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PANAD/C7orf25 interacts with NXF1 to promote CDK6 mRNA nuclear export and G1/S transition

GSE300612 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/06/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 8 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)
Nuclear export factor 1 (NXF1) exerts mRNA transporter activity via binding to adaptors. We aimed to identify new NXF1 adaptors, and found that the R122/E125/G133/D139 amino acid residues of C7orf25 interacted with the Q20/K22/K23 residues in the RBD domain of NXF1, which disrupted the intramolecular interaction between the RBD and NTF2L domains of NXF1, consequently enhancing the binding of NXF1 to target mRNAs and promoting mRNA nuclear export.
Read the full summary ↓
Furthermore, C7orf25 accelerated the G1/S transition and promoted tumor cell growth via interacting with NXF1 to promote nuclear export of CDK6 mRNA. The levels of C7orf25, NXF1, and CDK6 proteins were elevated in human hepatocellular carcinomas, and high C7orf25 levels were associated with worse survival. These findings identify C7orf25, which we named PANAD (Proliferation-Associated NXF1 Adaptor), as a novel NXF1-interacting adaptor and disclose the crucial roles of PANAD/C7orf25 in mRNA nuclear export and tumor growth, which provides potential target for cancer therapy.
This dataset
Open GSE300612 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 GSE300612_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 PRJNA1281543 and SRA study SRP594216. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42449115) ↗
Study design
8 conditions, mostly in duplicate
HepG2 cells, cytoplasm,NC, ×2 HepG2 cells, cytoplasm,siPANAD-1/2, ×2 HepG2 cells, nucleus,NC, ×2 HepG2 cells, nucleus,siPANAD-1/2, ×2 SNU-449 cells, cytoplasm,NC, ×2 SNU-449 cells, cytoplasm,siPANAD-1/2, ×2 SNU-449 cells, nucleus,NC, ×2 SNU-449 cells, nucleus,siPANAD-1/2, ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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