Predictive biomarker for treating adverse reaction of tumor patient by immune checkpoint inhibitor and application of predictive biomarker
By detecting changes in the proportion of CX3CR1+CD8+ T cells, this method solves the problem of the inability to predict adverse reactions of immune checkpoint inhibitors in cancer patients at an early stage in existing technologies. It achieves early risk warning and high-specificity detection, is applicable to various tumor types and immune checkpoint inhibitors, and has the potential for clinical promotion and translational application.
Patent Information
- Application Number
- CN202511653528.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-12
- Publication Date
- 2026-02-06
AI Technical Summary
Current technologies cannot predict adverse reactions in cancer patients treated with immune checkpoint inhibitors in the early stages, the specificity of detection indicators is insufficient, high-throughput methods are difficult to routinely implement, and clinical intervention strategies lack coordination.
The proportion of CX3CR1+CD8+ T cells was used as a predictive biomarker. Changes in the proportion of CX3CR1+CD8+ T cells in the peripheral blood of patients were detected by conventional methods such as flow cytometry. The results were dynamically compared with baseline levels to provide early risk warning.
It enables the early identification of high-risk patients before adverse reactions occur, improving the timeliness and specificity of prediction, facilitating clinical application, and is applicable to various tumor types and immune checkpoint inhibitors. It also has the potential to be transformed into in vitro diagnostic kits and standardized clinical tests.
Smart Images
Figure CN121476601A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of biotechnology, and in particular relates to a predictive biomarker for adverse reactions of immune checkpoint inhibitors in cancer patients and its application. Background Technology
[0002] In recent years, immune checkpoint inhibitors (ICIs), such as PD-1, PD-L1, and CTLA-4 monoclonal antibodies, have become important tools in cancer treatment. These drugs significantly improve remission rates and survival rates in various malignant tumors (such as melanoma, non-small cell lung cancer, and renal cell carcinoma) by relieving the tumor's suppression of the immune system. However, due to the overactivation of the immune system, the use of ICIs is often accompanied by immune-related adverse events (irAEs).
[0003] Intracytoplasmic adverse events (irAEs) can affect multiple organs, including the skin, intestines, lungs, heart, and endocrine glands. Mild cases may present as rashes or diarrhea, while severe cases can lead to myocarditis, pneumonia, or even death. Clinical studies have shown that approximately 10–20% of patients receiving intravascular coagulation (ICI) therapy experience severe (grade 3–4) irAEs, which is a major factor limiting the widespread use of this type of therapy.
[0004] Currently, most commonly used clinical monitoring methods for adverse reactions are post-hoc diagnostic, such as detecting myocardial injury markers (e.g., cTn-I), performing chest CT scans, or conducting endoscopy to detect pneumonia or enteritis. These methods can only indicate abnormalities after organ damage has occurred, lacking predictive ability before the appearance of clinical symptoms, leading to delayed intervention and hindering individualized patient management.
[0005] Some studies have attempted to utilize serum inflammatory factors (such as CRP and IL-6) levels, or peripheral blood total CD8+ levels. ＋T cell counts and their activation markers (such as HLA-DR and CD38) are used to infer the risk of irAEs. However, these indicators lack specificity and are easily affected by factors such as infection, comorbidities, or tumor progression, making it difficult to reliably distinguish between T cell expansion associated with antitumor effects and abnormal pro-inflammatory T cell expansion that triggers irAEs, thus limiting their clinical application value. In recent years, although some researchers have used single-cell transcriptome sequencing or TCR clonal profile analysis to explore the immunological mechanisms related to irAEs, these methods can reveal the functional trajectory of immune cell subsets, but they are costly, time-consuming, and complex to operate, making it difficult to promote them as routine clinical detection methods. More importantly, existing technologies have not yet been refined into a highly operable hematological prediction process with clearly defined threshold interpretation criteria.
[0006] Further research shows that CD8 ＋ T cells are not a homogeneous population. Among them, CTLs associated with antitumor effects primarily infiltrate tumor tissue; colitis-associated CTLs originate from intestinal memory cells; while a subset of CTLs closely associated with multi-organ irreversible adverse events (irAEs) such as cardiac and pulmonary injuries exhibits a marked inflammatory profile and expands after immune checkpoint blockade therapy. Notably, this cell subset can be detected in peripheral blood and is correlated with the severity of adverse reactions. CX3CR1, as its characteristic molecule, has been shown to effectively distinguish this cell population. Therefore, relying solely on total CD8+... ＋ T cell counts or non-specific inflammatory markers make it difficult to identify this key pro-inflammatory CTL subset.
[0007] In summary, existing technologies have the following main shortcomings: First, they are diagnostically delayed and cannot provide early warning of irAEs; second, the specificity of the detection indicators is insufficient and it is difficult to target inflammatory CTL subgroups; third, although some high-throughput methods have research value, they lack the feasibility of being routine and procedural; and fourth, the linkage between existing detection methods and clinical intervention strategies is insufficient and cannot effectively support decisions on drug dosage adjustment or targeted intervention. Summary of the Invention
[0008] The purpose of this application is to provide a predictive biomarker for adverse reactions in patients treated with immune checkpoint inhibitors and its application, aiming to solve the aforementioned problems in the detection methods for adverse reactions.
[0009] To achieve the above-mentioned objectives, the technical solution adopted in this application is as follows:
[0010] In one aspect, this application provides a predictive biomarker for adverse reactions to immune checkpoint inhibitor therapy in cancer patients, wherein the predictive biomarker is CX3CR1.＋ CD8 ＋ T cells.
[0011] As a preferred design, the predictive biomarker is CX3CR1. ＋ CD8 ＋ Dynamic changes in the proportion of T cells.
[0012] As a preferred design, the dynamic change refers to CX3CR1 ＋ CD8 ＋ Changes in the proportion of T cells before and after the use of immune checkpoint inhibitors; if the dynamic change is ≥50% or continues to increase, it indicates that the immune checkpoint inhibitor treatment has caused adverse reactions in cancer patients.
[0013] As one possible design, the tumor patients include non-small cell lung cancer, melanoma, kidney cancer, pancreatic cancer, or liver cancer.
[0014] Secondly, this application provides the application of a predictive biomarker detection reagent in the preparation of an adverse reaction detection kit, the detection kit being used to detect CX3CR1. ＋ CD8 ＋ T cell ratio.
[0015] As one possible design, the CX3CR1 ＋ CD8 ＋ T cells are derived from the peripheral blood of cancer patients.
[0016] As one possible design, the immune checkpoint inhibitor is a PD-1 inhibitor, a PD-L1 inhibitor, or a CTLA-4 inhibitor.
[0017] The detection and determination method proposed in this invention is applicable to a variety of immune checkpoint inhibitors, including but not limited to PD-1 inhibitors (such as nivolumab and pembrolizumab), PD-L1 inhibitors (such as atezolizumab and durvalumab), and CTLA-4 inhibitors (such as ipramazor). This ensures the broad clinical applicability of this invention.
[0018] As one possible design, the tumor patients include non-small cell lung cancer, melanoma, kidney cancer, pancreatic cancer, or liver cancer.
[0019] This invention is not limited to a single cancer type, but is applicable to patients with various cancers receiving immunotherapy, including non-small cell lung cancer, melanoma, kidney cancer, pancreatic cancer, and liver cancer. Because the mechanisms of irAEs (irAEs) are common, the kit of this invention can serve as a universal predictive tool across cancer types.
[0020] As one possible design, the detection kit is a flow cytometry kit, an immunofluorescence detection kit, or a single-cell RNA sequencing kit.
[0021] This invention is not limited to the conventional method of flow cytometry, but also encompasses techniques such as immunofluorescence detection and single-cell RNA sequencing. Flow cytometry can achieve high-throughput detection using standard antibody combinations (such as CD3, CD8, and CX3CR1), making it suitable for routine clinical applications; immunofluorescence detection is suitable for tissue or smear analysis; and single-cell sequencing helps to reveal the transcriptional characteristics of the cell population in depth. By encompassing different technical approaches, the scope of protection of this invention is not limited to a single platform.
[0022] Thirdly, this application provides a diagnostic reagent for predictive biomarkers or the application of such a diagnostic kit in a clinical follow-up system for monitoring adverse reactions.
[0023] This invention not only proposes a predictive biomarker for adverse reactions to immune checkpoint inhibitors, but also reserves the potential for translation into in vitro diagnostic kits or standardized clinical testing procedures. For example, commercial kits based on flow cytometry antibody combinations can be developed for direct use in hospital laboratories; they can also be embedded in clinical follow-up systems to achieve dynamic risk monitoring during treatment. Through this extension, this invention possesses both the translatability and scalability to move from research findings to clinical applications.
[0024] The beneficial effects of this invention are as follows:
[0025] Peripheral blood was collected periodically during patients' immune checkpoint inhibitor therapy, and CX3CR1 was detected using routine methods such as flow cytometry. ＋ CD8 ＋ The T-cell ratio, combined with the dynamic trend of baseline levels, can indicate risk before the onset of clinical symptoms of irAEs, thus providing a reference for early follow-up examinations, drug dosage adjustments, or combined immunosuppressant interventions. This invention not only improves the timeliness and specificity of prediction but also allows for clinically accessible implementation, facilitating its widespread application in routine laboratories. Furthermore, due to CX3CR1... ＋ CD8 ＋ T cell populations are closely related to the occurrence of irreversible adverse events (irAEs) in multiple organs such as the heart and lungs. Therefore, they can also provide a unified early risk warning indicator in multiple clinical scenarios, enhancing the ability to manage patients throughout the entire process.
[0026] 1. Enables early prediction
[0027] Unlike existing methods that rely on clinical symptoms or organ damage to indicate abnormalities, this invention can identify high-risk patients through peripheral blood testing before irAEs show obvious clinical manifestations, thereby providing clinicians with a basis for early intervention and reducing the probability of serious adverse events.
[0028] 2. Higher specificity
[0029] Existing detection total CD8 ＋ Methods using T cells or inflammatory factors often fail to distinguish between anti-tumor responses and immune responses to irAEs. This invention specifically selects CX3CR1. ＋ CD8 ＋ T cells, a subset that has been shown to be closely associated with the occurrence of multi-organ irAEs, provide higher predictive specificity.
[0030] 3. It is more operable and scalable.
[0031] The test can be performed by collecting peripheral blood from patients. The sampling is convenient and can be carried out using conventional immunological detection methods such as flow cytometry. The detection process is mature and laboratories generally have the relevant equipment. Compared with high-cost methods such as single-cell sequencing, it is easier to promote in clinical practice.
[0032] 4. Dynamic monitoring capability
[0033] This invention emphasizes assessing risk based on the dynamic trends of individual patients (the proportion of increase relative to baseline), rather than relying on a single point in time or absolute values. This not only enhances the applicability of the assessment but also allows for earlier detection of potential risks.
[0034] 5. Wide range of clinical applications
[0035] The method of this invention can be applied to a variety of immune checkpoint inhibitors (such as PD-1, PD-L1, and CTLA-4 inhibitors) and a variety of tumor types (including lung cancer, melanoma, and pancreatic cancer), and has strong universality, not limited to specific drugs or cancer types.
[0036] 6. Possesses potential for transformation and application.
[0037] This invention is not limited to scientific research testing; it can also be further developed into in vitro diagnostic kits or standardized clinical testing procedures, which can help to be incorporated into the patient treatment follow-up system and form an operable early warning tool. Attached Figure Description
[0038] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0039] Figure 1 The four types of patients in Example 1 of this application have Cd8 in their blood. + / CX3CR1 + A graph showing the correlation between the proportion of T cell populations and the severity of myocarditis;
[0040] Figure 2 These are CT scan images of 6 patients with PD-1 inhibitor-induced irae who received ICB treatment in Example 1 of this application;
[0041] Figure 3 This refers to the four stages of Cd8 in 6 PD-1 inhibitor-induced IRAE patients in Example 1 of this application. + / CX3CR1 + Plot showing the proportion of T cell populations;
[0042] Figure 4 This refers to the four stages of Cd8 in 6 PD-1 inhibitor-induced IRAE patients in Example 1 of this application. + / CX3CR1 + A bar chart showing the proportion of T cell populations. Detailed Implementation
[0043] To make the technical problems, technical solutions, and beneficial effects of this application clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0044] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0045] It should be understood that in the various embodiments of this application, the order of the above processes does not imply the order of execution. Some or all steps may be executed in parallel or sequentially. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0046] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.
[0047] The weights of the relevant components mentioned in the embodiments of this application can refer not only to the specific content of each component, but also to the proportional relationship between the weights of the components. Therefore, any scaling up or down of the content of the relevant components according to the embodiments of this application is within the scope disclosed in the embodiments of this application. Specifically, the mass described in the embodiments of this application can be a well-known unit of mass in the chemical industry, such as µg, mg, g, or kg.
[0048] The term "ICIs" is an abbreviation for "Immune Checkpoint Inhibitors," referring to immune checkpoint inhibitors; the term "irAEs" is an abbreviation for "Immune-Related Adverse Events," referring to adverse reactions.
[0049] The following description is based on specific embodiments.
[0050] Example 1
[0051] This embodiment discloses a method based on peripheral blood CX3CR1. ＋ CD8 ＋ Changes in T-cell ratio are used as a predictive biomarker for forecasting adverse reactions to immunotherapy. This method has a well-defined process and operable steps, specifically including the following steps:
[0052] 1. Sample Collection
[0053] During the treatment of patients with immune checkpoint inhibitors (such as PD-1, PD-L1 or CTLA-4 inhibitors), peripheral blood samples were collected according to the following time points: (1) Baseline samples: collected before the first dose; (2) Dynamic follow-up samples: collected before each dose and 1-2 days after each dose.
[0054] Sample volume: generally 2-5 mL, preserved in vacuum blood collection tubes containing anticoagulants (such as EDTA or heparin).
[0055] 2. Cell isolation
[0056] Peripheral blood mononuclear cells (PBMCs) were isolated from the collected peripheral blood using density gradient centrifugation with human lymphocyte separation medium.
[0057] Wash cells with PBS and adjust cell concentration to 1-2 × 10⁻⁶. 6 Cells / mL, used for subsequent staining.
[0058] 3. Immunophenotyping
[0059] CX3CR1 was detected by flow cytometry. ＋ CD8 ＋ The T cell ratio is determined through the following steps:
[0060] (1) Antibody selection: Commonly used markers include CD3 (T cell marker), CD8 (cytotoxic T cell marker), and CX3CR1 (chemokine receptor).
[0061] (2) Staining procedure: Add PBMC suspension to antibody mixture and incubate in the dark for 30 minutes; wash with PBS and resuspend;
[0062] (3) Measurement: CD33 cells were detected using flow cytometry and selected sequentially. ＋ T cells → CD8 ＋ T cells → Statistical analysis of CX3CR1 ＋ Subgroup proportions;
[0063] (4) Data analysis: CX3CR1 was calculated using FlowJo software. ＋ CD8 ＋ T cells in total CD8 ＋ The percentage of T cells.
[0064] 4. Risk Assessment
[0065] The dynamic detection results were compared with the baseline level, where the baseline level refers to the "CX3CR1" data collected before the first dose. ＋ CD8 ＋ T cells in total CD8 ＋ Percentage in T cells:
[0066] Risk-free / Low-risk: CX3CR1 ＋ CD8 ＋ The proportion of T cells did not change significantly from baseline.
[0067] High-risk warning: CX3CR1 ＋ CD8 ＋ The proportion of T cells increased by ≥50% from baseline or continued to increase;
[0068] Clinical application: Once a high risk is indicated, clinicians should be advised to conduct functional examinations of key organs such as the heart, lungs, and intestines, and to assess whether to adjust the medication regimen or intervene in advance.
[0069] 5. Clinical Application Scenarios
[0070] Personalized treatment monitoring: By using peripheral blood test results, the risk of patients developing irAEs is dynamically assessed to guide whether to continue, reduce, or suspend ICI treatment;
[0071] Early warning mechanism: alerting potentially high-risk individuals before patients develop clinical symptoms, thus reducing the incidence of serious irreversible adverse events (irAEs);
[0072] Adjunctive medication options: In high-risk patients, provide a reference for the use of immunosuppressants (such as selective JAK1 inhibitors) or enhanced monitoring.
[0073] The process forms a complete closed loop from "sample collection → cell isolation → immunophenotyping → risk assessment → clinical application", which has clear feasibility and reproducibility.
[0074] This embodiment also discloses the use of the above-described prediction method to detect myocarditis patients, as detailed below:
[0075] We analyzed the public single-cell transcriptome data (GSE228595 dataset) from blood biopsies of patients with myocarditis. This dataset included four patient categories: pre-ICB (n=7), on-ICB (n=4), pre-corticosteroid (n=17), and post-corticosteroid (n=27) patients with ir-related myocarditis. The results are as follows: Figure 1 As shown, Cd8 was found in the blood. + In cells, Cd8 + / CX3CR1 + The proportion of T-cell populations was correlated with the severity of myocarditis, and the level in the group before corticosteroid treatment was much higher than in the other three groups.
[0076] This embodiment also discloses CT scans of six patients with PD-1 inhibitor-induced IRB-induced irae and cancer patients receiving ICB therapy. The results are as follows: Figure 2 As shown, CT images before and after four doses of ICB treatment revealed homogeneous consolidation with surrounding ground-glass opacities (GGO) in the right lung of three patients (red arrows), consistent with IRAE-associated pneumonia. Three other patients who received four doses of ICB treatment showed no signs of pneumonia on CT images; their lung parenchyma was normal, without consolidation or GGO.
[0077] The detection method disclosed in this embodiment was used to test six patients with irae induced by PD-1 inhibitor blockade, as follows:
[0078] Blood biopsies were collected, including baseline and post-dosage samples. Flow cytometry was used to monitor dynamic changes in CTLirAE-II in patient blood samples during ICB treatment (n=6). Representative flow maps were generated for each treatment point, and CD8 was quantified. + CX3CR1 + The percentage of T cells, results as follows Figure 3 and Figure 4 As shown, the test results indicated that prior to the outbreak of irAEs, the CD8+ level in the patient's blood was... + / CX3CR1 + The T cell population showed a gradual increasing trend. During IRAE outbreaks, CD8... + / CX3CR1 + T cell levels plateaued significantly compared to each corresponding baseline (triangular stars in the graph indicate patients experiencing irae-associated pneumonia). In contrast, non-irae patients had significantly higher CD8+ levels in their blood. + / CX3CR1 + The T cell population did not change significantly, therefore the results indicate that CD8 + / CX3CR1 + T cell populations can serve as diagnostic biomarkers for monitoring and even predicting irae during immunotherapy.
[0079] Will Figure 2 and Figure 3 , Figure 4 The comparison showed that this detection method was feasible in 6 patients with PD-1 blockade-induced irae, which also verified that the kits obtained based on this detection method were feasible.
[0080] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A predictive biomarker for adverse reactions to immune checkpoint inhibitor therapy in cancer patients, characterized in that, The predictive biomarker is CX3CR1. ＋ CD8 ＋ T cells.
2. The predictive biomarker according to claim 1, characterized in that, The predictive biomarker is CX3CR1. ＋ CD8 ＋ Dynamic changes in the proportion of T cells.
3. The predictive biomarker according to claim 2, characterized in that, The dynamic change refers to CX3CR1 ＋ CD8 ＋ Changes in the proportion of T cells before and after the use of immune checkpoint inhibitors; if the dynamic change is ≥50% or continues to increase, it indicates that the immune checkpoint inhibitor treatment has caused adverse reactions in cancer patients.
4. The predictive biomarker according to claim 1, characterized in that, The cancer patients include those with non-small cell lung cancer, melanoma, kidney cancer, pancreatic cancer, or liver cancer.
5. The use of a detection reagent for the predictive biomarker according to any one of claims 1-4 in the preparation of an adverse reaction detection kit, wherein the detection kit is used to detect CX3CR1. ＋ CD8 ＋ T cell ratio.
6. The application according to claim 5, characterized in that, The CX3CR1 ＋ CD8 ＋ T cells are derived from the peripheral blood of cancer patients.
7. The application according to claim 5, characterized in that, The immune checkpoint inhibitor is a PD-1 inhibitor, a PD-L1 inhibitor, or a CTLA-4 inhibitor.
8. The application according to claim 5, characterized in that, The cancer patients include those with non-small cell lung cancer, melanoma, kidney cancer, pancreatic cancer, or liver cancer.
9. The application according to claim 5, characterized in that, The detection kit is a flow cytometry kit, an immunofluorescence detection kit, or a single-cell RNA sequencing kit.
10. The application of a detection reagent for a predictive biomarker as described in any one of claims 1-4 or a detection kit related to the application described in any one of claims 5-9 in a clinical follow-up system for monitoring adverse reactions.