GEO series

Microarray expression data from follicular lymphoma patients' lymph node biopsies (frozen)

GSE148070 Homo sapiens (human) Expression microarray 40 samples Submitted 2020/12/31 Platform GPL17586

At a glance

Expression microarray · human · 40 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Homo sapiens (human)
Topic: Follicular lymphomaThis series is part of our curated briefing on it.
Samples: 40 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

Abstract from the associated publication: Although PET allows an accurate staging of disease in follicular lymphoma (FL) patients, the impact of pre-treatment maximum standardized uptake (SUVmax) value in this population remains elusive as well as its real biological significance. A training cohort of 48 FL patients and a validation cohort of 84 patients unpreviously treated were included retrospectively.

Read the full summary ↓

SUVmax of 18-FDG PET was evaluated by centrally expert review and the optimum threshold of SUVmax value was determined in the training cohort to predict progression free survival (PFS). To explore the biologic meaning of PET results, tumor samples were analyzed from the two cohorts independantly :- the tumor microenvironment immune cartography by immunochemistry , - the cell gene-expression profiles assessed using Sample enrichment score combined to CIBERSORT method and - the tumor cell mutational profile determined by targeted Next Generation Sequencing (t-NGS). At baseline, patients with a SUVmax >14.5 had a significantly lower PFS compared to patients with SUVmax ≤14.5 (2y PFS: 40% vs 86%, HR = 0.16, p = 0.0009). The prognostic value of SUVmax was confirmed in the validation cohort (p= 0.006). Neither immune cell infiltration nor immune checkpoint expression were related to the baseline PET metrics including SUVmax. By constrast, high tumor cell proliferation (assessed by Ki67 staining) was significantly related to high SUVmax level ( p= 0.007). Interestingly FOXO1 mutated patients harbored high SUVmax and high tumor proliferation, that is why FOXO1 status could reflect to proliferation of FL tumor cells through SUVmax and Ki67 staining. So, FL patients with high baseline SUVmax related to high tumor cell proliferation have a poorer PFS despite absence of lymphoma transformation.

This dataset

Open GSE148070 in finder → Find more human microarray datasets → Follicular lymphoma landscape →

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.

Series matrix ↓

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 (GSE148070_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA622992. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 33327711) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 40 more — browse all 40 samples with per-sample file links →

More Follicular lymphoma datasets

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GSE103944 Gene Expression Profiling reveals a close relationship between Follicular lymphoma Grade 3A and 3B, but distinct profiles of Follicular Lymphoma Grade 1 and 2 84 samples same disease briefing · shares follicular, lymphoma, lymph
GSE93261 Transcriptome analysis of Follicular Lymphomas from the PRIMABIO cohort 149 samples same disease briefing · shares follicular, lymphoma, lymph
GSE66166 Integration of gene mutations in risk prognostication for patients receiving first-line immunochemotherapy for follicular lymphoma 138 samples same disease briefing · shares follicular, lymphoma, lymph
GSE42525 Affymetrix SNP array data for follicular lymphoma (FL) and transformed follicular lymphoma (tFL) samples 91 samples same disease briefing · shares follicular, lymphoma, lymph
GSE272403 Multi-omics profiling of longitudinal samples reveals early genomic changes in follicular lymphoma 76 samples same disease briefing · shares follicular, lymphoma, lymph
GSE261465 STAT6 mutations compensate for CREBBP mutations and hyperactivate IL4/STAT6/RRAGD/mTOR signaling in follicular lymphoma 46 samples same disease briefing · shares follicular, lymphoma, lymph
GSE290351 IRF4 promotes immune-evasion and shapes the Tumor Microenvironment in Follicular Lymphoma 42 samples same disease briefing · shares follicular, lymphoma, lymph

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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.