β-hydroxybutyrate-driven histone lysine β-hydroxybutyrylation promotes the immunostimulatory activity of monocyte-derived macrophages in rectal cancer
RNA-seq (gene expression) · human · 32 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
- Colorectal cancerThis series is part of our curated briefing on it.
- Samples
- 32 samples: 12 conditions, mostly in triplicateGroups 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
- Hypofractionated Radiotherapy Induces ISG15(+)MHC-I(+) Neutrophils to Augment Anti-Tumor Immunity and Prime Immune Checkpoint Blockade Responses in Rectal CancerAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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 GSE316027_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 PRJNA1400488. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 32 samples.
How we read this: 12 replicated groups read from 32 sample titles; they account for 32 of them. 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.
- GSM9443509 Donor1, SIC, scRNA-seq, T1 Donor1, SIC, scRNA-seq,…
- GSM9443510 Donor1, SIC, scRNA-seq, T2 Donor1, SIC, scRNA-seq,…
- GSM9443511 Donor1, SIC, scRNA-seq, T3 Donor1, SIC, scRNA-seq,…
- GSM9443512 Donor2, SIC, scRNA-seq, T1 Donor2, SIC, scRNA-seq,…
- GSM9443513 Donor2, SIC, scRNA-seq, T2 Donor2, SIC, scRNA-seq,…
- GSM9443514 Donor2, SIC, scRNA-seq, T3 Donor2, SIC, scRNA-seq,…
- GSM9443515 Donor3, SIC, scRNA-seq, T1 Donor3, SIC, scRNA-seq,…
- GSM9443516 Donor3, SIC, scRNA-seq, T2 Donor3, SIC, scRNA-seq,…
- GSM9443517 Donor3, SIC, scRNA-seq, T3 Donor3, SIC, scRNA-seq,…
- GSM9443518 Donor4, SIC, scRNA-seq, T1 Donor4, SIC, scRNA-seq,…
- GSM9443519 Donor4, SIC, scRNA-seq, T2 Donor4, SIC, scRNA-seq,…
- GSM9443520 Donor4, SIC, scRNA-seq, T3 Donor4, SIC, scRNA-seq,…
- GSM9443521 Donor5, SIC, scRNA-seq, T1 Donor5, SIC, scRNA-seq,…
- GSM9443522 Donor5, SIC, scRNA-seq, T3 Donor5, SIC, scRNA-seq,…
- GSM9443523 Donor6, SIC, scRNA-seq, T1 Donor6, SIC, scRNA-seq,…
- GSM9443524 Donor6, SIC, scRNA-seq, T2 Donor6, SIC, scRNA-seq,…
- GSM9443525 Donor6, SIC, scRNA-seq, T3 Donor6, SIC, scRNA-seq,…
- GSM9443526 Donor7, SIC, scRNA-seq, T1 Donor7, SIC, scRNA-seq,…
- GSM9443527 Donor7, SIC, scRNA-seq, T3 Donor7, SIC, scRNA-seq,…
- GSM9443528 Donor8, SIC, scRNA-seq, T1 Donor8, SIC, scRNA-seq,…
- GSM9443529 Donor8, SIC, scRNA-seq, T2 Donor8, SIC, scRNA-seq,…
- GSM9443530 Donor8, SIC, scRNA-seq, T3 Donor8, SIC, scRNA-seq,…
- GSM9443531 Donor9, SIC, scRNA-seq, T1 Donor9, SIC, scRNA-seq,…
- GSM9443532 Donor9, SIC, scRNA-seq, T2 Donor9, SIC, scRNA-seq,…
- GSM9443533 Donor9, SIC, scRNA-seq, T3 Donor9, SIC, scRNA-seq,…
- GSM9443534 Donor10, SIC, scRNA-seq, T1 Donor10, SIC, scRNA-seq…
- GSM9443535 Donor10, SIC, scRNA-seq, T2 Donor10, SIC, scRNA-seq…
- GSM9443536 Donor11, SIC, scRNA-seq, T1 Donor11, SIC, scRNA-seq…
- GSM9443537 Donor11, SIC, scRNA-seq, T2 Donor11, SIC, scRNA-seq…
- GSM9461027 Donor12, SIC, scRNA-seq, T1 Donor12, SIC, scRNA-seq…
- GSM9461028 Donor12, SIC, scRNA-seq, T2 Donor12, SIC, scRNA-seq…
- GSM9461029 Donor12, SIC, scRNA-seq, T3 Donor12, SIC, scRNA-seq…
- GSE250000 Bulk RNA-sequencing of transduced colorectal cancer cell line HCT-116 and breast cancer cell line MCF-7 overexpressing full-lenght p53β or p53β-stop-lost. 4 samples same disease briefing
- GSE12032 Inherent gene signature of stage II and III colorectal cancer leads in individual recurrence 198 samples same disease briefing
- GSE109308 Single-cell transcriptomic survey of adenomatous polyposis patients with germline APC mutations 97 samples same disease briefing
- GSE110009 Single cell transcriptome landscape of primary and metastatic tumor in colon cancer 76 samples same disease briefing
- GSE236156 Mycobacterium tuberculosis induced interferon pathways distinguish responses of Human Alveolar Macrophages from Monocyte-Derived Macrophages 55 samples shares monocyte-derived, macrophages
- GSE232628 Expansion of profibrotic monocyte-derived alveolar macrophages in patients with persistent respiratory symptoms and radiographic abnormalities after COVID-19 46 samples shares monocyte-derived, macrophages
- GSE335752 Characterization of human M2-like (TGFbeta/IL10) vs M0 monocyte-derived macrophages 36 samples shares monocyte-derived, macrophages
- GSE240075 Gene expression in human monocyte-derived macrophages: effect of loss of MYC or USF1 30 samples shares monocyte-derived, macrophages
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.