Molecular classification and application of multiple myeloma

A technology for patients with multiple myeloma and tumors, applied in the direction of instruments, biochemical equipment and methods, biostatistics, etc., can solve the problem that the plasma cell development process cannot be related, the cause of multiple myeloma has not been elucidated, and cannot be predicted Response to medication, etc.

Active Publication Date: 2020-06-12
北京瑞牧西康医疗器械有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the above molecular typing and expression signatures are not predictive of drug response, nor can they be correlated with plasma cell development, and the association between the genes used for molecular typing and the etiology of multiple myeloma has not been elucidated

Method used

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  • Molecular classification and application of multiple myeloma
  • Molecular classification and application of multiple myeloma
  • Molecular classification and application of multiple myeloma

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0067] Example 1, Screening of Molecular Diagnostic Markers for Multiple Myeloma and Implementation of Molecular Typing

[0068] Using the multiple myeloma expression data set GSE2658 provided by the NCBI GEO public database, 87 genes co-expressed with MCL1 were obtained through Pearson correlation analysis, and based on this, 46 genes with low expression of MCL1 were identified. -M genes enriched in multiple myeloma samples. In order to perform molecular typing more stably, 36 of the 133 genes with low classification efficiency were further screened out, and finally 97 classified genes with stable differential expression and relatively high abundance were retained.

[0069] The names of the 97 genes are as follows:

[0070] ACBD3, ADAR, ADSS, ALDH2, ANP32E, ANXA2, ATF3, ATP8B2, CACYBP, CAPN2, CCND1, CCT3, CDC42SE1, CERS2, CHSY3, CLIC1, CLMN, COPA, CSNK1G3, DAP3, DENND1B, ENSA, EPRS, EPSTI1, EVL, FAM13A, FAM49A, FLAD1, FRZB, GLRX2, HAX1, HDGF, HLA-A, HLA-B, HLA-C, HLA-F, HLA...

Embodiment 2

[0088] Example 2, Application of Bayesian Classifier for Multiple Myeloma in Predicting Patient Prognosis and Survival Rate

[0089] 1. Database GSE2658

[0090] According to the expression data of 97 classified genes of 551 cases of multiple myeloma patient samples (detection before treatment) in the GSE2658 database, the multiple myeloma Bayesian classifier obtained in Example 1 was used to classify the 551 cases of samples, and 249 samples were obtained. cases of MCL1-M-High subtype multiple myeloma and 302 cases of MCL1-M-Low subtype multiple myeloma.

[0091] 551 sample patients were followed up for 72 months after treatment, and survival analysis (K-M analysis and cox regression analysis) was carried out according to the follow-up results. The results are as follows: Figure 4 As shown, it can be seen that the two multiple myeloma subtypes, MCL1-M-High and MCL1-M-Low, have significantly different prognosis, and the overall survival rate of the MCL1-M-High subtype is hig...

Embodiment 3

[0100] Example 3. Molecular diagnostic markers and typing of multiple myeloma in predicting whether the patient to be tested can be treated with bortezomib

[0101] The GSE19784 multiple myeloma expression data set comes from a phase III drug clinical trial (HOVON-65 / GMMG-HD4), with the patient's drug treatment plan. In this trial, patients were randomly divided into two groups to receive two drug combinations of VAD (155 cases) and PAD (148 cases). The difference between the two is that the PAD program added bortezomib (trade name: Velcade). The gene expression data of the enrolled patients were collected before treatment.

[0102] The patients were stratified according to the above MCL1-M molecular classification, and then divided into MCL1-M-High (PAD 51 cases, VAD 56 cases) and MCL1-M-Low (PAD 104 cases, VAD 92 cases) subgroups. The survival analysis (K-M analysis and cox regression analysis) was carried out in groups according to the drug treatment regimen.

[0103] The...

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Abstract

The invention discloses a multiple myeloma molecular subtype and application. The product provided by the invention comprises a substance for obtaining or detecting 97 gene expressions in a multiple myeloma cancer patient to be detected. The product further comprises equipment for operating a multiple myeloma Bayes classifier. In the invention, a gene module (MCL1-M for short) co-expressed with anMCL1 gene is identified, and the gene module is applied to divide multiple myeloma into two main subtypes, namely an MCL-M-High subtype and an MCL-M-Low subtype. The two subtypes have prognosis and genetics characteristics which are significantly different.

Description

technical field [0001] The invention belongs to the field of biotechnology, and in particular relates to molecular classification and application of multiple myeloma. Background technique [0002] Multiple myeloma (Multiple Myeloma, MM) is a tumor caused by the malignant proliferation of plasma cells, and is the second most common hematological tumor, with an incidence rate of 1-2 / 100,000 people in China. Multiple myeloma is prone to occur in the elderly population over the age of 60. With the aggravation of the aging degree in our country, its incidence rate is increasing year by year, and it has become a disease that seriously threatens the health of the elderly. Multiple myeloma is typically characterized by a large number of abnormally proliferating plasma cells in the bone marrow that secrete an abnormal immunoglobulin or immunoglobulin fragment, the M protein. [0003] Survival in multiple myeloma has improved markedly with the use of proteasome inhibitors such as bor...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): C12Q1/6886G16B40/00
CPCC12Q1/6886C12Q2600/118C12Q2600/158G16B40/00
Inventor 樊小龙阿亚兹·阿里·萨莫李玖一卢绪章
Owner 北京瑞牧西康医疗器械有限公司
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