Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Transcription profiling of bone marrow from children with T-cell acute lymphoblastic leukamia comparing those who remained in continuous complete remission with those that relapsed


ABSTRACT: We compared the gene expression profile from a group of children with T-cell acute lymphoblastic leukamia who remained in continuous complete remission (CCR) (n = 7) with that from a group who relapsed (n = 5), using Affymetrix HG-U133A arrays. Using the decision-tree based supervised learning algorithm Random Forest (RF), genes were ranked with respect to their ability to discriminate between patients who remained in CCR and those who relapsed. From the 300 top-ranked probe sets 9 genes were selected for further investigation and validation in an independent cohort of 25 T-ALL patients using quantitative real time polymerase chain reaction.

ORGANISM(S): Homo sapiens

SUBMITTER: Nicholas Gottardo 

PROVIDER: E-TABM-255 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications

Identification of novel molecular prognostic markers for paediatric T-cell acute lymphoblastic leukaemia.

Gottardo Nicholas G NG   Hoffmann Katrin K   Beesley Alex H AH   Freitas Joseph R JR   Firth Martin J MJ   Perera Kanchana U KU   de Klerk Nicolas H NH   Baker David L DL   Kees Ursula R UR  

British journal of haematology 20070501 4


In the last four decades the survival of patients with newly diagnosed childhood T-cell acute lymphoblastic leukaemia (T-ALL) has improved dramatically. In sharp contrast, relapsed T-ALL continues to confer a dismal prognosis. We sought to determine if gene expression profiling could uncover a signature of outcome for children with T-ALL. Using 12 patient specimens obtained before therapy started, we examined the gene expression profile by oligonucleotide microarrays. We identified three genes,  ...[more]

Similar Datasets

2007-05-11 | E-TABM-125 | biostudies-arrayexpress
2012-06-12 | GSE34880 | GEO
2012-06-11 | E-GEOD-34880 | biostudies-arrayexpress
2022-03-23 | GSE190942 | GEO
2023-09-05 | GSE235923 | GEO
2015-05-07 | E-GEOD-52891 | biostudies-arrayexpress
2022-02-17 | GSE153173 | GEO
2023-12-31 | GSE225239 | GEO
2015-05-07 | GSE52891 | GEO
2015-04-23 | E-GEOD-62618 | biostudies-arrayexpress