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Time‑resolved multi-omic analysis of paclitaxel exposure in human iPSC‑derived sensory neurons unveils mechanisms of chemotherapy‑induced peripheral neuropathy

GSE312881 Homo sapiens (human) RNA-seq (gene expression) 71 samples Submitted 2026/02/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 71 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
71 samples: 24 conditions, mostly in triplicateGroups 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
Time‑resolved multi-omic analysis of paclitaxel exposure in human iPSC‑derived sensory neurons unveils mechanisms of chemotherapy‑induced peripheral neuropathyCell death & disease · 2026
Summary (written by the submitters)
The microtubule-stabilizing drug paclitaxel remains standard of care for various solid malignancies but frequently leads to chemotherapy-induced peripheral neuropathy (CIPN). CIPN is a leading cause for premature treatment termination and a significantly reduced quality of life in long-term cancer survivors. The molecular mechanisms of neuro-axonal degeneration, neuroinflammation and pain in patients treated with paclitaxel remain incompletely understood, and there are currently no predictive biomarkers or preventive treatments.
Read the full summary ↓
We used human iPSC-derived sensory neurons exposed to paclitaxel to comprehensively model the pathophysiology of CIPN. Neurotoxicity was assessed over time using viability assays and sequential RNA sequencing as well as deep proteome and lipidomic analyses. We observed a time and dose-dependent decline of cell viability at clinically relevant paclitaxel doses. Sequential RNA sequencing defined JUN as an early immediate gene, followed by the overexpression of genes of the neuronal stress response (e.g., ARID5A, WEE1, DUSP16, GADD45A), neuronal injury and apoptotic pathways (e.g., ATF3, HRK, BBC3 [PUMA], BCL2L11 [BIM], CASP3), neuroinflammation and nociception (CALCB, MMP10, IL31RA, CYSLTR2, C3AR1, TNFRSF12A) and neuronal transduction (e.g., CAMK2A, STOML3, PIRT), while key enzymes of lipid biosynthesis were markedly downregulated (e.g., LSS, HMGCS1, HMGCR, DHCR24). Deep proteome analyses following 48 hours of exposure to 100nM paclitaxel revealed a strong correlation of differentially expressed RNA with proteins, and a marked degradation of essential axonal transport proteins such as kinesins, stathmins and scaffold proteins. Consistent with the downregulation of rate-limiting enzymes of lipid biosynthesis, lipidome analysis confirmed deregulation of neuronal lipid homeostasis. In summary, paclitaxel induces transcriptomic and proteomic signatures of the neuronal stress response, neuroinflammation, nociception and disturbed metabolism. These may explain, in part, the clinical phenotype of sensory loss, hypersensitivity and neuropathic pain frequently observed in patients suffering from CIPN, but constitute pharmacologically addressable targets.
Published in
Time‑resolved multi-omic analysis of paclitaxel exposure in human iPSC‑derived sensory neurons unveils mechanisms of chemotherapy‑induced peripheral neuropathy
Schinke C, Maierhof SK, Hew L et al. · Cell death & disease 2026 · PMID 41667428 · doi:10.1038/s41419-026-08445-2
This dataset
Open GSE312881 in finder → Find more human RNA-seq datasets →
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 GSE312881_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 PRJNA1377546 and SRA study SRP653422. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41667428) ↗
Study design
24 conditions, mostly in triplicate
BIHi005-A, DMSO ×3 BIHi005-A, paclitaxel ×3 BIHi263-A, DMSO ×3 BIHi263-A, paclitaxel ×3 BIHi264-A, DMSO ×3 BIHi264-A, paclitaxel ×3 BIHi272-A, DMSO ×3 BIHi272-A, paclitaxel ×3 +16 more

Supports a between-group comparison across 71 samples.

How we read this: 24 replicated groups read from 71 sample titles; they account for 71 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

+ 31 more — browse all 71 samples with per-sample file links →

Datasets on a similar topic

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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.