A Single-Cell Atlas of HR+ Breast Cancer Reveals the Shifting of the Tumor Microenvironment in Response to Neoadjuvant Chemotherapy
Single-cell RNA-seq · human · 13 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 13 samples: 4 × HR+ breast cancer, luminal A, Pre-treatment, Resistant, S vs 3 × HR+ breast cancer, luminal B, Pre-treatment, Sensitive, S vs 2 × HR+ breast cancer, luminal B, Post-treatment, Sensitive, S vs 2 × HR+ breast cancer, luminal A, Post-treatment, Resistant, SGroups 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.
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE205472_RAW.tar (it can run to tens of gigabytes).
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: 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 PRJNA845793 and SRA study SRP378451. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 11 samples.
How we read this: 4 replicated groups read from 13 sample titles; they account for 11 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.
- GSM6213322 HR+ breast cancer, luminal B, Pre-treatment, Sensitive, S1 HR+ breast cancer, lumi…
- GSM6213323 HR+ breast cancer, luminal B, Pre-treatment, Sensitive, S2 HR+ breast cancer, lumi…
- GSM6213324 HR+ breast cancer, luminal B, Pre-treatment, Sensitive, S3 HR+ breast cancer, lumi…
- GSM6213325 HR+ breast cancer, luminal B, Pre-treatment, Resistant, S4
- GSM6213326 HR+ breast cancer, luminal A, Pre-treatment, Resistant, S5 HR+ breast cancer, lumi…
- GSM6213327 HR+ breast cancer, luminal A, Pre-treatment, Resistant, S6 HR+ breast cancer, lumi…
- GSM6213328 HR+ breast cancer, luminal A, Pre-treatment, Resistant, S7 HR+ breast cancer, lumi…
- GSM6213329 HR+ breast cancer, luminal A, Pre-treatment, Resistant, S8 HR+ breast cancer, lumi…
- GSM6213330 HR+ breast cancer, luminal B, Post-treatment, Sensitive, S9 HR+ breast cancer, lumi…
- GSM6213331 HR+ breast cancer, luminal B, Post-treatment, Sensitive, S10 HR+ breast cancer, lumi…
- GSM6213332 HR+ breast cancer, luminal B, Post-treatment, Resistant, S11
- GSM6213333 HR+ breast cancer, luminal A, Post-treatment, Resistant, S12 HR+ breast cancer, lumi…
- GSM6213334 HR+ breast cancer, luminal A, Post-treatment, Resistant, S14 HR+ breast cancer, lumi…
- GSE25066 Genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer 508 samples shares chemotherapy, neoadjuvant, breast
- GSE328275 Single-cell RNA sequencing of CD45+ immune cells across primary tumor, sentinel tumor-draining lymph node, and axillary lymph node in treatment-naive triple-negative breast cancer 28 samples shares single-cell, breast
- GSE198315 Multiregional single-cell profiling reveals extensive field cancerization and an immunosuppressive microenvironment in oral squamous cell carcinoma 36 samples shares microenvironment, single-cell
- GSE176078 A single-cell and spatially resolved atlas of human breast cancers 26 samples shares single-cell, breast
- GSE303346 Single-Cell RNA-Seq Reveals Immunosuppressive Effects of Triple-Negative Breast Cancer–Derived Exosomes on NK Cell Responses 16 samples shares single-cell, breast
- GSE263733 Single-cell transcriptome analysis reveals subtype-specific clonal evolution and microenvironmental changes in liver metastasis of pancreatic adenocarcinoma and their clinical implications 218 samples shares microenvironment, single-cell
- GSE326201 Single-cell RNA sequencing of human hepatocellular carcinoma and adjacent non-tumour liver tissues reveals etiology-associated and etiology-independent tumour microenvironmental features 18 samples shares microenvironment, single-cell
- GSE300595 Multiomic sequencing identifies myeloid cell associations with neoadjuvant chemotherapy treatment response in pancreatic adenocarcinoma (PDAC) 24 samples shares chemotherapy, neoadjuvant
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.