A comparative phosphoproteomic analysis of a human tumor metastasis model using a label-free quantitative approach

Abstract

Alterations in cellular phosphorylation patterns have been implicated in a number of diseases, including cancer, through multiple mechanisms. Herein we present a survey of the phosphorylation profiles of an isogenic pair of human cancer cell lines with opposite metastatic phenotype. Phosphopeptides were enriched from tumor cell lysates with titanium dioxide and zirconium dioxide, and identified with nano-LC-MS/MS using an automatic cross-validation of MS/MS and MS/MS/MS (MS2+MS3) data-dependent neutral loss method. A spectral counting quantitative strategy was applied to the two cell line samples on the MS2-only scan, which was implemented successively after each MS2+MS3 scan in the same sample. For all regulated phosphopeptides reported by spectral counting analysis, sequence and phosphorylation site assignments were validated by a MS2+MS3 data-dependent neutral loss method. With this approach, we identified over 70 phosphorylated sites on 27 phosphoproteins as being differentially expressed with respect to tumor cell phenotype. The altered expression levels of proteins identified by LC-MS/MS were validated using Western blotting. Using network pathway analysis, we observed that the majority of the differentially expressed proteins were highly interconnected and belong to two major intracellular signaling pathways. Our findings suggest that the phosphorylation of isoform A of lamin A/C and GTPase activating protein binding protein 1 is associated with metastatic propensity. The study demonstrates a quantitative and comparative proteomics strategy to identify differential phosphorylation patterns in complex biological samples.