GEO series

Single cell RNA-seq of relapsed and refractory multiple myeloma patients defines new resistance pathways and targeted treatments

GSE161195 Homo sapiens (human) Single-cell RNA-seq 213 samples Submitted 2021/01/27 Platform GPL18573Platform GPL24676

At a glance

Single-cell RNA-seq · human · 213 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Topic: Multiple myelomaThis series is part of our curated briefing on it.
Samples: 213 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)

Multiple myeloma (MM) is a neoplastic plasma cell (PC) disorder, characterized by clonal proliferation of malignant PC. Despite extensive research, disease heterogeneity within and between treatment resistant patients is poorly characterized. Here, we conduct a prospective multi-center single-arm clinical trial (NCT04065789), combined with longitudinal single cell RNA-seq to study the molecular dynamics of MM resistance mechanisms.

Read the full summary ↓

Forty-one newly diagnosed MM patients who either failed to respond or experienced early relapse after a bortezomib-containing induction regimen, were enrolled to evaluate the safety and efficacy of a daratumumab/carfilzomib/lenalidomide/dexamethasone combination. Primary clinical endpoint was safety and tolerability. Secondary endpoints included overall response rate; progression free survival, and overall survival. Treatment was safe and well-tolerated, deep and durable responses were achieved. In prespecified exploratory analyses, comparison of 41 primary-refractory and early-relapsed patients with 11 healthy subjects and 15 newly diagnosed MM patients revealed new MM molecular pathways of resistance, including hypoxia tolerance, protein folding, and mitochondria respiration, that generalized to larger clinical cohorts (CoMMpass). We found peptidylprolyl isomerase A (PPIA), a central gene in the protein-folding response pathway, as a potential new target for resistant MM. CRISPR/Cas9 deletion of PPIA or inhibition of PPIA with cyclosporin A significantly sensitizes MM tumor cells to proteasome inhibitors. Together, our study defines a roadmap for integrating scRNA-seq in clinical trials, identifies a signature of highly resistant MM patients and discovers PPIA as a potent therapeutic target for these tumors.

This dataset

Open GSE161195 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 GSE161195_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA675855 and SRA study SRP292331. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 33619369) ↗

Samples in this study

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

+ 213 more — browse all 213 samples with per-sample file links →

More Multiple myeloma datasets

GSE167968 RNA-seq of Multiple Myeloma 33 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.