title: Profiling phospho-signaling networks in breast cancer using reverse-phase protein arrays.
abstract: Measuring the states of cell signaling pathways in tumor samples promises to advance the understanding of oncogenesis and identify response biomarkers. Here, we describe the use of Reverse Phase Protein Arrays (RPPAs or RPLAs) to profile signaling proteins in 56 breast cancers and matched normal tissue. In RPPAs, hundreds to thousands of lysates are arrayed in dense regular grids and each grid is probed with a different antibody (100 in the current work, of which 71 yielded strong signals with breast tissue). Although RPPA technology is quite widely used, measuring changes in phosphorylation reflective of protein activation remains challenging. Using repeat deposition and well-validated antibodies, we show that diverse patterns of phosphorylation can be monitored in tumor samples and changes mapped onto signaling networks in a coherent fashion. The patterns are consistent with biomarker-based classification of breast cancers and known mechanisms of oncogenesis. We explore in detail one tumor-associated pattern that involves changes in the abundance of the Axl receptor tyrosine kinase (RTK) and phosphorylation of the cMet RTK. Both cMet and Axl have been implicated in breast cancer, or in resistance to anticancer drugs, but the two RTKs are not known to be linked functionally. Protein depletion and overexpression studies in a 'triple-negative' breast cell line reveal cross talk between Axl and cMet involving Axl-mediated modification of cMet, a requirement for cMet in efficient and timely signal transduction by the Axl ligand Gas6 and the potential for the two receptors to interact physically. These findings have potential therapeutic implications, as they imply that bi-specific receptor inhibitors (for example, ATP-competitive small-kinase inhibitors such as GSK1363089, BMS-777607 or MP470) may be more efficacious than the mono-specific therapeutic antibodies currently in development (for example, Onartuzumab).
authors.affiliation: Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
authors.forename: T S
authors.initials: TS
authors.lastname: Gujral
authors.forename: R L
authors.initials: RL
authors.lastname: Karp
authors.forename: A
authors.initials: A
authors.lastname: Finski
authors.forename: M
authors.initials: M
authors.lastname: Chan
authors.forename: P E
authors.initials: PE
authors.lastname: Schwartz
authors.forename: G
authors.initials: G
authors.lastname: MacBeath
authors.forename: P
authors.initials: P
authors.lastname: Sorger
mesh_terms: D001943:Breast Neoplasms / Q000378:metabolism*; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D040081:Protein Array Analysis / Q000379:methods*; D040901:Proteomics / Q000379:methods; D011518:Proto-Oncogene Proteins / Q000378:metabolism; D019859:Proto-Oncogene Proteins c-met / Q000378:metabolism; D020794:Receptor Protein-Tyrosine Kinases / Q000378:metabolism; D015398:Signal Transduction / Q000502:physiology*; D000094963:Axl Receptor Tyrosine Kinase
chemical_list: D011518:Proto-Oncogene Proteins; D019859:Proto-Oncogene Proteins c-met; D020794:Receptor Protein-Tyrosine Kinases; D000094963:Axl Receptor Tyrosine Kinase; C000722289:AXL protein, human