Modelling Myeloma Dissemination in vitro with hMSC-Interacting Subpopulations of INA-6 Cells and their Aggregation/Detachment Dynamics
Single-cell RNA-seq · human · 15 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Topic
- Multiple myelomaThis series is part of our curated briefing on it.
- Samples
- 15 samples: 15 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
- Modeling Myeloma Dissemination In Vitro with hMSC-interacting Subpopulations of INA-6 Cells and Their Aggregation/Detachment DynamicsCancer research communications · 2024
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 GSE261423_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: 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 PRJNA1086919 and SRA study SRP494780. 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 15 sample titles: 15 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.
- GSM8143797 CM-INA6 / F1, hMSC-conditioned Medium F1 (WPSC Control) (biol rep 1)
- GSM8143798 nMA-INA6 / F2, Removed by Centrifugation F2 (WPSC) (biol rep 1)
- GSM8143799 MA-INA6 / F3, Remaining after Centrifugation F3 (WPSC) (biol rep 1)
- GSM8143800 CM-INA6 / F1, hMSC-conditioned Medium F1 (WPSC Control) (biol rep 2)
- GSM8143801 nMA-INA6 / F2, Removed by Centrifugation F2 (WPSC) (biol rep 2)
- GSM8143802 MA-INA6 / F3, Remaining after Centrifugation F3 (WPSC) (biol rep 2)
- GSM8143803 CM-INA6 / F1, hMSC-conditioned Medium F1 (WPSC Control) (biol rep 3)
- GSM8143804 nMA-INA6 / F2, Removed by Centrifugation F2 (WPSC) (biol rep 3)
- GSM8143805 MA-INA6 / F3, Remaining after Centrifugation F3 (WPSC) (biol rep 3)
- GSM8143806 CM-INA6 / F1, hMSC-conditioned Medium F1 (WPSC Control) (biol rep 4)
- GSM8143807 nMA-INA6 / F2, Removed by Centrifugation F2 (WPSC) (biol rep 4)
- GSM8143808 MA-INA6 / F3, Remaining after Centrifugation F3 (WPSC) (biol rep 4)
- GSM8143809 CM-INA6 / F1, hMSC-conditioned Medium F1 (WPSC Control) (biol rep 5)
- GSM8143810 nMA-INA6 / F2, Removed by Centrifugation F2 (WPSC) (biol rep 5)
- GSM8143811 MA-INA6 / F3, Remaining after Centrifugation F3 (WPSC) (biol rep 5)
- GSE161195 Single cell RNA-seq of relapsed and refractory multiple myeloma patients defines new resistance pathways and targeted treatments 213 samples same disease briefing
- GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing
- GSE167968 RNA-seq of Multiple Myeloma 33 samples same disease briefing
- GSE179453 Expression data from control-knockdown (CTR-KD) and MAST4-KD human multiple myeloma (MM) cell lines 6 samples same disease briefing
- GSE178442 Genome-wide maps of transcription in DEAF1 overexpression(OE) and wildtype(WT) cells in Multiple Myeloma 4 samples same disease briefing
- GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 samples same disease briefing
- GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing
- GSE167042 Splicing modulation increases BCL2 dependence and sensitizes Multiple Myeloma cells to Venetoclax 4 samples same disease briefing
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.