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X-Linked Cancer-Associated Polypeptide, Encoded by a Putative Noncoding RNA, Regulates Gene Expression and Cellular Pathways in Breast Cancer [RNA-seq]

GSE288868 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/05/07 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 14 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.
Paper
X-linked cancer-associated polypeptide (XCP) from lncRNA1456 modulates PHF8 histone demethylase activity to regulate the epigenome, gene expression, and cellular pathways in breast cancerOncogene · 2026
Summary (written by the submitters)
Long noncoding RNAs (lncRNAs) have been found to play a critical role in cancer biology and other prevalent diseases. While most lncRNAs are poorly conserved and not evolutionarily neutral, they regulate biological processes at the RNA level. Recent studies have suggested that a subset of lncRNAs produce functional proteins, and in this study, we have discovered a protein named XCP ((X-linked Cancer-associated Polypeptide).
Read the full summary ↓
XCP is encoded by a pancreas- and testis-specific RNA annotated as a putative long noncoding RNA by Sun and Gadad et al. (lncRNA1456, aka RHOXF1P3), located on chromosome X. We found that lncRNA1456 and XCP are upregulated in luminal A, luminal B, and HER2 molecular subtypes of breast cancer, and XCP modulates estrogen-dependent as well as estrogen-independent growth of MCF-7 cells by regulating cancer pathways in xenograft models. We find that XCP shares homology with homeodomain-containing proteins and interacts with PHF8, which is also an X-linked gene, and demethylates H3K9me2 to activate transcription. Mechanistically, XCP positively regulates histone demethylase activity of PHF8 in vitro to regulate gene expression in breast cancer cells. These findings identify XCP as a coregulator of transcription and emphasize the need to interrogate the potential functional roles of open reading frames originating from noncoding RNAs.
Published in
X-linked cancer-associated polypeptide (XCP) from lncRNA1456 modulates PHF8 histone demethylase activity to regulate the epigenome, gene expression, and cellular pathways in breast cancer
Gadad SS, Camacho CV, Gong X et al. · Oncogene 2026 · PMID 41922576 · doi:10.1038/s41388-026-03740-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 GSE288868_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 PRJNA1219653 and SRA study SRP561801. Searching any of these in the dataset finder brings you back here.

Study design
14 conditions, mostly in duplicate
MCF-7 GFP ×8 MDA-MB-231 GFP ×8 MDA-MB-231 XCP ×8 MCF-7 XCP ×4 MCF-7, GFP, Control KD ×2 MCF-7, GFP, lncRNA1456 KD set1 ×2 MCF-7, GFP, lncRNA1456 KD set2 ×2 MCF-7, GFP, PHF8 KD set1 ×2 +6 more

Supports a between-group comparison across 48 samples.

How we read this: 14 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

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.