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Snord67 promotes breast cancer metastasis by guiding U6 modification and modulating the splicing landscape

GSE274590 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/03/15 Platform GPL34284Platform GPL21103
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples
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
Snord67 promotes breast cancer metastasis by guiding U6 modification and modulating the splicing landscapeNature communications · 2025
Summary (written by the submitters)
Previously considered “housekeeping” genes, small nucleolar RNAs (snoRNAs) are increasingly understood to have wide-ranging functions in cancer, yet their role in metastasis remains unknown. Here, we identify the snoRNA Snord67 as a regulator of lymph node (LN) metastasis in female breast cancer. Snord67 expression is enriched in LN metastases in an immune-competent mouse model of breast cancer.
Read the full summary ↓
In an orthotopic breast cancer model, loss of Snord67 decreases LN metastasis. In a model of lymphatic metastasis, Snord67 loss decreases LN tumor growth and distant metastases. In breast cancer cell lines, Snord67 knockout results in loss of targeted 2′-O-methylation on U6 small nuclear RNA, as well as widespread changes in splicing. Together, these results demonstrate that Snord67 regulates splicing and promotes the growth of LN metastases and subsequent spread to distant metastases. SnoRNA-guided modifications of the spliceosome and regulation of splicing may represent a previously unappreciated, potentially targetable pathway in cancer.
Published in
Snord67 promotes breast cancer metastasis by guiding U6 modification and modulating the splicing landscape
Chao YL, Zhou KI, Forbes KK et al. · Nature communications 2025 · PMID 40316533 · doi:10.1038/s41467-025-59406-w
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 GSE274590_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 PRJNA1147254 and SRA study SRP525993. Searching any of these in the dataset finder brings you back here.

Samples in this study

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