Germline variant in REXO2 is a novel candidate gene in familial pheochromocytoma

Non-Susceptibility Gene Variants in Head and Neck Paragangliomas

Head and neck paragangliomas (HNPGLs) are rare neoplasms that, along with pheochromocytomas and extra-adrenal paragangliomas, are associated with inherited mutations in at least 12 susceptibility genes in approximately 40% of cases. However, due to the rarity of HNPGLs, only a series of small-scale studies and individual cases have reported mutations in additional genes that may be involved in tumorigenesis. Consequently, numerous disease-causing mutations and genes responsible for the pathogenesis of HNPGLs remain poorly investigated. The aim of this study was to gain a deeper understanding of the genetic basis of HNPGLs by focusing on variants in genes that were not previously identified as well-known drivers. A whole-exome data analysis was conducted on a representative set of 152 HNPGLs. In 30% of the tumors examined, 53 potentially deleterious variants were identified in 36 different genes. The analysis identified pathogenic or likely pathogenic variants in the ARNT, IDH2, L2HGDH, MYH3, PIK3CA, and TERT genes. A functional network analysis of the mutated genes revealed numerous associations and a list of metabolic pathways (e.g., the TCA cycle, carbon metabolism, pyruvate metabolism, etc.) and signaling pathways (e.g., HIF1, PI3K-Akt, FoxO, AMPK, MAPK, etc.) that may play an important role in the development of HNPGLs. The identified range of genetic alterations affecting multiple genes and, potentially, influencing diverse cellular pathways provides an enhanced molecular genetic characterization of HNPGLs.

Heterozygous de novo dominant negative mutation of REXO2 results in interferonopathy

Mitochondrial RNA (mtRNA) in the cytosol can trigger the innate immune sensor MDA5, and autoinflammatory disease due to type I IFN. Here, we show that a dominant negative mutation in the gene encoding the mitochondrial exonuclease REXO2 may cause interferonopathy by triggering the MDA5 pathway. A patient characterized by this heterozygous de novo mutation (p.T132A) presented with persistent skin rash featuring hyperkeratosis, parakeratosis and acanthosis, with infiltration of lymphocytes and eosinophils around small blood vessels. In addition, circulating IgE levels and inflammatory cytokines, including IFNα, are found consistently elevated. Transcriptional analysis highlights a type I IFN gene signature in PBMC. Mechanistically, REXO2 (T132A) lacks the ability to cleave RNA and inhibits the activity of wild-type REXO2. This leads to an accumulation of mitochondrial dsRNA in the cytosol, which is recognized by MDA5, leading to the associated type I IFN gene signature. These results demonstrate that in the absence of appropriate regulation by REXO2, aberrant cellular nucleic acids may accumulate and continuously trigger innate sensors, resulting in an inborn error of immunity.

Computational identification of differentially-expressed genes as suggested novel COVID-19 biomarkers: A bioinformatics analysis of expression profiles

COVID-19 was declared a pandemic in March 2020, and since then, it has not stopped spreading like wildfire in almost every corner of the world, despite the many efforts made to stem its spread. SARS-CoV-2 has one of the biggest genomes among RNA viruses and presents unique characteristics that differentiate it from other coronaviruses, making it even more challenging to find a cure or vaccine that is efficient enough. This work aims, using RNA sequencing (RNA-Seq) data, to evaluate whether the expression of specific human genes in the host can vary in different grades of disease severity and to determine the molecular origins of the differences in response to SARS-CoV-2 infection in different patients. In addition to quantifying gene expression, data coming from RNA-Seq allow for the discovery of new transcripts, the identification of alternative splicing events, the detection of allele-specific expression, and the detection of post-transcriptional alterations. For this reason, we performed differential expression analysis on different expression profiles of COVID-19 patients, using RNA-Seq data coming from NCBI public repository, and we obtained the lists of all differentially expressed genes (DEGs) emerging from 7 experimental conditions. We performed a Gene Set Enrichment Analysis (GSEA) on these genes to find possible correlations between DEGs and known disease phenotypes. We mainly focused on DEGs coming out from the analysis of the contrasts involving severe conditions to infer any possible relation between a worsening of the clinical picture and an over-representation of specific genes. Based on the obtained results, this study indicates a small group of genes that result up-regulated in the severe form of the disease. EXOSC5, MESD, REXO2, and TRMT2A genes are not differentially expressed or not present in the other conditions, being for that reason, good biomarkers candidates for the severe form of COVID-19 disease. The use of specific over-expressed genes, whether up-regulated or down-regulated, which have an individual role in each different condition of COVID-19 as a biomarker, can assist in early diagnosis.

Genetics of Pheochromocytomas and Paragangliomas Determine the Therapeutical Approach

Pheochromocytomas and paragangliomas are the most heritable endocrine tumors. In addition to the inherited mutation other driver mutations have also been identified in tumor tissues. All these genetic alterations are clustered in distinct groups which determine the pathomechanisms. Most of these tumors are benign and their surgical removal will resolve patient management. However, 5–15% of them are malignant and therapeutical possibilities for them are limited. This review provides a brief insight about the tumorigenesis associated with pheochromocytomas/paragangliomas in order to present them as potential therapeutical targets.

Effects of RNA Binding Proteins on the Prognosis and Malignant Progression in Prostate Cancer

Prostate cancer (PCa) is a common lethal malignancy in men. RNA binding proteins (RBPs) have been proven to regulate the biological processes of various tumors, but their roles in PCa remain less defined. In the present study, we used bioinformatics analysis to identify RBP genes with prognostic and diagnostic values. A total of 59 differentially expressed RBPs in PCa were obtained, comprising 28 upregulated and 31 downregulated RBP genes, which may play important roles in PCa. Functional enrichment analyses showed that these RBPs were mainly involved in mRNA processing, RNA splicing, and regulation of RNA splicing. Additionally, we identified nine RBP genes (EXO1, PABPC1L, REXO2, MBNL2, MSI1, CTU1, MAEL, YBX2, and ESRP2) and their prognostic values by a protein-protein interaction network and Cox regression analyses. The expression of these nine RBPs was validated using immunohistochemical staining between the tumor and normal samples. Further, the associations between the expression of these nine RBPs and pathological T staging, Gleason score, and lymph node metastasis were evaluated. Moreover, these nine RBP genes showed good diagnostic values and could categorize the PCa patients into two clusters with different malignant phenotypes. Finally, we constructed a prognostic model based on these nine RBP genes and validated them using three external datasets. The model showed good efficiency in predicting patient survival and was independent of other clinical factors. Therefore, our model could be used as a supplement for clinical factors to predict patient prognosis and thereby improve patient survival.