Source:
@ARTICLE{Yeoh2002,
author = {Eng-Juh Yeoh
and Mary E Ross and Sheila A Shurtleff and W. Kent Williams and Divyen Patel
and Rami Mahfouz and Fred G Behm and Susana C Raimondi and Mary V Relling and
Anami Patel and Cheng Cheng and Dario Campana and Dawn Wilkins and Xiaodong
Zhou and Jinyan Li and Huiqing Liu and Ching-Hon Pui and William E Evans and
Clayton Naeve and Limsoon Wong and James R Downing},
title = {Classification, subtype discovery, and
prediction of outcome in pediatric acute lymphoblastic leukemia by gene
expression profiling.},
journal = {Cancer Cell},
year = {2002},
volume = {1},
pages = {133--143},
number = {2},
month = {Mar},
}
Original data: http://www.stjuderesearch.org/data/ALL1/all_datafiles.html
Description:
Treatment of pediatric
acute lymphoblastic leukemia (ALL) is based on the concept of tailoring the
intensity of therapy to a patient's risk of relapse. To determine whether gene
expression profiling could enhance risk assignment, the authors used
oligonucleotide microarrays to analyze the pattern of genes expressed in
leukemic blasts from 360 pediatric ALL patients. Distinct expression profiles
identified each of the prognostically important leukemia subtypes, including
T-ALL, E2A-PBX1, BCR-ABL, TEL-AML1, MLL rearrangement, and hyperdiploid >50
chromosomes. In addition, another ALL subgroup (OTHER) was identified based on
its unique expression profile. In order to build our data set, we discard the
samples belonging to OTHER. Also, we create another data set where we the samples
are labeled either as T-ALL or B-ALL.
Parameters used in our filter: