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CN-121978334-A - Group of immune combined chemotherapy severe adverse reaction prediction markers and application thereof

CN121978334ACN 121978334 ACN121978334 ACN 121978334ACN-121978334-A

Abstract

The invention belongs to the technical field of biological medicines, and particularly relates to a group of wide-period small cell lung cancer immune combined chemotherapy severe adverse reaction prediction markers and application thereof. The biomarker combination sampling is simple and convenient, and biopsy tissues do not need to be provided. The total T cell percentage CD3 + /CD45 + , the T cell toxicity cell percentage CD3 + CD8 + /CD45 +, and the combination of the two can predict that the ICI combined chemotherapy treatment of patients with extensive stage small cell lung cancer generate no less than 3 grade treatment related adverse reactions, and the combined prediction efficiency is superior to that of a single index. In the training set, the area under the AUC curve of the combined prediction model is 0.852, the optimal Cut-off value is 0.39, the sensitivity is 87.5%, and the specificity is 83.3%. Independent external verification was applied in the constructed prediction model with AUC of 0.847, model sensitivity of 85.2% and specificity of 73.9% for the combined prediction model. The invention has practicability and provides guidance of accurate treatment for clinical medicine.

Inventors

  • WEI SONG
  • LIU ZHE
  • GUO LILI

Assignees

  • 首都医科大学附属北京胸科医院

Dates

Publication Date
20260505
Application Date
20251229

Claims (8)

  1. 1. The application of a group of markers in the preparation of a reagent for predicting that a broad-phase small cell lung cancer patient subjected to ICI combined chemotherapy is subjected to grade 3 or more treatment-related adverse reaction, wherein the markers are selected from the total T cell percentage CD3 + /CD45 + and/or the T cell toxic cell percentage CD3 + CD8 + /CD45 + .
  2. 2. The use of claim 1, wherein the patient experiences a grade 3 or more severe adverse reaction when the marker is total T cell percentage CD3 + /CD45 + and the percentage is greater than 72.25%, wherein the patient experiences a grade 3 or more severe adverse reaction when the marker is T cytotoxic cell percentage CD3 + CD8 + /CD45 + and the percentage is greater than 28.8%, wherein the patient experiences a grade 3 or more severe adverse reaction when the marker is a combination of total T cell percentage CD3 + /CD45 + and T cytotoxic cell percentage CD3 + CD8 + /CD45 + , wherein the P value is calculated using a regression model, and wherein the P is greater than 0.39, and wherein the formula is as follows: Logit（P）= -9.077 + 0.104 * （CD3 + /CD45 + ）+ 0.063 *（CD3 + CD8 + /CD45 + ）; wherein the percent total T cells (CD 3 + /CD45 + ), percent T cytotoxic cells (CD 3 + CD4 + /CD45 + ) are in%.
  3. 3. A set of markers for predicting ≡3 grade treatment-related adverse reactions in patients with extensive stage small cell lung cancer treated by ICI combination chemotherapy, wherein the markers are selected from the group consisting of total T cell percentage CD3 + /CD45 + and/or T cell toxic cell percentage CD3 + CD8 + /CD45 + .
  4. 4. The set of markers of claim 3, wherein the patient experiences a grade 3 or greater severe adverse reaction when the marker is total T cell percentage CD3 + /CD45 + and the percentage is greater than 72.25%, wherein the patient experiences a grade 3 or greater severe adverse reaction when the marker is T cell percentage CD3 + CD8 + /CD45 + and the percentage is greater than 28.8%, wherein the patient experiences a grade 3 or greater severe adverse reaction when the marker is a combination of total T cell percentage CD3 + /CD45 + and T cell percentage CD3 + CD8 + /CD45 + , wherein the P value is calculated using a regression model, and wherein the P is greater than 0.39, and wherein the formula is as follows: Logit（P）= -9.077 + 0.104 * （CD3 + /CD45 + ）+ 0.063 *（CD3 + CD8 + /CD45 + ）; wherein the percent total T cells (CD 3 + /CD45 + ), percent T cytotoxic cells (CD 3 + CD4 + /CD45 + ) are in%.
  5. 5. A kit for predicting ≡3 grade treatment-related adverse reactions in patients with broad-phase small cell lung cancer treated by ICI-chemotherapy, said kit comprising reagents for detecting the expression levels of a set of markers according to claim 3, said markers being selected from the group consisting of total T cell percentage CD3 + /CD45 + and/or T cytotoxic cell percentage CD3 + CD8 + /CD45 + .
  6. 6. The kit of claim 5, wherein the patient experiences a grade 3 or more severe adverse reaction when the marker is total T cell percentage CD3 + /CD45 + and the percentage is greater than 72.25%, wherein the patient experiences a grade 3 or more severe adverse reaction when the marker is T cytotoxic cell percentage CD3 + CD8 + /CD45 + and the percentage is greater than 28.8%, wherein the patient experiences a grade 3 or more severe adverse reaction when the marker is a combination of total T cell percentage CD3 + /CD45 + and T cytotoxic cell percentage CD3 + CD8 + /CD45 + , wherein the P value is calculated using a regression model, and wherein the P is greater than 0.39, and wherein the formula is as follows: Logit（P）= -9.077 + 0.104 * （CD3 + /CD45 + ）+ 0.063 *（CD3 + CD8 + /CD45 + ）; wherein the percent total T cells (CD 3 + /CD45 + ), percent T cytotoxic cells (CD 3 + CD4 + /CD45 + ) are in%.
  7. 7. The kit of claim 5, wherein the kit is selected from the group consisting of ELISA detection kit, colloidal gold detection kit and/or flow detection kit.
  8. 8. The kit of claim 5, wherein the kit diagnosis method comprises a direct method, an indirect method, a double antibody sandwich method and a competition method.

Description

Group of immune combined chemotherapy severe adverse reaction prediction markers and application thereof Technical Field The invention belongs to the technical field of biological medicines, and particularly relates to a group of wide-period small cell lung cancer immune combined chemotherapy severe adverse reaction prediction markers and application thereof. Background Small cell Lung Cancer (SMALL CELL Lung Cancer, SCLC) is the second most common breast malignancy, accounting for 10-15% of all Lung cancers, and has the characteristics of high invasiveness, rapid proliferation, easy metastasis and the like. Wherein the content of the extensive stage small cell lung cancer (extensive-STAGE SMALL CELL lung cancer, ES-SCLC) is up to 60% -70%. The tumor has the obvious characteristics [1] of rapid growth, strong transfer capability and extremely poor clinical prognosis. In recent years, based on two phase III clinical studies IMpower and CASPIAN, the survival benefit of immune combination chemotherapy was fully demonstrated, raising the median total survival (OS) of ES-SCLC from 10.3-10.5 months to 12.3-12.9 months [2-4] in the chemotherapeutic group. The chemotherapy scheme of the inhibitor of programmed cell death factor ligand 1 (programmed CELL DEATH LIGAND, PD-L1) which is represented by the Ab Li Zhushan antibody and the Duvali You Shan antibody and combined with platinum-etoposide becomes a new standard of first-line treatment, and great progress is brought to ES-SCLC treatment. However, compared to non-small cell lung cancer patients, SCLC has "immune desert" phenotypic characteristics such as insufficient immune cell infiltration, low PD-L1 expression levels, and defective antigen presentation, making tumor cells more susceptible to evasion from monitoring and attack by the immune system of the body. Leading to a more limited degree of benefit in ES-SCLC patients receiving immune checkpoint inhibitor (immune checkpoint inhibitor, ICI) therapy, a shorter duration of response, survival benefits that usually develop after 6 months of treatment, and significant heterogeneity （PAZ-ARES L, CHEN Y, REINMUTH N, et al. Durvalumab, with or without tremelimumab, plus platinum-etoposide in first-line treatment of extensive-stage small-cell lung cancer: 3-year overall survival update from CASPIAN [J]. ESMO Open, 2022, 7(2): 100408.）. in clinical response, while benefiting from immunotherapy, the treatment is accompanied by non-negligible immune-related toxicity, and serious life-threatening adverse events such as severe liver injury, myocarditis, immune pneumonia and the like occur after a part of patients are treated by only one ICI. Therefore, there is a great clinical need to develop effective biomarkers that can predict prognosis of immunotherapy and occurrence of adverse events before treatment to promote accurate and personalized treatment of small cell lung cancer. While immune combination chemotherapy exerts anti-tumor effects, the resulting treatment-related adverse reactions have become a key factor affecting patient treatment tolerance and quality of life. According to clinical data, the incidence rate of any grade treatment-related adverse reaction in ES-SCLC patients receiving immune combination chemotherapy is up to 96.3%, wherein the incidence rate of serious adverse reaction of grade 3 or more is up to 58.8%, and the adverse reaction mainly comprises blood system toxicity such as neutropenia (52.5%), thrombocytopenia (21.3%), anemia (7.5%), and non-blood system toxicity such as digestive tract reaction, myocarditis, liver enzyme abnormality, and the like. More vigilantly, part of serious adverse reactions can endanger life, 1 patient dies due to severe liver injury and myocarditis, and 6.3% of patients are forced to pause treatment due to adverse reactions, so that the anti-tumor treatment process is interrupted, and the medical burden and death risk of the patients are obviously increased. Therefore, how to accurately identify patients with high serious adverse reaction risks before treatment and take intervention measures in advance becomes a core problem to be solved in clinical application of ES-SCLC immune combined chemotherapy. Previous studies have attempted to explore the association of a portion of biomarkers with adverse effects of immunotherapy, but have not yet formed a uniform, effective predictive system. For example, studies suggest that the indexes of inflammation such as neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) may be related to immune-related toxicity, but these indexes are easily interfered by various factors such as infection and anemia, and have insufficient stability and specificity, while the PD-L1 expression level, tumor mutation load (TMB) and other tumor-related markers are mainly focused on the prediction of therapeutic effect, the prediction value of adverse reaction is not yet confirmed （HORN L, MANSFIELD A S, SZCZESNA A, et al. First-