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ECD co-operates with ERBB2 to promote tumorigenesis through upregulation of unfolded protein response and glycolysis

GSE287075 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2026/01/20 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 21 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
Breast cancerThis series is part of our curated briefing on it.
Samples
21 samples: 3 × VEC vs 3 × ECD vs 3 × ERBB2 vs 3 × ECD+ERBB2Groups 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
ECD co-operates with ERBB2 to promote tumorigenesis through upregulation of unfolded protein response and glycolysisCancer letters · 2025
Summary (written by the submitters)
The mammalian orthologue of the Drosophila ecdysoneless (ECD) mRNA and protein are overexpressed in breast cancer, and its overexpression correlates with poor prognosis and short patient survival, particularly in ERBB2/HER2-positive breast cancer (BC). This work investigates the co-operative oncogenic mechanism of ECD and ERBB2 by deriving transgenic mice overexpressing ECD and/or ERBB2 (huHER2) in mammary epithelium under MMTV promoter (ECD+HER2Tg), as well as human mammary immortal epithelial cell lines (hMECs) overexpressing ECD and/or ERBB2.
Read the full summary ↓
While huHER2Tg mice developed more homogenous solid nodular carcinomas, double transgenic mice (ECD; huHER2Tg) developed heterogenous and histologically aggressive mammary tumors with basal-like phenotype and epithelial mesenchymal transition (EMT) features, similar to ECDTg tumors. Importantly, transcriptomic profile of ECD; huHER2Tg tumors revealed upregulation of two major oncogenic pathways, unfolded protein response (UPR) and glycolysis. Consistently, ECD; huHER2Tg tumors exhibited increased mRNA levels of cancer stem cell markers and EMT related genes. Further, hMECs expressing both ECD and ERBB2 as compared to ECD or ERBB2 expressing cells showed significant increase in oncogenic traits, such as enhanced migration, anchorage independence, mammosphere, and organoid formation. RNA sequencing analysis of single and double transfectants showed significant upregulation of glycolysis and UPR pathways in ECD+ERBB2 expressing cells as compared to ECD or ERBB2 overexpressing hMECs. Given our recent finding that ECD directly binds to RNA, we demonstrate mRNAs of three key glycolytic enzymes (LDHA, PKM2 and HK2) and mRNA of a major UPR regulated gene GRP78 directly associated with ECD protein using RNA immunoprecipitation assay. Higher expression of glycolytic mRNAs and GRP78 in ECD+ERBB2-expressing cells was due to increased mRNA stability. Lastly, we show an increase in glucose uptake and enhanced glycolytic rate in ECD+ERBB2-overexpressing cells as compared to ECD- or ERBB2-overexpressing hMECs. Taken together, our findings support a co-operative role of ECD and ERBB2 in oncogenesis by enhancing two major oncogenic pathways, UPR and glycolysis. These results provide experimental proof and mechanistic insights to our previous findings that ECD is overexpressed in ERBB2-positive BC patients, and its’ overexpression correlates with poor prognosis and short survival in patients.
Published in
ECD co-operates with ERBB2 to promote tumorigenesis through upregulation of unfolded protein response and glycolysis
Kennedy BB, Raza M, Mirza S et al. · Cancer letters 2025 · PMID 40738412 · doi:10.1016/j.canlet.2025.217959
This dataset
Open GSE287075 in finder → Find more RNA-seq datasets → Breast 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 GSE287075_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 PRJNA1211098 and SRA study SRP557592. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40738412) ↗
Study design
3 × VEC vs 3 × ECD vs 3 × ERBB2 vs 3 × ECD+ERBB2

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 21 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 Breast cancer datasets

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