screening of human tissues and biofluids for disease biomarkers is an important task in healthcare and disease prevention but is often hindered by the complexity of the system studied , for example , plasma . a substantially less complex system such as urine , which contains approximately 3000 proteins [ 1 , 2 ] , would be a preferred medium to screen for protein or peptide biomarkers as sampling is both simple and noninvasive , and unrestricted quantities are obtainable . urine is relatively stable in terms of protein / peptide composition and fragmentation state compared with other body fluids such as serum , where proteolytic degradation by endogenous proteases has been shown to occur during or after sample collection . several investigations have been published describing the urinary peptidome and proteome [ 4 , 5 ] , including biomarker discoveries for several disease processes [ 610 ] . these studies have used methodologies ranging from traditional 2d gel electrophoresis alone   or coupled with mass spectrometry ( 2-de - ms ) , immunohistochemistry , liquid chromatography mass spectrometry ( lc - ms ) , and surface enhanced laser desorption ionisation - time of flight mass spectrometry ( seldi - tof - ms ) [ 1517 ] . in complex disease processes , identification of the most robust urinary biomarkers will be enhanced by collating and correlating data from other published and current studies . the majority consists of lists of identified proteins derived from tryptic digests analysed by lc - ms / ms , such as mapu   and sys - bodyfluid   and does not cover naturally occurring mass - centric molecular entities . more recently , a urinary database , combining chromatographic reverse - phase retention times and m / z values , has been established . the mosaiques database [ 21 , 22 ] consists of naturally occurring protein and peptide patterns detected by capillary electrophoresis ms ( ce - ms ) from more than 3600 individuals , covering mainly an m / z range of 800 to 3000 . however , databases that give access to unprocessed data files are not available but would be the most useful resource with which to compare and validate novel datasets . it is also prudent , especially in urinary proteome research , to remember that any peak in any ms scan profile might be derived from the same molecule ( differing only in either its fragmentation or posttranslational modifications ) . this differentiation might be lost in an ms / ms screen , where proteolytic processing of the samples might alter the original protein / peptide signatures and intensities . additionally , such fragmentation steps are also time consuming and decrease the sensitivity of the analysis . other technologies such as esi ( electrospray ionization ) methods require off - line fractionation and sample clean - up steps , which can be avoided using lc - ms as a platform . however , the limitation of the inline lc step , usually employing a reverse - phase resin as a solid matrix , narrows the general usability of this method . alternatives which allow a suitable range of inline fractionation steps using various resins is seldi , and a novel emerging alternative termed material - enhanced laser desorption / ionization ( meldi ) [ 23 , 24 ] , where biomolecules are absorbed onto a solid phase resin and directly used for mass analysis using maldi . we chose the high - throughput seldi - tof - ms technology as our platform for biomarker pattern screening . the main advantages of the seldi technology are its ease of use including little or no sample preparation , high reproducibility , high volume throughput in a minimum of time , with proven methodology over time for the numerous diseases studied , whereas meldi might require further development before it can be generally applied . the main limitations of the seldi technology lie with the instrumentation where poor resolution on older instruments led to difficult reproducibility and sometimes questionable results . a number of reviews list the issues and compares the various ms - based methods in urinary research [ 2527 ] . utilizing data from both our own and published studies , we have established the urinary proteome fingerprint database updb , which will be publically available as a repository for seldi - ms data and as a reference for scientists to probe the urinary proteome for proteins implicated in disease processes . urine samples were obtained from 86 cancer patients , 93 noncancer controls , and 21 patients with a previous history of cancer but were diagnosed as cancer - free 6 to 18 months after resectional surgery . summary participant demographics are shown in table 1 , and full details are provided as part of the database . one - third of the cancer patients were diagnosed with pancreatic tumours , approximately one - third had oesophageal cancer , approximately one - sixth had malignancies of the oesophagogastric junction ( ogj ) , and approximately one - sixth suffered from gastric cancer . all procedures were approved by the local research ethics committee . written informed consent was obtained . all urine samples were stored at 40c . 0.1  ml human urine was applied directly to preconditioned seldi proteinchip arrays ( bio - rad laboratories inc . ) ( np20 , h50 , send , q10 , cm10 and imac30 ) , as recommended by the manufacturer , in a proteinchip bioprocessor and incubated with 0.1  ml binding buffer where appropriate . the chip - spots were washed with 0.2  ml binding buffer three times and air - dried , followed by application of emitter matrix ( alpha - cyano-4-hydroxycinnamic acid ( chca ) or sinapinic acid ( spa ) ) . the arrays were read twice , one at low laser settings ( focused on 10050,000  da m / z ) and one at high laser settings ( focused on 1000200,000  da m / z ) , on a proteinchip enterprise system pcs4000 ( biorad laboratories inc . ) , seldi - tof instrument , and spectral data collected over an average of 588 shots per spot using proteinchip data manager software . all spectra were processed using the expression difference mapping ( edm ) wizard in the proteinchip data manager software ( biorad laboratories inc . ) with a signal - to - noise - ratio cutoff of 5% , 3% valley depth , and a cluster mass window of 0.2% m / z . seldi - ms analysis of human urine samples has been reported to show little intra- and interchip variation , as well as low intraindividual day - to - day variation   and has been established as a key emerging technology to discover new biomarkers for a variety of diseases . we chose to establish a repository for urinary seldi data to be made available for the scientific community in order to enable an open exchange of research findings and data sharing . we analysed the 200 urine specimens using the seldi - ms platform on various chip types , ranging from small sized screens of 21 samples on np20 and hp50 surfaces , medium - sized screens of 63 samples on send and q10 surfaces , and full screens of all 200 samples on cm10 and imac30 chip - types ( table 2 ) . the selection of the appropriate chip - surface for a screening purpose depends on many factors , such as peak intensities , distribution , and the number of clearly identifiable ion species ( figure 1 ) . however , under certain conditions a nonoptimal chip type might resolve potential biomarkers and biomarker patterns better than another one . both cm10 and imac30 ( cu ) gave the best results in terms of signal intensities , peak resolution , and the number of observable peaks . figure 1 shows the seldi - ms scans of two samples on the six surfaces tested . we also observed that urines from different individuals display a certain degree of heterogeneity , which is easily overcome by increasing the number of analysed samples . using a 20% threshold for peaks commonly found in any sample , 31.7% of all molecules are present using the imac30 ( cu ) chip - type , 25.2% using cm10 , and 23.5% using hp50 surfaces . these low numbers are partially due to the various disease states and are higher by comparing samples from healthy control specimens . normalising on total ion count and aligning all spectra from individual chip - types resulted in the catalog of 2490 detected peaks , which are fully listed in the database ( figure 2 ) . the database structure also allows the storage and retrieval of information relating to the ms environment , pre- and subfractionation methods , chromatography setups , studied diseases , and other data . peak - specific data , such as identified biomarker , statistical information , and , if known , identified proteins , are provided . the database covers the mass range of 1500 to 150000 for seldi spectra and consists of averaged and median m / z , intensities and measurement specific data . all 1172 spectra ( raw data files ) are available for download in  .xml  format from the padb website at http://www.padb.org/.   initial literature data mining led to the identification of 29 additional urinary datasets , which were incorporated into our database ( table 3 ) . these sets are based on several ms platforms , ranging from seldi and maldi to ce - ms and ce - maldi . the median mass of each individual ms technology , based on the identified peaks per technique , shows that both maldi and ce - ms favor smaller compounds and peptides , whereas seldi has an advantage in the higher mass range , albeit with a lower resolution of measured peaks . in total , the database covers a mass range of 800 to 200000  m / z or da since most peaks using these technologies will have a charge of one . additionally , the updb database is part of the proteomic analysis database ( padb ) initiative , and a full integration , as well as development of specific analysis and retrieval tools , is envisaged . this platform should be used as a global resource to share and exchange primary data derived from seldi- , maldi- , meldi- , ce- , lc- , and other tof - ms analyses in urinary research . we encourage other laboratories to contribute to updb by submitting high quality ms spectra from human urine samples . we envisage providing full linkage of the identified m / z species to the large - scale screening resource ( lssr ) database ( in preparation ) , which will list molecules identified by ms or other large - scale proteomic methods by their protein or gene names and will also contain a substantial database of identified peptide sequences relating to the proteins listed .
the use of human urine as a diagnostic tool has many advantages , such as ease of sample acquisition and noninvasiveness . 
 however , the discovery of novel biomarkers , as well as biomarker patterns , in urine is hindered mainly by a lack of comparable datasets . to fill this gap 
 , we assembled a new urinary fingerprint database . 
 here , we report the establishment of a human urinary proteomic fingerprint database using urine from 200 individuals analysed by seldi - tof ( surface enhanced laser desorption ionisation - time of flight ) mass spectrometry ( ms ) on several chip surfaces ( send , hp50 , np20 , q10 , cm10 , and imac30 ) . 
 the database currently lists 2490 unique peaks / ion species from 1172 nonredundant seldi analyses in the mass range of 1500 to 150000 . 
 all unprocessed mass spectrometric scans are available as  .xml  data files . 
 additionally , 1384 peaks were included from external studies using ce ( capillary electrophoresis)-ms , maldi ( matrix assisted laser desorption / ionisation ) , and ce - maldi hybrids . 
 we propose to use this platform as a global resource to share and exchange primary data derived from ms analyses in urinary research .