← BioTransfer GEO Dataset Finder
GEO series

Characterization and comparative analysis of multifunctional natural killer cell engagers (NKCEs) during antitumor responses

GSE264122 Homo sapiens (human) RNA-seq (gene expression) 45 samples Submitted 2025/03/16 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 45 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
45 samples: 15 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
Characterization and comparative analysis of multifunctional natural killer cell engagers during antitumor responsesCell reports. Medicine · 2025
Summary (written by the submitters)
T cell engagers (TCEs) are transformational oncology therapies but limited in use due to the induction of cytokine release syndrome (CRS). In comparison to T cells, natural killer (NK) cells produce less cytokines upon activation, leading to the exploration of NK cell engagers (NKCEs). However, why NK cells secrete less cytokines such as tumor necrosis factor (TNF) and how NKCEs perform directly against TCEs remain unclear.
Read the full summary ↓
Here we report that relative to T cells, NK cells have reduced trafficking and processing of TNF. Systematic development and benchmarking studies show that NKCEs can be optimized to engage multiple activating receptors and incorporate the interleukin (IL)-2, thereby increasing their potency and durability. Furthermore, comparative studies of NKCE, IL-2, and TCE therapy in animal tumor models reveal both common and different therapeutic benefits. Our results provide a blueprint for development of multifunctional NKCEs that may serve as an alternative to current TCE therapies.
Published in
Characterization and comparative analysis of multifunctional natural killer cell engagers during antitumor responses
Lin H, Case R, Wei KY et al. · Cell reports. Medicine 2025 · PMID 40318632 · doi:10.1016/j.xcrm.2025.102117
This dataset
Open GSE264122 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 GSE264122_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 PRJNA1101020 and SRA study SRP502129. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40318632) ↗
Study design
15 conditions, mostly in triplicate
NK_NKCE-II_16H_D ×3 NK_NKCE-I+IL2_16H_D ×3 NK_NKCE-III_16H_D ×3 NK_NKCE-IV_16H_D ×3 NK_CTRL_16H_D ×3 CD8_CD3xCLL1_16H_D ×3 CD8_CTRL_16H_D ×3 CD4_CD3xCLL1_16H_D ×3 +7 more

Supports a between-group comparison across 45 samples.

How we read this: 15 replicated groups read from 45 sample titles; they account for 45 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.