RESUMO
Osteosarcoma (OS), a primary malignant bone tumor, poses significant challenges in diagnosis and prognosis. It is a painful medical burden, and treating it is still a difficult issue. Osteopontin (OPN), a multifunctional extracellular matrix protein, has emerged as a promising biomarker in this context. This systematic review explores the role of OPN as a diagnostic and prognostic marker in OS, highlighting its potential in enhancing early detection, monitoring disease progression, and predicting patient outcomes. Various studies have demonstrated elevated levels of OPN in OS patients, correlating with tumor aggressiveness, metastatic potential, and poor prognosis. In addition, OPN's involvement in tumor microenvironment regulation and metastatic processes underscores its clinical relevance as a biomarker. For this systematic review, comprehensive literature searches were conducted in the PubMed databases for research published between the database's establishment and November 11, 2022. Out of the nine studies that were available for analysis, a higher level of OPN in primary osteogenic sarcoma patients indicates a poorer prognosis and higher incidence of metastasis. OS has not shown commensurable progress with concerns to treatment approches and survical outcomes. However, the discovery of a biological marker that can predict metastasis and severity will be a groundbreaking development for advancements in OS diagnosis and treatment. Therefore, understanding the intricate interplay between OPN and OS pathogenesis holds promise for improving patient management and developing targeted therapeutic strategies.
RESUMO
COVID-19 related morbidities and mortalities are still continued due to the emergence of new variants of SARS-CoV-2. In the last few years, viral miRNAs have been the centre of study to understand the disease pathophysiology. In this work, we aimed to predict the change in coding potential of the viral miRNAs in SARS-CoV-2's VOCs, Delta and Omicron compared to the Reference (Wuhan origin) strain using bioinformatics tools. After ab-intio based screening by the Vmir tool and validation, we retrieved 22, 6, and 6 pre-miRNAs for Reference, Delta, and Omicron. Most of the predicted unique pre-miRNAs of Delta and Omicron were found to be encoded from the terminal and origin of the genomic sequence, respectively. Mature miRNAs identified by MatureBayes from the unique pre-miRNAs were used for target identification using miRDB. A total of 1786, 216, and 143 high-confidence target genes were captured for GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis. The GO and KEGG pathways terms analysis revealed the involvement of Delta miRNAs targeted genes in the pathways such as Human cytomegalovirus infection, Breast cancer, Apoptosis, Neurotrophin signaling, and Axon guidance whereas the Sphingolipid signaling pathway was found for the Omicron. Furthermore, we focussed our analysis on target genes that were validated through GEO's (Gene Expression Omnibus) DEGs (Differentially Expressed Genes) dataset, in which FGL2, TNSF12, OGN, GDF11, and BMP11 target genes were found to be down-regulated by Reference miRNAs and YAE1 and RSU1 by Delta. Few genes were also observed to be validated among in up-regulated gene set of the GEO dataset, in which MMP14, TNFRSF21, SGMS1, and TMEM192 were related to Reference whereas ZEB2 was detected in all three strains. This study thus provides an in-silico based analysis that deciphered the unique pre-miRNAs in Delta and Omicron compared to Reference. However, the findings need future wet lab studies for validation.