Identification of breast cancer hub genes and analysis of prognostic values using integrated bioinformatics analysis

Fang, Enhao; Zhang, Xiuqing

doi:10.3233/cbm-170550

Cited by 37 publications

(25 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In current, some relevant studies based on the database were published regarding hub genes in breast cancer. For instance, Fang et al identified 15 genes from one GEO datasets by bioinformatic approach including the raw data analysis of GSE10797, GO and KEGG pathway enrichment, PPI network construction and module analysis, survival analysis of hub genes, and Connectivity Map (cMap) database analysis (Fang and Zhang, 2017). Tang et al identified 10 hub genes in brain metastasis breast cancer from two GEO databases, and four hub gene expression of which were closely associated with the OS of breast cancer patients by developing an integrated method including GO and KEGG pathway enrichment analysis, PPI network analysis, hub gene identification, transcription factor (TF) analyses, and OS analysis (Tang et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

2019

View full text Add to dashboard Cite

Background: The molecular mechanism of tumorigenesis remains to be fully understood in breast cancer. It is urgently required to identify genes that are associated with breast cancer development and prognosis and to elucidate the underlying molecular mechanisms. In the present study, we aimed to identify potential pathogenic and prognostic differentially expressed genes (DEGs) in breast adenocarcinoma through bioinformatic analysis of public datasets. Methods: Four datasets (GSE21422, GSE29431, GSE42568, and GSE61304) from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) dataset were used for the bioinformatic analysis. DEGs were identified using LIMMA Package of R. The GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were conducted through FunRich. The protein-protein interaction (PPI) network of the DEGs was established through STRING (Search Tool for the Retrieval of Interacting Genes database) website, visualized by Cytoscape and further analyzed by Molecular Complex Detection (MCODE). UALCAN and Kaplan–Meier (KM) plotter were employed to analyze the expression levels and prognostic values of hub genes. The expression levels of the hub genes were also validated in clinical samples from breast cancer patients. In addition, the gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Results: In total, 203 up-regulated and 118 down-regulated DEGs were identified. Mitotic cell cycle and epithelial-to-mesenchymal transition pathway were the major enriched pathways for the up-regulated and down-regulated genes, respectively. The PPI network was constructed with 314 nodes and 1,810 interactions, and two significant modules are selected. The most significant enriched pathway in module 1 was the mitotic cell cycle. Moreover, six hub genes were selected and validated in clinical sample for further analysis owing to the high degree of connectivity, including CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK, and they were all correlated to worse overall survival (OS) in breast cancer. Conclusion: These results revealed that mitotic cell cycle and epithelial-to-mesenchymal transition pathway could be potential pathways accounting for the progression in breast cancer, and CDK1, CCNA2, TOP2A, CCNB1, KIF11, and MELK may be potential crucial genes. Further, it could be utilized as new biomarkers for prognosis and potential new targets for drug synthesis of breast cancer.

show abstract

Section: Discussionmentioning

confidence: 99%

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

2019

View full text Add to dashboard Cite

show abstract

“…The proteins, immune cells, vessels, and mural cells can become dysregulated during the progression of LSCC. Identification of these markers may provide value as prognostic tools (Fang & Zhang, 2017) and druggable targets (Finan et al, 2017). For example, Meng et al (2019) has identified differences in the immune microenvironment between LSCC and non-squamous NSCLCs and demonstrated the influence on patient prognosis.…”

Section: Introductionmentioning

confidence: 99%

Expression of collagen type 1 alpha 1 indicates lymph node metastasis and poor outcomes in squamous cell carcinomas of the lung

Dong

Zhu

Zhang

2020

PeerJ

View full text Add to dashboard Cite

Background Squamous cell carcinomas of the lung are an extremely common and deadly form of non-small cell lung cancers. Clinical management of the disease is dependent on staging and metastatic status. Metastasis to the lymph node is especially crucial to diagnose as it occurs at an earlier stage. However, lymphadenectomies are invasive and tumor cells may be overlooked during evaluation.There are limited approved biomarkers for predicting lymph node metastasis with squamous cell carcinomas of the lung (LSCC). Methods Genome data of 60 tumor-adjacent samples were downloaded from Genome Expression Omnibus. We identified over-expressed HUB genes using Cytoscape as key prognostic markers. The selected markers were further evaluated based on gene ontology and overall expression levels compared to normal tissue using The Cancer Genome Atlas. We further validated these results using clinical biopsy tissue taken from squamous cell carcinoma patients. Results Analysis of the genome expression data resulted in 13 relevant hub genes that were differentially expressed in cancerous samples. All of these genes are associated with collagen biosynthesis within the tumor microenvironment. We chose Collagen Type 1 Alpha 1 (COL1A1) as the most relevant prognostic marker due to its high number of pathway connections and over expression in the tumor microenvironment compared to the other 12 genes. Additionally, based on analysis of The Cancer Genome Atlas, tumors with higher levels of COL1A1 expression are associated with poorer overall survival. Finally, evaluation of clinical biopsy samples suggests that overexpression of COL1A1 in the LSCC microenvironment highly correlates with lymph node metastasis. These results suggest COL1A1 is a clinically relevant marker that should be used to justify lymphadenectomies.

show abstract

“…The dysfunction of ECM-receptor interaction may lead to the abnormal activation of signal transduction pathways, including Ras/ Raf/MAPK, Raf/JNK, Rho/RAC/Pak and PI3K/Akt/mTOR. So as to create a tumor microenvironment that can promote tumor survival, angiogenesis and invasion 29 . PI3K-Akt signaling pathway is the most common dysregulated pathway in many tumor cells.…”

Section: Discussionmentioning

confidence: 99%

Mechanism of Astragalus membranaceus in the treatment of laryngeal cancer based on gene co-expression network and molecular docking

Dong

Huo

Sun

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Astragalus membranaceus (HUANG QI, HQ) is a kind of traditional Chinese medicine. Researchers have widely concerned its antitumor effect. At present, there is still a lack of research on the treatment of laryngeal cancer with HQ. In this study, we integrated data from the weighted gene co-expression network of laryngeal cancer samples and the components and targets of HQ. A new method for dividing PPI network modules is proposed. Important targets of HQ treatment for laryngeal cancer were obtained through the screening of critical modules. These nodes performed differential expression analysis and survival analysis through external data sets. GSEA enrichment analysis reveals pathways for important targets participation. Finally, molecular docking screened active ingredients in HQ that could interact with important targets. Combined with the laryngeal cancer gene co expression network and HQ PPI network, we obtained the critical module related to laryngeal cancer. Among them, MMP1, MMP3, and MMP10 were chosen as important targets. External data sets demonstrate that their expression in tumor samples is significantly higher than in normal samples. The survival time of patients with high expression group was significantly shortened, which is a negative factor for prognosis. GSEA enrichment analysis found that they are mainly involved in tumor-related pathways such as ECM receptor interaction and Small cell lung cancer. The docking results show that the components that can well bind to important targets of HQ are quercetin, rutin, and Chlorogenic acid, which may be the primary mechanism of the anti-cancer effect of HQ. These findings provide a preliminary research basis for Chinese medicine treatment of laryngeal cancer and offer ideas to related drug design. Laryngeal cancer is one of the common malignant tumors of the head and neck, most of which are squamous cell carcinoma 1. It ranks second in the incidence of head and neck cancer (HNSC). The affected population is mainly middle-aged and older men over 40 years old, with a slight trend of youth 2. The occurrence and development of laryngeal cancer are related to many factors, including smoking, drinking, HPV infection, radiation, low intake of vegetables and fruits, insufficient trace elements, and disorders of sex hormone metabolism 3-5. In the early stage of laryngeal cancer, laser treatment has less damage and less postoperative complications 6. For most patients with laryngeal cancer, open surgery is still the main treatment. Radiotherapy and chemotherapy were used as auxiliary means 7. Targeted treatment of tumor can increase drug sensitivity, improve curative effect and reduce side effects 8. However, not all patients can benefit from it 9. Clearing tumors, preserving function, controlling recurrence, and improving quality of life are the goals of treating laryngeal cancer 5 .

show abstract

Identification of breast cancer hub genes and analysis of prognostic values using integrated bioinformatics analysis

Abstract: Fifteen genes were selected as hub genes because of high degrees, among which, low expression of four genes was associated with worse OS of patients with BC, including RPS9, RPL11, RPS14 and RPL10A. Additionally, the small molecular agent emetine may be a potential drug for BC.

Cited by 37 publications

References 40 publications

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

Identification of Potential Crucial Genes and Key Pathways in Breast Cancer Using Bioinformatic Analysis

Expression of collagen type 1 alpha 1 indicates lymph node metastasis and poor outcomes in squamous cell carcinomas of the lung

Mechanism of Astragalus membranaceus in the treatment of laryngeal cancer based on gene co-expression network and molecular docking

Contact Info

Product

Resources

About