Markers and methods for predicting primary drug resistance of immune checkpoint inhibitor therapy

A technology of immune checkpoints and inhibitors, applied in the biological field, can solve the problems of no unified conclusion on TMB threshold, lack of standard methods for TMB, and different products and algorithms

Pending Publication Date: 2022-07-12
北京大学肿瘤医院 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Although TMB has been approved by the US FDA as a biomarker for immunotherapy in patients with pan-solid tumors in 2020, its approval has caused a lot of controversy. There is still a lack of standard methods for TMB detection, and the products and algorithms of different testing institutions are different. The threshold of TMB There is no unified conclusion

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  • Markers and methods for predicting primary drug resistance of immune checkpoint inhibitor therapy
  • Markers and methods for predicting primary drug resistance of immune checkpoint inhibitor therapy
  • Markers and methods for predicting primary drug resistance of immune checkpoint inhibitor therapy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0120] Example 1. Characterization of Discovery Cohort dMMR / MSI-H Gastrointestinal Tumor Patients

[0121] Table 1. Basic characteristics of patients with dMMR / MSI-H gastrointestinal tumors in the discovery cohort

[0122]

[0123]

[0124] dMMR: mismatch repair deficiency; MSI-H: high microsatellite instability; GI: gastrointestinal; ICI: immune checkpoint inhibitor; ECOG PS: Eastern Cooperative Oncology Group performance status; IC: intestinal cancer; GC: gastric cancer; PD-1: programmed death 1; PD-L1: programmed death ligand 1; HER2: human epidermal growth factor receptor 2; CTLA4: cytotoxic T lymphocyte antigen-4; TPS: tumor proportion score; LS: Lin odd syndrome.

[0125] Most patients (62 / 65, 95.38%) had good physical condition (ECOG 0 or 1) and received at least one systemic therapy in the past (54 / 65, 83.08%). 1 patient was HER2 positive (1 / 53, 1.89%) and 8 patients (8 / 49, 16.33%) had PD-L1 TPS ≥ 1%. 14 cases (21.54%) were diagnosed with Lynch syndrome (LS). ...

Embodiment 2

[0126] Example 2. Screening of genes that can predict immunotherapy resistance in dMMR / MSI-H gastrointestinal cancer patients

[0127] Screening of primary drug resistance predictive genes by a three-step approach:

[0128] Step 1: Screening genomic mutations significantly associated with PFS by univariate Cox proportional hazards regression model (Pfigure 1 A).

[0129] Step 2: Compare the differences in the mutation frequencies of the three genes screened in the first step in the ICI-resistant group and the ICI-sensitive group, identify genes with significant mutation frequencies (Pfigure 1 B).

[0130] Step 3: Gene mutations need to meet the mutation frequency ≥5% criterion to ensure that the proportional difference between the two groups is not caused by randomly occurring mutations. Mutation frequencies of both AKT1 and CDH1 were ≥5%. Further analysis of the AKT1 and CDH1 gene mutation sites found that the gene mutation sites are scattered in the full length of AKT1 and...

Embodiment 3

[0132] Example 3. Construction of a combined AKT1 and CDH1 mutation model to predict immunotherapy resistance in dMMR / MSI-H gastrointestinal cancer patients

[0133] In the discovery cohort, there were 5 patients with AKT1-mut (mut:mutation), 6 patients with CDH1-mut, and 1 patient with co-mutation of AKT1 and CDH1.

[0134] Given that the following two conditions were met: 1. Multivariate Cox regression analysis showed that AKT1 and CDH1 were independent predictors of PFS (P image 3 A); 2, Multivariate logistic regression analysis showed that AKT1 and CDH1 were independently associated with primary drug resistance (P image 3 B-D). To further evaluate the predictive value of Iopred for the efficacy of immunotherapy, we performed a univariate Cox regression analysis between Iopred and clinicopathological parameters, and the results showed that Iopred was the only predictor of PFS in patients with dMMR / MSI-H gastrointestinal tumors treated with ICI (Table 1). 2). IOpred mutatio...

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Abstract

The present invention provides methods capable of predicting drug resistance of a tumor patient to immune checkpoint inhibitor therapy. The invention further provides drug-resistant genes AKT1 and/or CDH1, mRNA, cDNA or protein of the drug-resistant genes AKT1 and/or CDH1 and a detection reagent of the drug-resistant genes. The drug-resistant gene and the detection reagent thereof can be used for predicting the drug resistance of tumor patients to immunotherapy and the sensitivity of targeted therapy combined with or not combined with immunotherapy. The AKT1 and/or CDH1 gene mutation can be used as a biomarker for predicting the primary drug resistance of the immune checkpoint inhibitor therapy in dMMR/MSI-H gastrointestinal tumor patients, so that drug-resistant people can be accurately predicted, blind drug use is avoided, and the treatment economy of the immune checkpoint inhibitor therapy is improved.

Description

technical field [0001] The present invention relates to the field of biotechnology. More specifically, the present invention relates to a biomarker that can be used to predict primary resistance to immune checkpoint 321 formulation therapy in dMMR / MSI-H gastrointestinal cancer patients, and uses and methods of use thereof. Background technique [0002] In recent years, immune-checkpoint inhibitor therapy (ICI, including anti-PD-1 / PD-L1 / CTLA-4 inhibitors) has become a widely used treatment option in tumor treatment. In 2017, the US FDA approved dMMR (DNA mismatch repair-deficient) / MSI-H (microsatelliteinstability-high, high microsatellite instability) as a biomarker for immunotherapy in patients with pan-solid tumors. Gastrointestinal tumors, including gastric and colorectal cancers, are among the most common tumors in dMMR / MSI-H pan-solid tumors. The clinical efficacy of ICI for advanced or metastatic dMMR / MSI-H gastrointestinal tumors has been fully validated in multiple ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/6886G01N33/574
CPCC12Q1/6886G01N33/574G01N33/57446C12Q2600/156C12Q2600/106
Inventor 沈琳李健王正航张琪齐长松白跃宗陈慧赵飞龙蔡金萍陈世清赵晓忱熊磊
Owner 北京大学肿瘤医院
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