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Resistance-associated signatures in breast cancer
1Joint Research Laboratory, Semmelweis University Budapest and Hungarian Academy of Sciences, Budapest, Hungary.
Abstract:
A major obstacle in the treatment of breast cancer is the lack of adequate methods for predicting patient response to a particular chemotherapy regime. To date, single tumour markers have provided limited success. DNA array technologies identifying thousands of genes simultaneously can help to solve this problem. We investigated cancer cell lines sensitive and resistant to the topoisomerase inhibitors doxorubicin and mitoxantrone. These drugs are used in several different breast cancer treatment protocols. We have identified the top genes best associated with resistance against each cytostatic agent. We applied our gene expression signatures to a set of pre-characterised patients receiving doxorubicin monotherapy. The patients classified as sensitive to chemotherapy exhibited longer survival than the resistant ones. In summary, in our study we have successfully transferred experimental results to a clinical problem, and managed to perform a predictive test for a selected monotherapy protocol. However, many different studies have been performed using microarrays, each producing a different gene list for the same classification problem. It is likely that future diagnostic tools will include the results of several different laboratories, focus on genes validated on different technological platforms and use large cohorts of patients.
Insights
Predicting breast cancer chemotherapy response is challenging. This study identifies gene signatures to predict patient response to doxorubicin, improving treatment selection and survival outcomes.
Area of Science:
- Oncology
- Genomics
- Translational Medicine
Background:
- Accurate prediction of breast cancer patient response to chemotherapy remains a significant clinical challenge.
- Single tumor markers have shown limited success in predicting treatment efficacy.
- DNA microarray technologies offer potential for identifying comprehensive gene expression profiles.
Purpose of the Study:
- To identify gene expression signatures associated with resistance to topoisomerase inhibitors doxorubicin and mitoxantrone.
- To develop a predictive test for patient response to doxorubicin monotherapy in breast cancer treatment.
Main Methods:
- Investigated gene expression in breast cancer cell lines sensitive and resistant to doxorubicin and mitoxantrone.
- Applied identified gene expression signatures to a cohort of patients receiving doxorubicin monotherapy.
- Analyzed patient survival based on predicted chemotherapy sensitivity.
Main Results:
- Identified key genes associated with resistance to doxorubicin and mitoxantrone.
- Successfully applied gene signatures to predict patient response to doxorubicin.
- Patients classified as sensitive demonstrated significantly longer survival compared to resistant patients.
Conclusions:
- Experimental gene expression findings were successfully translated to a clinical predictive tool for doxorubicin monotherapy.
- Future diagnostic tools will likely integrate multi-laboratory data, validated genes across platforms, and large patient cohorts for robust prediction.