Key Features
Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreHepatosplenic T-cell lymphoma (HSTL) is an aggressive lymphoma cytogenetically characterized by isochromosome 7q [i(7)(q10)], of which the molecular consequences remain unknown. We report here results of an integrative genomic and transcriptomic (expression microarray and RNA-sequencing) study of six HSTL cases with i(7)(q10) and three cases with ring 7 [r(7)], a rare variant aberration. Using high resolution array CGH, we prove that HSTL is characterized by the common loss of a 34.88 Mb region at 7p22.1p14.1 (3506316-38406226 bp) and duplication/amplification of a 38.77 Mb region at 7q22.11q31.1 (86259620-124892276 bp). Our data indicate that i(7)(q10)/r(7)-associated loss of 7p22.1p14.1 is a critical event in the development of HSTL, while gain of 7q sequences drives progression of the disease and underlies its intrinsic chemoresistance. Loss of 7p22.1p14.1 does not target a postulated tumor suppressor gene but unexpectedly enhances the expression of CHN2 from the remaining 7p allele, resulting in dysregulation of a pathway involving RAC1 and NFATC2 with a cell proliferation response. Gain of 7q leads to increased expression of critical genes, including RUNDC3B, PPP1R9A and ABCB1, a known multidrug resistance gene. RNA-sequencing did not identify any additional recurrent mutations or fusion, suggesting that i(7)(q10) is the only driver event in this tumor. Our study confirms the previously described gene expression profile of HSTL and identifies a set of 24 genes, including three located on chromosome 7 (CHN2, ABCB1 and PPP1R9A), distinguishing HSTL from other malignancies SOURCE: Julio Finalet (julio.finaletferreiro@med.kuleuven.be) - KULeuven
View on GEOView in PlutoEnhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.
Learn MoreUse Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.
Read about post-pipeline analysisView quality control data and experiment metadata for this experiment.
Request imports from GEO or TCGA directly within Pluto Bio.
Chat with our Scientific Insights team