Novel Gene Signature Reveals Prognostic Model in Acute Myeloid Leukemia.

ABSTRACT:

Background

Acute myeloid leukemia (AML) is a clonal malignant disease with poor prognosis and a low overall survival rate. Although many studies on the treatment and detection of AML have been conducted, the molecular mechanism of AML development and progression has not been fully elucidated. The present study was designed to pursuit the molecular mechanism of AML using a comprehensive bioinformatics analysis, and build an applicable model to predict the survival probability of AML patients in clinical use.

Methods

To simplify the complicated regulatory networks, we performed the gene co-expression and PPI network based on WGCNA and STRING database using modularization design. Two machine learning methods, A least absolute shrinkage and selector operation (LASSO) algorithm a

SUBMITTER: Qu Y 

PROVIDER: S-EPMC7655922 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature