← BioTransfer GEO Dataset Finder
GEO series

Integration of gene mutations in risk prognostication for patients receiving first-line immunochemotherapy for follicular lymphoma

GSE66166 Homo sapiens Expression profiling by array 138 samples Submitted 2015/07/16 Platform GPL13938
Summary
Background: Follicular lymphoma (FL) is a clinically and genetically heterogeneous disease. The prognostic value of somatic mutations has not been systematically evaluated and no genetic factors have been identified that distinguish patients at highest risk of treatment failure. Methods: We performed deep sequencing of 74 genes in 151 patients treated with R-CHOP from a phase III trial. Mutations and clinical factors were incorporated into a risk model using multivariable L1-penalized Cox regression. We validated the risk model in an independent cohort of 107 patients treated with R-CVP. Results: The final clinicogenetic index, the “m7-FLIPI”, contained the FL International Prognostic Index (FLIPI), ECOG performance status, and mutation status of 7 genes (EZH2, ARID1A, MEF2B, EP300, FOXO1, CREBBP and CARD11). In the training cohort, the m7-FLIPI defined a high-risk group (28% of patients) with 5-year failure-free survival (FFS) of 38% vs 77% for the low-risk group (Hazard ratio (HR) 4.1, confidence Interval (CI)=[2.5;6.9], p<0.0001). In the validation cohort, the m7-FLIPI defined a high-risk group (22% of patients) with 5-year FFS of 25% versus 68% (HR 3.6, CI=[2.0;6.4], p<0.0001) in the low-risk group. In both cohorts, the m7-FLIPI outperformed the FLIPI alone. Strikingly, all 66 patients with EZH2 mutations in both cohorts were categorized as low-risk m7-FLIPI, and EZH2 mutations defined a distinct transcriptional profile. Conclusions: The combination of clinical factors and mutations in 7 genes can identify the subset of patients with FL at highest risk of treatment failure. The m7-FLIPI can be widely utilized for risk prognostication and patient stratification.
This dataset
Download

Direct links to NCBI, no account and no request form: the whole study as GSE66166_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 138 samples.

Also filed as BioProject PRJNA276026. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Sort into groups and it will be fetched from NCBI.

+ 138 more — browse all 138 samples with per-sample file links →

Similar datasets

Search all human microarray datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.