posted on 2015-12-17, 06:45authored byZhe Xu, Chaochao Wu, Fang Xie, Gordon
W. Slysz, Nikola Tolic, Matthew E. Monroe, Vladislav A. Petyuk, Samuel H. Payne, Grant M. Fujimoto, Ronald J. Moore, Thomas L. Fillmore, Athena A. Schepmoes, Douglas A. Levine, R. Reid Townsend, Sherri R. Davies, Shunqiang Li, Matthew Ellis, Emily Boja, Robert Rivers, Henry Rodriguez, Karin D. Rodland, Tao Liu, Richard D. Smith
Aberrant degradation of proteins
is associated with many pathological
states, including cancers. Mass spectrometric analysis of tumor peptidomes,
the intracellular and intercellular products of protein degradation,
has the potential to provide biological insights on proteolytic processing
in cancer. However, attempts to use the information on these smaller
protein degradation products from tumors for biomarker discovery and
cancer biology studies have been fairly limited to date, largely due
to the lack of effective approaches for robust peptidomics identification
and quantification and the prevalence of confounding factors and biases
associated with sample handling and processing. Herein, we have developed
an effective and robust analytical platform for comprehensive analyses
of tissue peptidomes, which is suitable for high-throughput quantitative
studies. The reproducibility and coverage of the platform, as well
as the suitability of clinical ovarian tumor and patient-derived breast
tumor xenograft samples with postexcision delay of up to 60 min before
freezing for peptidomics analysis, have been demonstrated. Moreover,
our data also show that the peptidomics profiles can effectively separate
breast cancer subtypes, reflecting tumor-associated protease activities.
Peptidomics complements results obtainable from conventional bottom-up
proteomics and provides insights not readily obtainable from such
approaches.