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Transcriptomic analyses of PDX tumors (QQX-17) to gain insight into the mechanisms underlying FOLFOXIRI-induced DTP state.

GSE300623 Homo sapiens (human) RNA-seq (gene expression) 17 samples Submitted 2026/06/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 17 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
Colorectal cancerThis series is part of our curated briefing on it.
Samples
17 samples: 6 × cells, Con vs 6 × cells, FOLFOXIRI treatment vs 5 × cells, Relapse after treatmentGroups 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)
Chemotherapy resistance remains a significant challenge, often leading to tumor relapse and poor prognosis. While past efforts to overcome treatment resistance have focused primarily on genetic alterations—such as somatic mutations, chromosomal aberrations, and dysregulated signaling pathways—these insights have yet to translate into effective clinical interventions.
Read the full summary ↓
The recent discovery of drug-tolerant persister (DTP) cells, which survive therapy through reversible, non-genetic adaptations akin to embryonic diapause, has unveiled a novel mechanism of chemotherapy resistance. To investigate this further, we employed treatment-naïve colorectal cancer (CRC) patient-derived xenograft (PDX) models. Upon reaching a tumor volume of 100 mm³, the PDX models were treated with a single maximum-tolerated dose of the FOLFOXIRI regimen. Post-treatment responses varied, including initial tumor shrinkage followed by regrowth, mirroring the "sensitivity-DTP-regrowth" pattern observed in CRC patients. Transcriptomic analyses of these PDX tumors were then conducted to elucidate the mechanisms underlying the FOLFOXIRI-induced DTP state.
This dataset
Open GSE300623 in finder → Find more human RNA-seq datasets → Colorectal 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 GSE300623_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: 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 PRJNA1281563 and SRA study SRP594233. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 × cells, Con vs 6 × cells, FOLFOXIRI treatment vs 5 × cells, Relapse after treatment

Supports a between-group comparison across 17 samples.

How we read this: 3 replicated groups read from 17 sample titles; they account for 17 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 Colorectal 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.