This review outlines the concept of population proteomics and its implication in the discovery and validation of cancer-specific protein modulations. Population proteomics is an applied subdiscipline of proteomics engaging in the investigation of human proteins across and within populations to define and better understand protein diversity. Population proteomics focuses on interrogation of specific proteins from large number of individuals, utilizing top-down, targeted affinity mass spectrometry approaches to probe protein modifications. Deglycosylation, sequence truncations, side-chain residue modifications, and other modifications have been reported for myriad of proteins, yet little is know about their incidence rate in the general population. Such information can be gathered via population proteomics and would greatly aid the biomarker discovery efforts. Discovery of novel protein modifications is also expected from such large scale population proteomics, expanding the protein knowledge database. In regard to cancer protein biomarkers, their validation via population proteomics-based approaches is advantageous as mass spectrometry detection is used both in the discovery and validation process, which is essential for the detection of those structurally modified protein biomarkers. Molecular & Cellular Proteomics 5: 1811-1818, 2006.In the past 5 years proteomics and its subdiscipline clinical proteomics (1-3) have taken a leading role in the discovery of new and improved cancer biomarkers. In its inception, clinical proteomics was an application of high end MS tools for evaluation of proteomic differences in the proteomes between healthy and cancer-bearing individuals. The tools were mainly based on the SELDI technology and utilization of wide specificity surfaces (e.g. hydrophobic or hydrophilic mass spectrometer targets) to bind groups of proteins from biological samples and generate distinct mass spectra containing hundreds of peaks (4, 5). These so-called proteomic patterns entered mainstream proteomics with the publication of a Lancet study in 2002 (6), which was quickly followed by a significant number of research studies (7-11) and reviews (12-15) describing proteomic patterns capable of discriminating between disease (e.g. ovarian cancer, prostate cancer, etc.) and healthy cohorts with relatively high sensitivity and specificity. However, critical assessment of those results quickly followed, outlining significant shortcomings and uncertainties in regard to the reproducibility of the findings, identity of the proteins behind the pattern peaks, and validation of the results (16 -23). Interlaboratory SELDI experiments performed recently alleviated some of the reproducibility concerns (24, 25). Furthermore, current research efforts have led to identification of several proteins behind the discriminating patterns peaks, including serum amyloid A (26), vitamin D-binding protein (27), and apolipoprotein A-II (28), which were identified as potential biomarkers for prostate cancer; haptoglobin (29), apolipopro...