Abstract
BackgroundThis study aimed to determine and verify the prognostic value and potential functional mechanism of signal recognition particle 14 (SRP14) in acute myeloid leukemia (AML) using a genome-wide expression profile dataset.MethodsWe obtained an AML genome-wide expression profile dataset and clinical prognostic data from The Cancer Genome Atlas (TCGA) and GSE12417 databases, and explored the prognostic value and functional mechanism of SRP14 in AML using survival analysis and various online tools.ResultsSurvival analysis showed that AML patients with high SRP14 expression had poorer overall survival than patients with low SRP14 expression. Time-dependent receiver operating characteristic curves indicated that SRP14 had good accuracy for predicting the prognosis in patients with AML. Genome-wide co-expression analysis suggested that SRP14 may play a role in AML by participating in the regulation of biological processes and signaling pathways, such as cell cycle, cell adhesion, mitogen-activated protein kinase, tumor necrosis factor, T cell receptor, DNA damage response, and nuclear factor-kappa B (NF-κB) signaling. Gene set enrichment analysis indicated that SRP14 was significantly enriched in biological processes and signaling pathways including regulation of hematopoietic progenitor cell differentiation and stem cell differentiation, intrinsic apoptotic signaling pathway by p53 class mediator, interleukin-1, T cell mediated cytotoxicity, and NF-κB-inducing kinase/NF-κB signaling. Using the TCGA AML dataset, we also identified four drugs (phenazone, benzydamine, cinnarizine, antazoline) that may serve as SRP14-targeted drugs in AML.ConclusionThe current results revealed that high SRP14 expression was significantly related to a poor prognosis and may serve as a prognostic biomarker in patients with AML.
Highlights
This study aimed to determine and verify the prognostic value and potential functional mechanism of signal recognition particle 14 (SRP14) in acute myeloid leukemia (AML) using a genome-wide expression profile dataset
The time-dependent receiver operating characteristic (ROC) survival curve indicated that SRP14 had the highest accuracy for prognostic prediction in the The Cancer Genome Atlas (TCGA) AML cohort at 1 year, with an area under the curve (AUC) of 0.737 (Fig. 1c), while its accuracy for predicting 5-year survival was 0.634 (Fig. 1c)
The timedependent ROC survival curve indicated that SRP14 had the highest accuracy for prognostic prediction in AML patients in the GSE12417 cohort at 3 years, with an AUC of 0.648 (Fig. 2c), while its accuracy for predicting 5-year survival was 0.632 (Fig. 2c)
Summary
This study aimed to determine and verify the prognostic value and potential functional mechanism of signal recognition particle 14 (SRP14) in acute myeloid leukemia (AML) using a genome-wide expression profile dataset. Gene expression profiling has been widely used in AML, and the resulting gene profiles can assist in the typing diagnosis and in assessing the prognostic risk and chemotherapeutic drug resistance. These applications require high-throughput sequencing to screen and identify AML-related biomarkers. The main purpose of this study was to identify and verify the prognostic value and potential functional mechanism of SRP14 in AML using a genome-wide expression profile dataset
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