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TGF-β-induced MIR99AHG synergizes with PTBP1 to trigger an alternative splicing switch of SMARCA1 that promotes invadopodia formation for metastasis in colorectal cancer

GSE240485 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/08/08 Platform GPL18573
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)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
12 samples: 5 conditions, mostly in duplicateGroups 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)
Alternative splicing (AS) of pre-mRNAs is an essential process that regulates gene expression and functional diversity, yet the underlying regulatory mechanisms that control this process during cancer metastasis are not clear. Here, we uncovered that a long non-coding RNA (lncRNA), MIR99AHG, mediates regulation of AS to alter chromatin remodeler function and promote invadopodia formation in colorectal cancer (CRC).
Read the full summary ↓
We found that MIR99AHG is highly expressed in metastatic CRC cells and patient tissue samples. In vitro and in vivo assays showed that MIR99AHG potently drove CRC cell motility, invasion, and metastasis. MIR99AHG bound to and stabilized the RNA splicing factor PTBP1, which cooperatively increased cassette exon inclusion of the chromatin remodeling gene SMARCA1. Mechanistically, MIR99AHG acted as an address label for PTBP1 to fine-tune its binding pattern on SMARCA1 pre-mRNA, thereby controlling the skipping-to-inclusion splicing switch of SMARCA1 and favouring the production of a long isoform (SMARCA1-L). Canonical SMARCA1 was found to suppress cell migration and invasiveness by inhibiting invadopodia formation, but SMARCA1-L was functionally inert. Clinical data revealed that MIR99AHG was positively correlated with PTBP1 and SMARCA1-L in human CRC specimens and predicted patient outcome. Furthermore, we showed that the crosstalk with cancer-associated fibroblasts triggers TGF-β/SMAD signalling in CRC cells and activates MIR99AHG expression. Our findings establish a novel mechanism for a lncRNA that interacts with PTBP1 to regulate AS process, providing a potential therapeutic target and predictive biomarker of CRC.
This dataset
Open GSE240485 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →
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 GSE240485_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 PRJNA1003889 and SRA study SRP454298. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in duplicate
siNC# ×3 siSMARCA1# ×3 ASO-MIR99AHG# ×2 siPTBP1# ×2 ASO-NC# ×2

Supports a between-group comparison across 12 samples.

How we read this: 5 replicated groups read from 12 sample titles; they account for 12 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
More Colorectal cancer datasets

Search all human RNA-seq datasets in GEO →

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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.