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Preclinical activity of brincidofovir in Peripheral T-cell and NK/T-cell Lymphoma [RNAseq_tumor]

GSE295563 Homo sapiens (human) RNA-seq (gene expression) 53 samples Submitted 2026/03/18 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 53 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
53 samples: 36 × NKTCL tumor tissue, NKTL vs 10 × NKTCL tumor tissue, NKTL_FGroups 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
Preclinical activity of brincidofovir in peripheral T-cell and NK/T-cell lymphomaBMC medicine · 2026
Summary (written by the submitters)
Introduction: Brincidofovir (BCV) is a novel nucleoside phosphonate analogue with unique dual anti-viral and anti-tumor properties. Methods: Activity of BCV was evaluated in forty-four cell-line models, including T/NK-NHL (n=25) and B-cell lymphoma (BCL, n=19), as well as their respective NOD/SCID mice xenograft models (NK/T-cell lymphoma, peripheral T-cell lymphoma, not otherwise specified, TP63-rearranged anaplastic large cell lymphoma, and MYC/BCL2-rearranged diffuse large B-cell lymphoma).
Read the full summary ↓
Potential in vivo immunogenic effects were examined in a syngeneic EL4-C57BL/6 murine lymphoma model. Results: BCV demonstrated potent anti-tumor activity in vitro across the majority of cell-lines regardless of EBV positivity, with IC50 values within clinically-achievable human plasma concentrations (2 µg/ml) in 17/25 (68.0%) T/NK-NHL and in 13/19 (68.4%) BCL. In vivo treatment via intraperitoneal BCV (IP, 40mg/kg, 2X per week) significantly inhibited tumor growth in all xenograft models when compared to vehicle control. Notably, RNAseq analysis demonstrated BCV downregulated MYC and MYC-target pathways in T/NK-NHL models. Further mechanistic studies showed that BCV evoked S-phase cell cycle arrest, replication stress, DNA damage and apoptosis, while also triggering STING pathway-mediated interferon responses, PD-L1 expression and immunogenic cell death. In the syngeneic EL4-C57BL/6 model, BCV in combination with anti-PD1 significantly inhibited tumor growth and triggered an immune reaction characterized by highest scores for adaptive immune response, cytokines/chemokines & receptors, cytotoxic cells, dendritic cells, NK CD56dim cells and neutrophils (NanoString Immunology Panel). Conclusions: Taken together, these results demonstrate a novel role of BCV in the treatment of lymphoma, and suggest potential for combination with checkpoint immunotherapy.
Published in
Preclinical activity of brincidofovir in peripheral T-cell and NK/T-cell lymphoma
Chan JY, Lee ECY, Chai KXY et al. · BMC medicine 2026 · PMID 41652589 · doi:10.1186/s12916-026-04680-8
This dataset
Open GSE295563 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 GSE295563_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 PRJNA1255191 and SRA study SRP581135. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41652589) ↗
Study design
36 × NKTCL tumor tissue, NKTL vs 10 × NKTCL tumor tissue, NKTL_F

Supports a between-group comparison across 46 samples.

How we read this: 2 replicated groups read from 53 sample titles; they account for 46 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

+ 13 more — browse all 53 samples with per-sample file links →

Datasets on a similar topic

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.