Multiplexed mosaic tumor models reveal natural phenotypic variations in drug response within and between populations
RNA-seq (gene expression) · human · 52 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
- 52 samples: 49 distinct titles, 1 of them repeatedGroups 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
- The GENEVA platform models tumor mosaicism to reveal variations of responses to KRAS inhibitors and identify improved drug combinationsNature cancer · 2026
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 GSE283335_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 PRJNA1193214 and SRA study SRP546252. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 52 sample titles: 49 distinct titles with little repetition. 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.
- GSM8641728 pooled cell lines, GEX
- GSM8641729 pooled cell lines, Multi-Seq
- GSM8656669 8 pooled cell lines, GEX
- GSM8656670 8 pooled cell lines, Multi-Seq
- GSM9332549 in vitro H23 soto
- GSM9332550 in vitro H23 veh
- GSM9332551 in vitro H441 soto
- GSM9332552 in vitro H441 veh
- GSM9332553 in vitro H2030 soto
- GSM9332554 in vitro H2030 veh
- GSM9332555 in vitro H2122 soto
- GSM9332556 in vitro H2122 veh
- GSM9332557 in vivo H23 soto 1L
- GSM9332558 in vivo H23 soto 1R
- GSM9332559 in vivo H23 soto 3L
- GSM9332560 in vivo H23 soto 3R
- GSM9332561 in vivo H23 veh 1L
- GSM9332562 in vivo H23 veh 1R
- GSM9332563 in vivo H23 veh 2L
- GSM9332564 in vivo H23 veh 2R
- GSM9332565 in vivo H441 soto 1L
- GSM9332566 in vivo H441 soto 2L
- GSM9332567 in vivo H441 soto 2R
- GSM9332568 in vivo H441 veh 1L
- GSM9332569 in vivo H441 veh 3L
- GSM9332570 in vivo H441 veh 3R
- GSM9332571 in vivo H2030 soto 1L
- GSM9332572 in vivo H2030 soto 1R
- GSM9332573 in vivo H2030 soto 3L
- GSM9332574 in vivo H2030 soto 3R
- GSM9332575 in vivo H2030 veh 2L
- GSM9332576 in vivo H2030 veh 2R
- GSM9332577 in vivo H2030 veh 3L
- GSM9332578 in vivo H2030 veh 3R
- GSM9332579 in vivo H2122 soto 1L
- GSM9332580 in vivo H2122 soto 1R
- GSM9332581 in vivo H2122 soto 2L
- GSM9332582 in vivo H2122 soto 2R
- GSM9332583 in vivo H2122 soto 3L
- GSM9332584 in vivo H2122 soto 3R
+ 12 more — browse all 52 samples with per-sample file links →
- GSE330178 Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface 35 samples shares populations, phenotypic, within
- GSE319493 Phenotypically similar but functionally distinct NK cell populations within the human maternal-fetal interface [scRNA-seq] 15 samples shares populations, phenotypic, within
- GSE261171 High-Resolution Single-Cell RNA Sequencing Uncovers Disparate Neutrophil Populations within Metastatic Cancer Lesions Linked to Progression Free Survival in Multiple Myeloma Patients 28 samples shares populations, within
- GSE235863 T cell populations correlate with response and resistance to anti-PD-1 plus lenvatinib combination therapy in hepatocellular carcinoma 69 samples shares populations
- GSE269600 Multiplexed single-cell characterization of alternative polyadenylation regulators 52 samples shares multiplexed
- GSE280318 Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling 39 samples shares populations
- GSE268210 Single-cell analysis of human PBMCs in healthy and type 2 diabetes populations: Dysregulated immune networks in type 2 diabetes unveiled through single-cell profiling 30 samples shares populations
- GSE279304 Genetic landscape and functional exploration of kidney cancer predisposition causality in cross-ancestral populations [screen] 24 samples shares populations
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.