Work

Editorial: Bioinformatics analysis of omics data for biomarker identification in clinical research, Volume II

Year: 2023

Type: editorial

Abstract: Bioinformatics analysis of omics data for biomarker identification in clinical research, Volume II Biomarker identification is one of the essential steps in omics data analysis for biomedical research.Significant advances have been achieved in the field of omics data and the ever-lower price have made it more and more easy to investigate the molecular features of multi-types of diseases at various levels, like animal models, bulk tissues, and single cells.The abundant information contained in the omics data provides solid foundation for preclinical research and the development of new disease treatment strategies, including understanding disease mechanisms, finding molecular targets, and identifying biomarkers.Following the success of our Research Topic on the first volume on biomarker identification in clinical research based on omics data analysis, we make further remarkable progress of soliciting more than 50 impressive research articles in our Volume II in this Research Topic.Eighteen papers aimed at detecting biomarkers from omics data generated from various tumors and diseases.Ning et al. showed that ANXA2 expression was significantly correlated with immune infiltration and might potentially serve as a prognostic biomarker for tumors. Specifically, by performing differential expression analysis, Ning et al. revealed that a high expression of ANXA2 was associated with reduced overall survival, disease-specific survival and progression-free interval in seven cancers.They also found that ANXA2 expression was related to immune cell infiltration and immune-related pathways in cancers, suggesting that it can function as a potential target for immunotherapy in pan-cancer.With the help of network pharmacology and molecular docking technology, Chen et al. studied the therapeutic mechanism of 4-octyl itaconate (4-OI), a cell-permeable derivative of itaconate, and found that 4-OI treats sepsis by regulating hub genes.The enrichment analysis further revealed that 4-OI participated in inflammatory imbalance, immunosuppression, and oxidative stress in developing sepsis.In another study, Cui et al. characterized the role of serine racemase (SRR) as a prognostic biomarker in endometrial cancer.By conducting differential expression analysis and GEO data mining, Yu et al. identified the correlation between immune cell types and recurrent implantation failure (RIF).They also provided new immune-related hub genes that serve

Source: Frontiers in Genetics

DOI: 10.3389/fgene.2023.1256468

Authors: Mengtao Sun, Lusheng Li, Hanyu Xiao, Junxi Feng, Jieqiong Wang, Shibiao Wan

Institutions: University of Nebraska Medical Center, Harvard University

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,295