ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Identification of Hub Genes Using Co-Expression Network Analysis in Breast Cancer as a Tool to Predict Different Stages.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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24 citing papers in PubMed, 26 citations in OpenAlex.
- Literature-informed gene extraction and ranking for multimodal data fusion.Briefings in bioinformatics · 2026Article
- Integrated Analysis of Bulk and Single-Cell Transcriptomics Identifies Prognostic Biomarkers in Breast Cancer Metastasis.Biochemical genetics · 2026Article
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- Representation Methods of Transcriptomics with Applications in Neuroimmune Biology.bioRxiv : the preprint server for biology · 2026Article
- Genome-wide cis-expression Quantitative Trait Loci (eQTL) and transcriptomic signals reveal distinct molecular regulation across correlated feed efficiency traits.Frontiers in genetics · 2026Article
- Evaluation of genes and molecular pathways involved in ferroptosis in breast cancer: A systems biology and bioinformatics approach.Biochemistry and biophysics reports · 2025Article
- Biophysical investigation of the molecular interaction between minichromosome maintenance protein 6 and Bloom syndrome helicase.The FEBS journal · 2025Article
- Identification of candidate biomarkers correlated with the pathogenesis of breast cancer patients.Scientific reports · 2025Article
- Human CKAP2L shows a cell cycle-dependent expression pattern and exhibits microtubule-stabilizing properties.FEBS open bio · 2024Article
- Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer.Medicina (Kaunas, Lithuania) · 2023Article
- Review
- Integrative bioinformatics and RNA sequencing based methodology results in the exploration of breast invasive carcinoma biomarkers.American journal of translational research · 2023Article
- Combined analysis of expression, prognosis and immune infiltration of GINS family genes in human sarcoma.Aging · 2022Article
- Knockdown of CDCA5 suppresses malignant progression of breast cancer cells by regulating PDS5A.Molecular medicine reports · 2022Article
- KIF18B promotes breast cancer cell proliferation, migration and invasion by targeting TRIP13 and activating the Wnt/β-catenin signaling pathway.Oncology letters · 2022Article
- Effect of CDCA5 on Proliferation and Metastasis of Triple Negative Breast Cancer Cells under shRNA Interference Technology.Journal of oncology · 2022Article
- Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis and clinical data from The Cancer Genome Atlas.Bioscience reports · 2021Article
- Bioinformatics identification of hub genes and signaling pathways regulated by intravenous immunoglobulin treatment in acute Kawasaki disease.Experimental and therapeutic medicine · 2021Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Breast cancer has a high mortality rate and is the most common cancer of women worldwide. Our gene co-expression network analysis identified the genes closely related to the pathological stage of breast cancer. MATERIAL AND METHODS We performed weighted gene co-expression network analysis (WGCNA) from the Gene Expression Omnibus (GEO) database, and performed pathway enrichment analysis on genes from significant modules. RESULTS A non-metastatic sample (374) of breast cancer from GSE102484 was used to construct the gene co-expression network. All 49 hub genes have been shown to be upregulated, and 19 of the 49 hub genes are significantly upregulated in breast cancer tissue. The roles of the genes CASC5, CKAP2L, FAM83D, KIF18B, KIF23, SKA1, GINS1, CDCA5, and MCM6 in breast cancer are unclear, so in order to better reveal the staging of breast cancer markers, it is necessary to study those hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes indicated that 49 hub genes were enriched to sister chromatid cohesion, spindle midzone, microtubule motor activity, cell cycle, and something else. Additionally, there is an independent data set - GSE20685 - for module preservation analysis, survival analysis, and gene validation. CONCLUSIONS This study identified 49 hub genes that were associated with pathologic stage of breast cancer, 19 of which were significantly upregulated in breast cancer. Risk stratification, therapeutic decision making, and prognosis predication might be improved by our study results. This study provides new insights into biomarkers of breast cancer, which might influence the future direction of breast cancer research.
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