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Analysis of endometrial mRNA in patients with different pregnancy outcomes after immunotherapy: A cohort study

GSE272778 Homo sapiens (human) RNA-seq (gene expression) 29 samples Submitted 2024/09/09 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 29 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
29 samples: 29 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.
Summary (written by the submitters)
Purpose: The efficacy of immunomodulators in improving pregnancy outcomes in infertile patients is controversial, with some reports finding improvements in pregnancy outcomes and some studies finding lack of efficacy in unselected patient populations. Therefore, the aim of this study was to identify people who could benefit from immunotherapy.
Read the full summary ↓
Methods: 29 patients who had at least one previous embryo transfer failure and planned to undergo another frozen-thawed embryo transfer (FET) cycle were included. Peripheral blood of the patients was collected for detection of serum cytokines, T cell subsets at D3-D9 days of menstrual cycle before FET, mRNA was extracted from endometrial tissues during the window of implantation (WOI) for analysis. All patients began treatment with immunomodulators, including prednisone, hydroxychloroquine, cyclosporine, on the first day of the FET cycle. They were divided into pregnant group and non-pregnant group according to clinical pregnancy. Results: There were no differences in cytokines and T cell subsets between the two groups. Functional annotation of endometrial mRNA revealed functional enrichment in leucocyte mediated immunity, innate immune response, regulation of T cell receptor (TCR) signaling, T cell activation and positive T cell selection. Conclusion: The cytokines and immune cell subsets of peripheral blood cannot accurately predict the outcome of pregnancy after immunotherapy, and endometrial biopsy on the WOI may be a target to identify people who benefit from immunotherapy.
This dataset
Open GSE272778 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE272778_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1138716 and SRA study SRP521379. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
29 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 29 sample titles: 29 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.

Samples in this study
Datasets on a similar topic

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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.