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Multi-omics profiling of longitudinal samples reveals early genomic changes in follicular lymphoma

GSE272403 Homo sapiens (human) RNA-seq (gene expression) 76 samples Submitted 2024/08/20 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 76 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Follicular lymphomaThis series is part of our curated briefing on it.
Samples
76 samples: 20 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Multi-omics profiling of longitudinal samples reveals early genomic changes in follicular lymphomaBlood cancer journal · 2024
Summary (written by the submitters)
Follicular lymphoma (FL) is the most common indolent type of B-cell non-Hodgkin lymphoma. Advances in treatment have improved overall survival, but early relapse or transformation to aggressive disease is associated with inferior outcome. To identify early genetic events and track tumor clonal evolution, we performed multi-omics analysis of 94 longitudinal biopsies from 44 FL patients; 22 with transformation (tFL) and 22 with relapse without transformation (nFL).
Read the full summary ↓
Deep whole-exome sequencing confirmed recurrent mutations in genes encoding epigenetic regulators (CREBBP, KMT2D, EZH2, EP300), with similar mutational landscape in nFL and tFL patients. Calculation of genomic distances between longitudinal samples revealed complex evolutionary patterns in both subgroups. CREBBP and KMT2D mutations were identified as genetic events that occur early in the disease course, and cases with CREBBP KAT domain mutations had low risk of transformation. Gains in chromosomes 12 and 18 (TCF4), and loss in 6q were identified as early and stable copy number alterations. Identification of such early and stable genetic events may provide opportunities for early disease detection and disease monitoring. Integrative analysis revealed that tumors with EZH2 mutations exhibited reduced gene expression of numerous histone genes, including histone linker genes. This might contribute to the epigenetic dysregulation in FL.
Published in
Multi-omics profiling of longitudinal samples reveals early genomic changes in follicular lymphoma
Bai B, Wise JF, Vodák D et al. · Blood cancer journal 2024 · PMID 39191762 · doi:10.1038/s41408-024-01124-5
This dataset
Open GSE272403 in finder → Find more human RNA-seq datasets → Follicular lymphoma landscape →
Download · which file do I need?

Direct links to NCBI and ENA, 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, or the whole study as GSE272403_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1136789. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39191762) ↗
Study design
20 conditions, mostly in duplicate
P23 ×3 P27 ×3 P31 ×3 P46 ×3 P75 ×3 P1 ×2 P10 ×2 P11 ×2 +43 more

Supports a between-group comparison across 45 samples.

How we read this: 20 replicated groups read from 76 sample titles; they account for 45 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 36 more — browse all 76 samples with per-sample file links →

More Follicular lymphoma datasets

Search all human RNA-seq datasets in GEO →

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