ArticleBMC medical informatics and decision making2016
Prognostic factor analysis for breast cancer using gene expression profiles.
Article in BMC medical informatics and decision making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Identification and evaluation of a risk model predicting the prognosis of breast cancer based on characteristic signatures.Translational cancer research · 2023Article
- Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosis.Cell reports methods · 2021Article
- Improving prediction performance of colon cancer prognosis based on the integration of clinical and multi-omics data.BMC medical informatics and decision making · 2020Article
- The Construction of Bone Metastasis-Specific Prognostic Model and Co-expressed Network of Alternative Splicing in Breast Cancer.Frontiers in cell and developmental biology · 2020Article
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2 authors.
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Abstract
backgroundThe survival of patients with breast cancer is highly sporadic, from a few months to more than 15 years. In recent studies, the gene expression profiling of tumors has been used as a promising means of predicting prognosis factors.
methodsIn this study, we used gene expression datasets of tumors to identify prognostic factors in breast cancer. We conducted log-rank tests and used unsupervised clustering methods to find reciprocally expressed gene sets associated with worse survival rates. Prognosis prediction scores were determined as the ratio of gene expressions.
resultsAs a result, four prognosis prediction gene set modules were constructed. The four prognostic gene sets predicted worse survival rates in three independent gene expression data sets. In addition, we found that cancer patient with poor prognosis, i.e., triple-negative cancer, HER2-enriched, TP53 mutated and high-graded patients had higher prognosis prediction scores than those with other types of breast cancer.
conclusionsIn conclusion, based on a gene expression analysis, we suggest that our well-defined scoring method of the prediction of survival outcome may be useful for developing prognostic factors in breast cancer.
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