Novel comprehensive risk scoring method for multiple myeloma

Abstract

The invention provides a comprehensive risk scoring method for multiple myeloma, comprising the following steps: S1, obtaining a gene expression profile GSE24080 of an MM patient from a GEO database,and pre-treating genes in the gene expression profile GSE24080 to obtain the first 25% of the 5413 genes with the largest variance of expression value; S2, subjecting the 5413 genes to WGCNA gene co-expression network analysis to identify co-expressed functional modules; S3, evaluating the correlation between the functional modules and clinical information through Pearson correlation test to determine the most significant modules; S4, performing univariate survival analysis on the genes in the most significant modules by using a Cox proportional hazard model, and screening out a ten-gene scoring model composed of the 10 best genes through LASSO regression; and S5, setting the rule that each factor scores 1 point when the ten-gene scoring model or serum [beta]2M or LDH is higher than a cut-off value and otherwise 0, and establishing a comprehensive risk scoring system.

Description

technical field [0001] The invention relates to a multiple myeloma-based comprehensive risk scoring method. Background technique [0002] Multiple myeloma (MM) is a malignant plasma cell disease in which tumor cells originate from plasma cells in the bone marrow, which are cells that develop to the final functional stage of B lymphocytes. At present, the heterogeneity of multiple myeloma has been paid more and more attention. However, there is no effective and simple comprehensive risk scoring method for MM in the world. Contents of the invention [0003] The invention provides a multiple myeloma comprehensive risk scoring method, which can effectively solve the above problems. [0004] The present invention is achieved like this: [0005] A multiple myeloma comprehensive risk scoring method, comprising the following steps: [0006] S1, obtaining the gene expression profile GSE24080 of MM patients from the GEO database, and preprocessing the genes in the gene expression...

AI Technical Summary

Problems solved by technology

At present, the heterogeneity of multiple myeloma has been paid more and more attention. However, there is no effective and simple comprehensive risk scoring method for MM in the world.

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