Construction of a solid Cox model for AML patients based on multiomics bioinformatic analysis

BioRxiv : the Preprint Server for Biology
Lei GaoY. Su

Abstract

Acute myeloid leukemia (AML) is a highly heterogeneous hematological malignancy. The bone marrow (BM) microenvironment in AML plays an important role in leukemogenesis, drug resistance and leukemia relapse. In this study, we aimed to identify reliable immune-related biomarkers for AML prognosis by multiomics analysis. We obtained expression profiles from The Cancer Genome Atlas (TCGA) database and constructed a LASSO-Cox regression model to predict the prognosis of AML using multiomics bioinformatic analysis data. This was followed by independent validation of the model in the GSE106291 (n=251), GSE12417 (n=163) and GSE37642 (n=137) datasets and mutated genes in clinical samples for predicting overall survival (OS). Molecular docking was performed to predict the most optimal ligands to these hub genes. The single-cell RNA sequence dataset GSE116256 was used to clarify the expression of the hub genes in different immune cell types. According to their significant differences in immune gene signatures and survival trends, we concluded that the immune infiltration-lacking subtype (IL type) is associated with better prognosis than the immune infiltration-rich subtype (IR type). Using the LASSO model, we built a classifier based on 5...Continue Reading

Datasets Mentioned

BETA
GSE116256
GSE37642
GPL18460
GSE106291

Methods Mentioned

BETA
scRNA sequencing
single-cell sequencing
Methylation450 Bead Array

Software Mentioned

- CDS
DIANO TOOLS
AutoDock Vina
SingleR
methylmix
GO
Cytoscape
microT
MethylCor
Discovery Studio Visualizer

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