GEO series

RNA-seq of Multiple Myeloma

GSE167968 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2021/03/03 Platform GPL20301

At a glance

RNA-seq (gene expression) · human · 33 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: Multiple myelomaThis series is part of our curated briefing on it.
Samples: 33 samples
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.

Summary (written by the submitters)

Purpose: Multiple myeloma is a malignancy of plasma cells. Extensive genetic and transcriptional characterization of myeloma has identified subtypes with prognostic and therapeutic implications. In contrast, relatively little is known about the myeloma epigenome. Experimental Design: CD138+CD38+ myeloma cells were isolated from fresh bone marrow aspirate or the same aspirate after freezing for one to six months.

Read the full summary ↓

Gene expression and chromatin accessibility were compared between fresh and frozen samples by RNA-seq and ATAC-seq. Chromatin accessible regions were used to identify regulatory RNA expression in over 700 samples from newly diagnosed patients in the MMRF CoMMpass trial (NCT01454297). Results: Gene expression and chromatin accessibility of cryopreserved myeloma recapitulated that of freshly isolated samples. ATAC-seq performed on a series of biobanked specimens identified thousands of chromatin accessible regions with hundreds being highly coordinated with gene expression. Over 4,700 of these chromatin accessible regions were transcribed in newly diagnosed myelomas from the CoMMpass trial. Regulatory element activity alone recapitulated myeloma gene expression subtypes, and in particular myeloma subtypes with IGH translocations were defined by transcription of distal regulatory elements. Moreover, enhancer activity predicted oncogene expression implicating gene regulatory mechanisms in aggressive myeloma. Conclusions: These data demonstrate the feasibility of using biobanked specimens for retrospective studies of the myeloma epigenome and illustrate the unique enhancer landscapes of myeloma subtypes that are coupled to gene expression and disease progression.

This dataset

Open GSE167968 in finder → Find more human RNA-seq datasets → Multiple myeloma 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 GSE167968_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 PRJNA705687 and SRA study SRP308709. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 33731366) ↗

Samples in this study

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

+ 33 more — browse all 33 samples with per-sample file links →

More Multiple myeloma datasets

GSE161195 Single cell RNA-seq of relapsed and refractory multiple myeloma patients defines new resistance pathways and targeted treatments 213 samples same disease briefing · shares multiple, rna-seq, myeloma
GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing · shares multiple, rna-seq, myeloma
GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing · shares multiple, myeloma
GSE179453 Expression data from control-knockdown (CTR-KD) and MAST4-KD human multiple myeloma (MM) cell lines 6 samples same disease briefing · shares multiple, myeloma
GSE178442 Genome-wide maps of transcription in DEAF1 overexpression(OE) and wildtype(WT) cells in Multiple Myeloma 4 samples same disease briefing · shares multiple, myeloma
GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 samples same disease briefing · shares multiple, myeloma
GSE167042 Splicing modulation increases BCL2 dependence and sensitizes Multiple Myeloma cells to Venetoclax 4 samples same disease briefing · shares multiple, myeloma
GSE178328 Genome-wide maps of chromatin state in DEAF1 overexpression (OE in Multiple Myeloma) 2 samples same disease briefing · shares multiple, myeloma

Search all human RNA-seq datasets in GEO →

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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.