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Molecular Portraits of Social Adversity in Breast Cancer [RNA-Seq]

GSE290733 Homo sapiens (human) RNA-seq (gene expression) 66 samples Submitted 2025/08/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 66 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
66 samples: 33 × BCG vs 32 × BSSGroups 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
Molecular Portraits of Social Adversity in Breast Cancer: Neighborhood Disadvantage Is Associated with Epigenetic Deregulation of Key Oncogenic PathwaysCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
Summary (written by the submitters)
Neighborhood disadvantage (ND) is associated with shorter breast cancer (BCa) survival. Although studies have identified that ND is associated with alterations in DNA methylation (DNAme) or gene expression, a comprehensive study integrating DNAme with coding (mRNA) and non-coding (miRNA, tRNA) transcriptomic data to understand how the epigenome regulates key biological pathways is lacking.
Read the full summary ↓
DNAme, mRNA, miRNA, and tRNA-derived fragment data were analyzed from 80 ER+/HER2- BCa samples from Hispanic White women with no significant differences in genetic ancestry, BMI, smoking, alcohol, Oncotype DX scores, and stage. We analyzed the association between objective ND [Area Deprivation Index (ADI)], subjective ND [Neighborhood Social Environment Adversity Survey (NSEAS)], DNAme, coding, and non-coding data to understand how the epigenome regulates key biological pathways among women living in ND. The cohort was divided into neighborhood advantage (NA, ADI<5; n=55, 69%) and ND (ADI≥5; n=25, 31%). In tumors from ND, calcium signaling and cell adhesion pathways were hypermethylated, immune-related pathways hypomethylated, immune response genes upregulated, and estrogen response genes downregulated. Small RNA analysis showed differential expression of miRNA isoforms and tRNA-derived fragments related to ND. Subjective ND correlated with epigenetic changes in calcium signaling, cell adhesion, and metabolic pathways, along with upregulation of proliferative and stemness pathways. We discovered novel associations between ND and epigenomic regulation of key clinically relevant oncogenesis pathways associated with aggressive biology, such as estrogen response pathways. These findings lay the foundation for multi-institutional studies to validate our findings and guide future treatment and cancer control interventions.
Published in
Molecular Portraits of Social Adversity in Breast Cancer: Neighborhood Disadvantage Is Associated with Epigenetic Deregulation of Key Oncogenic Pathways
Telonis AG, Hernandez AE, Borowsky PA et al. · Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2025 · PMID 40810618 · doi:10.1158/1055-9965.EPI-25-0123
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 GSE290733_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 PRJNA1229680 and SRA study SRP566941. Searching any of these in the dataset finder brings you back here.

Study design
33 × BCG vs 32 × BSS

Supports a between-group comparison across 65 samples.

How we read this: 2 replicated groups read from 66 sample titles; they account for 65 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

+ 26 more — browse all 66 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.