ABSTRACT
With the use of the breast cancer metastatic model, which comprises four isogenic cell lines, iTRAQ-based ESI-LC/MS/MS proteomics was employed to catalog protein expression changes as cancer cells acquire increasing metastatic potential. From more than 1000 proteins detected, 197 proteins, including drug-targetable kinases, phosphatases, proteases and transcription factors, displayed differential expression when cancer cells becomes more metastatic. Overall, the number of protein expression changes was evenly distributed across mildly ( approximately 30%), moderately ( approximately 40%) and aggressively ( approximately 30%) metastatic cancer cells. Some changes were found to be specific to one while others were required for two or more phenotypes. KEGG Orthology suggests major reprogramming in cell metabolism and to smaller extents in genetic and environmental information processing. Ten novel metastasis-associated proteins were identified and the iTRAQ-based expression profiles of 7 proteins were verified to be congruent with antibody-based methods. With the use of tissue microarrays comprising 50 matched cases of invasive and metastatic lesions, the expression profiles of SH3GLB1 and SUB1, SND1, TRIM28 were validated to be down- and up-regulated, respectively, during clinical progression of carcinoma in situ to invasive and metastatic carcinomas. Our study has unraveled proteome-wide molecular aberrations and potentially new players in breast cancer metastasis.
Subject(s)
Breast Neoplasms/chemistry , Breast Neoplasms/pathology , Neoplasm Metastasis , Neoplasm Proteins/chemistry , Animals , Breast Neoplasms/metabolism , Cell Line, Tumor , Female , Humans , Mice , Mice, Inbred BALB C , Molecular Sequence Data , Neoplasm Proteins/metabolism , Protein Array Analysis/methods , Reproducibility of Results , Tissue Array AnalysisABSTRACT
The past 5 years have seen an explosion of phosphoproteomics methods development. In this review, using epidermal growth-factor signaling as a model, we will discuss how phosphoproteomics, along with bioinformatics and computational modeling, have impacted key aspects of oncogenic signaling such as in the temporal fine mapping of phosphorylation events, and the identification of novel tyrosine kinase substrates and phosphorylation sites. We submit that the next decade will see considerable exploitation of phosphoproteomics in cancer research. Such a phenomenon is already happening as exemplified by its use in promoting the understanding of the molecular etiology of cancer and target-directed therapeutics.
