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Identification of PEG10 as a biomarker for DICER1-related tumor predisposition syndrome [RNA-Seq]

GSE299033 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/07/02 Platform GPL13112

At a glance

RNA-seq (gene expression) · mouse · 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: Mus musculus (mouse)
Samples: 12 samples: 3 × mouse MSCs RNAseq EV vs 3 × mouse MSCs RNAseq WT vs 3 × mouse MSCs RNAseq D1320A vs 3 × mouse MSCs RNAseq E1705KGroups 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: MicroRNAs (miRNAs) are short non-coding RNA molecules that downregulate messenger RNA (mRNA) expression. Mature miRNAs (designated -5p or -3p) are produced by the endonuclease DICER1. Mature miRNAs are loaded into the AGO2-containing RNA-Induced Silencing Complex where they target mRNAs via a seed sequence in the mRNA’s 3’ untranslated region (3’ UTR).

Read the full summary ↓

Children with pathogenic variants of DICER1 have a highly elevated risk of cancers in many different organs– recognized as DICER1-related tumour predisposition (DRTP). These tumours/lesions have one inactivated copy and one “hotspot” mutated copy of DICER1. All “hotspot” DICER1 mutations impair 5p miRNA production. DICER1 DNA sequencing has become the diagnostic standard but an immunohistochemical (IHC) diagnostic method may improve patient care via faster return of results. Methods: Using AGO2 miR-eCLIP and RNAseq data of a mouse cell model of DRTP (E1705K) I identified paternally expressed gene 10 (Peg10) as a diagnostic candidate. Validation of cell overexpression (mRNA and protein) and de-repression of Peg10 3’ UTR was assessed. Dependence on Peg10 for cell viability was measured (post 72-hour siRNA-mediated knockdown). IHC staining of two tumour microarrays (TMAs) was performed and scored (H-score) to evaluate its use in the clinic (Area Under Curve, AUC). Results: In E1705K, Peg10 displayed elevated RNA and protein levels as well as de-repression of its 3’ UTR. Peg10 knockdown does not impact cell viability. TMA1 (41 female samples) had an AUC of 0.80 (considered of good clinical utility) while TMA2 (95 male and female samples) had an AUC was 0.71 (fair clinical utility). Conclusion: E1705K identified Peg10 as a biomarker that is elevated in DRTP tumours from both sexes bearing a variety of DICER1 hotspot variants. Elevated Peg10 mRNA levels are in part due to lack of 5p-mediated interactions with its 3’ UTR.

This dataset

Open GSE299033 in finder → Find more mouse 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 GSE299033_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 PRJNA1272350 and SRA study SRP590054. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × mouse MSCs RNAseq EV vs 3 × mouse MSCs RNAseq WT vs 3 × mouse MSCs RNAseq D1320A vs 3 × mouse MSCs RNAseq E1705K

Supports a between-group comparison across 12 samples.

How we read this: 4 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

GSM9031145 mouse MSCs RNAseq EV replicate 1 mouse MSCs RNAseq EV
GSM9031146 mouse MSCs RNAseq EV replicate 2 mouse MSCs RNAseq EV
GSM9031147 mouse MSCs RNAseq EV replicate 3 mouse MSCs RNAseq EV
GSM9031148 mouse MSCs RNAseq WT replicate 1 mouse MSCs RNAseq WT
GSM9031149 mouse MSCs RNAseq WT replicate 2 mouse MSCs RNAseq WT
GSM9031150 mouse MSCs RNAseq WT replicate 3 mouse MSCs RNAseq WT
GSM9031151 mouse MSCs RNAseq D1320A replicate 1 mouse MSCs RNAseq D1320A
GSM9031152 mouse MSCs RNAseq D1320A replicate 2 mouse MSCs RNAseq D1320A
GSM9031153 mouse MSCs RNAseq D1320A replicate 3 mouse MSCs RNAseq D1320A
GSM9031154 mouse MSCs RNAseq E1705K replicate 1 mouse MSCs RNAseq E1705K
GSM9031155 mouse MSCs RNAseq E1705K replicate 2 mouse MSCs RNAseq E1705K
GSM9031156 mouse MSCs RNAseq E1705K replicate 3 mouse MSCs RNAseq E1705K

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