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Effect of anti-PD-1 and/or anti-TIGIT antibodies on hepatocellular carcinoma-patient derived xenografts in humanized mice

GSE265769 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2024/12/28 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 12 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples
12 samples
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
Single-cell RNA sequencing reveals anti-tumor potency of CD56(+) NK cells and CD8(+) T cells in humanized mice via PD-1 and TIGIT co-targetingMolecular therapy : the journal of the American Society of Gene Therapy · 2024
Summary (written by the submitters)
In solid tumors, the exhaustion of natural killer (NK) cells and cytotoxic T cells in the immunosuppressive tumor microenvironment poses challenges for effective tumor control. Conventional humanized mouse models of hepatocellular carcinoma-patient-derived xenografts (HCC-PDX) encounter limitations in NK-cell infiltration, hindering studies on NK-cell immunobiology.
Read the full summary ↓
Here, we introduce an improved humanized mouse model with restored NK-cell reconstitution and infiltration in HCC-PDX, coupled with single-cell RNA-sequencing (scRNA-seq) to identify potential anti-HCC treatments. A single administration of adeno-associated virus carrying human interleukin-15 (AAV-hIL15) reinstated persistent NK-cell reconstitution and infiltration in HCC-PDX in humanized mice. ScRNA-seq revealed exhausted NK-cell and T-cell subpopulations with heightened PDCD1 and TIGIT levels. Notably, combination therapy with anti-PD-1 and anti-TIGIT antibodies alleviated HCC burden in humanized mice, demonstrating NK cell-dependent efficacy. Bulk-RNA sequencing analysis also revealed significant alterations in the tumor transcriptome that may contribute to further resistance after combination therapy, warranting further investigations. As an emerging strategy, ongoing clinical trials with anti-PD-1 and anti-TIGIT antibodies provide limited data. The improved humanized mouse HCC-PDX model not only sheds light on the pivotal role of NK cells but also serves as a robust platform for evaluating safety and anti-tumor efficacy of combination therapies and other potential regimens, complementing clinical insights.
Published in
Single-cell RNA sequencing reveals anti-tumor potency of CD56(+) NK cells and CD8(+) T cells in humanized mice via PD-1 and TIGIT co-targeting
Liu WN, Harden SL, Tan SLW et al. · Molecular therapy : the journal of the American Society of Gene Therapy 2024 · PMID 39318093 · doi:10.1016/j.ymthe.2024.09.025
This dataset
Open GSE265769 in finder → Find more human RNA-seq datasets → Hepatocellular carcinoma 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 GSE265769_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1104166 and SRA study SRP503906. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39318093) ↗
Samples in this study

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