In this prospective study we identified a pronounced HDAC3 expression pattern in CRC. Our findings support an important role of HDAC3 as a complementary molecular marker for existing histopathological diagnostic elements; it might also have applications in prognostic and targeted therapy. Furthermore, HDAC3 can be used as a biomarker to differentiate between tumor borders and margins, and it may also be useful for characterizing field cancerization in CRC.

This prospective study proposes that upregulation of miR-216a might represent an important mechanism for the development of gastric cancer.

ABSTRACT. Phenylketonuria (PKU) is a heterogeneous and autosomal recessive metabolic disorder that is mainly caused by mutations in the hepatic phenylalanine hydroxylase (PAH) gene. This study was designed to identify PAH mutations within exons 6, 7, and 10-12 in PKU patients from southwest Iran. Forty Iranian patients with clinical and biochemically confirmed PKU were enrolled. The exons were sequenced directly and 13 different mutations were identified including I224T, S231P, R176X, c.592_613del22, R243X, R252W, R261Q, Y356X, V388M, IVS10-11G>A, IVS11+1G>C, IVS11-2A>G, and Q375R, which were associated with 23 genotypes. A novel sequence variant, Q375R (c.1124A>G), was detected in exon 11. In one patient, a typical genotype with more than two mutations (R243X/S231P/ S231P) was found. Seven different polymorphisms and three new variants were also detected in intron regions of PAH. A high mutation spectrum was predicted in the southwestern region of Iran due to its ethnic heterogeneity, especially the Khuzestan Province. The detection PAH mutations in southwest Iran of 13 different mutations, corresponding to a mutation detection rate of 53.75%, confirmed this phenomenon.

Long non-coding ribonucleic acids (LncRNAs) are recently known for their role in regulating gene expression and the development of cancer. Controversial results indicate a correlation between the tissue expression of LncRNA and LncRNA content of extracellular vesicles. The present study aimed to evaluate the expression of different LncRNAs in non-small cell lung cancer (NSCLC) patients in tumor tissue, adjacent non-cancerous tissue (ANCT), and exosome-mediated lncRNA. Tumor and ANCT, as well as serum samples of 168 patient with NSCLC, were collected. The GHSROS, HNF1A-AS1, HOTAIR, HMlincRNA717, and LINCRNA-p21 relative expressions in tumor tissue, ANCT, and serum exosomes were evaluated in NSCLC patients. Among 168 NSCLC samples, the expressions of GHSROS (REx = 3.64, p = 0.028), HNF1A-AS1 (REx = 2.97, p = 0.041), and HOTAIR (REx = 2.9, p = 0.0389) were upregulated, and the expressions of HMlincRNA717 (REx = −4.56, p = 0.0012) and LINCRNA-p21 (REx = −5.14, p = 0.00334) were downregulated in tumor tissue in contrast to ANCT. Moreover, similar statistical differences were seen in the exosome-derived RNA of tumor tissues in contrast to ANCT samples. A panel of the five lncRNAs demonstrated that the area under the curve (AUC) for exosome and tumor was 0.937 (standard error: 0.012, p value < 0.0001). LncRNAs GHSROS, HNF1A-AS1, and HOTAIR showed high expression in tumor tissue and exosome content in NSCLC, and a panel that consisted of all five lncRNAs improved diagnosis of NSCLC.

We describe a 3.5‐year‐old Iranian female child and her affected 10‐month‐old brother with a maternally inherited derivative chromosome 9 [der(9)]. The postnatally detected rearrangement was finely characterized by aCGH analysis, which revealed a 15.056 Mb deletion of 9p22.3‐p24.3p22.3 encompassing 14 OMIM morbid genes such as DOCK8, KANK1, DMRT1 and SMARCA2, and a gain of 3.309 Mb on 18p11.31‐p11.32 encompassing USP14, THOC1, COLEC12, SMCHD1 and LPIN2. We aligned the genes affected by detected CNVs to clinical and functional phenotypic features using PhenogramViz. In this regard, the patient's phenotype and CNVs data were entered into PhenogramViz. For the 9p deletion CNV, 53 affected genes were identified and 17 of them were matched to 24 HPO terms describing the patient's phenotypes. Also, for CNV of 18p duplication, 22 affected genes were identified and six of them were matched to 13 phenotypes. Moreover, we used DECIPHER for in‐depth characterization of involved genes in detected CNVs and also comparison of patient phenotypes with 9p and 18p genomic imbalances. Based on our filtration strategy, in the 9p22.3‐p24.3 region, approximately 80 pathogenic/likely pathogenic/uncertain overlapping CNVs were in DECIPHER. The size of these CNVs ranged from 12.01 kb to 18.45 Mb and 52 CNVs were smaller than 1 Mb in size affecting 10 OMIM morbid genes. The 18p11.31‐p11.32 region overlapped 19 CNVs in the DECIPHER database with the size ranging from 23.42 kb to 1.82 Mb. These CNVs affect eight haploinsufficient genes.