Pharmacological Downregulation of De Novo Active and Essential lncRNA SMILO via Inhibition of FLI1 Transcription Factor in Multiple Myeloma.
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Topic
- Multiple myelomaThis series is part of our curated briefing on it.
- Samples
- 24 samples: 24 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
- BET inhibitors downregulate the expression of the essential lncRNA SMILO in multiple myeloma through regulation of the transcription factor FLI1Haematologica · 2025
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 GSE260566_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1082237 and SRA study SRP492549. 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 24 sample titles: 24 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.
- GSM8119534 KMS-11, C, R1 RNA-seq
- GSM8119535 KMS-11, JQ1, R1 RNA-seq
- GSM8119536 KMS-12, C, R1 RNA-seq
- GSM8119537 KMS-12, JQ1, R1 RNA-seq
- GSM8119538 RPMI8226, C, R1 RNA-seq
- GSM8119539 RPMI8226, JQ1, R1 RNA-seq
- GSM8119540 KMS-11, C, R2 RNA-seq
- GSM8119541 KMS-11, JQ1, R2 RNA-seq
- GSM8119542 KMS-12, C, R2 RNA-seq
- GSM8119543 KMS-12, JQ1, R2 RNA-seq
- GSM8119544 RPMI8226, C, R2 RNA-seq
- GSM8119545 RPMI8226, JQ1, R2 RNA-seq
- GSM8119546 KMS-11, C, ATAC-seq
- GSM8119547 KMS-11, JQ1, ATAC-seq
- GSM8119548 KMS-12, C, ATAC-seq
- GSM8119549 KMS-12, JQ1, ATAC-seq
- GSM8119550 RPMI8226, C, ATAC-seq
- GSM8119551 RPMI8226, JQ1, ATAC-seq
- GSM8119560 KMS-11, C, ChIP-seq
- GSM8119561 KMS-11, JQ1, ChIP-seq
- GSM8119562 KMS-12, C, ChIP-seq
- GSM8119563 KMS-12, JQ1, ChIP-seq
- GSM8119564 RPMI8226, C, ChIP-seq
- GSM8119565 RPMI8226, JQ1, ChIP-seq
- GSE178442 Genome-wide maps of transcription in DEAF1 overexpression(OE) and wildtype(WT) cells in Multiple Myeloma 4 samples same disease briefing · shares transcription, multiple
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing · shares multiple
- 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
- GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 samples same disease briefing · shares multiple
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing · shares multiple
- GSE167968 RNA-seq of Multiple Myeloma 33 samples same disease briefing · shares multiple
- GSE179453 Expression data from control-knockdown (CTR-KD) and MAST4-KD human multiple myeloma (MM) cell lines 6 samples same disease briefing · shares multiple
- GSE167042 Splicing modulation increases BCL2 dependence and sensitizes Multiple Myeloma cells to Venetoclax 4 samples same disease briefing · shares multiple
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.