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Innate and Acquired Transcriptional Programs Shape Heterogeneous Tumor Cell Responses to PARP, Akt, and CDK4/6 Inhibitors

GSE328823 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2026/05/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
16 samples: 8 × Multiplexed sublibrary of all samples, whole-transcriptome poly-A capture; sublibrary vs 8 × Multiplexed sublibrary of all samples, hU6-targeted gRNA ClonMapper barcode capture; sublibraryGroups 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.
Summary (written by the submitters)
Targeted therapies are increasingly utilized across cancer types, yet their efficacy in triple-negative breast cancer (TNBC) remains limited due to the disease’s high heterogeneity and aggressive nature. In a heterogeneous tumor, treatment failure can occur due to the presence of therapy-tolerant cells, which may either be innately drug-tolerant or readily adaptive to therapy cytotoxicity.
Read the full summary ↓
To investigate how transcriptomic heterogeneity influences response and adaptation to targeted therapy in TNBC, this study leverages the ClonMapper cell barcoding system combined with single-cell RNA sequencing (scRNA-seq) to track differential responses of DNA barcoded clonal subpopulations during treatment with PARP-, Akt-, and CDK4/6-targeting therapy. For the three different targeted therapies, distinct innate and acquired gene signatures, unique to each therapy type, are shown to be predictive of a cell’s level of persistence during treatment. This work demonstrates that non-genetic heterogeneity plays a central role in response and resistance to targeted therapy, highlighting the need to consider tumor heterogeneity to guide effective use of targeted chemotherapy in TNBC.
This dataset
Open GSE328823 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 GSE328823_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 PRJNA1456597 and SRA study SRP694020. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 × Multiplexed sublibrary of all samples, whole-transcriptome poly-A capture; sublibrary vs 8 × Multiplexed sublibrary of all samples, hU6-targeted gRNA ClonMapper barcode capture; sublibrary

Supports a between-group comparison across 16 samples.

How we read this: 2 replicated groups read from 16 sample titles; they account for 16 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

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.