ArticleIranian journal of biotechnology2022
Meta-Analysis of EGF-Stimulated Normal and Cancer Cell Lines to Discover EGF-Associated Oncogenic Signaling Pathways and Prognostic Biomarkers.
Article in Iranian journal of biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- [Risk modeling based on HER-2 related genes for bladder cancer survival prognosis assessment].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2023Article
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Authors and funding
8 authors at 1 institution in 1 country.
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Abstract
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.
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