title: Prognostic factor analysis for breast cancer using gene expression profiles.
abstract: The 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.
  
  
  
  In 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.
  
  
  
  As 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.
  
  
  
  In 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.
authors.affiliation: School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, Republic of Korea.
authors.forename: Soobok
authors.initials: S
authors.lastname: Joe
authors.affiliation: School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, Republic of Korea. hjnam@gist.ac.kr.
authors.forename: Hojung
authors.initials: H
authors.lastname: Nam
mesh_terms: D014408:Biomarkers, Tumor / Q000235:genetics*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D005819:Genetic Markers / Q000235:genetics*; D006801:Humans; D011379:Prognosis; D016019:Survival Analysis
chemical_list: D014408:Biomarkers, Tumor; D005819:Genetic Markers