ArticlePeerJ2021
Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis.
Article in PeerJ, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 34 citations in OpenAlex.
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- Prognostic and immunotherapeutic significance of NCAPD2 in pan-cancer and its role in hepatocellular carcinoma progression via the AKT/GSK-3β signaling pathway.Scientific reports · 2025Article
- Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction.BMC bioinformatics · 2024Article
- Proteo-genomic characterization of cirrhosis-associated liver cancers reveals potential subtypes and therapeutic targets.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024Article
- Function-Genes and Disease-Genes Prediction Based on Network Embedding and One-Class Classification.Interdisciplinary sciences, computational life sciences · 2024Article
- NCAPD2 augments the tumorigenesis and progression of human liver cancer via the PI3K‑Akt‑mTOR signaling pathway.International journal of molecular medicine · 2024Article
- Comparative proteomic profiling of the ovine and human PBMC inflammatory response.Scientific reports · 2024Article
- NCPAD2 is a favorable predictor of prognostic and immunotherapeutic biomarker for multiple cancer types including lung cancer.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2024Article
- NCAPD2 serves as a potential prognostic biomarker for lung adenocarcinoma and promotes cell proliferation, migration, invasion and cell cycleOncology research · 2024Article
- A functional gene module identification algorithm in gene expression data based on genetic algorithm and gene ontology.BMC genomics · 2023Article
- Deciphering the Divergent Gene Expression Landscapes of m6A/m5C/m1A Methylation Regulators in Hepatocellular Carcinoma Through Single-Cell and Bulk RNA Transcriptomic Analysis.Journal of hepatocellular carcinoma · 2023Article
- Identification of Differentially Expressed Genes Associated with the Prognosis and Diagnosis of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis.BioMed research international · 2022Article
- Machine learning algorithm and deep neural networks identified a novel subtype in hepatocellular carcinoma.Cancer biomarkers : section A of Disease markers · 2022Article
- Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatocellular carcinoma (HCC), the main type of liver cancer in human, is one of the most prevalent and deadly malignancies in the world. The present study aimed to identify hub genes and key biological pathways by integrated bioinformatics analysis.
methodsA bioinformatics pipeline based on gene co-expression network (GCN) analysis was built to analyze the gene expression profile of HCC. Firstly, differentially expressed genes (DEGs) were identified and a GCN was constructed with Pearson correlation analysis. Then, the gene modules were identified with 3 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Moreover, we used the Search Tool for the Retrieval of Interacting Genes (STRING) database to construct a protein protein interaction (PPI) network of the key gene module, and we identified the hub genes using nine topology analysis algorithms based on this PPI network. Further, we used the Oncomine analysis, survival analysis, GEO data set and random forest algorithm to verify the important roles of hub genes in HCC. Lastly, we explored the methylation changes of hub genes using another GEO data (GSE73003).
resultsFirstly, among the expression profiles, 4,130 up-regulated genes and 471 down-regulated genes were identified. Next, the multi-level algorithm which had the highest modularity divided the GCN into nine gene modules. Also, a key gene module (m1) was identified. The biological processes of GO enrichment of m1 mainly included the processes of mitosis and meiosis and the functions of catalytic and exodeoxyribonuclease activity. Besides, these genes were enriched in the cell cycle and mitotic pathway. Furthermore, we identified 11 hub genes,
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Registered trials
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