Ep
ithel
ial ovar
ian cancer
is the most lethal gynecolog
ical mal
ignancy, and d
isease-spec
if
ic b
iomarkers are urgently needed to
improve d
iagnos
is, prognos
is, and to pred
ict and mon
itor treatment eff
ic
iency. We present an
in-depth proteom
ic analys
is of selected b
iochem
ical fract
ions of human ovar
ian cancer asc
ites, result
ing
in the str
ingent and conf
ident
ident
if
icat
ion of over 2500 prote
ins. R
igorous f
ilter schemes were appl
ied to object
ively m
in
im
ize the number of false-pos
it
ive
ident
if
icat
ions, and we only report prote
ins w
ith substant
ial pept
ide ev
idence. Integrated computat
ional analys
is of the asc
ites proteome comb
ined w
ith several recently publ
ished proteom
ic data sets of human plasma, ur
ine, 59 ovar
ian cancer related m
icroarray data sets, and prote
in–prote
in
interact
ions from the Interologous Interact
ion Database I
2D (
id.utoronto.ca/i2d" target="_blank">http://ophid.utoronto.ca/i2d) resulted
in a short-l
ist of 80 putat
ive b
iomarkers. The presented proteom
ics analys
is prov
ides a s
ign
if
icant resource for ovar
ian cancer research, and a framework for b
iomarker d
iscovery.