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Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
The analysis of doxorubicin resistance in human breast cancer cells using antibody microarrays
Laura Smith1, Mark B Watson, Sara L O'Kane
1Cancer Biology Proteomics Group, Postgraduate Medical Institute of the University of Hill in association with the Hull-York Medical School, University of Hull, Hull, United Kingdom.
Abstract:
Doxorubicin is considered to be the most effective agent in the treatment of breast cancer patients. Unfortunately, resistance to this agent is common, representing a major obstacle to successful treatment. The identification of novel biomarkers that are able to predict treatment response may allow therapy to be tailored to individual patients. Antibody microarrays provide a powerful new technique, enabling the global comparative analysis of many proteins simultaneously. This technology may identify a panel of proteins to discriminate between drug-resistant and drug-sensitive samples. The Panorama Cell Signaling Antibody Microarray was exploited to analyze the MDA-MB-231 breast cancer cell line and a novel derivative, which displays significant resistance to doxorubicin at clinically relevant concentrations. The microarray comprised 224 antibodies selected from a variety of pathways, including apoptotic and cell signaling pathways. A standard >/=2.0-fold cutoff value was used to determine differentially expressed proteins. A decrease in the expression of mitogen-activated protein kinase-activated monophosphotyrosine (phosphorylated extracellular signal-regulated kinase; 2.8-fold decrease), cyclin D2 (2.5-fold decrease), cytokeratin 18 (2.5-fold decrease), cyclin B1 (2.4-fold decrease), and heterogeneous nuclear ribonucleoprotein m3-m4 (2.0-fold decrease) was associated with doxorubicin resistance. Western blotting was exploited to confirm results from the antibody microarray experiment. These results suggest that antibody microarrays can be used to identify novel biomarkers and further validation may reveal mechanisms of chemotherapy resistance and identify potential therapeutic targets. [Mol Cancer Ther 2006;5(8):2115-20].
Insights
Antibody microarrays identified decreased protein expression, including mitogen-activated protein kinase, in doxorubicin-resistant breast cancer cells. This finding may lead to new biomarkers for predicting treatment response.
Area of Science:
- Oncology
- Molecular Biology
- Biochemistry
Background:
- Doxorubicin is a key breast cancer treatment, but drug resistance limits efficacy.
- Identifying biomarkers to predict treatment response is crucial for personalized therapy.
- Antibody microarrays offer a high-throughput method for comparative proteomic analysis.
Purpose of the Study:
- To identify protein biomarkers that distinguish doxorubicin-sensitive from doxorubicin-resistant breast cancer cells.
- To explore the utility of antibody microarrays in discovering chemotherapy resistance mechanisms.
Main Methods:
- Utilized the Panorama Cell Signaling Antibody Microarray with 224 antibodies.
- Analyzed MDA-MB-231 breast cancer cells and a doxorubicin-resistant derivative.
- Applied a >=2.0-fold change cutoff for differential protein expression analysis.
- Confirmed findings using Western blotting.
Main Results:
- Decreased expression of mitogen-activated protein kinase-activated monophosphotyrosine (pERK) by 2.8-fold was observed.
- Reduced levels of cyclin D2 (2.5-fold), cytokeratin 18 (2.5-fold), cyclin B1 (2.4-fold), and heterogeneous nuclear ribonucleoprotein m3-m4 (2.0-fold) were associated with resistance.
- These proteins were differentially expressed between sensitive and resistant cell lines.
Conclusions:
- Antibody microarrays are effective in identifying potential protein biomarkers for doxorubicin resistance in breast cancer.
- The identified proteins may serve as novel biomarkers for predicting treatment response.
- Further validation could elucidate mechanisms of chemotherapy resistance and reveal therapeutic targets.
