A screening method for a therapeutic intervention for aromatase inhibitor associated pain and a medicament

Abstract

The application discloses a screening method and a drug for treating aromatase inhibitor related pain intervention measures. Through a large number of experimental researches, it is found that virtual memory T cells change abnormally in pain, and the change is closely related to a pain phenotype and an effect of an intervention measure. Therefore, by detecting changes of the virtual memory T cells in a biological sample, the intervention measure for treating pain can be screened. The screening method has a very wide application prospect in the field of pain treatment, such as aromatase inhibitor related pain.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, and in particular relates to a screening method and drug for treating aromatase inhibitor-related pain interventions. Background Technology

[0002] Aromatase inhibitors (AIs) are first-line endocrine therapy drugs for hormone receptor-positive breast cancer, including letrozole, anastrozole, and exemestane. These drugs work by inhibiting aromatase activity, reducing the conversion of androgens to estrogens in peripheral tissues, thereby significantly lowering estrogen levels in the body, inhibiting tumor growth, and reducing the risk of recurrence.

[0003] However, AI-induced pain often presents with a range of adverse reactions, primarily muscle and joint pain, including joint stiffness, muscle weakness, and limited mobility. These symptoms are clinically termed aromatase inhibitor-associated musculoskeletal syndrome (AIMSS). AIMSS has a high incidence and can severely impact patients' quality of life and treatment adherence; some patients even prematurely discontinue endocrine therapy due to pain. Early discontinuation of medication can significantly affect the efficacy of endocrine therapy, leading to increased cancer recurrence rates and reduced long-term survival. Therefore, early treatment of this type of pain is crucial. However, the mechanism of AI-induced pain is currently unclear, and clinical treatment primarily focuses on symptomatic relief, with limited effectiveness. A 5%-20% proportion of patients are still forced to discontinue medication due to pain.

[0004] The pathogenesis of AIMSS is not yet fully understood. Existing mechanisms include: ① estrogen deficiency leading to abnormal bone, joint, and muscle metabolism; ② elevated local or systemic inflammatory factors; ③ neurosensitization and abnormal activation of pain pathways; and ④ pathological changes in the synovium, cartilage, muscle, and peripheral nerve terminals. However, a key influencing factor that directly links estrogen deprivation, immune changes, and pain phenotype is currently lacking. Therefore, there is an urgent need to develop new efficacy evaluation indicators and corresponding therapeutic drugs. Summary of the Invention

[0005] To address at least some of the technical problems in the prior art, the present invention provides a method and a drug for screening interventions to treat aromatase inhibitor-related pain. Specifically, the present invention includes the following.

[0006] A first aspect of the present invention provides a method for screening compounds useful for treating aromatase inhibitor-related pain, comprising the following steps: (1) Prepare an aromatase inhibitor-associated pain model, wherein the number and / or proportion of virtual memory T cells in the model is a first value; (2) Apply the test compound to the model; (3) Detect the number and / or proportion of virtual memory T cells in the model after administration of the test compound to obtain a second value; (4) The first and second values ​​are compared to assess whether the test compound is effective in treating aromatase inhibitor-related pain.

[0007] In some embodiments, according to the method for screening compounds useful for treating aromatase inhibitor-related pain according to the present invention, the aromatase inhibitor-related pain model is a cell model, specifically a CD8 cell model. + T cells are induced T cells or cells that maintain a virtual memory T cell state.

[0008] In some embodiments, the method for screening compounds useful for treating aromatase inhibitor-related pain according to the present invention includes the step of identifying at least one of CD8, CD45, CD44, CD49d, CD122, and Eomes in cells.

[0009] In some embodiments, the method for screening compounds useful for treating aromatase inhibitor-related pain according to the present invention, wherein the model is an animal model constructed by removing the ovaries of an animal and treating it with an aromatase inhibitor.

[0010] In some embodiments, according to the method for screening compounds useful for treating aromatase inhibitor-related pain according to the present invention, the test compound is determined to be useful for treating or improving aromatase inhibitor-related pain when the second value is less than the first value, and the test compound is determined to be useless for treating or improving aromatase inhibitor-related pain when the second value is greater than or equal to the first value.

[0011] A second aspect of the invention provides the use of virtual memory T cells in the analysis of aromatase inhibitor-related pain, wherein the use is for non-diagnostic or non-therapeutic purposes.

[0012] In some embodiments, according to the application described in the invention, the application includes the evaluation of the efficacy of the test compound, the development of candidate interventions, or the study of intervention targets.

[0013] In some embodiments, according to the application described in the present invention, the analysis includes the step of detecting the number or proportion of virtual memory T cells.

[0014] In some embodiments, according to the application described in the invention, the detection includes using a reagent capable of displaying virtual memory T cells.

[0015] In some embodiments, according to the application described in the invention, the detection includes a step of identification using flow cytometry.

[0016] This invention, through extensive experimental research, has discovered that virtual memory T cells undergo abnormal changes in pain, and these changes are closely related to pain phenotypes and the effectiveness of interventions. Therefore, by detecting changes in virtual memory T cells in biological samples, interventions for treating pain can be screened. Furthermore, animal models of pain can be constructed by inducing changes in virtual memory T cells. Attached Figure Description

[0017] Figure 1 A flowchart for establishing the AIMSS animal model is shown.

[0018] Figure 2 The results of the pain behavior test are shown.

[0019] Figure 3 T is shown VM Flow cytometry detection and gating diagram.

[0020] Figure 4 This shows T in the AIMSS animal model. VM The changes are shown in Figure 1, where A represents the results of flow cytometry analysis, and B and C represent the changes in T cells. VM The quantity and proportion.

[0021] Figure 5 This demonstrates the T after in vivo intervention with baricitinib. VM The changes are shown in Figure 1, where A represents the results of flow cytometry analysis, and B and C represent the changes in T cells. VM The quantity and proportion.

[0022] Figure 6 This demonstrates the in vitro regulation of T by baricitinib. VM In the given information, A represents the results of flow cytometry analysis, and B and C represent the results of T... VM The quantity and proportion.

[0023] Figure 7 T is shown VM Changes during pain. Detailed Implementation

[0024] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0025] It should be understood that the terminology used in this invention is merely for describing particular embodiments and is not intended to limit the invention. Furthermore, with respect to numerical ranges in this invention, it should be understood that the upper and lower limits of the range and each intermediate value between them are specifically disclosed. Any stated value or intermediate value within a stated range, as well as each smaller range between any other stated value or intermediate value within said range, are also included in this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range.

[0026] Unless otherwise stated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. While only preferred methods and materials have been described herein, any methods and materials similar or equivalent to those described herein may be used in the implementation or testing of this invention.

[0027] Filtering methods One aspect of the present invention provides a method for screening compounds useful for treating aromatase inhibitor-related pain, comprising the following steps: (1) Prepare an aromatase inhibitor-associated pain model, wherein the number and / or proportion of virtual memory T cells in the model is a first value; (2) Apply the test compound to the model; (3) Detect the number and / or proportion of virtual memory T cells in the model after administration of the test compound to obtain a second value; (4) The first and second values ​​are compared to assess whether the test compound is effective in treating aromatase inhibitor-related pain.

[0028] In some embodiments, the aromatase inhibitor-related pain model is a cell model, specifically a CD8 cell model. + T cells are induced T cells or cells that maintain a virtual memory T cell state.

[0029] In this invention, the method and apparatus for detecting virtual memory T cells are not particularly limited, and methods or apparatus known in the art can be used, such as, but not limited to, flow cytometry. In some embodiments, the detection of virtual memory T cells is achieved by identifying at least one of CD8, CD45, CD44, CD49d, CD122, and Eomes in the cells.

[0030] In some implementations, the model is an animal model, which is obtained by the following method: (I) Artificial menopause was induced in young female animals; (II) Administer aromatase inhibitors to artificially postmenopausal animals at a dose of 0.1–1.5 mg / kg per day; (III) Detect the behavioral characteristics and / or biological indicators of the animal after step (II), wherein the behavioral characteristics include, but are not limited to, pain threshold, heat withdrawal reflex latency, motor ability, anxiety, pleasure-like behavior, etc., and the biological indicators include, but are not limited to, IL-1β content, thymocyte count, etc.

[0031] In some implementations, when the second value is less than the first value, the test compound is determined to be a compound useful for treating or improving aromatase inhibitor-related pain, and when the second value is greater than or equal to the first value, the test compound is determined to be a compound useless for treating or improving aromatase inhibitor-related pain.

[0032] application One aspect of the present invention provides the use of virtual memory T cells in the analysis of aromatase inhibitor-related pain, wherein the use is for non-diagnostic or non-therapeutic purposes. The analysis includes a step of detecting the number or proportion of virtual memory T cells, the detection comprising using a reagent capable of displaying virtual memory T cells. The use includes, but is not limited to, the evaluation of the efficacy of the test compound, the development of candidate interventions, and the study of intervention targets. In this invention, the interventions include, but are not limited to, compounds, physical measures, etc. The physical measures include, but are not limited to, heat therapy, infrared irradiation, transcutaneous electrical nerve stimulation, ultrasound therapy, and massage.

[0033] The present invention also provides a method for constructing an animal model of pain, which includes the step of inducing an increase in the proportion and / or number of virtual memory T cells in the animal.

[0034] In a preferred embodiment, the method for constructing a pain animal model includes: (1) preparing a healthy animal and detecting the proportion and / or number of virtual memory T cells in the animal's blood or tissue sample; (2) administering a virtual memory T cell inducer to the animal; and (3) detecting the proportion and / or number of virtual memory T cells in the animal's blood or tissue sample after induction. When the proportion and / or number of virtual memory T cells increases, the pain animal model is successfully constructed.

[0035] This invention further provides the use of virtual memory T-cell inhibitors in the preparation of medicaments for treating or improving aromatase inhibitor-related pain. The virtual memory T-cell inhibitor is not particularly limited and includes any substance capable of inhibiting virtual memory T cells, examples of which include, but are not limited to, small molecule compounds, nucleic acids, proteins, peptides, antibodies, etc.

[0036] Example 1 The following illustrates the role of virtual memory T cells in aromatase inhibitor-related pain.

[0037] The flowchart for constructing the AIMSS animal model is as follows: Figure 1 As shown, the specific procedure included: selecting 8-10 week old female C57BL / 6J mice and dividing them into Sham, OVX, and OVX+AI groups. The Sham group underwent sham surgery, the OVX group underwent ovariectomy, and the OVX+AI group underwent ovariectomy followed by aromatase inhibitor gavage to model pain. Von Frey fibers were used to evaluate pain phenotypes, and the results are as follows... Figure 2 As shown, compared with the Sham group, the mechanical pain threshold decreased in both the OVX group and the OVX+AI group at different time points; among them, the mechanical pain threshold in the OVX+AI group decreased further compared with the OVX group. Their pain phenotype was distinct and stable, consistent with actual clinical patterns.

[0038] Spleen samples were taken from model mice, ground and separated into single cells, and then T cells were detected by flow cytometry. VM The changes between different groups are illustrated in the following diagram: Figure 3 As shown. The test results are as follows. Figure 4 As shown, compared with the OVX group, the T of the OVX+AI group was... VM An increase in quantity / proportion has occurred.

[0039] Example 2 The following shows the changes in virtual memory T cells when aromatase inhibitor-related pain is suppressed.

[0040] Animal models were constructed using the method described in Example 1. The OVX+AI group was treated with baricitinib at model establishment. Changes in pain behavior and T... VM Changes between different groups. Results showed that the mechanical pain threshold was significantly increased in the OVX+AI group after baricitinib treatment, while T... VM The proportion / quantity decreased. The result is as follows: Figure 5 As shown, virtual memory T cells can serve as an intervention target or efficacy evaluation indicator for aromatase inhibitor-related bone pain.

[0041] Example 3 The following illustrates the regulatory effect of pain inhibitors on virtual memory T cells in vitro.

[0042] CD8 derived from mouse lymph nodes +T cells were cultured in vitro. CD3 antibody, CD28 antibody, IL-4, and IFN-α were added to the culture system to induce or maintain a virtual memory T cell-related state. Subsequently, the cells were treated with 150 nM baricitinib for 24 hours. After treatment, flow cytometry was used to detect changes in the number and proportion of virtual memory T cells. The results showed that, compared with the control group, the proportion and number of virtual memory T cells were reduced in the baricitinib-treated group.

[0043] The results are as follows Figure 6 As shown, baricitinib can regulate abnormal changes in virtual memory T cells in vitro, thereby supporting the application value of virtual memory T cells as an intervention target and efficacy evaluation indicator for aromatase inhibitor-related musculoskeletal pain.

[0044] Example 4 The following illustrates the role of virtual memory T cells in pain.

[0045] Adoptive transfer was used to increase virtual memory T cells in WT mice. The method involved isolating mouse lymph node cells and culturing them in vitro. CD3 antibody, CD28 antibody, IL-4, and IFN-α were added to the culture system to induce or maintain the virtual memory T cell-related state. The cultured virtual memory T cells were then adoptively transferred to mice, and changes in the mouse pain phenotype were detected using Von Frey fibers. The results showed that, compared with the control group, mice in the virtual memory T cell-increased group exhibited a decreased mechanical pain threshold.

[0046] The results are as follows Figure 7 As shown, an increase in virtual memory T cells can lead to enhanced pain sensitivity, indicating that virtual memory T cells are not only associated with aromatase inhibitor-related musculoskeletal pain, but also participate in its development, suggesting that they can serve as an intervention target and efficacy evaluation indicator.

[0047] Example 5 The following describes a screening method for compounds that are useful in treating aromatase inhibitor-related pain.

[0048] Female C57BL / 6J mice aged 8-10 weeks were selected, and an aromatase inhibitor-related pain animal model was constructed according to the method in Example 1. Blood samples were obtained from the animal model, and the number and proportion of virtual memory T cells in the blood samples were detected to obtain a first value. The test compound (e.g., baricitinib) was administered to the animal model. Blood samples from the animal model after treatment with the test compound were obtained, and the number and proportion of virtual memory T cells in them were detected to obtain a second value. The first value and the second value were compared.

[0049] The results showed that after administration of baricitinib, the second value was significantly smaller than the first value, thus indicating that the test compound was a useful compound for treating aromatase inhibitor-related pain.

[0050] Example 6 The following illustrates the method for constructing animal models of pain.

[0051] Female C57BL / 6J mice aged 8-10 weeks were selected, and blood samples were obtained from the mice. The proportion and number of virtual memory T cells in the blood samples were detected. A virtual memory T cell inducer was administered to the mice. Blood samples of the animals after induction were obtained, and the proportion and number of virtual memory T cells were detected. When the proportion and / or number of virtual memory T cells increased, the pain animal model was successfully constructed.

[0052] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for screening compounds useful for treating aromatase inhibitor-related pain, characterized in that, Includes the following steps: (1) Prepare an aromatase inhibitor-associated pain model, wherein the number and / or proportion of virtual memory T cells in the model is a first value; (2) Apply the test compound to the model; (3) Detect the number and / or proportion of virtual memory T cells in the model after administration of the test compound to obtain a second value; (4) The first and second values ​​are compared to assess whether the test compound is effective in treating aromatase inhibitor-related pain.

2. The method for screening compounds useful for treating aromatase inhibitor-related pain according to claim 1, characterized in that, The aromatase inhibitor-related pain model is a cell model, specifically CD8. + T cells are induced T cells or cells that maintain a virtual memory T cell state.

3. The method for screening compounds useful for treating aromatase inhibitor-related pain according to claim 2, characterized in that, The detection includes the step of identifying at least one of CD8, CD45, CD44, CD49d, CD122, and Eomes in the cells.

4. The method for screening compounds useful for treating aromatase inhibitor-related pain according to claim 3, characterized in that, The model is an animal model, which is a pain animal model constructed by removing the ovaries of animals and treating them with aromatase inhibitors.

5. The method for screening compounds useful for treating aromatase inhibitor-related pain according to claim 1, characterized in that, When the second value is less than the first value, the test compound is determined to be a compound useful for treating or improving aromatase inhibitor-related pain; when the second value is greater than or equal to the first value, the test compound is determined to be a compound useless for treating or improving aromatase inhibitor-related pain.

6. The application of virtual memory T cells in the analysis of aromatase inhibitor-related pain, characterized in that, The application described is for non-diagnostic or non-therapeutic purposes.

7. The application according to claim 6, characterized in that, The applications include evaluating the efficacy of the test compound, developing candidate interventions, or studying intervention targets.

8. The application according to claim 6, characterized in that, The analysis includes the step of detecting the number or proportion of virtual memory T cells.

9. The application according to claim 8, characterized in that, The detection includes using reagents capable of displaying virtual memory T cells.

10. The application according to claim 8, characterized in that, The detection includes a step of identification using flow cytometry.

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