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Disruption of TGF-β signaling pathway is required to mediate effective killing of hepatocellular carcinoma by human iPSC-derived NK cells

GSE263459 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/04/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples
12 samples: 12 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
Disruption of TGF-β signaling pathway is required to mediate effective killing of hepatocellular carcinoma by human iPSC-derived NK cellsCell stem cell · 2024
Summary (written by the submitters)
Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. Transforming growth factor beta (TGF-β) is highly expressed in the liver tumor microenvironment and is known to inhibit immune cell activity. Here, we used human iPSCs to produce natural killer (NK) cells engineered to mediate improved anti-HCC activity. Specifically, we produced iPSC-NK cells with either knock out TGF-β receptor 2 (TGFBR2-KO) or expression of a dominant negative (DN) form of the TGF-β receptor 2 (TGFBR2-DN) combined with CARs that target either GPC3 or AFP.
Read the full summary ↓
The TGFBR2-KO and TGFBR2-DN iPSC-NK cells are resistant to TGF-β inhibition and improved anti-HCC activity. However, expression of anti-HCC CARs on iPSC-NK cells did not lead to effective anti-HCC activity unless there was also inhibition of TGF-b activity. Our findings demonstrate that TGF-β signaling blockade is required for effective NK cell function against HCC and potentially other malignancies which express high levels of TGF-β.
Published in
Disruption of TGF-β signaling pathway is required to mediate effective killing of hepatocellular carcinoma by human iPSC-derived NK cells
Thangaraj JL, Coffey M, Lopez E et al. · Cell stem cell 2024 · PMID 38986609 · doi:10.1016/j.stem.2024.06.009
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 GSE263459_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.

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 PRJNA1097585 and SRA study SRP500337. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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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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.