ArticleAnnals of translational medicine2020
Identification of a six-gene signature associated with tumor mutation burden for predicting prognosis in patients with invasive breast carcinoma.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed, 31 citations in OpenAlex.
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- TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures.Frontiers in genetics · 2024Article
- Epithelial-Mesenchymal Transition-Based Gene Signature and Distinct Molecular Subtypes for Predicting Clinical Outcomes in Breast Cancer.International journal of general medicine · 2022Article
- A 16-gene signature associated with homologous recombination deficiency for prognosis prediction in patients with triple-negative breast cancer.Open medicine (Warsaw, Poland) · 2022Article
- Construction of the model for predicting prognosis by key genes regulating EGFR-TKI resistance.Frontiers in genetics · 2022Article
- Identification of a novel glycolysis-related signature to predict the prognosis of patients with breast cancer.World journal of surgical oncology · 2021Article
- Establishment of a novel CNV-related prognostic signature predicting prognosis in patients with breast cancer.Journal of ovarian research · 2021Article
- Identification and development of an independent immune-related genes prognostic model for breast cancer.BMC cancer · 2021Article
- A systematic analysis of a potential metabolism-related prognostic signature for breast cancer patients.Annals of translational medicine · 2021Article
- Bioinformatic Analysis of Immune Significance of RYR2 Mutation in Breast Cancer.BioMed research international · 2021Article
- Identification of the Upregulation of MRPL13 as a Novel Prognostic Marker Associated with Overall Survival Time and Immunotherapy Response in Breast Cancer.Computational and mathematical methods in medicine · 2021Article
- Identification of a Novel Glycolysis-Related Gene Signature for Predicting Breast Cancer Survival.Frontiers in oncology · 2020Article
- Systemic Analysis of the Prognosis-Associated Alternative Polyadenylation Events in Breast Cancer.Frontiers in genetics · 2020Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBreast cancer (BC) is one of the most common cancers with high mortality worldwide. In the present study, through bioinformatics analysis, we aimed to identify new biomarkers to predict the survival rate of BC patients.
methodsDifferentially expressed genes (DEGs) between low- and high-tumor mutation burden (TMB) groups were identified by using The Cancer Genome Atlas (TCGA) dataset and integrated analysis. Gene Ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network, were applied to predict the function of these above DEGs. Then, the Cox proportional hazard model was developed to screen DEGs. Based on the prognostic signature, survival analysis was used on The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) dataset. Finally, the single-sample gene set enrichment (ssGSEA) analysis was employed to estimate immune cells related to this signature.
resultsTo create a prognostic signature, 6 DEGs were identified. The results revealed that the survival time of patients with high-risk scores based on the expression of the six-gene signature was dramatically shorter than that of patients with low-risk scores in BC. Furthermore, survival analysis and multivariate cox analysis indicated that the six-gene signature was an independent prognostic factor of BC. Then, we built a nomogram that integrated the clinicopathological factors with the six-gene signature to predict the survival probability of BC patients. We eventually predicted the 20 most vital small molecule drugs by CMap, and Nadolol was considered as the most promising small molecule to treat BC. Moreover, ssGSEA analysis showed that the 6 genes were closely associated with immune cells.
conclusionsWe constructed a six-gene signature associated with TMB that can improve the prognosis prediction and could be seen as a biomarker for BC patients.
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