ArticleOncology letters2018
Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation.
Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Recent Multiomics Approaches in Endometrial Cancer.International journal of molecular sciences · 2022Review
- Transcriptome analysis of sinensetin-treated liver cancer cells guided by biological network analysis.Oncology letters · 2021Article
- Colitis-induced IL11 promotes colon carcinogenesis.Carcinogenesis · 2021Article
- Current Achievements and Applications of Transcriptomics in Personalized Cancer Medicine.International journal of molecular sciences · 2021Review
- INTS7-ABCD3 Interaction Stimulates the Proliferation and Osteoblastic Differentiation of Mouse Bone Marrow Mesenchymal Stem Cells by Suppressing Oxidative Stress.Frontiers in physiology · 2021Article
- Network-based identification of biomarkers for colon adenocarcinoma.BMC cancer · 2020Article
- Abnormal expression of ABCD3 is an independent prognostic factor for colorectal cancer.Oncology letters · 2020Article
- Exploration of an Prognostic Signature Related to Endoplasmic Reticulum Stress in Colorectal Adenocarcinoma and Their Response Targeting Immunotherapy.Technology in cancer research & treatmentArticle
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Authors and funding
3 authors.
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Abstract
The aim of the present study was to investigate more colon cancer-related genes in different stages. Gene expression profile E-GEOD-62932 was extracted for differentially expressed gene (DEG) screening. Series test of cluster analysis was used to obtain significant trending models. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, functional and pathway enrichment analysis were processed and a pathway relation network was constructed. Gene co-expression network and gene signal network were constructed for common DEGs. The DEGs with the same trend were clustered and in total, 16 clusters with statistical significance were obtained. The screened DEGs were enriched into small molecule metabolic process and metabolic pathways. The pathway relation network was constructed with 57 nodes. A total of 328 common DEGs were obtained. Gene signal network was constructed with 71 nodes. Gene co-expression network was constructed with 161 nodes and 211 edges. ABCD3, CPT2, AGL and JAM2 are potential biomarkers for the diagnosis of colon cancer.
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