Prediction and prognosis: Impact of gene expression profiling in personalized treatment of breast cancer patients

Michael R. Mallmann, Andrea Staratschek-Jox, Christian Rudlowski, Michael Braun, Andrea Gaarz, Matthias Wolfgarten, Walther Kuhn, Joachim L. Schultze

Research output: Contribution to journalReview articlepeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)421-437
Number of pages17
JournalEPMA Journal
Volume1
Issue number3
DOIs
StatePublished - Sep 2010
Externally publishedYes

Keywords

  • Breast cancer
  • Gene expression profile
  • Microarray
  • Pattern-based biomarkers
  • Prediction
  • Prognosis

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