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miR-193b-5p and miR-374b-5p are aberrantly expressed in endometriosis and suppress endometrial cell migration in vitro

GSE279835 Homo sapiens (human) RNA-seq (gene expression) 44 samples Submitted 2024/11/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 44 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
44 samples: 44 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
miR-193b-5p and miR-374b-5p Are Aberrantly Expressed in Endometriosis and Suppress Endometrial Cell Migration In VitroBiomolecules · 2024
Summary (written by the submitters)
Endometriosis is a highly prevalent gynecological disease affecting 10% of women of reproductive age worldwide. miRNAs may play a role in endometriosis, though their exact function remains unclear. Here, we identified differentially expressed miRNAs in endometriosis and studied their functional role in the disease. (2) Methods: Endometrial tissue was collected from women with endometriosis (n=15) and non-endometriosis controls (n=17).
Read the full summary ↓
Dysregulated miRNAs were identified through small RNA-sequencing, and their biological significance was explored by target gene prediction and pathway analysis. Selected miRNAs were examined in paired ectopic endometriomas and eutopic endometrium (n=10) using qRT-PCR. Their roles in cell migration and proliferation were further examined in vitro using functional assays. To identify potential target genes, we performed mRNA sequencing on transfected cells and the endometrioma cohort. (3) Results: We identified 14 dysregulated miRNAs in the eutopic endometrium of women with endometriosis compared to endometrial tissue from women without endometriosis. Pathway analysis indicated enrichment in cell migration and proliferation associated pathways. Further ex-vivo studies of miR-193b-5p and miR-374b-5p showed that both miRNAs were up-regulated in endometriomas. Overexpression of these two miRNAs in vitro inhibited cell migration and mRNA sequencing revealed several migration-related genes that are targeted by these miRNAs. (4) Conclusions: Our study identified two key endometrial miRNAs that may be involved in the pathogenesis of endometriosis by regulating cell migration.
Published in
miR-193b-5p and miR-374b-5p Are Aberrantly Expressed in Endometriosis and Suppress Endometrial Cell Migration In Vitro
Frisendahl C, Tang Y, Boggavarapu NR et al. · Biomolecules 2024 · PMID 39595577 · doi:10.3390/biom14111400
This dataset
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.

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 GSE279835_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1174758 and SRA study SRP539391. Searching any of these in the dataset finder brings you back here.

Study design
44 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 44 sample titles: 44 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

+ 4 more — browse all 44 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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