ArticleCancer biology & medicine2022
Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets.
Article in Cancer biology & medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Hypoxia upregulates the expression of PD-L1 via NPM1 in breast cancer.Journal for immunotherapy of cancer · 2025Article
- From complexity to clarity: development of CHM-FIEFP for predicting effective components in Chinese herbal formulas by using big data.Cancer biology & medicine · 2024Article
- Identification of HTRA1, DPT and MXRA5 as potential biomarkers associated with osteoarthritis progression and immune infiltration.BMC musculoskeletal disorders · 2024Article
- Study on the mechanism of heterogeneous tumor-associated macrophages in three subtypes of breast cancer through the integration of single-cell RNA sequencing and in vitro experiments.Molecular biology reports · 2024Article
- Unveiling Collagen's Role in Breast Cancer: Insights into Expression Patterns, Functions and Clinical Implications.International journal of general medicine · 2024Review
- Blood regulator of G protein signalling 1 as a potential prognostic biomarker in surgical nonsmall cell lung cancer patients: Correlation with clinical features and survival.The clinical respiratory journal · 2024Article
- Understanding the mechanisms underlying obesity in remodeling the breast tumor immune microenvironment: from the perspective of inflammation.Cancer biology & medicine · 2023Review
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe aim of this study was to identify hub genes associated with immune cell infiltration in breast cancer through bioinformatic analyses of multiple datasets.
methodsNonparametric (NOISeq) and robust rank aggregation-ranked parametric (EdgeR) methods were used to assess robust differentially expressed genes across multiple datasets. Protein-protein interaction network, GO, KEGG enrichment, and sub-network analyses were performed to identify immune-associated hub genes in breast cancer. Immune cell infiltration was evaluated with the CIBERSORT, XCELL, and TIMER methods. The association between the hub gene-based risk signature and survival was determined through Kaplan-Meier survival analysis, multivariate Cox analysis, and a nomogram with external verification.
resultsWe identified 163 robust differentially expressed genes in breast cancer through applying both nonparametric and parametric methods to multiple GEO (
conclusionsIntegrated analyses of multiple databases led to the discovery of 10 robust hub genes that together may serve as a risk factor characteristic of the immune microenvironment in breast cancer.
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