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Iranian Journal of Biotechnology، جلد ۲۰، شماره ۳، صفحات ۱-۱۱
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عنوان انگلیسی Meta-Analysis of EGF-Stimulated Normal and Cancer Cell Lines to Discover EGF-Associated Oncogenic Signaling Pathways and Prognostic Biomarkers
چکیده انگلیسی مقاله Background: Although epidermal growth factor (EGF) controls many crucial processes in the human body, it can increase the risk of developing cancer when overexpresses.
Objectives: This study focused on detecting cancer-associated genes that are dysregulated by EGF overexpression.
Materials and Methods: To identify differentially expressed genes (DEGs), two independent meta-analyses with normal and cancer RNA-Seq samples treated by EGF were conducted. The new DEGs detected only via two meta-analyses were used in all downstream analyses. To reach count data, the tools of FastQC, Trimmomatic, HISAT2, SAMtools, and HTSeq-count were employed. DEGs in each individual RNA-Seq study and the meta-analysis of RNA-Seq studies were identified using DESeq2 and metaSeq R package, respectively. MCODE detected densely interconnected top clusters in the protein-protein interaction (PPI) network of DEGs obtained from normal and cancer datasets. The DEGs were then introduced to Enrichr and ClueGO/CluePedia, and terms, pathways, and hub genes enriched in Gene Ontology (GO) and KEGG and Reactome were detected.
Results: The meta-analysis of normal and cancer datasets revealed 990 and 541 new DEGs, all upregulated. A number of DEGs were enriched in protein K48-linked deubiquitination, ncRNA processing, ribosomal large subunit binding, and protein processing in endoplasmic reticulum. Hub genes overexpression (DHX33, INTS8, NMD3, OTUD4, P4HB, RPS3A, SEC13, SKP1, USP34, USP9X, and YOD1) in tumor samples were validated by TCGA and GTEx databases. Overall survival and disease-free survival analysis also confirmed worse survival in patients with hub genes overexpression.
Conclusions: The detected hub genes could be used as cancer biomarkers when EGF overexpresses.
کلیدواژه‌های انگلیسی مقاله Biomarker,cancer,EGF,Meta-analysis,RNA-Seq
نویسندگان مقاله Shahrokh Garousi |
Department of plant genetics and production engineering, Faculty of agriculture and natural resources, University of Mohaghegh Ardabili, Ardabil, Iran

Soodabeh Jahanbakhsh Godehkahriz |
Department of plant genetics and production engineering, Faculty of agriculture and natural resources, University of Mohaghegh Ardabili, Ardabil, Iran.

Kasra Esfahani |
Plant Bioproducts Department, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.

Tahmineh Lohrasebi |
Plant Bioproducts Department, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.

Amir Mousavi |
Plant Molecular Biotechnology Department, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.

Ali Hataf Salmanian |
Plant Bioproducts Department, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.

Mahsa Rezvani |
Institute of Agricultural Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.

Maryam Moein |
Institute of Agricultural Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran.

نشانی اینترنتی https://www.ijbiotech.com/article_152853_360d556ef53d2b098a63134b2156b85c.pdf
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