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Venetoclax Enhances gamma-deltaT cell Antileukemia Activity via Fatty Acid Oxidation in Relapsed Acute Myeloid Leukemia

GSE306605 Homo sapiens (human) RNA-seq (gene expression) 6 samples Submitted 2026/09/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 6 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
Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples
6 samples: 6 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.
Summary (written by the submitters)
Relapse remains a leading cause of death in acute myeloid leukemia (AML), in part because host immune surveillance declines over time. Gamma delta (gamma-delta) T cells contribute to immune surveillance and have been linked to better outcomes in AML. Here we show that gamma-deltaT cells from patients with relapsed AML display reduced effector programs compared with those from patients in complete remission.
Read the full summary ↓
In a targeted screen of approved AML drugs, the B-cell lymphoma 2 (Bcl-2) inhibitor venetoclax emerged as a potent enhancer of gamma-deltaT-cell cytotoxicity against primary AML blasts from both newly diagnosed and relapsed patients. Short ex vivo venetoclax exposure activated gamma-deltaT cells, increased proliferation, and lowered markers of exhaustion, thereby sustaining antileukemia activity over time. Venetoclax also increased mitochondrial respiration (oxidative phosphorylation) and respiratory reserve and shifted metabolism toward fatty acid oxidation. In AML xenograft models, adoptive transfer of venetoclax-pretreated gamma-deltaT cells, including chimeric antigen receptor (CAR)–engineered gamma-deltaT cells, produced superior tumor clearance compared with untreated cells. These findings indicate that venetoclax rejuvenates gamma-deltaT-cell function through metabolic remodeling and supports combining venetoclax with gamma-deltaT-cell–based immunotherapy for relapsed AML.
This dataset
Open GSE306605 in finder → Find more human RNA-seq datasets → Acute myeloid leukemia 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 GSE306605_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 PRJNA1311462 and SRA study SRP613471. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 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 6 sample titles: 6 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
More Acute myeloid leukemia datasets

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.