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METTL3/YTHDF2 axis inhibits cell proliferation and fibrosis by degrading the N6-methyladenosine modification of TCF7L2-Smad2/Smad3 mRNA in pterygium

GSE298598 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/05/29 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 12 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)
Background: Proliferation and fibrosis of stromal fibroblasts are key mechanisms in pterygium development and recurrence. N6-methyladenosine (m6A) is the most abundant mRNA modification, of which methyltransferase-like 3 (METTL3) is the only catalytic subunit. This study aimed to investigate the regulatory role of METTL3-mediated m6A modification on cell proliferation and fibrosis in pterygium.
Read the full summary ↓
Methods: Primary human conjunctival fibroblasts (HCFs) and human pterygium fibroblasts (HPFs) were isolated and cultured from fresh conjunctival grafts and pterygium tissues. Adenovirus (ADV) system was used to construct overexpression and silencing of METTL3 in HCFs, combined with TGF-β1 induction, for cell phenotypic analysis. The regulatory role of the METTL3/YTHDF2 axis on target genes (TCF7L2, Smad2, Smad3 and Smad7) was determined using methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA Immunoprecipitation qPCR (RIP-qPCR). The regulatory role of the transcription factors (TCF7L2, Smad2 and Smad3) on the fibrosis genes fibronectin-1 (FN-1) and collagen, type I, alpha 1 (COL1A1) was determined by dual luciferase reporter gene assay. Protein-protein docking (PPD) experiments and co-immunoprecipitation (co-IP) assays were conducted to investigate whether TCF7L2 forms a complex with Smad2/Smad3. Results: HCFs induced by TGF-β1 decreased METTL3 expression, and the reduced METTL3 enhanced HCFs’ proliferation and promoted the expression of fibrotic proteins FN-1 and COL1A1. MeRIP-seq and RIP-qPCR results showed that METTL3-mediated the m6A modification of TCF7L2, Smad2, Smad3 and Smad7 mRNA, was further recognized and degraded by YTHDF2. Dual luciferase reporter gene experiments revealed that TCF7L2, Smad2 and Smad3 is involved in the transcription of genes FN-1 and COL1A1. PPD and co-IP results demonstrate that TCF7L2 is capable of forming a complex with Smad2/Smad3 to regulate the transcription of FN-1 and COL1A1. Conclusion: The METTL3/YTHDF2 axis in pterygium regulates the degradation of the transcriptional complex TCF7L2-Smad2/Smad3 mRNA, promoting the transcription of FN-1 and COL1A1 and the progression of fibrosis. Our study findings untangle the biological characteristics of the METTL3/YTHDF2-regulated transcriptional complex in the pathophysiology of pterygium. Keywords: Pterygium, Fibrosis, m6A, METTL3, YTHDF2, Transcription factors
This dataset
Open GSE298598 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 GSE298598_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 PRJNA1269998 and SRA study SRP588872. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 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 12 sample titles: 12 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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