Integrated Bottom-Up and Top-Down Proteomics of Patient-Derived Breast Tumor Xenografts

Mol Cell Proteomics. 2016 Jan;15(1):45-56. doi: 10.1074/mcp.M114.047480. Epub 2015 Oct 26.

Abstract

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the "peptide-to-protein" inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Breast Neoplasms / genetics
  • Breast Neoplasms / metabolism*
  • Chromatography, High Pressure Liquid
  • Female
  • Genotype
  • Heterografts / metabolism*
  • Humans
  • Mice
  • Molecular Weight
  • Peptides / genetics
  • Peptides / metabolism
  • Polymorphism, Single Nucleotide
  • Proteome / chemistry
  • Proteome / genetics
  • Proteome / metabolism*
  • Proteomics / methods*
  • Tandem Mass Spectrometry
  • Transplantation, Heterologous

Substances

  • Peptides
  • Proteome