ArticleCancer biology & therapy2015
Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen.
Article in Cancer biology & therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed, 64 citations in OpenAlex.
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- Genetic co-expression networks contribute to creating predictive model and exploring novel biomarkers for the prognosis of breast cancer.Scientific reports · 2021Article
- Nucleolar and spindle‑associated protein 1 promotes non‑small cell lung cancer progression and serves as an effector of myocyte enhancer factor 2D.Oncology reports · 2021Article
- Decision theory for precision therapy of breast cancer.Scientific reports · 2021Article
- Identification of Atrial Fibrillation-Associated GenesFrontiers in genetics · 2021Article
- Identification of Ten Mitosis Genes Associated with Tamoxifen Resistance in Breast Cancer.OncoTargets and therapy · 2021Article
- A Novel IGLC2 Gene Linked With Prognosis of Triple-Negative Breast Cancer.Frontiers in oncology · 2021Article
- Luminal A Breast Cancer Co-expression Network: Structural and Functional Alterations.Frontiers in genetics · 2021Article
- Mechanism-Centric Approaches for Biomarker Detection and Precision Therapeutics in Cancer.Frontiers in genetics · 2021Review
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- Identification of gene modules associated with survival of diffuse large B-cell lymphoma treated with CHOP-based chemotherapy.The pharmacogenomics journal · 2020Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to identify effective gene networks and prognostic biomarkers associated with estrogen receptor positive (ER+) breast cancer using human mRNA studies. Weighted gene coexpression network analysis was performed with a complex ER+ breast cancer transcriptome to investigate the function of networks and key genes in the prognosis of breast cancer. We found a significant correlation of an expression module with distant metastasis-free survival (HR = 2.25; 95% CI .21.03-4.88 in discovery set; HR = 1.78; 95% CI = 1.07-2.93 in validation set). This module contained genes enriched in the biological process of the M phase. From this module, we further identified and validated 5 hub genes (CDK1, DLGAP5, MELK, NUSAP1, and RRM2), the expression levels of which were strongly associated with poor survival. Highly expressed MELK indicated poor survival in luminal A and luminal B breast cancer molecular subtypes. This gene was also found to be associated with tamoxifen resistance. Results indicated that a network-based approach may facilitate the discovery of biomarkers for the prognosis of ER+ breast cancer and may also be used as a basis for establishing personalized therapies. Nevertheless, before the application of this approach in clinical settings, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed.
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