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CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy I

GSE246342 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/07/29 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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)
Samples
18 samples: 18 samples, each with a distinct title — no replicated groupsGroups 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
CD4+ CAR T-cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR T-cell therapyBlood advances · 2024
Summary (written by the submitters)
Multiple myeloma is characterized by frequent clinical relapses following conventional therapy. Recently, chimeric antigen receptor T (CAR-T) cells targeting B-cell maturation antigen (BCMA) has been established as a treatment for patients with relapsed or refractory disease. However, while >70% of patients initially respond to this treatment, clinical relapse and disease progression occurs in most cases.
Read the full summary ↓
Recent studies showed persistent expression of BCMA at the time of relapse, indicating that immune intrinsic mechanisms may contribute to this resistance. While there were no pre-existing T cell features associated with clinical outcomes, we found that patients with a durable response to CAR-T cell treatment had greater persistence of their CAR-T cells compared to patients with transient clinical responses. They also possessed a significantly higher proportion of CD8+ T effector memory cells. In contrast, patients with short-lived responses to treatment have increased frequencies of cytotoxic CD4+ CAR-T cells. These cells expand in vivo early after infusion but express exhaustion markers (HAVCR2 and TIGIT) and remain polyclonal. Finally, we demonstrate that non-classical monocytes are enriched in the myeloma niche and may induce CAR-T cell dysfunction through mechanisms that include TGFβ. These findings shed new light on the role of cytotoxic CD4+ T cells in disease progression after CAR-T cell therapy.
Published in
CD4+ CAR T-cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR T-cell therapy
Ledergor G, Fan Z, Wu K et al. · Blood advances 2024 · PMID 38574299 · doi:10.1182/bloodadvances.2023012416
This dataset
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.

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 GSE246342_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1032579 and SRA study SRP468635. Searching any of these in the dataset finder brings you back here.

Study design
18 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 14 samples read as cases, 4 as controls.

How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. 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
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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.