Regulatory Non-coding RNAs in Atherosclerosis.

Regulatory RNAs like microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) control vascular and immune cells' phenotype and thus play a crucial role in atherosclerosis. Moreover, the mutual interactions between miRNAs and lncRNAs link both types of regulatory RNAs in a functional network that affects lesion formation. In this review, we deduce novel concepts of atherosclerosis from the analysis of the current data on regulatory RNAs' role in endothelial cells (ECs) and macrophages. In contrast to arterial ECs, which adopt a stable phenotype by adaptation to high shear stress, macrophages are highly plastic and quickly change their activation status. At predilection sites of atherosclerosis, such as arterial bifurcations, ECs are exposed to disturbed laminar flow, which generates a dysadaptive stress response mediated by miRNAs. Whereas the highly abundant miR-126-5p promotes regenerative proliferation of dysadapted ECs, miR-103-3p stimulates inflammatory activation and impairs endothelial regeneration by aberrant proliferation and micronuclei formation. In macrophages, miRNAs are essential in regulating energy and lipid metabolism, which affects inflammatory activation and foam cell formation.Moreover, lipopolysaccharide-induced miR-155 and miR-146 shape inflammatory macrophage activation through their oppositional effects on NF-kB. Most lncRNAs are not conserved between species, except a small group of very long lncRNAs, such as MALAT1, which blocks numerous miRNAs by providing non-functional binding sites. In summary, regulatory RNAs' roles are highly context-dependent, and therapeutic approaches that target specific functional interactions of miRNAs appear promising against cardiovascular diseases.

p53 immunostaining cannot be used to predict TP53 mutations in gastric cancer: results from a large Central European cohort.

Four molecular subgroups of gastric cancer (GC) have been proposed, ie, Epstein-Barr virus (EBV)-positive, microsatellite instable, chromosomal instable (CIN), and genomically stable GC. Based on the complex relationship between chromosomal instability and TP53 mutational status, we hypothesized that the typical clinicopathological characteristics caused by chromosomal instability are correlated with the p53 expression that is detected by immunohistochemistry. Four hundred sixty-seven whole-tissue sections of patients with therapy-naive GC were stained with anti-p53 antibody. The histoscore and staining pattern were analyzed for each slide. Different algorithms of immunohistochemistry evaluation were formed and correlated with clinicopathological characteristics. The algorithms were validated by assessing the mutational status of TP53 in 111 cases. Four hundred forty-two GCs were p53 positive, and 25 were negative, including 414 GCs with a homogeneous pattern and 53 GCs with a heterogeneous staining pattern. There was no correlation with overall or tumor-specific survival. In comparison with clinicopathological characteristics, the algorithm high versus low showed correlations with microsatellite instability, hepatocyte growth factor receptor (MET), and TP53 mutational status. The algorithm Q1/Q4 versus Q2/Q3 appeared to be correlated with the phenotype as per the Laurén classification, microsatellite instability, EBV status, and p53 expression pattern. The algorithm <90% = 0 and <50% = 3+ versus ≥90% = 0 or ≥50% = 3+ showed correlations with the EBV status, microsatellite instability, grading, and p53 expression pattern. The algorithm homogeneous versus heterogeneous did not correlate with any clinicopathological characteristic. Our results showed that the immunohistochemistry of p53, TP53 mutational status, and CIN subtype were connected. However, different algorithms for p53 immunohistochemical evaluation cannot be used to predict TP53 mutations in CIN GCs in individual cases.

Chromosomal Instability in Gastric Cancer Biology.

Gastric cancer (GC) is the fifth most common cancer in the world and accounts for 7% of the total cancer incidence. The prognosis of GC is dismal in Western countries due to late diagnosis: approximately 70% of the patients die within 5 years following initial diagnosis. Recently, integrative genomic analyses led to the proposal of a molecular classification of GC into four subtypes, i.e.,microsatellite-instable, Epstein-Barr virus-positive, chromosomal-instable (CIN), and genomically stable GCs. Molecular classification of GC advances our knowledge of the biology of GC and may have implications for diagnostics and patient treatment. Diagnosis of microsatellite-instable GC and Epstein-Barr virus-positive GC is more or less straightforward. Microsatellite instability can be tested by immunohistochemistry (MLH1, PMS2, MSH2, and MSH6) and/or molecular-biological analysis. Epstein-Barr virus-positive GC can be tested by in situ hybridization (Epstein-Barr virus encoded small RNA). However, with regard to CIN, testing may be more complicated and may require a more in-depth knowledge of the underlying mechanism leading to CIN. In addition, CIN GC may not constitute a distinct subgroup but may rather be a compilation of a more heterogeneous group of tumors. In this review, we aim to clarify the definition of CIN and to point out the molecular mechanisms leading to this molecular phenotype and the challenges faced in characterizing this type of cancer.