GEO series

Systemic and breast chronic inflammation and hormone disposition promote a tumor-permissive environment for breast cancer in older women (Human Bulk RNA-Seq)

GSE276755 Homo sapiens (human) Single-nucleus RNA-seq 168 samples Submitted 2026/06/05 Platform GPL24676

At a glance

Single-nucleus RNA-seq · human · 168 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 168 samples
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)

Estrogen receptor positive (ER+) breast cancer, the most common subtype of breast cancer, is an age-related disease, with the peak incidence of diagnosis occurring around age 70 despite low circulating levels of estradiol. Despite the hormone sensitivity of these age-related tumors, our understanding of the interplay between the systemic and local hormonal disposition and chronic inflammaging is limited.

Read the full summary ↓

We show that aged F344 rats treated with the DMBA/MPA carcinogen develop more tumors at faster rates than their younger counterparts, suggesting that the aged environment accelerates tumor growth. snRNA-seq of the tumors showed broad local immune dysfunction that was associated with circulating chronic inflammation. Across a broad cohort of specimens from patients with ER+ breast cancer and age-matched donors of normal breast tissue, we observe that even with E1-predominant estrogen disposition in the systemic circulation, tumors in older patients upregulate HSD17B7 expression to convert E1 to E2 in the TME. Age-related accumulation of tumor-associated macrophages serve as signaling hubs that integrate the E2 and chemokine-driven chronic inflammatory signaling in the TME, which polarize TAMs towards a CD206+/PD-L1+, immunosuppressive phenotype. Overall, these findings suggest that the host’s chronic inflammation and hormonal disposition shape the local tumor microenvironment and are critical contributors to the age-related nature of ER+ breast cancer development and growth.

This dataset

Open GSE276755 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 GSE276755_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1158811 and SRA study SRP531646. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

A cohort of 168 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run AL_001 … AL_168 and carry no group information.

Samples in this study

GSM8505220 AL_001
GSM8505221 AL_002
GSM8505222 AL_003
GSM8505223 AL_004
GSM8505224 AL_005
GSM8505225 AL_006
GSM8505226 AL_007
GSM8505227 AL_008
GSM8505228 AL_009
GSM8505229 AL_010
GSM8505230 AL_011
GSM8505231 AL_012
GSM8505232 AL_013
GSM8505233 AL_014
GSM8505234 AL_015
GSM8505235 AL_016
GSM8505236 AL_017
GSM8505237 AL_018
GSM8505238 AL_019
GSM8505239 AL_020
GSM8505240 AL_021
GSM8505241 AL_022
GSM8505242 AL_023
GSM8505243 AL_024
GSM8505244 AL_025
GSM8505245 AL_026
GSM8505246 AL_027
GSM8505247 AL_028
GSM8505248 AL_029
GSM8505249 AL_030
GSM8505250 AL_031
GSM8505251 AL_032
GSM8505252 AL_033
GSM8505253 AL_034
GSM8505254 AL_035
GSM8505255 AL_036
GSM8505256 AL_037
GSM8505257 AL_038
GSM8505258 AL_039
GSM8505259 AL_040

+ 128 more — browse all 168 samples with per-sample file links →

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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.