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Targeting the Non-Homologous End-Joining Pathway Sensitizes MDM2-Amplified Liposarcoma to Doxorubicin-Induced Senescence, p53-Mediated Senescence.

GSE315862 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/02/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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
Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples
36 samples: 12 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
Targeting the Non-Homologous End Joining Pathway Sensitizes MDM2-Amplified Liposarcoma to Doxorubicin by Enhancing p53-Mediated SenescenceCancer research · 2026
Summary (written by the submitters)
Introduction Dedifferentiated liposarcoma (DDLPS) is a rare cancer defined by amplification of MDM2 and CDK4. Conventional chemotherapy (Doxorubicin) and targeted inhibition of MDM2 and CDK4 show sporadic responses, but most tumors display primary resistance. We used an unbiased approach to identify therapeutic strategies sensitizing to these DDLPS therapies.
Read the full summary ↓
Methods Three parallel genome-wide CRISPR-Cas9 knockout screens were conducted in DDLPS cells to sensitize to palbociclib (CDK4 inhibitor), nutlin-3a (MDM2 inhibitor) or Doxorubicin. Top screen hits were validated and characterized in both in vitro and in vivo models, while clinical data were used to corroborate molecular findings. Results We uncovered pathways related to G1/S transition (CDK2, CKS1B, E2F3 and CCNE1) and Non-Homologous End-Joining (NHEJ; TDP2, PRKDC and XRCC4), inactivation of which sensitized to palbociclib and Doxorubicin, respectively. Following validation of both pathways, we focused on mechanistic characterization of Doxorubicin sensitization by genetic perturbation of TDP2 or pharmacological inhibition of DNA-PKcs using peposertib. Synergistic cell cycle arrest and senescence were induced by prolonged administration of low-dose doxorubicin. Senescent cells were triggered to undergo apoptosis by subsequent senolytic treatment with Bcl2 inhibitor navitoclax. Despite the amplification of MDM2, senescence proved dependent on p53. Consistent with this, TCGA and DepMap data suggest p53 activity in DDLPS. Conclusion These findings provide a rationale for targeting the NHEJ pathway to enhance the efficacy of low-dose Doxorubicin in DDLPS, highlighting a potential therapeutic strategy exploiting p53-dependent cell cycle arrest and senescence. Furthermore, we provide, to our knowledge, the first evidence of maintained baseline p53 activity in MDM2-amplified DDLPS.
Published in
Targeting the Non-Homologous End Joining Pathway Sensitizes MDM2-Amplified Liposarcoma to Doxorubicin by Enhancing p53-Mediated Senescence
Jalving T, Dufau C, Simon Nieto J et al. · Cancer research 2026 · PMID 41811692 · doi:10.1158/0008-5472.CAN-25-1858
This dataset
Open GSE315862 in finder → Find more human RNA-seq datasets → Soft tissue sarcoma 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 GSE315862_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 PRJNA1399455 and SRA study SRP660448. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41811692) ↗
Study design
12 conditions, mostly in triplicate
LPS853, sgNTC, ×3 LPS853, sgNTC, 4nM dox, ×3 LPS853, 0.5uM Peposertib, ×3 LPS853, 0.5uM Peposertib, 4nM dox, ×3 LPS853, sgTDP2, ×3 LPS853, sgTDP2, 4nM dox, ×3 T778, sgNTC, ×3 T778, sgNTC, 4nM dox, ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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 Soft tissue sarcoma datasets

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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.