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Construction of a ceRNA network and screening of potential biomarkers and molecular targets in male smokers with chronic obstructive pulmonary disease

GSE268499 Homo sapiens (human) Non-coding RNA profiling 10 samples Submitted 2024/06/09 Platform GPL20301
At a glance

Non-coding RNA profiling · human · 10 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Homo sapiens (human)
Samples
10 samples: 5 × Con vs 5 × COPDGroups 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
Construction of a ceRNA network and screening of potential biomarkers and molecular targets in male smokers with chronic obstructive pulmonary diseaseFrontiers in genetics · 2024
Summary (written by the submitters)
Background. Circular RNAs (circRNAs) play an important role in the occurrence and development of diseases. However, the role of circRNAs in male smokers with chronic obstructive pulmonary disease (COPD) remains unclear. Methods. Stable COPD patients and healthy controls were recruited. Peripheral blood mononuclear cells (PBMCs) were extracted.
Read the full summary ↓
After high-throughput RNA sequencing (RNA-Seq) of PBMCs, a bioinformatics method was used to analyse differentially expressed (DE) circRNAs (DEcircRNAs) and mRNAs (DEmRNAs). Results. Total of 114 DEcircRNAs and 58 DEmRNAs were identified. Functional enrichment analysis showed that processes related to COPD include the regulation of interleukin (IL)-18, IL-5 and the NLRP3 inflammasome; differentiation of T helper type 1 (Th1), Th2, and Th17 cells, and the AMPK, Wnt, JAK-STAT, and PI3K-Akt signalling pathways. In the protein–protein interaction (PPI) network, the core genes were MYO16, MYL4, SCN4A, NRCAM, HMCN1, MYOM2, and IQSEC3. Small-molecule prediction results revealed potential drugs for the COPD treatment. Additionally, the circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory network was constructed. Conclusion. This study identified a set of dysregulated circRNAs and mRNAs and revealed potentially important genes, pathways, new small-molecule drugs and ceRNA regulatory networks in male smokers with COPD. These circRNAs might be prospective biomarkers or potential molecular targets of the ceRNA mechanism for COPD.
Published in
Construction of a ceRNA network and screening of potential biomarkers and molecular targets in male smokers with chronic obstructive pulmonary disease
Zhang J, Xu S, Liu J et al. · Frontiers in genetics 2024 · PMID 38933922 · doi:10.3389/fgene.2024.1376721
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 GSE268499_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.

Also filed as BioProject PRJNA1117468 and SRA study SRP510315. Searching any of these in the dataset finder brings you back here.

Study design
5 × Con vs 5 × COPD

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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.

Samples in this study
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