Plasmacytoma variant translocation 1 stabilized by EIF4A3 promoted malignant biological behaviors of lung adenocarcinoma by generating circular RNA LMNB2

Identification of Novel Prognostic Long Non-coding RNAs in Lung Adenocarcinoma Using WGCNA Analysis

Long non-coding RNAs play crucial role in the tumorigenesis of lung adenocarcinoma (LUAD). However, the function of a large number of lncRNAs in LUAD has not been investigated yet. Weighted gene correlation network analysis (WGCNA) was applied to construct the co-expression module in the TCGA-LUAD cohort. Protein-protein interaction (PPI) network was used to explore the relationship of genes in the key module. The function of the key module on the prognosis in LUAD was analyzed using GO and KEGG analysis. Finally, we constructed the mRNA-lncRNA co-expression network in the key module to identify the hub lncRNAs that play crucial role in the prognosis in LUAD. The most highly expressed 2500 mRNAs and 2500 lncRNAs in the TCGA-LUAD cohort were clustered into 21 modules. After analyzing the correlation between the module and prognostic clinical traits, the Tan module, consisting of 130 genes, was selected as the key module on the prognosis in LUAD. And then, we found that genes in the key module were majorly enriched in ten multiple signaling pathways. Subsequently, we constructed the mRNA-lncRNA co-expression network based on the genes in the key module. Finally, we identified three lncRNAs and nineteen mRNAs that could be the promising prognostic biomarkers for LUAD. We identified three lncRNAs (MIR99AHG, ADAMTS9-AS2, and AC037459.2) and nineteen mRNAs as potential prognostic biomarkers in LUAD, which provided new insight for prognosis monitoring and therapy development in LUAD.

DDX52 gene expression in LUAD tissues indicates potential as a prognostic biomarker and therapeutic target

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related morbidity and mortality globally. While DDX52, an ATP-dependent RNA helicase, plays a role in several biological processes, its specific involvement in LUAD is yet to be elucidated. We utilized ROC curves to determine DDX52's predictive potential for LUAD. Kaplan-Meier survival curves, along with univariate and multivariate Cox analyses, assessed the prognostic implications of DDX52 in LUAD. We constructed nomogram models to further delineate DDX52's influence on prognosis, employed GSEA for functional analysis, and used qRT-PCR to examine DDX52 expression in LUAD tissues. DDX52 expression was notably higher in LUAD tissues, suggesting its potential as a negative prognostic marker. We observed a direct relationship between DDX52 expression and advanced T and N stages, as well as higher grading and staging in LUAD patients. Cox analyses further underscored DDX52's role as an independent prognostic determinant for LUAD. GSEA insights indicated DDX52's influence on LUAD progression via multiple signaling pathways. Our nomogram, founded on DDX52 expression, effectively projected LUAD patient survival, as validated by calibration curves. Elevated DDX52 expression in LUAD tissues signals its potential as a poor prognostic marker. Our findings emphasize DDX52's role not only as an independent prognostic factor for LUAD but also as a significant influencer in its progression through diverse signaling pathways. The constructed nomogram also underscores the feasibility of predicting LUAD patient survival based on DDX52 expression.

Molecular interplay between EIF4 family and circular RNAs in cancer: Mechanisms and therapeutics

The eukaryotic translation initiation factor 4 (EIF4) family is a major contributor to the recruitment of mRNAs to ribosomes during the initial translation stage in eukaryotes, whose dysregulation either allows for cancer transformation or prevents disordered cancerous cell growth. Circular RNAs (circRNAs), which exhibit distinctive structures and are widely expressed in eukaryotes, are anticipated to be a clinical diagnostic biomarker for cancer therapy. There is considerable evidence that EIF4s can influence the biogenesis, transport, and function of circRNAs and, in turn, circRNAs can control the expressions of EIF4s through certain molecular pathways. Herein, we primarily review the emerging studies of the EIF4 family and pinpoint the roles of dysregulated EIF4s in cancer. We also evaluate the patterns of intricate interactions between circRNAs and EIF4s and discuss the potential utility of circRNA-based therapeutics targeting EIF4s in clinical cancer research.

Circ_0020256 induces fibroblast activation to drive cholangiocarcinoma development via recruitment of EIF4A3 protein to stabilize KLF4 mRNA

Cancer-associated fibroblasts (CAFs) are a kind of stromal cells in the cholangiocarcinoma (CCA) microenvironment, playing crucial roles in cancer development. However, the potential mechanisms of the interaction between CCA cells and CAFs remain obscure. This work investigated the role of circ_0020256 in CAFs activation. We proved circ_0020256 was up-regulated in CCA. High circ_0020256 expression facilitated TGF-β1 secretion from CCA cells, which activated CAFs via the phosphorylation of Smad2/3. Mechanistically, circ_0020256 recruited EIF4A3 protein to stabilize KLF4 mRNA and upregulate its expression, then KLF4 bound to TGF-β1 promoter and induced its transcription in CCA cells. KLF4 overexpression abrogated the inhibition of circ_0020256 silencing in TGF-β1/Smad2/3-induced CAFs activation. Furthermore, CCA cell growth, migration, and epithelial-mesenchymal transition were favored by CAFs-secreted IL-6 via autophagy inhibition. We also found circ_0020256 accelerated CCA tumor growth in vivo. In conclusion, circ_0020256 promoted fibroblast activation to facilitate CCA progression via EIF4A3/KLF4 pathway, providing a potential intervention for CCA progression.

Promotive role of eukaryotic translation initiation factor 4A isoform 3 in ovarian cancer cell growth and aerobic glycolysis through the pyruvate dehydrogenase kinase 4 signaling

Ovarian cancer (OC) represents one of the most detrimental gynecological malignancies. RNA-binding protein eukaryotic translation initiation factor 4A isoform 3 (EIF4A3) is well-regarded as a definitive oncogene that contributes to the development of multiple malignant tumors. This study sought to elucidate the molecular mechanism of EIF4A3 in OC growth and aerobic glycolysis by regulation of pyruvate dehydrogenase kinase 4 (PDK4) mRNA stability. We determined the EIF4A3 and PDK4 expression levels in OC cell lines and normal ovarian epithelial cells, and subsequently evaluated the cell viability and colony formation by cell counting kit-8 and colony formation assays. The degree of cell aerobic glycolysis was evaluated by measurements of lactic acid production, glucose intake, adenosine triphosphate level, extracellular oxygen consumption, and protein levels of pyruvate kinase isozymes M2 and hexokinase-2. Afterwards, we verified the binding of EIF4A3 and PDK4 mRNA via RNA immunoprecipitation, and determined the mRNA stability after actinomycin D treatment. Finally, a series of rescue experiments was performed with pcDNA3.1-PDK4. EIF4A3 and PDK4 were upregulated in OC cells. Silencing EIF4A3 obstructed cell proliferation and aerobic glycolysis, while the same was annulled by EIF4A3 overexpression. Mechanically, EIF4A3 could bind to PDK4 mRNA to stabilize its mRNA and upregulate its protein levels. PDK4 overexpression inverted the inhibitory role of silencing EIF4A3 in proliferation and aerobic glycolysis. Overall, our findings highlighted that EIF4A3 induced OC progression by stabilizing PDK4 mRNA.

The role of Lamin B2 in human diseases

Lamin B2 (LMNB2), on the inner side of the nuclear envelope, constitutes the nuclear skeleton by connecting with other nuclear proteins. LMNB2 is involved in a wide range of nuclear functions, including DNA replication and stability, regulation of chromatin, and nuclear stiffness. Moreover, LMNB2 regulates several cellular processes, such as tissue development, cell cycle, cellular proliferation and apoptosis, chromatin localization and stability, and DNA methylation. Besides, the influence of abnormal expression and mutations of LMNB2 has been gradually discovered in cancers and laminopathies. Therefore, this review summarizes the recent advances of LMNB2-associated biological roles in physiological or pathological conditions, with a particular emphasis on cancers and laminopathies, as well as the potential mechanism of LMNB2 in related cancers.

Identification of Three Genes Associated with Metastasis in Melanoma and Construction of a Predictive Model: A Multiracial Identification

The aim of this study was to identify hub genes associated with metastasis and prognosis in melanoma. Weighted gene coexpression network analysis (WGCNA) was performed to screen and identify hub genes. ROC and K-M analyses were used to verify the hub genes in the internal and external data sets. The risk score model and nomogram model were constructed based on the IHC result. Through WGCNA, the three hub genes, SNRPD2, SNRPD3, and EIF4A3, were identified. In the external data set, the hub genes identified were associated with the worse prognosis (TCGA, SNRPD2, $P\le 0.02$ ; SNRPD3, $P=0.12$ ; EIF4A3, $P=0.11$ ; GSE65904, SNRPD2, $P=0.04$ ; SNRPD3, $P=0.10$ ; EIF4A3, $P<0.01$ ; GSE19234, SNRPD2, $P<0.01$ ; SNRPD3, $P<0.01$ ; EIF4A3, $P<0.01$ ). In the GSE8401, we found that the hub genes were highly expressed in the metastasis compared with the nonmetastasis group (SNRPD2, $988.5\pm 47.83$ vs. $738.4\pm 35.35$ , $P<0.01$ ; SNRPD3, $502.7\pm 25.7$ vs. $416.4\pm 23.88$ , $P=0.02$ ; EIF4A3, $567.6\pm 19.56$ vs. $495.2\pm 21.1$ , $P=0.01$ ). Moreover, the hub genes were identified by the IHC in our data set. The result was similar with the external data set. The hub genes could predict the metastasis and prognosis in the Chinese MM patients. Finally, the GSEA and Pearson analysis demonstrated that the SNRPD2 was associated with the immunotherapy. The three hub genes were identified and validated in MM patients in external and internal data sets. The risk factor model was constructed and verified as a powerful model to predict metastasis and prognosis in MM patients.