Identification and validation of signal recognition particle 14 as a prognostic biomarker predicting overall survival in patients with acute myeloid leukemia

Abstract

Background 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. Methods We 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. Results Survival 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. Conclusion The 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.

Cysteine- and glycine-rich protein 1 predicts prognosis and therapy response in patients with acute myeloid leukemia

“…KEGG enrichment analysis revealed that CSRP1 was associated with cell adhesion molecules, rap1 signaling pathway, HIF-1 signaling pathway, JAK-STAT signaling pathway, and apoptosis. Cellular adhesion molecules also impact the poor prognosis of AML and may be used as targets for AML-specific therapies [36]. Also, the Rap1 signaling pathway plays a crucial role in cancer [37].…”

Construction and validation of a risk prediction model for clinical axillary lymph node metastasis in T1–2 breast cancer

“…Glycogen phosphorylase B (PYGB) has potential applications in the prevention of BC metastasis 31 . Signal recognition particle 14 (SRP14) plays a role in OS in acute myeloid leukemia patients 32 . The expression of 2′,3′-cyclic nucleotide 3′ phosphodiesterase (CNP) correlates with glioblastoma patient survival 33 .…”

Multi-Level High-Throughput Screening for Discovery of Ligands That Inhibit Insulin Aggregation

“…Development of stable formulations of protein therapeutics can significantly benefit from discovery of small molecules that provide stabilization against aggregation-induced product degradation. High-throughput virtual screening (VS) methods have been widely used for discovery of potential inhibitors of protein–protein interactions (PPIs) implicated in dysfunctional signaling pathways − or protein aggregation, in turn leading to several human diseases or biotherapeutic product loss. − Here, “virtual” refers to the use of computational in place of wet lab experiments. It can involve a series of steps with an increasing level of structural, thermodynamic, and kinetic details to obtain an increased specificity for target PPIs.…”