ArticleCancer biomarkers : section A of Disease markers2020
Integrative analyses of molecular pathways and key candidate biomarkers associated with colorectal cancer.
Article in Cancer biomarkers : section A of Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- A combined transcriptomic, epigenetic, and functional analysis identifies novel biomarkers in breast cancer.Hereditas · 2025Article
- A pancancer analysis of the oncogenic role of cyclin B1 (CCNB1) in human tumors.Scientific reports · 2023Article
- Bioinformatics screening of colorectal-cancer causing molecular signatures through gene expression profiles to discover therapeutic targets and candidate agents.BMC medical genomics · 2023Article
- Candidate Genes and Pathways in Cervical Cancer: A Systematic Review and Integrated Bioinformatic Analysis.Cancers · 2023Review
- Article
- Prognostic Impact and Functional Annotations of KIF11 and KIF14 Expression in Patients with Colorectal Cancer.International journal of molecular sciences · 2021Article
- Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis.Cancer cell international · 2021Article
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1 author.
Funding
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Abstract
backgroundColorectal cancer (CRC) is one of the leading causes of cancer-related deaths and mining the molecular factors underlying CRC pathogenesis is imperative for alleviating the disease burden.
objectiveTo highlight key molecular pathways, prioritize hub genes and their regulators related to CRC.
methodsData sets of TCGA-COAD and GTEx were used to identify differentially expressed genes (DEGs) and their functional enrichments in pathways and biological processes were analyzed using bioinformatics tools. Protein-protein interaction network was constructed and hub genes were identified using Cytoscape. Ingenuity Pathway Analysis was used to analyze the relations of the hub genes with diseases and canonical pathways. Key regulators targeting the hub genes such as TFs, miRNAs and their interactions were identified using in silico tools.
resultsAURKA, CDK1, MYC, CDH1, CCNB1, CDC20, UBE2C, PLK1, KIF11, and CCNA2 were prioritized as hub genes based on their topological properties. Enrichment analyses emphasized the roles of DEGs and hub genes in the cell cycle process. Interactions of the hub genes with TFs and miRNAs suggested TP53, EZH2 and KLF4 as being promising candidate biomarkers for CRC.
conclusionsOur results provide in silico evidence for candidate biomolecules that may have strong biomarker potential for CRC-related translational strategies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.