Publications by authors named "E S Vasileva"

Echinochrome A (EchA), a marine-derived natural product, has shown promise in treating cardiovascular and inflammatory diseases due to its antioxidant and anti-inflammatory properties. However, its cardiac safety remains underexplored. In this study, we utilized human induced pluripotent stem cell-derived cardiac organoids (hCOs) to validate their ability to model the cardiac safety profile of EchA in a human-relevant system.

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Ewing sarcoma is a malignant small round blue cell tumor of bones and soft tissues caused by chromosomal translocations that generate aberrant fusion oncogenes, most frequently EWSR1::FLI1. The cell of origin and mechanisms of EWSR1::FLI1-driven transformation have remained unresolved, largely due to lack of a representative animal model. By developing a zebrafish Ewing sarcoma model, we provide evidence for a neural crest origin of this cancer.

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Chemerin and resistin are adipokines studied as potential markers for early diagnosis and disease severity in patients with knee osteoarthritis (KOA) Therefore, we aimed to investigate the associations serum and synovial levels of chemerin and resistin with inflammatory parameters and ultrasonographic scores (US) in KOA individuals. Serum was collected from 28 patients with KOA and synovial fluid was obtained from 16 of them. Another 31 age and sex matched cases with no joint disease were included as healthy controls.

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Echinochrome A (Ech A), a marine biosubstance isolated from sea urchins, is a strong antioxidant, and its clinical form, histochrome, is being used to treat several diseases, such as ophthalmic, cardiovascular, and metabolic diseases. Cancer-associated fibroblasts (CAFs) are a component of the tumor stroma and induce phenotypes related to tumor malignancy, including epithelial-mesenchymal transition (EMT) and cancer stemness, through reciprocal interactions with cancer cells. Here, we investigated whether Ech A modulates the properties of CAFs and alleviates CAF-induced lung cancer cell migration.

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With the increased use of gene expression profiling for personalized oncology, optimized RNA sequencing (RNA-seq) protocols and algorithms are necessary to provide comparable expression measurements between exome capture (EC)-based and poly-A RNA-seq. Here, we developed and optimized an EC-based protocol for processing formalin-fixed, paraffin-embedded samples and a machine-learning algorithm, Procrustes, to overcome batch effects across RNA-seq data obtained using different sample preparation protocols like EC-based or poly-A RNA-seq protocols. Applying Procrustes to samples processed using EC and poly-A RNA-seq protocols showed the expression of 61% of genes (N = 20,062) to correlate across both protocols (concordance correlation coefficient > 0.

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