Project description:CD4+ T-cells from three follicular lymphoma tumors were sorted by flow cytometry into three subsets based on high (hi), intermediate (int), or low (lo) levels of PD-1 and CXCR5 expression and whole genome gene expression profiling was performed.

2013-11-21 | GSE52561 | GEO

Gene expression profiling in follicular lymphoma (FL) samples and paired transformed follicular lymphoma (tFL) (n=6 samples)

Project description:Follicular lymphoma (FL) is the second most common forms of B cell lymphoma that result from the expansion of germinal center (GC) B cells. Here, we aimed to find differential expression of genes between patient samples isolated from indoent FL or transformed and aggressive FL.

2019-12-20 | GSE142334 | GEO

Gene expression Profiling in Follicular Lymphomas

Project description:Follicular lymphoma (FL) is an indolent, but incurable subtype of non-Hodgkin lymphoma. These tumor harbor t (14;18) translocation in at least 90% of patients. Recently, activating EZH2 mutations have been Follicular lymphoma (FL) is an indolent, but incurable subtype of non-Hodgkin lymphoma. These tumor harbor t (14;18) translocation in at least 90% of patients. Recently, activating EZH2 mutations have been found in a significant number of patients with FL. Gene expression profiling (GEP) was performed to determine differential gene-expression between the EZH2 mutated vs unmutated subgroups in FL.

2014-07-01 | GSE55267 | GEO

Follicular Lymphoma expression array

Project description:We used microarrays to detail gene expression profile of several follicular lymphoma patient samples with different grades

2012-04-30 | GSE37088 | GEO

Predicting Outcome in Follicular Lymphoma by Using Interactive Gene Pairs

Project description:Purpose: Follicular lymphoma is a common lymphoma of adults. Although its course is often indolent, a substantial proportion of patients have a poor prognosis, often due to rapid progression or transformation to a more aggressive lymphoma. Currently available clinical prognostic scores, such as the follicular lymphoma international prognostic index, are not able to optimally predict transformation or poor outcome. Experimental Design: Gene expression profiling was done on primary lymphoma biopsy samples. Results: Using a statistically conservative approach, predictive interaction analysis, we have identified pairs of interacting genes that predict poor outcome, measured as death within 5 years of diagnosis. The best gene pair performs >1,000-fold better than any single gene or the follicular lymphoma international prognostic index in our data set. Many gene pairs achieve outcome prediction accuracies exceeding 85% in extensive cross-validation and noise sensitivity computational analyses.Many genes repeatedly appear in top-ranking pairs, suggesting that they reproducibly provide predictive capability. Conclusions:The evidence reported here may provide the basis for an expression-based, multigene test for predicting poor follicular lymphoma outcomes. Keywords: Comparative genomics

2008-10-15 | GSE13029 | GEO

Follicular Lymphoma expression array

Project description:We used microarrays to detail gene expression profile of several follicular lymphoma patient samples with different grades We analyzed 72 FL samples

2012-04-29 | E-GEOD-37088 | biostudies-arrayexpress

Gene expression profiling of lymph node mesenchymal stromal cells in follicular lymphoma.

Project description:Gene expression profiling of lymph node mesenchymal stromal cells in follicular lymphoma.

| PRJNA1127480 | ENA