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Genomic profiles of diffuse large B-cell lymphomas

GSE15127 Homo sapiens (human) Genome variation profiling by SNP array 167 samples Submitted 2009/04/01 Platform GPL3718
At a glance

human · 167 samples

Organism
Homo sapiens (human)
Topic
Diffuse large B-cell lymphomaThis series is part of our curated briefing on it.
Samples
167 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
Despite recent therapeutic improvements, the clinical course of diffuse large B-cell lymphoma (DLBCL) still differs considerably among patients. We conducted this retrospective multi-centre study to evaluate the impact of genomic aberrations detected using a high-density genome wide-single nucleotide polymorphism-based array on clinical outcome in a population of DLBCL patients treated with R-CHOP-21 (rituximab, cyclophosphamide, doxorubicine, vincristine and prednisone repeated every 21 d).
Read the full summary ↓
167 DNA samples were analysed using the GeneChip Human Mapping 250K NspI. Genomic anomalies were analysed regarding their impact on the clinical course of 124 patients treated with R-CHOP-21. Unsupervised clustering was performed to identify genetically related subgroups of patients with different clinical outcomes. Twenty recurrent genetic lesions showed an impact on the clinical course. Loss of genomic material at 8p23.1 showed the strongest statistical significance and was associated with additional aberrations, such as 17p- and 15q-. Unsupervised clustering identified five DLBCL clusters with distinct genetic profiles, clinical characteristics and outcomes. Genetic features and clusters, associated with a different outcome in patients treated with R-CHOP, have been identified by arrayCGH. DNA copy number profiling by SNP array.
This dataset
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE15127_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Also filed as BioProject PRJNA114945. Searching any of these in the dataset finder brings you back here.

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