Advanced stage, high-grade primary tumor ovarian cancer: a multi-omics dissection and biomarker prediction process.
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ABSTRACT: Ovarian cancer (OC) incidence and mortality rates continue to escalate globally. Early detection of OC is challenging due to extensive metastases and the ambiguity of biomarkers in advanced High-Grade Primary Tumors (HGPTs). In the present study, we conducted an in-depth in silico analysis in OC cell lines using the Gene Expression Omnibus (GEO) microarray dataset with 53 HGPT and 10 normal samples. Differentially-Expressed Genes (DEGs) were also identified by GEO2r. A variety of analyses, including gene set enrichment analysis (GSEA), ChIP enrichment analysis (ChEA), eXpression2Kinases (X2K) and Human Protein Atlas (HPA), elucidated signaling pathways, transcription factors (TFs), kinases, and proteome, respectively. Protein-Protein Interaction (PPI) networks were generated using STRING a
SUBMITTER: Honar YS
PROVIDER: S-EPMC10570268 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
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