate oligonucleotides to amplify the target and its complementary strand using multiple cycles of hybridization, ligation, and denaturation (eg, EP Patent Application Publication No. 0320308). SDA is a method in which a primer contains a recognition site for a restriction endonuclease that allows the endonuclease to cleave one strand of a semi-modified DNA duplex that includes the target sequence, followed by a series of primers Amplification is performed in extension and strand displacement steps (eg Walker et al., US Patent No. 5,422,252). Two other known strand replacement amplification methods do not require endonuclease cleavage (Dattagupta et al., US Patent No. 6,087,133 and US Patent No. 6,124,120 (MSDA)). Those skilled in the art will appreciate that the oligonucleotide primer sequences of the invention can readily be used in any in vitro amplification method based on primer extension by a polymerase. (See generally Kwoh et al., 1990, Am. Biotechnol. Lab. 8:14-25 and Kwoh et al., 1989, Proc. Natl. Acad. Sci. USA 86, 1173-1177; Lizardi et al., 1988, BioTechnology 6: 1197 -1202; Malek et al., 1994, Methods Mol. Biol., 28:253-260; and Sambrook et al., 2000, Molecular Cloning A Laboratory Manual, Third Edition, CSHL Laboratories). As is well known in the art, oligonucleotides are designed to bind complementary sequences under selected conditions.

As used herein, the term "marker" or "biomarker" is a biomolecule or group of biomolecules whose expression levels correlate, eg, positively or negatively, with the efficacy of IBC therapy in a tumor (eg, melanoma).

As used herein, the term "expression" refers to the process of producing a polypeptide from DNA. The process involves the transcription of genes into mRNA and the translation of that mRNA into polypeptides. "Expression" as used may refer to the production of RNA or protein or both, depending on the context.

As used herein, "patient" or "subject" may refer to a human or non-human animal, preferably a mammal. "Subject" means any animal, including horses, dogs, cats, pigs, goats, rabbits, hamsters, monkeys, guinea pigs, rats, mice, lizards, snakes, sheep, cattle, fish and birds. Human subjects may be referred to as patients.

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the present invention will be further described below in conjunction with specific embodiments. It should be understood that these examples are only used to illustrate the invention and are not intended to limit the scope of the invention. Experimental methods without specifying specific conditions in the following examples usually follow conventional conditions or conditions recommended by the manufacturer. Unless otherwise stated, percentages and parts are by weight. The experimental materials and reagents used in the following examples can be obtained from commercial sources unless otherwise specified.

Unless otherwise specified, technical and scientific terms used herein have the same meanings as commonly understood by those of ordinary skill in the technical field to which this application belongs. It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the present invention. Exemplary embodiments of the application.

The raw RNAseq data and clinical information for Cohort 1 used in this study can be downloaded from the European Nucleotide Archive (ENA) (https://www.ebi.ac.uk/ena) under accession number PRJEB23709. Briefly, melanoma patients were treated with either single-agent anti-PD-1 (nivolumab or pembrolizumab) or a combination of anti-PD-1 and anti-CTLA-4 (ipilimumab). Patient response was determined using RECIST1.1 criteria. Pre-medication means collecting samples before immunotherapy, and during treatment means collecting samples 7-14 days after immunotherapy. This patient cohort included a total of 88 samples with RNA-seq data, including 47 patients who received anti-PD-1 monotherapy (before treatment, n = 38; during treatment, n = 9) and 41 patients who received anti-PD-1 monotherapy. Pilimumab and anti-PD-1 immunotherapy (before treatment, n = 32; during treatment, n = 9). The raw RNAseq data and clinical information of cohort 2 used in this study were downloaded from the Database of Genotypes and Phenotypes (dbGaP) (https://www.ncbi.nlm.nih.gov/gap/), with the accession number phs000452.v3. p1. Included were patients with advanced melanoma treated with single-agent anti-PD-1 (nivolumab or pembrolizumab) with or without prior anti-CTLA-4 therapy. The RECIST1.1 criteria were used to evaluate the patient efficacy, including 30 patients with progressive disease (PD), 9 patients with stable disease (SD), 1 patient with mixed response (MR), 19 patients with partial response (PR) and 10 patients with complete response (CR). A total of 69 samples collected before immunotherapy with RNA-seq data were included in this patient cohort.

Example 1. Abnormal expression of circRNA in patients treated with CB

In this example, the inventor collected two independent whole RNA sequencing data cohorts, and the cohorts were treated with a single drug anti-PD-1 or a combination of anti-CTLA-4 and anti-PD-1. Cohort 1 included 88 patients who received anti-PD-1 monotherapy (47 patients, including 38 pre-drug patients and 9 on-treatment patients) or combined anti-CTLA-4 and anti-PD-1 therapy (41 patients patients (including 32 patients before treatment and 9 patients during treatment); 69 patients with melanoma in cohort 2 received anti-PD-1 treatment (nivolumab or pembrolizumab).

To identify reliable circRNAs, the inventors combined four excellent circRNA detection tools, including cirri2, Find_circ, CircExplorer2 and CircRNA_finder, to quantify backsplicing reads (see Figure 1. Figure 1 shows the results in an independent melanoma patient cohort 1 (A) and cohort 2 (B), the number of circRNAs identified by each tool). Different circRNA detection tools identify different numbers of circRNAs, so at least two circRNAs with back-splicing read numbers ≥ 2 and identified by more than 2 tools are retained. Specifically, the inventors identified a total of 89,204 circRNAs from 88 samples in cohort 1, and 43,911 circRNAs from 69 samples in cohort 2. The detectable number of circRNAs in each patient in cohort 1 was 1440-16653, and in each patient in cohort 2, the detectable number of circRNAs was 39-11652. To reduce potential inaccuracies, the inventors only considered circRNAs identified in more than 20% of the samples in each cohort. A total of 5350 circRNAs were retained in cohort 1, with the retention range for each patient ranging from 774 to 4525 (see Figure 2C), and a total of 3654 circRNAs were retained in cohort 2, with the retention range for each patient ranging from 20 to 3013 (see Figure 2D). 90.4% (3293/3644) of circRNAs in cohort 2 could be detected in cohort 1 (Fisher test, p<2.2e-16). Among these detected circRNAs, 96.6% of circRNAs (5167/5350) in cohort 1 and 97.3% of circRNAs in cohort 2 (3544/3644) circRNAs present in the MiOncoCirc database were quantified from tumor samples, indicating that the circRNA profiles in these two cohorts are tumor-related.

The nucleic acid sequence (coding sequence) of Circ-TMTC3 is SEQ ID NO: 1

The nucleic acid sequence (coding sequence) of Circ-FAM117B is SEQ ID NO: 2

Example 2. Construction of circRNA differential regulatory network

In this example, the inventor used a linear mixed effect model to identify differential circRNAs that responded and did not respond to immunotherapy, and selected up-regulated circRNAs common to non-benefiting patients and benefiting patients for analysis.

(1) Identification of differential circRNA between immunotherapy response and non-response

To identify differentially expressed circRNAs in non-benefit samples and benefit samples before treatment and early in treatment, respectively, the inventors applied a linear mixed effects model (LME) to calculate differential circRNAs, which considers nested random effects (for each individual sample) Taking potential confounding factors into consideration, the lme program in the nlme-R package was used to execute the results. The p value was <0.05, and |log2(fold change)|≥0.5 was considered a statistically significant difference. Specifically, a linear mixed effects model was first utilized to identify differentially expressed circRNAs between the benefit group (n=54) and the non-benefit group (n=16) before treatment, and then the effects of these differentially expressed circRNAs during treatment were studied. Expression differences (benefit group, n=13; non-benefit group, n=5).

In pre-treatment samples, the inventors found 227 up-regulated and 23 down-regulated circRNAs in non-benefit patients compared with benefit patients (P<0.05 and |log2(fold change)|≥0.5). In the on-treatment samples, 1547 up-regulated and 10 down-regulated circRNAs were found after ICB treatment (see Figure 3. Figure 3A shows the up-regulated (red) and down-regulated (blue) circRNAs in PRE non-benefit and benefit melanoma samples before treatment. Volcano plot; Figure 3B is a volcano plot of upregulation (red) and downregulation (blue) of EDTcircRNA during treatment). In the non-responsive group before treatment and during treatment, more up-regulated circRNAs and less down-regulated circRNAs were found, suggesting a potential relationship between circRNA overexpression and immunotherapy resistance. In order to further explore the functional role of circRNA in immunotherapy, the inventors selected 81 up-regulated circRNAs common to non-benefit patients and beneficiary patients at time points before treatment and during treatment for subsequent analysis (see Figure 4).

(2) Identification of circRNA-miRNA-mRNA relationship network

In order to predict circRNA-miRNA interactions, the inventors used Miranda software, which identifies potential target sites of miRNAs in genome sequences, to predict circRNA target sites. It ranks candidate miRNAs for each circRNA based on alignment scores and minimum free energy. The miranda algorithm was used to predict high-confidence binding sites, and the top 30 scoring miRNAs were selected for each of the 81 up-regulated circRNAs.

Then, the miRNA-mRNA relationship pairs were downloaded from the Tarbase database (containing experimentally supported miRNA-mRNA interactions) and the TargetScan database, and the shared miRNA-mRNA pairs in both databases were retained. The inventors detected a total of 773 miRNAs and 2429 interaction relationships in the circRNA-miRNA axis.

Finally, circRNA-miRNA-mRNA interactions were screened according to the following criteria:

1) Retain the 95% quantile miRNAs expressed in TCGA melanoma to filter non-melanoma-related miRNAs;

2) Retain the top 30 scoring and sorting miRNAs that interact with circRNA;

3) retain miRNAs that interact with both circRNA and mRNA;

4) The circRNA-miRNA-mRNA interaction is retained, in which there is a significant positive correlation between circRNA and mRNA (Rs>0.2 and p<0.05).

Based on the above screening principles, the inventors identified 184,587 circular circRNA-miRNA-mRNA interactions based on the common miRNA target sites of circRNA and mRNA.

In addition, the inventors further screened high-confidence associations based on multiple steps such as expression correlation, and retained 8449 (81 circRNAs-183 miRNAs-2046 mRNAs) ICB response-related interactions (Figure 5, Figure 5 The upper part is the ICB-related circular circRNA-miRNA-mRNA axis; the lower part is the network of all circRNA-miRNA-mRNA interaction pairs). Pathway analysis based on these 2046 mRNAs showed that they were significantly enriched in tumor signaling pathways, such as the Hippo signaling pathway, p53 signaling pathway, mTOR signaling pathway, and AMPK signaling pathway (see Figure 6). These mRNAs are also enriched in several biological processes such as cell cycle checkpoints, cellular hypoxia response, autophagy, and Wnt signaling pathway regulation. For example, targeting the Wnt signaling pathway may reverse immunotherapy resistance by altering antigen presentation. Analysis showed that circRNAs were abnormally up-regulated in non-beneficiary patients, indicating the potential role of circRNAs in resisting cancer immunotherapy by changing cancer signaling pathways.

Example 3. Constructing a circRNA model to predict immunotherapy effects

In this embodiment, the inventor uses a machine learning-based algorithm to construct ICBcircSig. (i) Univariate survival analysis was performed on progression-free survival (PFS) and circRNA expression to identify prognostic-related circRNAs; (ii) Based on the LASSO Cox regression model, the optimal combination was selected from the circRNAs in (i). The inventor named the final marker "ICBcirSig", (iii) each sample This ICBcircSig score was established based on the weighted expression value and multivariable cox regression coefficient (1.001*circ-TMTC3+1.048*circ-FAM117B). The specific method is as follows:

(1) Patient Cohort 1 constructed circRNA markers to predict the effect of immunotherapy

To identify circRNAs associated with prognosis, the inventors performed univariate Cox regression analysis on the expression levels and progression-free survival (PFS) of 227 upregulated circRNAs in pre-drug samples in cohort 1. The results showed that high expression of 25 circRNAs was significantly associated with poor PFS (log-rank test, FDR<0.05, Cox FDR<0.05).

In order to determine the best circRNA combination as a biomarker for predicting prognosis, the inventor applied the LASSO Cox regression model to analyze 25 circRNA expression profiles and clinical information (results shown in Figure 7), and selected 4 regression coefficients with non-zero circRNA (see Figure 8). Multivariate Cox regression analysis was performed using these four circRNAs as variables, and it was found that circ-TMTC3 and circ-FAM117B were significant predictors (see Figure 9). The expression of these two circRNAs was associated with poor PFS (Figure 10 and Figure 11), circ-TMTC3 and circ- The expression of FAM117B is significantly lower than that in patients with progressive diseases (such as Parkinson's disease, PD) (Figure 12 and Figure 13).

Further weighting the expression value of circRNA in ICBcircSig by the multivariable Cox regression coefficient, the inventor constructed an ICB-related circRNA marker (ICBcircSig) score (1.001*circ-TMTC3+1.048*circ-FAM117B). Further evaluating the clinical relevance, the inventors found that patients with high ICBcircSig scores had worse PFS than patients with low ICBcircSig scores (log-rank test, p<0.001, Figure 14).

The 12-month and 24-month progression rates of the high ICBcircSig score group were 100% and 100% respectively, which were significantly higher than the 27% and 30% of the low ICBcircSig score group. For 12-month and 24-month PFS as the standard, the area under the curve (AUC) of the ROC curve of ICBcircSig score over time was 0.76 and 0.75, respectively (Figure 15).

The inventor further studied the relationship between ICBcircSig score and patient response to ICB treatment and found that the ICBcircSig score of CR/PR patients was significantly lower than that of PD/SD patients (CR/PR vs PD/SD, p=5.6×10 ^-5 ; Figure 16).

In addition, the inventor further studied whether the ICBcircSig score can be used as an independent prognostic factor through multi-factor Cox regression analysis to correct the influence of other traditional clinical factors. Including age, gender, ICB treatment method, CD274 (PD-L1) and PDCD1. After correcting for confounding factors, ICBcircSig score (hazard ratio [HR]=2.975, 95% confidence interval [CI] 1.723-5.138, p<0.001) is an independent prognostic risk factor for PFS (Figure 17).

(2) Evaluation of ICBcircSig score performance in independent patient cohort 2:

The inventors further evaluated the performance of ICBcircSig score in independent patient cohort 2 and found that circ-TMTC3 and circ-FAM117B were associated with poor PFS and tended to be enriched in patients with PD response to ICB treatment in cohort 2 (Figure 18 -twenty one).

Further calculation of ICBcircSig score for each sample showed that patients with high ICBcircSig score had lower FPS compared with ICBcircSig score (Figure 22). For 12-month and 24-month PFS as the standard, the area under the curve of the ROC curve of ICBcircSig score over time. (AUC) were 0.69 and 0.65 respectively (Figure 23). CR/PR patients had significantly lower ICBcircSig scores than PD or SD patients (CR/PR vs PD/SD, p=0.0015; Figure 24), which is consistent with observations in Cohort 1. Further multivariate Cox analysis showed that ICBcircSig score (HR=1.32, 95% CI 1.0721-1.630, p=0.009) is an independent prognostic factor (Figure 25).

Example 5. Verification of circRNA model to predict immunotherapy effect

(1) PCR amplification of circular RNA after ribonuclease treatment

RNA isolation from tumor samples of patients treated with ICB using specific primer pair for linear circ-TMTC3

[F5′-AATACTTCTTACAGGCTACCCATGT-3′ and R5′-AACCACAAAAGAGGCTGTTCC-3′] and circ-FAM117B [F5′-CTTTGCCCAAATATGCAACC-3′ and R5′-CTTTGGAACAGGAGCGAGCA-3′] were PCR amplified.

SEQ ID NO:3

SEQ ID NO:4

SEQ ID NO:5

SEQ ID NO:6

2 micrograms of RNAs were incubated with ribonuclease (RNase R, VWR) at 37°C for 30 minutes to degrade linear RNAs. The RNA was incubated at 70°C for 10 minutes to inactivate RNase R, and then reverse transcription RT-PCR was performed. RNA is generated into cDNA for use in PCR reactions. No reverse transcriptase (No RT) was used as a negative control, and circ-TMTC3 and circ-FAM117B were used as positive controls to localize the occurrence of circ-TMTC3 and circ-FAM117B respectively. Sanger sequencing was performed after treatment with RNase R. Among them, the primers are 5'-AATACTTCTTACAGGCTACCCATGT-3'(circ-TMTC3), and 5'-CTTTGCCCAAATATGCAACC-3'(circ-FAM117B).

The inventors further collected pre-treatment tumor samples from 11 patients and 4 patients who did or did not respond to anti-PD1 treatment. qRT-PCR was used to detect the expression levels of circ-TMTC3 and circ-FAM117B in these samples. The results are shown in Figures A and C. The results showed that the two circRNAs were significantly higher in non-responders than in responders (Figures 26 and 28).

Sanger sequencing further confirmed that the PCR product spanned the circular connection site of circ-TMTC3 and circ-FAM117B (the red dotted line indicates the intersection of the circles) (Figures 27 and 29).

Those of ordinary skill in the art can understand that the above-mentioned embodiments are specific examples for realizing the present invention, and in practical applications, various changes can be made in form and details without departing from the spirit and spirit of the present invention. scope.

Claims (10)

1. A biomarker used to evaluate the efficacy of tumor IBC therapy, characterized in that the biomarker includes circ-TMTC3 and/or circ-FAM117B.
2. The biomarker according to claim 1, wherein the biomarker includes circ-TMTC3 and circ-FAM117B; wherein at least part of the nucleic acid sequence of circ-TMTC3 is the same as SEQ ID NO: 1; At least part of the nucleic acid sequence of circ-FAM117B is identical to SEQ ID NO:2.
3. The biomarker according to claim 1, wherein the tumor is melanoma.
4. A kit for evaluating the efficacy of tumor IBC therapy, characterized in that the kit includes:

   A primer pair set and a probe, the primer pair set includes a first primer pair and a second primer pair;

   A first primer pair, the first primer pair includes a forward primer with a sequence shown in SEQ ID NO:3, and a reverse primer with a sequence shown in SEQ ID NO:4;

   A second primer pair, the second primer pair includes a forward primer of the sequence shown in SEQ ID NO:5, and a reverse primer of the sequence shown in SEQ ID NO:6.
5. Use of circ-TMTC3 and/or circ-FAM117B detection reagents for preparing kits for evaluating the efficacy of tumor IBC therapy.
6. A system for evaluating the efficacy of tumor IBC therapy, characterized in that the system includes:

   a biomarker detection unit configured to determine the expression level of the biomarker in the patient's tumor tissue; and

   a data processing unit configured to compare the expression levels and thresholds of biomarkers in the patient's tumor tissue to evaluate the efficacy of tumor IBC therapy on the patient;

   Wherein, the biomarkers include: circ-TMTC3 and/or circ-FAM117B.
7. The system according to claim 6, wherein the biomarker includes circ-TMTC3 or circ-FAM117B.
8. The system according to claim 7, wherein the biomarker detection unit The element was set up to determine the expression level of circ-TMTC3 E1 and the expression level of circ-FAM117B E2 in the patient's tumor tissue; and

   The data processing unit is configured to compare E1 with the threshold value E1', and compare the values of E2 with the threshold value E2', to determine the efficacy of the tumor IBC therapy on the patient;

   When E1 is less than E1', and E2 is less than E2', it is determined that the tumor IBC therapy is sensitive (effective) to the patient, otherwise it is determined that the tumor IBC therapy is resistant (ineffective) to the patient.
9. The system according to claim 7, wherein the biomarker detection unit is configured to measure the expression level E1 of circ-TMTC3 and the expression level E2 of circ-FAM117B in the patient's tumor tissue;

   The data processing unit is configured for:

   Calculate the ICBcirSig score R according to E1 and E2,

   Calculate the ICBcirSig score value R’ according to the threshold E1’ and the threshold E2’;

   Evaluate the efficacy of tumor IBC therapy in the patient by comparing the magnitudes of R and R';

   Among them, the ICBcirSig score is obtained by weighting multivariate Cox regression coefficients of circ-TMTC3 and circ-FAM117B.
10. A method for evaluating the efficacy of tumor IBC therapy, characterized in that the method includes the steps:

    Determine the expression levels of biomarkers in patient tumor tissues;

    Evaluate the efficacy of tumor IBC therapy on the patient by comparing the expression levels and thresholds of biomarkers in the patient's tumor tissue;

    Wherein, the biomarkers include: circ-TMTC3 and/or circ-FAM117B.