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Whole transcriptome sequencing of HCT116 cells with altered DNA repair capacities treated with RTX or 5FdUR

GSE318306 Homo sapiens (human) Non-coding RNA profiling 36 samples Submitted 2026/07/08 Platform GPL24676
At a glance

Non-coding RNA profiling · human · 36 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Homo sapiens (human)
Samples
36 samples: 36 samples, each with a distinct title — no replicated groupsGroups 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
Thymidylate synthase inhibitory drugs induce p53-dependent pathways differentlyPloS one · 2026
Summary (written by the submitters)
Thymidylate synthase (TS) is a key enzyme in thymidylate biosynthesis and an established target of chemotherapeutics such as 5-fluoro-2’-deoxyuridine (5FdUR) and raltitrexed (RTX). Inhibition of TS disrupts the dUTP:dTTP balance, leading to uracil misincorporation, futile base excision repair cycles, DNA strand breaks, and ultimately cell death.
Read the full summary ↓
However, active U-DNA repair is apparently not required for the cytotoxic effect of these drugs, indicating that alternative pathways contribute to the observed S-phase arrest. To dissect these mechanisms, we investigated the transcriptomic effects of TS inhibition in HCT116 colon cancer cell lines with altered DNA repair capacities treated with 5-fluoro-2′-deoxyuridine (5FdUR) or raltitrexed (RTX). Both drugs induced similar DNA damage responses and S-phase arrest, yet displayed distinct transcriptional signatures. Our findings underscore the multifaceted impact of TS inhibition and reveal drug-specific differences in cellular responses.
Published in
Thymidylate synthase inhibitory drugs induce p53-dependent pathways differently
Holub E, Szajkó MB, Felföldi A et al. · PloS one 2026 · PMID 42384741 · doi:10.1371/journal.pone.0332491
This dataset
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.

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 GSE318306_RAW.tar (it can run to tens of gigabytes).

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.

Also filed as BioProject PRJNA1418580 and SRA study SRP674429. Searching any of these in the dataset finder brings you back here.

Study design
36 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 36 sample titles: 36 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.

Samples in this study
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