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The effects of PD-L1 and SCE over-expression on CAR-NK cell cytotoxicity against tumor cells

GSE276388 Homo sapiens (human) RNA-seq (gene expression) 32 samples Submitted 2025/08/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 32 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
32 samples: 32 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
Selective HLA knockdown and PD-L1 expression prevent allogeneic CAR-NK cell rejection and enhance safety and anti-tumor responses in xenograft miceNature communications · 2025
Summary (written by the submitters)
This experiment aims to investigate how the overexpression of PD-L1 and SCE enhances the cytotoxic activity of CAR-NK cells against tumor cells. Pathway enrichment analysis revealed that CAR-NK cells with reduced HLA-ABC and overexpressed PD-L1 showed enrichment in proliferation and pro-inflammatory pathways. In contrast, CAR-NK cells with reduced HLA-ABC and overexpressed SCE exhibited enrichment in homeostasis-related pathways. On the other hand, cellular stress pathways were more prominently enriched in HLA-ABC reduced CAR NK cells following co-culture with target cells.
Published in
Selective HLA knockdown and PD-L1 expression prevent allogeneic CAR-NK cell rejection and enhance safety and anti-tumor responses in xenograft mice
Liu F, Tarannum M, Zhao Y et al. · Nature communications 2025 · PMID 41062480 · doi:10.1038/s41467-025-63863-8
This dataset
Open GSE276388 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 GSE276388_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 PRJNA1157192 and SRA study SRP530583. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41062480) ↗
Study design
32 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 32 sample titles: 32 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
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.