Bioinformatics, RNA sequencing, and targeted bisulfite sequencing analyses identify the role of PROM2 as a diagnostic and prognostic biomarker.

Objectives: Prominin 2 (PROM2) gene has been reported as a molecular biomarker of human cancers; however, its role is still controversial. This study was therefore arranged to seek the role of PROM2 in different cancers with Bioinformatics and in vitro analyses.

Methods: A combination of bioinformatics and molecular experiments.

A pan-cancer analysis of pituitary tumor-transforming 3, pseudogene.

Background: Although evidence regarding pituitary tumor-transforming 3, pseudogene (PTTG3P) involvement in human cancers has been acquired via human and animal model-based molecular studies, there is a lack of pan-cancer analysis of this gene in human tumors.

Methods: Tumor-causing effects of PTTG3P in 24 human tumors were explored using The Cancer Genome Atlas (TCGA) datasets from different bioinformatics databases and applying in silico tools such as The University of ALabama at Birmingham CANcer (UALCAN), Human Protein Atlas (HPA), Kaplan Meier (KM) plotter, cBioPortal, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Cytoscape, Database for Annotation, Visualization, and Integrated Discovery (DAVID), Tumor IMmune Estimation Resource (TIMER), and Comparative Toxicogenomics Database (CTD). Then, via in vitro experiments, including RNA sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq), expression and promoter methylation levels of PTTG3P were verified in cell lines.

Decoding signal transducer and activator of transcription 1 across various cancers through data mining and integrative analysis.

Objectives: Using different online available databases and Bioinformatics tools, we extensively studied the role STAT1 across different cancers.

Methods: STAT1 mRNA, protein expression, and promoter methylation were analyzed and validated using UALCAN, GENT2, Human Protein Atlas (HPA), and MEXPRESS. Furthermore, the potential prognostic values were evaluated through KM plotter.

Screening a novel six critical gene-based system of diagnostic and prognostic biomarkers in prostate adenocarcinoma patients with different clinical variables.

The mechanisms behind prostate adenocarcinoma (PRAD) pathogenicity remain to be understood due to tumor heterogeneity. In the current study, we identified by microarray technology six eligible real hub genes from already identified hub genes through a systematic approach that could be useful to lower the heterogenetic-specific barriers in PRAD patients for diagnosis, prognosis, and treatment. For this purpose, microarray technology-based, already-identified PRAD-associated hub genes were initially explored through extensive literature mining; then, a protein-protein interaction (PPI) network construction of those hub genes and its analysis helped us to identify six most critical genes (real hub genes).