Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer
RNA-seq (gene expression) · human · 168 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
- 168 samples: 168 × Patient sampleGroups 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
- Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancerOncogene · 2025
Read the full summary ↓
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 GSE285861_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: 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 PRJNA1206461. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 168 samples.
How we read this: 1 replicated groups read from 168 sample titles; they account for 168 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.
- GSM8711491 Patient sample 1 Patient sample
- GSM8711492 Patient sample 2 Patient sample
- GSM8711493 Patient sample 3 Patient sample
- GSM8711494 Patient sample 4 Patient sample
- GSM8711495 Patient sample 5 Patient sample
- GSM8711496 Patient sample 6 Patient sample
- GSM8711497 Patient sample 7 Patient sample
- GSM8711498 Patient sample 8 Patient sample
- GSM8711499 Patient sample 9 Patient sample
- GSM8711500 Patient sample 10 Patient sample
- GSM8711501 Patient sample 11 Patient sample
- GSM8711502 Patient sample 12 Patient sample
- GSM8711503 Patient sample 13 Patient sample
- GSM8711504 Patient sample 14 Patient sample
- GSM8711505 Patient sample 15 Patient sample
- GSM8711506 Patient sample 16 Patient sample
- GSM8711507 Patient sample 17 Patient sample
- GSM8711508 Patient sample 18 Patient sample
- GSM8711509 Patient sample 19 Patient sample
- GSM8711510 Patient sample 20 Patient sample
- GSM8711511 Patient sample 21 Patient sample
- GSM8711512 Patient sample 22 Patient sample
- GSM8711513 Patient sample 23 Patient sample
- GSM8711514 Patient sample 24 Patient sample
- GSM8711515 Patient sample 25 Patient sample
- GSM8711516 Patient sample 26 Patient sample
- GSM8711517 Patient sample 27 Patient sample
- GSM8711518 Patient sample 28 Patient sample
- GSM8711519 Patient sample 29 Patient sample
- GSM8711520 Patient sample 30 Patient sample
- GSM8711521 Patient sample 31 Patient sample
- GSM8711522 Patient sample 32 Patient sample
- GSM8711523 Patient sample 33 Patient sample
- GSM8711524 Patient sample 34 Patient sample
- GSM8711525 Patient sample 35 Patient sample
- GSM8711526 Patient sample 36 Patient sample
- GSM8711527 Patient sample 37 Patient sample
- GSM8711528 Patient sample 38 Patient sample
- GSM8711529 Patient sample 39 Patient sample
- GSM8711530 Patient sample 40 Patient sample
+ 128 more — browse all 168 samples with per-sample file links →
- GSE104193 Hypoxia-mediated translational activation of ITGB3 in breast cancer cells enhances TGF-β signalling and malignant features in vitro and in vivo 32 samples same disease briefing · shares features
- GSE11121 The humoral immune system has a key prognostic impact in node-negative breast cancer 200 samples same disease briefing · shares prognostic
- GSE104675 Role for the Transcriptional Activator ZRF1 in Breast Cancer Progression and Endocrine Resistance 6 samples same disease briefing
- GSE10885 An integromic analysis reveals that metaplastic carcinomas are distinct from basal-like tumors. 244 samples same disease briefing
- GSE10886 A Supervised Risk Predictor of Breast Cancer Based on Biological Subtypes 226 samples same disease briefing
- GSE309430 Blood-Based Gene Signatures Associated with Therapeutic Response to Anti-TNF Therapy in Rheumatoid Arthritis: A Combined Meta-Analytical and Machine Learning Approach 8 samples shares signatures, learning, machine
- GSE323965 Transcriptional signatures indicating RB function may predict response to CDK4/6 inhibition in endometrial cancer [RNA-Seq] 39 samples shares cdk4, signatures
- GSE285944 Divergent therapeutic and prognostic impacts of immunogenic features in undifferentiated pleomorphic sarcoma and myxofibrosarcoma 23 samples shares prognostic, features
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.