Document Type
Article
Publication Date
2010
College/Unit
Statler College of Engineering and Mining Resources
Department/Program/Center
Chemical and Biomedical Engineering
Abstract
Background
Molecularly targeted drugs inhibit aberrant signaling within oncogenic pathways. Identifying the predominant pathways at work within a tumor is a key step towards tailoring therapies to the patient. Clinical samples pose significant challenges for proteomic profiling, an attractive approach for identifying predominant pathways. The objective of this study was to determine if information obtained from a limited sample (i.e., a single gel replicate) can provide insight into the predominant pathways in two well-characterized breast cancer models.
Methods
A comparative proteomic analysis of total cell lysates was obtained from two cellular models of breast cancer, BT474 (HER2+/ER+) and SKBR3 (HER2+/ER-), using two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Protein interaction networks and canonical pathways were extracted from the Ingenuity Pathway Knowledgebase (IPK) based on association with the observed pattern of differentially expressed proteins.
Results
Of the 304 spots that were picked, 167 protein spots were identified. A threshold of 1.5-fold was used to select 62 proteins used in the analysis. IPK analysis suggested that metabolic pathways were highly associated with protein expression in SKBR3 cells while cell motility pathways were highly associated with BT474 cells. Inferred protein networks were confirmed by observing an up-regulation of IGF-1R and profilin in BT474 and up-regulation of Ras and enolase in SKBR3 using western blot.
Conclusion
When interpreted in the context of prior information, our results suggest that the overall patterns of differential protein expression obtained from limited samples can still aid in clinical decision making by providing an estimate of the predominant pathways that underpin cellular phenotype.
Digital Commons Citation
Kulkarin, Yogesh M.; Suarez, Vivian; and Klinke II, David J., "Inferring predominant pathways in cellular models of breast cancer using limited sample proteomic profiling" (2010). Faculty & Staff Scholarship. 2808.
https://researchrepository.wvu.edu/faculty_publications/2808
Source Citation
Kulkarni, Y.M., Suarez, V. & Klinke, D.J. Inferring predominant pathways in cellular models of breast cancer using limited sample proteomic profiling. BMC Cancer 10, 291 (2010). https://doi.org/10.1186/1471-2407-10-291
Comments
© 2010 Kulkarni et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.