background: numerous studies used microarray gene expression data to extract metastasis-driving gene signatures for the prediction of breast cancer relapse. however, the accuracy and generality of the previously introduced biomarkers are not acceptable for reliable usage in independent datasets. this inadequacy is attributed to ignoring gene interactions by simple feature selection methods, due...

background: using primary tumor gene expression has been shown to have the ability of finding metastasis-driving gene markers for the prediction of breast cancer recurrence (bcr). however, there are some difficulties associated with the analysis of microarray data which led to poor predictive power and inconsistency of the previously introduced gene signatures. methods: in this study a hybrid m...

abstract breast cancer is one of the major health problems of the eastern world. regardless of the survival rate improvement with progression in screening and adjuvant systemic therapies, still one – third of the patients with primary breast cancer have recurrence of micro metastasis after 10 years.  it is important to discover a reliable biomarker for detection of breast cancer. the underlying...

Non-invasive blood-based molecule markers are evaluated as promising biomarkers these days. Here we investigated the potential of cell-free circulating DNA Integrity (cfDI) as blood-based marker for the prediction of recurrence during the follow-up of breast cancer patients within a prospective study cohort. cfDI was determined in plasma of 212 individuals, by measuring ALU and LINE1 repetitive...

prediction, diagnosis, recovery and recurrence of the breast cancer among the patients are always one of the most important challenges for explorers and scientists. nowadays by using of the bioinformatics sciences, these challenges can be eliminated by using of the previous information of patients records. in this paper has been used adaptive nero fuzzy inference system and data mining techniqu...

Prediction, diagnosis, recovery and recurrence of the breast cancer among the patients are always one of the most important challenges for explorers and scientists. Nowadays by using of the bioinformatics sciences, these challenges can be eliminated by using of the previous information of patients records. In this paper has been used adaptive nero fuzzy inference system and data mining techniqu...

introduction: breast cancer is the most common cancer in women worldwide and her-2 is one importantly prognostic factor in this cancer. tumor markers use as a criterion for predicting recurrence, but in breast cancer physical examination and mammography are important factors that are recommended for following up the recurrence. the aim of this study was to assess the correlation between breast ...

Discrepancies in the prognosis of triple negative breast cancer exist between Caucasian and Asian populations. Yet, the gene signature of triple negative breast cancer specifically for Asians has not become available. Therefore, the purpose of this study is to construct a prediction model for recurrence of triple negative breast cancer in Taiwanese patients. Whole genome expression profiling of...

Introduction: Breast cancer is the most common cancer and the leading cause of cancer-related death in women. Clinicopathological variables are important factors in deciding on breast cancer treatment. This study evaluated the association between the recurrence score generated by the Oncotype DX® 21-gene assay and classic clinicopathological variables. Methods: A single-institution retrospect...