The adenomas in Cushing’s disease frequently exhibit mutations in exon 14, within a binding motif for the regulatory protein 14-3-3 located between the catalytic domain (DUB), responsible for ubiquitin hydrolysis, and the WW-like domain that mediates autoinhibition, resulting in constantly active USP8. The exact molecular mechanism of deubiquitinase activity disruption in Cushing’s disease remains unclear. To address this, Sanger sequencing of USP8 was performed to identify mutations in corticotropinomas. These mutations were subjected to computational screening, followed by molecular dynamics simulations to assess the structural alterations that might change the biological activity of USP8. Eight different variants of the USP8 gene were identified both within and outside the “hotspot” region. Six of these had previously been reported in Cushing’s disease, while two were detected for the first time in our patients with CD. One of the two new variants, initially classified as benign during screening, was found in the neighboring SH3 binding motif at a distance of 20 amino acids. This variant demonstrated pathogenicity patterns similar to those of known pathogenic variants. All USP8 variants identified in our patients caused conformational changes in the USP8 protein in a similar manner. The identified mutations, despite differences in annotation results—including evolutionary conservation assessments, automated predictor data, and variations in localization within exon 14—exhibit similar patterns of protein conformational change. This suggests a pathogenic effect that contributes to the development of CD.

A number of sequencing studies identified the prognostic impact of somatic mutations in myelodysplastic syndrome (MDS). However the majority of them focused on methylation regulation, apoptosis and proliferation genes. Despite the number of experimental studies published on the role of micro-RNA processing and checkpoint genes in the development of MDS, the clinical data about mutational landscape in these genes is limited. We performed a pilot study which evaluated mutational burden in these genes and their association with common MDS mutations. High prevalence of mutations was observed in the genes studied: 54% had mutations in DICER1, 46% had mutations in LAG3, 20% in CTLA4, 23% in B7-H3, 17% in DROSHA, 14% in PD-1 and 3% in PD-1L. Cluster analysis that included these mutations along with mutations in ASXL1, DNMT3A, EZH2, IDH1, RUNX1, SF3B1, SRSF2, TET2 and TP53 effectively predicted overall survival in the study group (HR 4.2, 95%CI 1.3–13.6, p = 0.016). The study results create the rational for incorporating micro-RNA processing and checkpoint genes in the sequencing panels for MDS and evaluate their role in the multicenter studies.

Untranslated gene regions (UTRs) play an important role in controlling gene expression. 3′-UTRs are primarily targeted by microRNA (miRNA) molecules that form complex gene regulatory networks. Cancer genomes are replete with non-coding mutations, many of which are connected to changes in tumor gene expression that accompany the development of cancer and are associated with resistance to therapy. Therefore, variants that occurred in 3′-UTR under cancer progression should be analysed to predict their phenotypic effect on gene expression, e.g., by evaluating their impact on miRNA target sites. Here, we analyze 3′-UTR variants in DICER1 and DROSHA genes in the context of myelodysplastic syndrome (MDS) development. The key features of this analysis include an assessment of both “canonical” and “non-canonical” types of mRNA-miRNA binding and tissue-specific profiling of miRNA interactions with wild-type and mutated genes. As a result, we obtained a list of DICER1 and DROSHA variants likely altering the miRNA sites and, therefore, potentially leading to the observed tissue-specific gene downregulation. All identified variants have low population frequency consistent with their potential association with pathology progression.

Osteopetrosis is a group of rare inheritable disorders of the skeleton characterized by increased bone density. The disease is remarkably heterogeneous in clinical presentation and often misdiagnosed. Therefore, genetic testing and molecular pathogenicity analysis are essential for precise diagnosis and new targets for preventive pharmacotherapy. Mutations in the CLCN7 gene give rise to the complete spectrum of osteopetrosis phenotypes and are responsible for about 75% of cases of autosomal dominant osteopetrosis. In this study, we report the identification of a novel variant in the CLCN7 gene in a patient diagnosed with osteopetrosis and provide evidence for its significance (likely deleterious) based on extensive comparative genomics, protein sequence and structure analysis. A set of automated bioinformatics tools used to predict consequences of this variant identified it as deleterious or pathogenic. Structure analysis revealed that the variant is located at the same “hot spot” as the most common CLCN7 mutations causing osteopetrosis. Deep phylogenetic reconstruction showed that not only Leu614Arg, but any non-aliphatic substitutions in this position are evolutionarily intolerant, further supporting the deleterious nature of the variant. The present study provides further evidence that reconstructing a precise evolutionary history of a gene helps in predicting phenotypical consequences of variants of uncertain significance.

Myelodysplastic syndrome (MDS) refers to a heterogeneous group of closely related clonal hematopoietic disorders, which are characterized by accumulation of somatic mutations. The acquired mutation burden is suggested to define the pathway and consequent phenotype of the pathology. Recent studies have called attention to the role of miRNA biogenesis genes in MDS progression; in particular, the mutational pressure of the DROSHA gene was determined. Therefore, this highlights the importance of studying the impact of all collected missense mutations found within the DROSHA gene in oncohematology that might affect the functionality of the protein. In this study, the selected mutations were extensively examined by computational screening, and the most deleterious were subjected to a further molecular dynamic simulation in order to uncover the molecular mechanism of the structural damage to the protein altering its biological function. The most significant effect was found for variants I625K, L1047S, and H1170D, presumably affecting the endonuclease activity of DROSHA. Such alterations arisen during MDS progression should be taken into consideration as evoking certain clinical traits in the malignifying clonal evolution.

Introduction. Cancer is accounting for 16.8% of all deaths and 22.8% of noncommunicable disease-related deaths, approximately. The diagnostic, prognostic, and therapeutic aspects of patient management majorly depend on mutations that drive the oncogenic process. However, evaluating the clinical significance of the variant is a major challenge, as many of them become variants of unknown significance (VUS).Aim: of the current study is to create a new algorithm for classification of missense variants.Material and Methods. Data from the NCBI Assembly, Uniprot, GnomAD, and OncoKB databases was processed with Python 3 to assess oncogenicity, population frequency of missense variants, as well as their occurrence in orthologous sequences. We selected 314 known benign polymorphisms and 332 reported pathogenic mutations of BRCA1, BRCA2, DICER1, PIK3CA, and TP53 genes from the ClinVar database for training and testing datasets.Results. We have developed the algorithm that provides three criteria based on oncogenicity and population frequency of a variant, as well as its occurrence in orthologous sequences for assessing its potential pathogenicity. A variant was classified as neutral if the following was true: a) a variant doesn’t meet the criterion for oncogenicity; b) a variant meets at least one of the remaining criteria. All other variants were deemed to be pathogenic. The new algorithm demonstrates high sensitivity (94.95% (88.61%, 98.34%)) and specificity (96.52% (91.33%, 99.04%)) in classifying benign and pathogenic variants. The algorithm requires a position of a variant to be represented in population databases and to correspond to an appropriately aligned region in a multiple sequence alignment of orthologs, along with two adjacent positions.Conclusion. The algorithm might be used to evaluate the variants of other oncogenic genes, possibly making the classification of genetic variants more precise, intensifying molecular diagnostics.