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A method, kit and application for lymphoma prognosis judgment

A technology for prognosis judgment and lymphoma, applied in data processing applications, genomics, instruments, etc., can solve the problems of tumor suppressor genes losing their tumor suppressor effect, poor prognosis of patients, and low detection ratio, so as to reduce adverse effects and save treatment Costs, effects of reducing overtreatment

Active Publication Date: 2022-05-20
RUIJIN HOSPITAL AFFILIATED TO SHANGHAI JIAO TONG UNIV SCHOOL OF MEDICINE +1
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

In 2018, R. Schmitz and B. Chapuy respectively conducted a global multi-center clinical study on the molecular pathology of DLBCL, studied hundreds of related genes in hundreds of patients, and identified 4 genes based on the characteristics of gene changes. The molecular subtypes of DLBCL class and class 5 not only explained the pathogenic process of DLBCL from the perspective of molecular biology, but also found that changes in some driver genes may be related to the prognosis of DLBCL, such as: CD79A / B, CARD11, TNFAIP3 activate BCR -NF-KB signaling pathway, mutations in TP53 and PTEN make tumor suppressor genes lose their tumor suppressor effect, which will accelerate the progression of the disease, and patients with such mutations often have a poor prognosis
[0006] Due to the differences in the population, the model algorithm established with Western data is not applicable to the Chinese population, and the detection rate is very low

Method used

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  • A method, kit and application for lymphoma prognosis judgment
  • A method, kit and application for lymphoma prognosis judgment
  • A method, kit and application for lymphoma prognosis judgment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0090] A kit for lymphoma prognosis judgment, comprising the following components: component A, component B, component C, and component D;

[0091] Component A is a kit for library preparation and hybrid capture of lymphoma prognosis-related genes. Lymphoma prognosis-related genes include: CD79B gene, CREBBP gene, EP300 gene, KMT2C gene, KMT2D gene, MYD88 gene, SOCS1 gene, CD70 gene, GNA13 gene, NOTCH1 gene, TNFAIP3 gene, BTG1 gene, BTG2 gene, STAT3 gene, PIM1 gene, DTX1 gene and TP53 gene. Component A can specifically use IDT’s library preparation reagents, hybridization reagents and hybridization purification reagents, wherein the library preparation reagents include end repairing and polyA buffer, end repairing and polyA enzyme solution, ligation buffer, DNA ligase solution, UDI linker , 2X HiFi PCR buffer, amplification primer mixture, process water, TE mixture, purified magnetic beads, hybridization reagents include 2X hybridization buffer, hybridization enhancement buffe...

Embodiment 2

[0108] 1. Patient selection

[0109] 1. Experimental group: 100 patients who underwent whole genome / whole exome / targeted sequencing and obtained mutation information were selected as the experimental group.

[0110] 2. Verification group: Retrospectively select 40 patients with newly diagnosed diffuse large B-cell lymphoma who were treated in Shanghai Ruijin Hospital and used the R-CHOP standard measurement plan as the verification group.

[0111] 2. Initial Gene Selection Conditions

[0112] 82 genes were selected, and genes with at least 3 or more mutations in all sequenced patients of NHL001 were screened for calculation.

[0113] 3. Build a Prognostic Model

[0114] 1. Logistic regression is performed on the IPI International Prognostic Index and each gene mutation, and the factor with the largest P-value (P-value) is gradually removed.

[0115] 2. The modeling results are shown in Table 2:

[0116] Table 2

[0117] prognostic factor prognostic factor ...

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Abstract

The invention relates to the field of gene mutation detection, in particular, to a method, kit and application for judging the prognosis of lymphoma. The present invention calculates the prognostic risk value of patients with IPI classification as medium and high risk through data analysis, assists in distinguishing high-risk and low-risk risk groups, can effectively distinguish potential non-recurrence patients whose IPI classification cannot be determined, and reduces excessive treatment of such patients Therefore, it can reduce the adverse effects of patients, help to save the cost of treatment, and improve the living conditions of patients.

Description

technical field [0001] The invention relates to the field of gene mutation detection, in particular to a method, kit and application for lymphoma prognosis judgment. Background technique [0002] Lymphoma is the hematological malignancy with the highest incidence rate in my country, and it has the characteristics of various types and complex classification. It ranks among the top ten in the statistics of cancer incidence in our country. As a highly heterogeneous disease, the traditional classification of lymphoma mainly relies on pathological morphology, cytogenetics, and single gene mutation detection methods to judge the source and malignancy of lymphoma cells. In the existing understanding of lymphoma and multi-parameter classification methods, it can be roughly divided into two categories: Hodgkin's Lymphoma (HL) and Non-Hodgkin's Lymphoma (NHL). , which can be further divided into different categories such as B-cell non-Hodgkin's lymphoma or T-cell non-Hodgkin's lymph...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16B20/50G16B20/30G06Q10/06
CPCG16B20/50G16B20/30G06Q10/06393
Inventor 赵维莅许彭鹏付迪王黎俞浩刘以哲熊慧
Owner RUIJIN HOSPITAL AFFILIATED TO SHANGHAI JIAO TONG UNIV SCHOOL OF MEDICINE
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