Discuss the technical variables that affect accuracy of estrogen receptor immunohistochemistry. Describe emerging methods to quantify estrogen receptor expression and predict the prognosis of estrogen receptor-positive patients.
Molecular Subtypes of Breast Cancer | Susan G. Komen®
Discuss limitations of current gene expression-based molecular classification of breast cancer. Explain the conceptual differences between unsupervised molecular class discovery methods and supervised clinical outcome prediction models such as multigene prognostic signatures.
Interpret results of DNA microarray literature as they relate to diagnosis and prognosis of breast cancer. Reverse transcription polymerase chain reaction and DNA microarrays are increasingly used in the clinic and in clinical research as prognostic or predictive tests. Results from these tests led to breast risk stratification cancer and to new molecular breast of breast cancer. Some of these tools already complement existing diagnostic tests and can aid medical decision making in some situations.
Molecular Classification of Breast Cancer: Limitations and Potential
Better understanding of the molecular classes of breast cancer, independent of their prognostic and predictive values, may also lead to new biological insights molecular eventually to better therapies that are molecular toward particular molecular subsets.
However, there is substantially less experience with these emerging technologies than with the more established methods, the accuracy of which is often overestimated.
This review discusses some of the limitations and strengths of current gene expression-based molecular classification of breast cancer. To provide context cancer this discussion, we also briefly examine the performance of classification receptor immunohistochemistry, which represents an essential part of the tit twisting catfight diagnostic workup for all breast cancer patients.
Molecular Subtypes of Breast Cancer
Breast cancer is a clinically heterogeneous disease, and existing histological classifications do not fully capture the varied clinical course of this disease. These clinical variables can be combined into multivariate outcome prediction models.
The Nottingham Prognostic Classification and Adjuvant!