Kyriakos Kouirouxis

This study aimed to explore the correlation between Angiopoietin-1 (Ang-1) and Angiopoietin-2 (Ang-2) concentrations and the Angiopoietin-2/Angiopoietin-1 ratio (Ang-2/Ang-1) with clinical outcomes, potentially serving as disease severity and survival biomarkers. A study at AHEPA University Hospital involved 90 Coronavirus Disease 2019 (COVID-19) adult patients, 30 hospitalized intensive care units (ICU), 30 inward units (non-ICU), and 30 asymptomatic non-hospitalized individuals as controls. Estimated endothelial dysfunction markers related to angiogenesis were measured. There was a statistically significant difference only between outpatient and hospitalized patients (non-ICU–ICU groups) for the Ang-1 and Ang-2 indices. The Ang-2/Ang-1 ratio has differed significantly among the individual patient groups. An ROC analysis was conducted to find an optimal threshold for distinguishing between (outpatients–non-ICU) and (non-ICU–ICU) groups. It was based on Youden’s index of 0.1122 and 0.3825, respectively. The Ang-1, Ang-2 levels, and Ang-2/Ang-1 ratio were analyzed as severity indicators in COVID-19 patients. The Ang-2/Ang-1 ratio demonstrated better prognostic and diagnostic utility than individual biomarker levels. Monitoring the Ang-2/Ang-1 ratio can identify COVID-19 patients at risk and assist clinicians in tailoring treatment strategies to improve outcomes.

The study aimed to explore the correlation among Angiopoietin-1, (Ang-1) and Angiopoietin-2, (Ang-2) concentrations and the Angiopoietin-2/Angiopoietin-1 ratio, (Ang-2/Ang-1) with clinical outcomes, potentially serving as disease severity and survival biomarkers. A study at AHEPA University Hospital involved 90 COVID-19 adult patients, with 30 hospitalized in intensive care and 30 in ward units and 30 asymptomatic non-hospitalized individuals as controls. Estimated endothelial dysfunction markers related to angiogenesis were measured, and statistical analysis was performed using IBM SPSS Statistics software, version 29. There was a statistically significant difference only between outpatient and hospitalized patients (non-ICU -ICU groups) for the Ang-1 and Ang-2 indexes. The Ang-2/Ang-1 ratio has differed significantly among all individual patient groups. A ROC analysis was conducted to find an optimal threshold for distinguishing (outpatients – non-ICU) and (non-ICU –ICU) groups. It was based on Youden's Index and was 0.1122 and 0.3825, respectively. The Ang-1, Ang-2 levels, and Ang-2/Ang-1 ratio were analysed as indicators for severity in COVID-19 patients. The Ang-2/Ang-1 ratio demonstrated more excellent prognostic and diagnostic utility than individual biomarker levels. Monitoring the Ang-2/Ang-1 ratio can identify COVID-19 patients at risk and assist clinicians in tailoring treatment strategies for improved outcomes.

The poly(A) tail at the 3′ end of mRNAs determines their stability, translational efficiency, and fate. The shortening of the poly(A) tail, and its efficient removal, triggers the degradation of mRNAs, thus, regulating gene expression. The process is catalyzed by a family of enzymes, known as deadenylases. As the dysregulation of gene expression is a hallmark of cancer, understanding the role of deadenylases has gained additional interest. Herein, the genetic association network shows that CNOT6 and CNOT7 are the most prevalent and most interconnected nodes in the equilibrated diagram. Subsequent silencing and transcriptomic analysis identifies transcripts possibly regulated by specific deadenylases. Furthermore, several gene ontologies are enriched by common deregulated genes. Given the potential concerted action and overlapping functions of deadenylases, we examined the effect of silencing a deadenylase on the remaining ones. Our results suggest that specific deadenylases target unique subsets of mRNAs, whilst at the same time, multiple deadenylases may affect the same mRNAs with overlapping functions.

Lung cancer is the leading cause of cancer mortality worldwide, mainly due to late diagnosis, poor prognosis and tumor heterogeneity. Thus, the need for biomarkers that will aid classification, treatment and monitoring remains intense and challenging and depends on the better understanding of the tumor pathobiology and underlying mechanisms. The deregulation of gene expression is a hallmark of cancer and a critical parameter is the stability of mRNAs that may lead to increased oncogene and/or decreased tumor suppressor transcript and protein levels. The shortening of mRNA poly(A) tails determines mRNA stability, as it is usually the first step in mRNA degradation, and is catalyzed by deadenylases. Herein, we assess the clinical significance of deadenylases and we study their role on gene expression in squamous cell lung carcinoma (SCC). Computational transcriptomic analysis from a publicly available microarray was performed in order to examine the expression of deadenylases in SCC patient samples. Subsequently we employed real-time PCR in clinical samples in order to validate the bioinformatics results regarding the gene expression of deadenylases. Selected deadenylases were silenced in NCI-H520 and Hep2 human cancer cell lines and the effect on gene expression was analyzed with cDNA microarrays. The in silico analysis revealed that the expression of several deadenylases is altered in SCC. Quantitative real-time PCR showed that four deadenylases, PARN, CNOT6, CNOT7 and NOC, are differentially expressed in our SCC clinical samples. PARN overexpression correlated with younger patient age and CNOT6 overexpression with non-metastatic tumors. Kaplan-Meier analysis suggests that increased levels of PARN and NOC correlate with significantly increased survival. Gene expression analysis upon PARN and NOC silencing in lung cancer cells revealed gene expression deregulation that was functionally enriched for gene ontologies related to cell adhesion, cell junction, muscle contraction and metabolism. Our results highlight the clinical significance of PARN and NOC on the survival in SCC diagnosed patients. We demonstrate that the enzymes are implicated in important phenotypes pertinent to cancer biology and provide information on their role in the regulation of gene expression in SCC. Overall, our results support an emerging role for deadenylases in SCC and contribute to the understanding of their role in cancer biology.