ArticleFrontiers in oncology2023
Prognostic analysis of patients with breast cancer based on tumor mutational burden and DNA damage repair genes.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 8 citations in OpenAlex.
- PSMB1 screened by CRISPR-CAS9 promoted breast cancer progression via PI3K-AKT-mTOR signaling.Discover oncology · 2026Article
- FOXM1 Signaling Network Transcriptionally Upregulates Expression of Proteins Involved in Mitotic Progression to Induce High Proliferation and Chromosomal Instability in Androgen Receptor-Low Triple-Negative Breast Cancer.International journal of molecular sciences · 2026Article
- Integrated machine learning and bioinformatic analyses constructed a sulfur metabolism-related breast cancer risk model and identified heat-shock protein A9 as a potential therapeutic target for human breast cancer.Discover oncology · 2026Article
- PSMD14 as a translational target in cancer and beyond: from deubiquitination mechanisms to drug resistance and precision therapy.Cancer drug resistance (Alhambra, Calif.) · 2026Review
- Breaking Barriers: Immune Checkpoint Inhibitors in Breast Cancer.Pharmaceutics · 2025Review
- Tumor Imaging Heterogeneity Index-Inspired Insights into the Unveiling Tumor Microenvironment of Breast Cancer.International journal of molecular sciences · 2025Article
- Circulating tumor DNA predicts clinical benefits of immune checkpoint blockade in HER2-negative patients with advanced gastric cancer.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2025Article
- Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature.Journal of cellular and molecular medicine · 2024Article
- Synthetic Lethality between Cohesin and WNT Signaling Pathways in Diverse Cancer Contexts.Cells · 2024Article
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Breast cancer has a high tumor-specific death rate and poor prognosis. In this study, we aimed to provide a basis for the prognostic risk in patients with breast cancer using significant gene sets selected by analyzing tumor mutational burden (TMB) and DNA damage repair (DDR). Methods: Breast cancer genomic and transcriptomic data were obtained from The Cancer Genome Atlas (TCGA). Breast cancer samples were dichotomized into high- and low-TMB groups according to TMB values. Differentially expressed DDR genes between high- and low-TMB groups were incorporated into univariate and multivariate cox regression model to build prognosis model. Performance of the prognosis model was validated in an independently new GEO dataset and evaluated by time-dependent ROC curves. Results: Between high- and low-TMB groups, there were 6,424 differentially expressed genes, including 67 DDR genes. Ten genes associated with prognosis were selected by univariate cox regression analysis, among which seven genes constituted a panel to predict breast cancer prognosis. The seven-gene prognostic model, as well as the gene copy numbers are closely associated with tumor-infiltrating immune cells. Conclusion: We established a seven-gene prognostic model comprising
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