Source:
@ARTICLE{Lapointe2004,
author = {Jacques Lapointe and Chunde Li and John P
Higgins and Matt van de Rijn and Eric Bair and Kelli Montgomery and Michelle
Ferrari and Lars Egevad and Walter Rayford and Ulf Bergerheim and
Peter Ekman and Angelo M DeMarzo
and Robert Tibshirani and David Botstein and Patrick
O Brown and James D Brooks and Jonathan R Pollack},
title = {Gene expression profiling identifies
clinically relevant subtypes of prostate cancer.},
journal = {Proc Natl Acad Sci U S A},
year = {2004},
volume = {101},
pages = {811--816},
number = {3},
month = {Jan},
doi =
{10.1073/pnas.0304146101},
url =
{http://dx.doi.org/10.1073/pnas.0304146101}
}
Original data: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE3933
Description:
Prostate cancer displays
a broad range of clinical behavior from relatively indolent to aggressive
metastatic disease. To explore potential molecular variation underlying this clinical heterogeneity, we
profiled gene expression in 62 primary prostate tumors, as well as 41 normal
prostate specimens and nine lymph node
metastases, using cDNA microarrays containing
approximately 26,000 genes. Unsupervised
hierarchical clustering readily distinguished tumors from normal samples, and
further identified three subclasses (PT1, PT2 and PT3) of prostate tumors based
on distinct patterns of gene expression.
Parameters used in our filter: