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Optimized Method to Generate Well-Characterized Macrophages from Induced Pluripotent Stem Cells

GSE277609 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/12/01 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 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
Optimized Method to Generate Well-Characterized Macrophages from Induced Pluripotent Stem CellsBiomedicines · 2025
Summary (written by the submitters)
Background: Macrophages play a pivotal role in various pathogenic processes, necessitating the development of efficient differentiation techniques to meet the high demand for these cells in research and therapy. Human macrophages can be obtained via culturing of peripheral blood monocytes; however, this source has limited yields and requires patient contact for each proposed use.
Read the full summary ↓
In addition, it would be difficult to perform gene editing on peripheral blood monocytes. The differentiation of induced pluripotent stem cells (iPSCs) into macrophages can meet these needs for recurrent studies with high yields with the possibility of gene editing. Methods: We refined the traditional embryoid body-based differentiation strategy to create a novel three-phase method that optimizes yield, consistent quality, and reproducibility. This approach incorporates the use of microwell plates and cell filtration to standardize the production of embryoid bodies and subsequent macrophage progenitors. Using up to five independent iPSC donors, we performed several assays for macrophage functions and polarization. such as marker protein staining by flow cytometry, lipoprotein uptake, phagocytosis, cytokine release, inflammasome activation, and the effects of M1-like and M2-like polarization. RNA sequencing was performed to determine segregation of cells at different stages of differentiation and by iPSC donor, as well as to identify marker genes for each stage of differentiation. Results: The iPSC-derived macrophages generated through this method exhibit characteristic features and cell marker proteins, as well as classical macrophage activities including lipoprotein uptake, bacterial phagocytosis, cytokine release, and inflammasome activation. We demonstrate the effects of M1-like and M2-like polarization on cytokine release. The first three principal components of the RNA sequencing data showed clear clustering by differentiation stage, while the fourth and fifth principal components clustered the differentiated macrophages by their respective iPSC donor. Marker genes were identified for each stage of differentiation and polarization. Conclusions: The methods provide an optimized and simplified procedure to produce iPSC-derived macrophages. Our results demonstrate the reproducibility of this method in generating high-quality macrophages suitable for a variety of biomedical applications.
Published in
Optimized Method to Generate Well-Characterized Macrophages from Induced Pluripotent Stem Cells
Hai Q, Bazeley P, Han J et al. · Biomedicines 2025 · PMID 39857683 · doi:10.3390/biomedicines13010099
This dataset
Open GSE277609 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 GSE277609_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 PRJNA1162901. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39857683) ↗
Study design
18 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 18 sample titles: 18 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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