ArticleCancer gene therapy2022
Identification of a five genes prognosis signature for triple-negative breast cancer using multi-omics methods and bioinformatics analysis.
Article in Cancer gene therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 41 citations in OpenAlex.
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- Overexpression of cytoplasmic poly(A)-binding protein 1 as a biomarker for the prognosis and selection of postoperative regimen in breast cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- MASP1 modulation as a novel therapeutic target in severe pediatric pertussis: insights from a multi-omics approach.Infection and immunity · 2025Article
- Association of microtubule-based processes gene expression with immune microenvironment and its predictive value for drug response in oestrogen receptor-positive breast cancer.Frontiers in immunology · 2025Article
- Mechanistic insights curcumin's anti-inflammatory in pancreatic cancer: experimental and computational evidence implicating IL1B interferenceFrontiers in cell and developmental biology · 2025Article
- Comprehensive analysis of the metabolomics and transcriptomics uncovers the dysregulated network and potential biomarkers of Triple Negative Breast Cancer.Journal of translational medicine · 2024Article
- The crucial prognostic signaling pathways of pancreatic ductal adenocarcinoma were identified by single-cell and bulk RNA sequencing data.Human genetics · 2024Article
- Article
- Deciphering the miRNA-mRNA Interaction Landscape between Breast Cancer and Triple-Negative Breast Cancer: An Integrated Bioinformatics Approach.ACS omega · 2024Article
- An engineered niche delineates metastatic potential of breast cancer.Bioengineering & translational medicine · 2024Article
- Characterization of protein-based risk signature to predict prognosis and evaluate the tumor immune environment in breast cancer.Breast cancer (Tokyo, Japan) · 2023Article
- Identification of key genes and pathways in adrenocortical carcinoma: evidence from bioinformatic analysis.Frontiers in endocrinology · 2023Article
- Construction of a prognostic 6-gene signature for breast cancer based on multi-omics and single-cell data.Frontiers in oncology · 2023Article
- Overview of triple negative breast cancer prognostic signatures in the context of data science-driven clinico-genomics research.Annals of translational medicine · 2022Article
- High expression of hypoxia-inducible factor 1-alpha predicts poor prognosis in pancreatic ductal adenocarcinoma: a meta-analysis and database validation protocol.Translational cancer research · 2022Article
- Gene expression profile analysis to discover molecular signatures for early diagnosis and therapies of triple-negative breast cancer.Frontiers in molecular biosciences · 2022Article
- Identification and validation of a 17-gene signature to improve the survival prediction of gliomas.Frontiers in immunology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Triple-negative breast cancer (TNBC) has a high degree of malignancy, lack of effective diagnosis and treatment, and poor prognosis. Bioinformatics methods are used to screen the hub genes and signal pathways involved in the progress of TNBC to provide reliable biomarkers for the diagnosis and treatment of TNBC. Download the raw data of four TNBC-related datasets from the Gene Expression Omnibus (GEO) database and use them for bioinformatics analysis. GEO2R tool was used to analyze and identify differentially expressed (DE) mRNAs. DAVID database was used to carry out gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genome Pathways (KEGG) signal pathway enrichment analysis for DE mRNAs. STRING database and Cytoscape were used to build DE mRNAs protein-protein interaction (PPI) network diagram and visualize PPI network, respectively. Through cytoHubba, cBioPortal database, Kaplan-Meier mapper database, Gene Expression Profiling Interactive Analysis (GEPIA) Database, UALCAN Database, The Cancer Genome Atlas (TCGA) database, Tumor Immunity Estimation Resource identify hub genes. Perform qRT-PCR, Human Protein Atlas analysis, mutation analysis, survival analysis, clinical-pathological characteristics, and infiltrating immune cell analysis. 22 DE mRNAs were identified from the four datasets, including 16 upregulated DE mRNAs and six downregulated DE mRNAs. Enrichment analysis of the KEGG showed that DE mRNAs were principally enriched in pathways in cancer, mismatch repair, cell cycle, platinum drug resistance, breast cancer. Six hub genes were screened based on the PPI network diagram of DE mRNAs. Survival analysis found that TOP2A, CCNA2, PCNA, MSH2, CDK6 are related to the prognosis of TNBC. In addition, mutations, clinical indicators, and immune infiltration analysis show that these five hub genes play an important role in the progress of TNBC and immune monitoring. Compared with MCF-10A, MCF-7, and SKBR-3 cells, TOP2A, PCNA, MSH2, and CDK6 were significantly upregulated in MDA-MB-321 cells. Compared with normal, luminal, and Her-2 positive tissues, CCNA2, MSH2, and CDK6 were significantly upregulated in TNBC. Through comparative analysis of GEO datasets related to colorectal cancer and lung adenocarcinoma, it was determined that these five hub genes were unique differentially expressed genes of TNBC. At last, the hub genes related to the progression, prognosis, and immunity of TNBC have been successfully screened. They are indeed specific to TNBC as prognostic features. They can be used as potential markers for the prognosis of TNBC and provide potential therapeutic targets.
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