Prospective study of the predictive power of mass spectrometric profiles of plasma proteins and peptides in detecting early stage breast cancer

Women with a high risk for breast cancer urgently need more effective and sensitive, early screening options. Promising advances in cancer detection using human blood plasma have recently been reported using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry. Using seed funding from the Susan G. Komen Breast Cancer Research Foundation we implemented this technology in our laboratory. Our major goal is to validate the Ciphergen PBSIIc SELDI-TOF platform for direct analysis of cancer-specific proteins in clinical samples collected at Stanford University Hospital and the General Hospital of Vienna, Austria.

Personnel

SGTC:
Peter Oefner (PI)
Georg Hölzl 
Birgit Timischl

The study is designed with three specific aims.

First, we will obtain SELDI-TOF mass spectra of plasma proteins from healthy volunteers, and from patients with a known cancer diagnosis. To establish both the sensitivity and specificity of the method, we will train the data analysis software with specimens from early stage breast cancer, and compare them with other cancers. Then, we will perform cluster analysis to identify proteomic patterns that correlate with early signs of breast cancer, or with an increased risk of breast cancer.
Second, we will evaluate the method as a screening tool by prospectively following 100-150 high-risk women in our comprehensive screening program. We will compare proteomic analysis with other early detection strategies, including magnetic resonance imaging (MRI), and ductal lavage cytology.
Third, we will begin chemical characterization of cancer-specific patterns using high-performance liquid chromatography coupled to electro-spray ionization tandem mass spectrometry. The more detailed, and accurate mass spectra afforded by ESI-MS/MS may allow a definitive identification of cancer-specific proteins.

In a second approach we are using an integrated strategy combining immunodepletion, multi-dimensional HPLC and MELDI-MS (Fig. 1) to tackle the complexity and dynamic range of the plasma proteome with the goal of finding and identifying differentially expressed proteins indicative of early breast cancer.

Depletion of high abundance proteins:

Protein concentrations in blood span a dynamic range of at least 10 orders of magnitude, with only 10 proteins constituting 90% of the protein content in human plasma. Typical methods for protein analysis cover a dynamic range of maximal 105. Thus, the depletion of the high-abundance proteome is of utmost importance for the detection of cancer-specific protein alterations. Depletion methods have to be refined in a way to release proteins bound to high abundance species such as albumin and make them readily available for analysis.

Peptide fractionation – 2D liquid chromatography (2D LC):

Tryptic digestion of the proteins remaining after depletion of the high-abundance proteins yields a highly complex peptide sample that has to undergo extensive separation to resolve and identify as many peptides as possible in the subsequent mass spectrometric analysis. The most promising chromatographic steps for this task are strong cation exchange coupled to reversed phase (SCX-RP) LC, but other separation steps have to be investigated either (isoelectric focussing, capillary electrophoresis).

Material assisted laser desorption ionization mass spectrometry (MALDI-MS):

The MELDI-approach on novel surfaces such as graphite unites differential protein- (peptide-) enrichment and analysis on one platform, allowing for the rapid detection of differences in the amount of proteins (peptides) present in the sample. By coupling on-chip separation with the exquisite mass resolution and capability for MS/MS of modern time-of-flight (TOF) MS, we will be able to directly assess the biological significance of the detected alterations in protein expression in breast cancer samples.

Quantitative mass spectrometry:

In both MALDI- and ESI-MS the relationship between the amount of analyte present and measured signal intensity is complex and only marginally understood. Thus for the analysis of protein expression reliable quantification methods have to be established. Existing methods make use of ratiometric approaches exploiting stable isotope labels, e.g. ICAT, ITRAQ and enzymatic labeling with 18O, or constant sample properties, e.g. MELDI or SELDI. We will also investigate the benefits of spiked-in protein standards for quantitation. The use of different mass spectrometers leads to the identification of different proteins, thereby increasing coverage and the probability for significant results. The methods we are investigating include:
  • Ionization by MELDI; analysis by QSTAR (Q-TOF), Protein Chip Reader (TOF)
  • Ionization by ESI-MS; analysis by  QSTAR (Q-TOF), Ion trap (LCQ/LTQ), FT-ICR

Bioinformatics:

The above described methods will yield an enormous amount of data, which will require powerful tools for data handling and interpretation. Our collaboration partners from the Institute for Genomics and Bioinformatics at the Technical University of Graz, Austria will develop algorithms that use our identified biomarkers for cancer diagnostic and prognosis, for protein identification existing programs such as SEQUEST (Thermo Finnigan) and Spectrum Mill (Agilent) will be evaluated.
The combination of extensive protein and peptide separation methods with the protein identification capabilities of state-of the-art mass spectrometers will enable us to thoroughly search the human serum proteome for discriminating biomarkers in breast cancer. The detected proteins will be valuable targets for the development of screening methods for the early detection of cancer and will also help to improve our understanding of the factors responsible for cancer development and progression.
last updated 12/13/2004
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