← BioTransfer GEO Dataset Finder
GEO series

APOE-mediated immunometabolic reprogramming of macrophages drives lipid delivery to tumor cells in clear-cell renal cell carcinoma — a metabolic checkpoint

GSE301221 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2026/05/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 9 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
Kidney cancerThis series is part of our curated briefing on it.
Samples
9 samples: 7 distinct titles, 1 of them repeatedGroups 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)
Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of kidney cancer. Extensive evidence highlights the critical role of the von Hippel-Lindau (VHL) tumor suppressor gene in the initiation and progression of ccRCC. Our previous studies demonstrated that VHL deficiency in renal tubular epithelial cells promotes activation of the endothelial vascular network and facilitates immune cell infiltration, particularly by macrophages (Ms), into the ccRCC microenvironment.
Read the full summary ↓
These interactions between VHL-deficient renal cells and the recruited stromal components are essential for ccRCC development. In our investigation of ccRCC-associated macrophages, we observed a significant upregulation of genes related to lipid metabolism in MΦs co-cultured with VHL-deficient tubular cells. Further analysis confirmed that these tumor-associated macrophages (TAMs) actively uptake lipids, and we called them lipid-laden macrophages (LLMs). Notably, Apolipoprotein E (APOE) emerged as one of the most highly upregulated lipid-related genes. Given APOE’s established function as a lipid-binding protein involved in lipoprotein formation and lipid uptake, we hypothesize that these macrophages transfer lipid contents to VHL-deficient tubular cells, thereby promoting the lipid-rich “clear cell” phenotype characteristic of ccRCC. To further investigate this mechanism, we isolated macrophage populations with high (APOEhi. MΦs) and low (APOElo. MΦs) APOE expression, along with control macrophages (MΦCtr), from the co-culture system. We then performed mRNA sequencing to elucidate the transcriptional landscape and functional roles of LLMs in ccRCC pathogenesis.
This dataset
Open GSE301221 in finder → Find more human RNA-seq datasets → Kidney cancer 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 GSE301221_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 PRJNA1284296 and SRA study SRP596215. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 distinct titles, 1 of them repeated
Ma Ct ×3

How we read this: Read from 9 sample titles: 7 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 Kidney cancer datasets

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.