NEW YORK (GenomeWeb) – Researchers at Harvard Medical School have generated a protein interactome based on the proteomic profiles of 41 breast cancer cell lines.
In a paper published this week in Nature Biotechnology, they used this data to identify established breast cancer subtypes and predict the sensitivity of specific lines to drug treatment.
The study also demonstrates the large-scale use of protein co-regulation analysis to establish protein-protein interactions and associations, which could prove a higher-throughput alternative to interaction mapping approaches like affinity purification mass spec (AP-MS), said Wilhelm Haas, assistant professor of medicine at HMS and senior author on the paper.
Interest in protein interaction mapping has grown among proteomics researchers as the field has come to explore not just the detecting and quantitation of discrete proteins, but their behavior within the larger complexes and pathways in which they exist and through which they function in vivo.
A primary method for studying protein interactions is AP-MS, wherein target proteins are pulled down using antibodies or another affinity reagent and then they and attached proteins are identified via mass spec to determine interactions. As Haas and his co-authors noted, however, this is a laborious process, and generating a proteome-wide interactome