The pro-inflammatory cytokines IFN-α and TNF-α inhibit extravillous trophoblast invasion
RNA-seq (gene expression) · human · 9 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)
- Samples
- 9 samples: 3 × untreated vs 3 × IFNA vs 3 × TNFAGroups 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
- The pro-inflammatory cytokines IFN-α and TNF-α inhibit organoid-derived extravillous trophoblast invasioniScience · 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 GSE302798_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 PRJNA1292184 and SRA study SRP601262. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9111406 untreated_1 untreated
- GSM9111407 IFNA_1 IFNA
- GSM9111408 TNFA_1 TNFA
- GSM9111409 untreated_2 untreated
- GSM9111410 IFNA_2 IFNA
- GSM9111411 TNFA_2 TNFA
- GSM9111412 untreated_3 untreated
- GSM9111413 IFNA_3 IFNA
- GSM9111414 TNFA_3 TNFA
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- GSE268743 Effect of TNFα and RELA inhibition on gene expression in human PDAC cells 28 samples shares tnf, inhibit
- GSE254537 Inhibition of CXCL10 and IFN-γ ameliorates myocarditis in preclinical models of SARS-CoV- 2 mRNA vaccination 24 samples shares ifn, inhibit
- GSE296117 A single-cell RNA-seq dataset of synovial fluid from rheumatoid arthritis treated with TNF-α/JAK inhibitor 18 samples shares tnf, inhibit
- GSE281408 TNF-α inhibits the chemotherapy resistance caused by upregulation of the PERK-ATF4 pathway in colorectal cancer cells 16 samples shares tnf, inhibit
- GSE275227 Transcriptomic changes in Human Umbilical Vein Endothelial Cells (HUVEC) after exposure to Tumor Necrosis Factor-Alpha(TNF-a), AdipoRon, and Sphingosine Kinase Inhibitor (SKI-I) 12 samples shares tnf, inhibit
- GSE273020 Long non-coding RNA GRASLND affects melanoma phenotypic switch and modulates immunogenicity by inhibition of the IFNγ signaling pathway (IFNg treatment and GRASLND KD). 12 samples shares ifn, inhibit
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.