ArticleBMC cancer2010
Inferring predominant pathways in cellular models of breast cancer using limited sample proteomic profiling.
Article in BMC cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 18 citations in OpenAlex.
- A Catalogue of Altered Salivary Proteins Secondary to Invasive Ductal Carcinoma: A Novel In Vivo Paradigm to Assess Breast Cancer Progression.Scientific reports · 2016Trial
- Association of Enolase-1 with Prognosis and Immune Infiltration in Breast Cancer by Clinical Stage.Journal of inflammation research · 2023Article
- A proteomics approach to identifying key protein targets involved in VEGF inhibitor mediated attenuation of bleomycin-induced pulmonary fibrosis.Proteomics · 2016Article
- iTRAQ-Based Quantitative Proteomic Analysis of the Initiation of Head Regeneration in Planarians.PloS one · 2015Article
- Inferring alterations in cell-to-cell communication in HER2+ breast cancer using secretome profiling of three cell models.Biotechnology and bioengineering · 2014Article
- Applying of hierarchical clustering to analysis of protein patterns in the human cancer-associated liver.PloS one · 2014Article
- Article
- A quantitative systems approach to identify paracrine mechanisms that locally suppress immune response to Interleukin-12 in the B16 melanoma model.Integrative biology : quantitative biosciences from nano to macro · 2012Article
- Protein-based identification of quantitative trait loci associated with malignant transformation in two HER2+ cellular models of breast cancer.Proteome science · 2012Article
- Salivary Protein Profiles among HER2/neu-Receptor-Positive and -Negative Breast Cancer Patients: Support for Using Salivary Protein Profiles for Modeling Breast Cancer Progression.Journal of oncology · 2012Article
- Investigation of plasma biomarkers in HIV-1/HCV mono- and coinfected individuals by multiplex iTRAQ quantitative proteomics.Omics : a journal of integrative biology · 2011Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMolecularly 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.
methodsA 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.
resultsOf 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.
conclusionWhen 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.
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