Background: Expression analysis of estrogen response genes ERGs may help to predict the effectiveness of endocrine therapies in breast cancer patients. Materials and Methods: aRNA was synthesized from 27 breast cancer tumors. Data were analyzed by cluster analysis.
Breast cancer is a complex disease comprising molecularly distinct subtypes. The prognosis and treatment differ between subtypes; thus, it is important to distinguish one subtype from another. In this chapter, we make use of high-throughput microarray dataset to perform breast cancer subtyping of samples.
TNBC is more aggressive than other breast cancer subtypes. Furthermore an integrated analysis was conducted based on our own and published data, leading to more robust, reproducible and accurate predictions. Additionally, we performed qRT-PCR in breast cancer cell lines to verify the findings in integrated analysis.
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The DNA microarray is a tool used to determine whether the DNA from a particular individual contains a mutation in genes. Scientists know that a mutation - or alteration - in a particular gene's DNA may contribute to a certain disease. However, it can be very difficult to develop a test to detect these mutations, because most large genes have many regions where mutations can occur.
There are more than 1. At present, only small numbers of accurate prognostic and predictive factors are used clinically for managing the patients with breast cancer. DNA microarrays have the potential to assess the expression of thousands of genes simultaneously. Recent preliminary researches indicate that gene expression profiling based on DNA microarray can offer potential and independent prognostic information in patients with newly diagnosed breast cancer.
Microarray gene expression profiling in the diagnostic setting offers the opportunity of reading out multiple profiles and genes from a single array. They also demonstrate the versatility of gene expression profiling in the diagnostic setting, enabling the addition of many more clinically relevant profiles such as drug response profiles as experience grows. E: Femke.