TY - JOUR
T1 - Prediction and prognosis
T2 - Impact of gene expression profiling in personalized treatment of breast cancer patients
AU - Mallmann, Michael R.
AU - Staratschek-Jox, Andrea
AU - Rudlowski, Christian
AU - Braun, Michael
AU - Gaarz, Andrea
AU - Wolfgarten, Matthias
AU - Kuhn, Walther
AU - Schultze, Joachim L.
PY - 2010/9
Y1 - 2010/9
N2 - Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.
AB - Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.
KW - Breast cancer
KW - Gene expression profile
KW - Microarray
KW - Pattern-based biomarkers
KW - Prediction
KW - Prognosis
UR - http://www.scopus.com/inward/record.url?scp=79953042128&partnerID=8YFLogxK
U2 - 10.1007/s13167-010-0044-z
DO - 10.1007/s13167-010-0044-z
M3 - Review article
AN - SCOPUS:79953042128
SN - 1878-5077
VL - 1
SP - 421
EP - 437
JO - EPMA Journal
JF - EPMA Journal
IS - 3
ER -