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NELFA-mediated promoter-proximal pausing restrains YAP-driven transcription and shapes context-dependent outcomes in breast cancer

GSE311396 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/05/15 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
12 samples: 3 × Scrambled_siRNA_transfection vs 3 × siNELFA_transfection vs 3 × siYAP_transfection vs 3 × siNELFA+siYAP_cotransfectionGroups 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
NELFA-mediated pausing restrains YAP transcription and context-dependent outcomes in breast cancerFrontiers in oncology · 2026
Summary (written by the submitters)
Overexpression of YAP is associated with oncogenesis and tumor progression in multiple malignancies. YAP is the key transcriptional effector of a highly conserved Hippo signaling pathway, from Drosophila (Yki) to humans (YAP). In our previous Drosophila screen, we identified NELFA, a core component of the promoter-proximal pausing (PPP) complex, as a suppressor of Yki-driven hyperproliferation.
Read the full summary ↓
Building on this observation, we investigated whether this PPP–YAP regulatory interaction is conserved in mammalian cells, using breast cancer as a model system. Using HEK293T and MDA-MB-231 cells, we demonstrate that NELFA depletion selectively amplifies YAP-driven transcription, thereby enhancing the expression of canonical YAP target genes. Whole-transcriptome analysis of NELFA-depleted MDA-MB-231 cells revealed widespread reprogramming upon NELFA loss, with strong enrichment of conserved YAP signatures, EMT and TGF-β pathways, and AP-1/TEAD-SMAD3 transcriptional networks—indicating that NELFA regulates a broad YAP-centered oncogenic module. Clinical analysis of an Indian breast cancer cohort and TCGA revealed a striking context-dependent role for NELFA. Low NELFA expression predicted poor disease-free survival in YAP-high tumors—particularly in triple-negative breast cancer (TNBC)—suggesting a tumor-suppressive role. While High NELFA expression correlated with poorer overall survival. Collectively, these findings reveal that NELFA’s role in YAP-driven transcription is context-dependent in the breast cancer setting.
Published in
NELFA-mediated pausing restrains YAP transcription and context-dependent outcomes in breast cancer
Vasave BS, Atreya AA, Kulkarni RD et al. · Frontiers in oncology 2026 · PMID 42100387 · doi:10.3389/fonc.2026.1808415
This dataset
Open GSE311396 in finder → Find more human 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 GSE311396_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 PRJNA1366098 and SRA study SRP646763. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42100387) ↗
Study design
3 × Scrambled_siRNA_transfection vs 3 × siNELFA_transfection vs 3 × siYAP_transfection vs 3 × siNELFA+siYAP_cotransfection

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
More Breast cancer datasets

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