In silico identification of novel biomarkers for key players in transition from normal colon tissue to adenomatous polyps.

Autor: Isik Z; Faculty of Engineering, Department of Computer Engineering, Dokuz Eylul University, Izmir, Turkey., Leblebici A; Department of Translational Oncology, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey., Demir Karaman E; Department of Computer Engineering, Institute of Natural and Applied Sciences, Dokuz Eylul University, Izmir, Turkey., Karaca C; Department of Translational Oncology, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey., Ellidokuz H; Department of Preventive Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey., Koc A; Gentan Genetic Medical Genetics Diagnosis Center, Izmir, Turkey., Ellidokuz EB; Faculty of Medicine, Department of Gastroenterology, Dokuz Eylul University, Izmir, Turkey., Basbinar Y; Department of Translational Oncology, Institute of Oncology, Dokuz Eylul University, Izmir, Turkey.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2022 Apr 29; Vol. 17 (4), pp. e0267973. Date of Electronic Publication: 2022 Apr 29 (Print Publication: 2022).
DOI: 10.1371/journal.pone.0267973
Abstrakt: Adenomatous polyps of the colon are the most common neoplastic polyps. Although most of adenomatous polyps do not show malign transformation, majority of colorectal carcinomas originate from neoplastic polyps. Therefore, understanding of this transformation process would help in both preventive therapies and evaluation of malignancy risks. This study uncovers alterations in gene expressions as potential biomarkers that are revealed by integration of several network-based approaches. In silico analysis performed on a unified microarray cohort, which is covering 150 normal colon and adenomatous polyp samples. Significant gene modules were obtained by a weighted gene co-expression network analysis. Gene modules with similar profiles were mapped to a colon tissue specific functional interaction network. Several clustering algorithms run on the colon-specific network and the most significant sub-modules between the clusters were identified. The biomarkers were selected by filtering differentially expressed genes which also involve in significant biological processes and pathways. Biomarkers were also validated on two independent datasets based on their differential gene expressions. To the best of our knowledge, such a cascaded network analysis pipeline was implemented for the first time on a large collection of normal colon and polyp samples. We identified significant increases in TLR4 and MSX1 expressions as well as decrease in chemokine profiles with mostly pro-tumoral activities. These biomarkers might appear as both preventive targets and biomarkers for risk evaluation. As a result, this research proposes novel molecular markers that might be alternative to endoscopic approaches for diagnosis of adenomatous polyps.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
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