Although variants of uncertain significance (VUS) cannot be clearly defined and classified, VUS make up about 40% of the total variants in human, and their impact on the function or health of the organism is not known. It is necessary to implement a new and systematic experimental approach for the characterization of VUS at high throughput, and to contribute to the reduction of the amount of VUS in the relevant databases for a better understanding of genomic variation in humans.

EASIGEN-DS is about the establishment of a distributed European Research Infrastructure (RI) on Advanced Genomics Technologies. The project aims to become a world-leading research infrastructure in genomics, which is fully integrated into the European landscape. The project is expected to strengthen European capacity in sequencing technology, with a particular focus on third-generation sequencing offering longer reads and the ability to sequence without the need for amplification, and on single cell genomics and spatial transcriptomics.

The GoE project will create the first large-scale repository of genomic and phenotypic data in Europe, filling an important existing gap and removing dependence from non-European repositories for research and clinical applications. At the same time, it will also improve competitiveness by building key expertise and facilities for large-scale genomic analyses paving the way for additional data collection in the future. This project will bring Europe in line with similar ongoing projects in other countries including the US, China and Qatar. The benefits for society include applications in personalised medicine as well as the development of intellectual property in the EU based on complex large-scale genome data.

The goal of the GDI project is to create a cross-border platform for the collection of genomic data for biomedical research and individualized medical solutions. The project is financed by the funds of the European Commission through the Digital Europe Program and by the countries participating in the project.

The Hedgehog-GLI (HH-GLI) signalling pathway is an important regulator of embryonic development, while it is mostly inactive in the adult organism. It only remains active in somatic stem cells. Aberrant activation of the pathway contributes to tumorigenesis in many tumor types. The GLI1, GLI2 and GLI3 transcription factors regulate gene expression of targets involved in proliferation, metastasis and cancer stem cell renewal. In our previous research we were the first to analyse the transcriptomes of all three GLI proteins in melanoma, and we have identified a large number of target genes, some of them previously known from literature data, but also some novel.

EVroPAR is a Slovenian-Croatian multidisciplinary research project which combines basic, preclinical and clinical research, including partners from Ruđer Bošković Institute (Croatia), Institute of Biochemistry (Faculty of Medicine in Ljubljana, Slovenia), University Foundation San Pablo CEU (Spain), University Hospital Centre Zagreb (Croatia), University Psychiatric Clinic Ljubljana (Slovenia) and Labena d.o.o. (Slovenia). Project incorporates cutting-edge metabolomics approach and miRNA profiling in order to identify novel biomarkers that could help clinicians to tailor treatment strategies in depression for individual patients. Currently available therapy for depression involves pharmacotherapy combined with psychotherapy, while dealing with poor response/nonresponse and a frequent discontinuation of treatment. The objective of the study is to give better insights into the efficacy and molecular mechanisms behind the effects of a widely used antidepressant (duloxetine), and compare this to the mechanism behind the effects of alternative methods of treatment in patients with treatment-resistant depression (transcranial magnetic stimulation (TMS), phototherapy (bright light therapy, BTL), esketamine treatment). The study will focus on circulating extracellular vesicles (EVs) as easily obtainable and non-invasive biomarkers. We aim to measure the dysregulation of epigenetic markers, the EV miRNA expression, and to determine metabolic alterations in four groups of patients (duloxetine vs. BLT vs. TMS vs. esketamine), by sampling 50 patients per group before and after the treatment. Another goal is to identify specific metabolic and miRNA signatures of depression by comparing patients with an appropriate control group (100 subjects). We expect that new biomarkers identified in this project will help determine treatment efficiency in depression and predict good/poor response to treatment, as a key step towards the inevitable personalized and effective medicine approach.