Analysis of mass spectral serum profiles for biomarker selection

Authors:
Habtom W. Ressom;Rency S. Varghese;Mohamed Abdel-Hamid;Sohair Abdel-Latif Eissa;Daniel Saha;Lenka Goldman;Emanuel F. Petricoin;Thomas P. Conrads;Timothy D. Veenstra;Christopher A. Loffredo;Radoslav Goldman
Affiliations:
Lombardi Comprehensive Cancer Center, Georgetown University Washington, DC, USA;Lombardi Comprehensive Cancer Center, Georgetown University Washington, DC, USA;Viral Hepatitis Research Laboratory, NHTMRI Cairo, Egypt;Natinal Cancer Institute Cairo, Egypt;Lombardi Comprehensive Cancer Center, Georgetown University Washington, DC, USA;Lombardi Comprehensive Cancer Center, Georgetown University Washington, DC, USA;Clinical Proteomics Program, NCI/FDA, Center for Biologics Evaluation, FDA USA;SAIC-Frederick and Biomedical Proteomics Program, NCI Frederick, MD, USA;SAIC-Frederick and Biomedical Proteomics Program, NCI Frederick, MD, USA;Lombardi Comprehensive Cancer Center, Georgetown University Washington, DC, USA;Lombardi Comprehensive Cancer Center, Georgetown University Washington, DC, USA
Venue:
Bioinformatics
Year:
2005

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Abstract

Motivation: Mass spectrometric profiles of peptides and proteins obtained by current technologies are characterized by complex spectra, high dimensionality and substantial noise. These characteristics generate challenges in the discovery of proteins and protein-profiles that distinguish disease states, e.g. cancer patients from healthy individuals. We present low-level methods for the processing of mass spectral data and a machine learning method that combines support vector machines, with particle swarm optimization for biomarker selection. Results: The proposed method identified mass points that achieved high prediction accuracy in distinguishing liver cancer patients from healthy individuals in SELDI-QqTOF profiles of serum. Availability: MATLAB scripts to implement the methods described in this paper are available from the HWR's lab website http://lombardi.georgetown.edu/labpage Contact: hwr@georgetown.edu