The intricacies of isomiRs: from classification to clinical relevance.

MicroRNAs (miRNAs) and isoforms of their archetype, called isomiRs, regulate gene expression via complementary base-pair binding to messenger RNAs (mRNAs). The partially evolutionarily conserved isomiR sequence variations are differentially expressed among tissues, populations, and genders, and between healthy and diseased states. Aiming towards the clinical use of isomiRs as diagnostic biomarkers and for therapeutic purposes, several challenges need to be addressed, including (i) clarification of isomiR definition, (ii) improved annotation in databases with new standardization (such as the mirGFF3 format), and (iii) improved methods of isomiR detection, functional verification, and in silico analysis. In this review we discuss the respective challenges, and highlight the opportunities for clinical use of isomiRs, especially in the light of increasing amounts of next-generation sequencing (NGS) data.

Skin treatment with non-thermal plasma modulates the immune system through miR-223-3p and its target genes.

Non-thermal plasma, a partially ionized gas, holds significant potential for clinical applications, including wound-healing support, oral therapies, and anti-tumour treatments. While its applications showed promising outcomes, the underlying molecular mechanisms remain incompletely understood. We thus apply non-thermal plasma to mouse auricular skin and conducted non-coding RNA sequencing, as well as single-cell blood sequencing. In a time-series analysis (five timepoints spanning 2 hours), we compare the expression of microRNAs in the plasma-treated left ears to the unexposed right ears of the same mice as well as to the ears of unexposed control mice. Our findings indicate specific effects in the treated ears for a set of five miRNAs: mmu-miR-144-5p, mmu-miR-144-3p, mmu-miR-142a-5p, mmu-miR-223-3p, and mmu-miR-451a. Interestingly, mmu-miR-223-3p also exhibits an increase over time in the right non-treated ear of the exposed mice, suggesting systemic effects. Notably, this miRNA, along with mmu-miR-142a-5p and mmu-miR-144-3p, regulates genes and pathways associated with wound healing and tissue regeneration (namely ErbB, FoxO, Hippo, and PI3K-Akt signalling). This co-regulation is particularly remarkable considering the significant seed dissimilarities among the miRNAs. Finally, single-cell sequencing of PBMCs reveals the downregulation of 12 from 15 target genes in B-cells, Cd4+ and Cd8+ T-cells. Collectively, our data provide evidence for a systemic effect of non-thermal plasma.

A novel entity of massive multifocal osteolyses in the elderly.

Osteolyses are common findings in elderly patients and most frequently represent malignant or locally aggressive bone tumors, infection, inflammatory and endocrine disorders, histiocytoses, and rare diseases such as Gorham-Stout syndrome. We here report on a novel entity of massive multifocal osteolyses in both shoulders, the right hip and left knee joint and the dens of an 83-year-old patient not relatable to any previously known etiopathology of bone disorders. The soft tissue mass is of myxoid stroma with an unspecific granulomatous inflammatory process, aggressively destroying extensive cortical and cancellous bone segments and encroaching on articulating bones in diarthrodial large joints. Radiological, nuclear medical, serological, histological, and immunohistochemical analyses were incapable of further classifying the disease pattern within the existing scheme of pathology. Quantitative polymerase chain reaction and next generation sequencing revealed that mutations are not suggestive of any known hereditary or acquired bone disease. Possible treatment options include radionuclide therapy for pain palliation and percutaneous radiation to arrest bone resorption while surgical treatment is inevitable for pathological fractures. This case study shall increase the awareness of the musculoskeletal community and motivate to collect further information on this rare but mutilating disorder.

Experimental capture of miRNA targetomes: disease-specific 3'UTR library-based miRNA targetomics for Parkinson's disease.

The identification of targetomes remains a challenge given the pleiotropic effect of miRNAs, the limited effects of miRNAs on individual targets, and the sheer number of estimated miRNA-target gene interactions (MTIs), which is around 44,571,700. Currently, targetome identification for single miRNAs relies on computational evidence and functional studies covering smaller numbers of targets. To ensure that the targetome analysis could be experimentally verified by functional assays, we employed a systematic approach and explored the targetomes of four miRNAs (miR-129-5p, miR-129-1-3p, miR-133b, and miR-873-5p) by analyzing 410 predicted target genes, both of which were previously associated with Parkinson's disease (PD). After performing 13,536 transfections, we validated 442 of the 705 putative MTIs (62,7%) through dual luciferase reporter assays. These analyses increased the number of validated MTIs by at least 2.1-fold for miR-133b and by a maximum of 24.3-fold for miR-873-5p. Our study contributes to the experimental capture of miRNA targetomes by addressing i) the ratio of experimentally verified MTIs to predicted MTIs, ii) the sizes of disease-related miRNA targetomes, and iii) the density of MTI networks. A web service to support the analyses on the MTI level is available online ( https://ccb-web.cs.uni-saarland.de/utr-seremato ), and all the data have been added to the miRATBase database ( https://ccb-web.cs.uni-saarland.de/miratbase ).

A Multidisciplinary Hyper-Modeling Scheme in Personalized In Silico Oncology: Coupling Cell Kinetics with Metabolism, Signaling Networks, and Biomechanics as Plug-In Component Models of a Cancer Digital Twin.

The massive amount of human biological, imaging, and clinical data produced by multiple and diverse sources necessitates integrative modeling approaches able to summarize all this information into answers to specific clinical questions. In this paper, we present a hypermodeling scheme able to combine models of diverse cancer aspects regardless of their underlying method or scale. Describing tissue-scale cancer cell proliferation, biomechanical tumor growth, nutrient transport, genomic-scale aberrant cancer cell metabolism, and cell-signaling pathways that regulate the cellular response to therapy, the hypermodel integrates mutation, miRNA expression, imaging, and clinical data. The constituting hypomodels, as well as their orchestration and links, are described. Two specific cancer types, Wilms tumor (nephroblastoma) and non-small cell lung cancer, are addressed as proof-of-concept study cases. Personalized simulations of the actual anatomy of a patient have been conducted. The hypermodel has also been applied to predict tumor control after radiotherapy and the relationship between tumor proliferative activity and response to neoadjuvant chemotherapy. Our innovative hypermodel holds promise as a digital twin-based clinical decision support system and as the core of future in silico trial platforms, although additional retrospective adaptation and validation are necessary.