Secretory IgA dysfunction underlies poor prognosis in Fusobacterium-infected colorectal cancer
Single-cell RNA-seq · human · 42 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
- Colorectal cancerThis series is part of our curated briefing on it.
- Samples
- 42 samples: 42 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
- Secretory IgA dysfunction underlies poor prognosis in Fusobacterium-infected colorectal cancerGut microbes · 2025
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 GSE273567_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 PRJNA1142424 and SRA study SRP523332. 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 42 sample titles: 42 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.
- GSM8432398 primary tumor, validation cohort, YCC-020, 3' scRNA-seq
- GSM8432399 primary tumor, validation cohort, YCC-036, 3' scRNA-seq
- GSM8432400 primary tumor, validation cohort, YCC-038, 3' scRNA-seq
- GSM8432401 primary tumor, validation cohort, YCC-040, 3' scRNA-seq
- GSM8432402 primary tumor, validation cohort, YCC-050, 3' scRNA-seq
- GSM8432403 primary tumor, validation cohort, YCC-061, 3' scRNA-seq
- GSM8432404 primary tumor, validation cohort, YCC-064, 3' scRNA-seq
- GSM8432405 primary tumor, validation cohort, YCC-065, 3' scRNA-seq
- GSM8432406 primary tumor, validation cohort, YCC-074, 3' scRNA-seq
- GSM8432407 primary tumor, validation cohort, YCC-078, 3' scRNA-seq
- GSM8432408 primary tumor, validation cohort, YCC-080, 3' scRNA-seq
- GSM8432409 primary tumor, validation cohort, YCC-081, 3' scRNA-seq
- GSM8432410 primary tumor, validation cohort, YCC-087, 3' scRNA-seq
- GSM8432411 primary tumor, validation cohort, YCC-097, 3' scRNA-seq
- GSM8432412 primary tumor, validation cohort, YCC-102, 3' scRNA-seq
- GSM8432413 primary tumor, validation cohort, YCC-103, 3' scRNA-seq
- GSM8432414 primary tumor, validation cohort, YCC-104, 3' scRNA-seq
- GSM8432415 primary tumor, validation cohort, YCC-105, 3' scRNA-seq
- GSM8432416 primary tumor, discovery cohort, YCC-150, 5' scRNA-seq
- GSM8432417 primary tumor, discovery cohort, YCC-151, 5' scRNA-seq
- GSM8432418 primary tumor, discovery cohort, YCC-155, 5' scRNA-seq
- GSM8432419 primary tumor, discovery cohort, YCC-162, 5' scRNA-seq
- GSM8432420 primary tumor, discovery cohort, YCC-166, 5' scRNA-seq
- GSM8432421 primary tumor, discovery cohort, YCC-172, 5' scRNA-seq
- GSM8432422 primary tumor, discovery cohort, YCC-175, 5' scRNA-seq
- GSM8432423 primary tumor, discovery cohort, YCC-180, 5' scRNA-seq
- GSM8432424 primary tumor, discovery cohort, YCC-186, 5' scRNA-seq
- GSM8432425 primary tumor, discovery cohort, YCC-187, 5' scRNA-seq
- GSM8432426 primary tumor, discovery cohort, YCC-189, 5' scRNA-seq
- GSM8432427 primary tumor, discovery cohort, YCC-190, 5' scRNA-seq
- GSM8432428 primary tumor, discovery cohort, YCC-191, 5' scRNA-seq
- GSM8432429 primary tumor, discovery cohort, YCC-192, 5' scRNA-seq
- GSM8432430 primary tumor, discovery cohort, YCC-194, 5' scRNA-seq
- GSM8432431 primary tumor, discovery cohort, YCC-195, 5' scRNA-seq
- GSM8432432 primary tumor, discovery cohort, YCC-197, 5' scRNA-seq
- GSM8432433 primary tumor, discovery cohort, YCC-211, 5' scRNA-seq
- GSM8432434 primary tumor, discovery cohort, YCC-212, 5' scRNA-seq
- GSM8432435 primary tumor, discovery cohort, YCC-223, 5' scRNA-seq
- GSM8432436 primary tumor, discovery cohort, YCC-225, 5' scRNA-seq
- GSM8432437 primary tumor, discovery cohort, YCC-227, 5' scRNA-seq
+ 2 more — browse all 42 samples with per-sample file links →
- 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 · shares colorectal
- GSE12032 Inherent gene signature of stage II and III colorectal cancer leads in individual recurrence 198 samples same disease briefing · shares colorectal
- GSE110009 Single cell transcriptome landscape of primary and metastatic tumor in colon cancer 76 samples same disease briefing
- GSE109308 Single-cell transcriptomic survey of adenomatous polyposis patients with germline APC mutations 97 samples same disease briefing
- GSE312983 A single-nucleus RNA-seq atlas of colorectal cancer across the age continuum reveals distinct features of early-onset colorectal cancer 189 samples shares colorectal
- GSE319878 Interrogating the mechanistic link between neighborhood deprivation and colorectal cancer risk through gene expression analysis of normal colorectal biopsies 171 samples shares colorectal
- GSE319722 Spatial dynamics links PD-L1 and Tumor-Associated Macrophage–Enriched Niches to Immune and Mesenchymal States in microsatellite stable colorectal cancer 117 samples shares colorectal
- GSE289582 Baseline tumor features and peripheral blood immune dynamics that underlie efficacy in MSS metastatic colorectal cancer treated with regorafenib, ipilimumab, and nivolumab [Blood] 115 samples shares colorectal
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.