Dataset Information

Investigation of Biomarkers Associated with Low Platelet Counts in Normal Karyotype Acute Myeloid Leukemia.

ABSTRACT: Acute myeloid leukemia (AML) patients are at risk of bleeding due to disease-related lack of platelets and systemic coagulopathy. Platelets play a role in hemostasis. Leukemic blasts have been shown to alter platelet activation in vitro. Here we investigated biomarkers associated with thrombocytopenia in normal karyotype AML (NK-AML). From The Cancer Genome Atlas database, case-control study was performed between normal karyotype (NK) platelet-decreased AML (PD-AML, platelet count < 100 × 10⁹/L, n = 24) and NK platelet-not-decreased AML (PND-AML, with platelet count ≥ 100 × 10⁹/L, n = 13). Differentially expressed gene analysis, pathway analysis and modelling for predicting platelet decrease in AML were performed. DEG analysis and pathway analysis revealed 157 genes and eight pathways specific for PD-AML, respectively. Most of the eight pathways were significantly involved in G-protein-coupled receptor-related pathway, cytokine-related pathway, and bone remodeling pathway. Among the key genes involved in at least one pathway, three genes including CSF1R, TNFSF15 and CLEC10A were selected as promising biomarkers for predicting PD-AML (0.847 of AUC in support vector machine model). This is the first study that identified biomarkers using RNA expression data analysis and could help understand the pathophysiology in AML with low platelet count.

SUBMITTER: Park CH

PROVIDER: S-EPMC9320053 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Acute myeloid leukemia with normal karyotype (NK-AML) is a group of diseases with high heterogeneity and immunological processes are significantly associated with its initiation and development. The implication of the immunogenomic landscape in the prognosis of patients with NK-AML has remained largely elusive. In the present study, the expression profiles of immune-related genes (IRGs) were examined and their association with overall survival (OS) was determined in 60 patients with NK-AML from The Cancer Genome Atlas dataset and 104 patients from the Gene Expression Omnibus (GEO) dataset no. GSE71014. Univariate Cox regression analysis was used to identify 42 and 203 IRGs in the two respective cohorts, which were significantly associated with OS in NK-AML. A risk model was constructed based on the regression coefficient and expression values of nine survival-associated IRGs shared between the two datasets [zinc finger CCCH-type containing, antiviral 1 like; transferrin receptor; suppressor of cytokine signaling 1; ELAV like RNA binding protein 1; roundabout guidance receptor 3; unc-93 homolog B1, Toll-like receptor signaling regulator; protein tyrosine phosphatase non-receptor type 6; interleukin 2 receptor subunit alpha (IL2RA) and IL3RA]. Using this risk model, patients with NK-AML may be divided into high- and low-risk groups in prognostic predictions. The area under the receiver operating characteristic curve for predicting OS was 0.793. The prognostic role of this risk model was successfully verified in another independent cohort (GEO dataset no. GSE71014). The prognostic risk score was positively associated with age and fms related receptor tyrosine kinase 3 mutation and correlated with infiltration by T regulatory cells. In conclusion, the results of the present study provided an IRG score model for prognostic stratification of adult patients with NK-AML, as well as further insight into the implication of IRGs in NK-AML that may lead to the development of novel immunotherapy approaches for this disease.

Dataset Information

Investigation of Biomarkers Associated with Low Platelet Counts in Normal Karyotype Acute Myeloid Leukemia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets