Transcriptomics

Dataset Information

0

Expression data from skin biopsies in cutaneous T-cell lymphoma


ABSTRACT: Cutaneous T cell lymphoma (CTCL) is defined by infiltration of activated and malignant T cells in skin. The clinical manifestations and prognosis in CTCL are highly variable. In this study, we hypothesized that gene expression analysis in lesional skin biopsies can improve understanding of the disease and its management. Based on 63 skin samples, we performed consensus clustering, revealing three patient clusters. Two clusters tended to differentiate limited CTCL (stages IA and IB) from more extensive CTCL (stages IB and III). Stage IB subjects appeared in both clusters, but those in the limited CTCL cluster were more responsive to treatment than those in the more extensive CTCL cluster. The third cluster was enriched in lymphocyte activation genes and was associated with a high proportion of tumor (stage IIB) lesions. Survival analysis revealed significant differences in event-free survival between clusters, with poorest survival seen in the activated lymphocyte cluster. Using supervised analysis, we further characterized genes significantly associated with lower stage/treatment responsive versus higher stage/treatment resistant CTCL. We conclude that transcriptional profiling of CTCL skin lesions reveals clinically relevant signatures, correlating with differences in survival and response to treatment. Additional prospective long-term studies to validate and refine these findings appear warranted. Keywords: disease state analysis

ORGANISM(S): Homo sapiens

PROVIDER: GSE9479 | GEO | 2007/11/01

SECONDARY ACCESSION(S): PRJNA103253

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2008-06-16 | E-GEOD-9479 | biostudies-arrayexpress
2015-06-27 | E-GEOD-70328 | biostudies-arrayexpress
2015-06-27 | GSE70328 | GEO
2019-05-10 | GSE128531 | GEO
2020-04-13 | GSE122934 | GEO
2024-12-22 | GSE192646 | GEO
2024-10-24 | GSE266862 | GEO
2018-08-21 | GSE113113 | GEO
2011-11-22 | GSE31408 | GEO
2011-11-22 | E-GEOD-31408 | biostudies-arrayexpress