Dataset Information

Expression of a specific extracellular matrix signature is a favorable prognostic factor in acute myeloid leukemia.

ABSTRACT: Relapse of acute myeloid leukemia (AML) is still dramatically frequent, imposing the need for early markers to quantify such risk. Recent evidence point to a prominent role for extracellular matrix (ECM) in AML, but its prognostic value has not yet been investigated. Here we have investigated whether the expression of a 15-ECM gene signature could be applied to clinical AML research evaluating a retrospective cohort of 61 AML patients and 12 healthy donors. Results show that patients whose ECM signature expression is at least twice as that of healthy donors have considerably longer relapse-free survival, with further stage-specific therapy outcomes.

SUBMITTER: Izzi V

PROVIDER: S-EPMC5735295 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Expression of a specific extracellular matrix signature is a favorable prognostic factor in acute myeloid leukemia.

Izzi Valerio V Lakkala Juho J Devarajan Raman R Savolainen Eeva-Riitta ER Koistinen Pirjo P Heljasvaara Ritva R Pihlajaniemi Taina T

Leukemia research reports 20171213

Relapse of acute myeloid leukemia (AML) is still dramatically frequent, imposing the need for early markers to quantify such risk. Recent evidence point to a prominent role for extracellular matrix (ECM) in AML, but its prognostic value has not yet been investigated. Here we have investigated whether the expression of a 15-ECM gene signature could be applied to clinical AML research evaluating a retrospective cohort of 61 AML patients and 12 healthy donors. Results show that patients whose ECM s ...[more]

PMID: 29270355

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Project description:BackgroundAcute 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.MethodsTo 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 and support vector machine-recursive feature elimination (SVM-RFE), were used to filter the common hub genes by five-fold cross-validation. The candidate hub genes were used to build the predictive model of AML by the cox-proportional hazards analysis, and validated in The Cancer Genome Atlas (TCGA) cohort and ohsu cohort, which were reliable in the experimental verification by qRT-PCR and western blotting in mRNA and protein levels.ResultsThree hub genes, FLT3, CD177 and TTPAL were used to build a clinically applicable model to predict the survival probability of AML patients and divided them into high and low groups. To compare the survival ability of the model with the classical clinical features, we generated the nomogram. The model displayed the most risk points contrast to other clinical characteristics, which was compatible with the data of cox multivariate regression.ConclusionThis study reveal the novel molecular mechanism of AML, and construct a clinical model significantly related to AML patient prognosis. We showed the integrated roles of critical pathways, hub genes associated, which provide potential targets and new research ideas for the treatment and early detection of AML.

Dataset Information

Expression of a specific extracellular matrix signature is a favorable prognostic factor in acute myeloid leukemia.

Publications

Expression of a specific extracellular matrix signature is a favorable prognostic factor in acute myeloid leukemia.

Similar Datasets

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