NEAT1-driven ceRNA network in multiple myeloma
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)
- Topic
- Multiple myelomaThis series is part of our curated briefing on it.
- 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
- Identification of ceRNA Regulatory Networks Driven by the lncRNA NEAT1 in Multiple MyelomaJournal of cellular and molecular medicine · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE304590_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1301852 and SRA study SRP606659. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
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.
- GSM9153567 AMO1 multiple myeloma celll line with SCR GapmeR replicate A
- GSM9153568 AMO1 multiple myeloma celll line with SCR GapmeR replicate C
- GSM9153569 AMO1 multiple myeloma celll line with SCR GapmeR replicate D
- GSM9153570 AMO1 multiple myeloma celll line with gN1E GapmeR replicate A
- GSM9153571 AMO1 multiple myeloma celll line with gN1E GapmeR replicate C
- GSM9153572 AMO1 multiple myeloma celll line with gN1E GapmeR replicate D
- GSM9153573 LP1 multiple myeloma celll line with SCR GapmeR replicate A
- GSM9153574 LP1 multiple myeloma celll line with SCR GapmeR replicate B
- GSM9153575 LP1 multiple myeloma celll line with SCR GapmeR replicate D
- GSM9153576 LP1 multiple myeloma celll line with gN1E GapmeR replicate A
- GSM9153577 LP1 multiple myeloma celll line with gN1E GapmeR replicate B
- GSM9153578 LP1 multiple myeloma celll line with gN1E GapmeR replicate D
- GSM9153579 H929 multiple myeloma celll line with SCR GapmeR replicate A
- GSM9153580 H929 multiple myeloma celll line with SCR GapmeR replicate B
- GSM9153581 H929 multiple myeloma celll line with SCR GapmeR replicate C
- GSM9153582 H929 multiple myeloma celll line with gN1E GapmeR replicate A
- GSM9153583 H929 multiple myeloma celll line with gN1E GapmeR replicate B
- GSM9153584 H929 multiple myeloma celll line with gN1E GapmeR replicate C
- 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, myeloma
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing · shares multiple, myeloma
- GSE167968 RNA-seq of Multiple Myeloma 33 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
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 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
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.