Transcriptomics

Dataset Information

0

Single-cell profiling of cutaneous T-cell lymphoma reveals underlying heterogeneity predicting with disease progression.


ABSTRACT: Cutaneous T cell lymphomas (CTCL), encompassing a spectrum of T-cell lymphoproliferative disorders involving the skin, have collectively increased in incidence over the last 40 years. Sézary syndrome (SS) is an aggressive form of CTCL characterized by significant presence of malignant cells in both the blood and skin. The guarded prognosis for SS reflects a lack of reliably effective therapy, due in part to an incomplete understanding of disease pathogenesis. Using single-cell sequencing of RNA, we confirm that SS is a clonal disease, but we further define a more complex model featuring distinct transcriptomic states within SS. Our analysis showed the involvement of FOXP3+ malignant T cells during clonal evolution, transitioning from FOXP3+ T cells to GATA3+ or IKZF2+ (HELIOS) tumor cells. Transcriptomic diversities in a clonal tumor can be used to predict disease stage, and we were able to characterize a gene signature that predicts disease stage with close to 80% accuracy. Supporting the critical role of FOXP3+ T cell involvement during clonal evolution, FOXP3 was found to be the most important factor to predict early disease in SS, along with another 19 genes used to predict CTCL stage. This work offers insight into the heterogeneity of SS, providing better understanding of the transcriptomic diversities within a clonal tumor, which can predict tumor stage and thereby offer guidance of therapy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE122703 | GEO | 2019/03/22

REPOSITORIES: GEO

Dataset's files

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

Similar Datasets

2022-03-04 | GSE146586 | GEO
2019-06-25 | GSE124898 | GEO
2015-07-01 | GSE59179 | GEO
2015-07-01 | E-GEOD-59179 | biostudies-arrayexpress
2023-09-29 | GSE229406 | GEO
2023-09-29 | GSE227326 | GEO
2008-06-16 | E-GEOD-9479 | biostudies-arrayexpress
2015-06-27 | E-GEOD-70328 | biostudies-arrayexpress
2007-11-01 | GSE9479 | GEO
2009-02-21 | E-GEOD-14746 | biostudies-arrayexpress