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Von Hippel Lindau tumor suppressor controls m6A-dependent gene expression in renal tumorigenesis

GSE239892 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2024/03/19 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 6 conditions, mostly in triplicateGroups 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
Von Hippel Lindau tumor suppressor controls m6A-dependent gene expression in renal tumorigenesisThe Journal of clinical investigation · 2024
Summary (written by the submitters)
N6‐Methyladenosine (m6A) is the most abundant internal post‐translational modification, and its contribution to cancer evolution has recently been appreciated. Renal cancer is the most common adult genitourinary cancer, of which ~85% is accounted for by the clear cell subtype (ccRCC) characterized by VHL loss. In this study, we demonstrate for the first time that VHL binds with m6A enzymatic complex proteins and promotes METTL3-METTL14 complex formation, and VHL depletion suppresses mRNA m6A modification.
Read the full summary ↓
m6A RIP-seq coupled with RNA-seq in renal cells with or without VHL allowed us to identify a selection of genes whose expression may be regulated by m6A. Specifically, PIK3R3 is identified to be one critical gene whose mRNA stability is regulated by VHL in a m6A-dependent but HIF-independent manner. Functionally, PIK3R3 depletion promotes renal cancer cell growth and orthotopic tumor growth while vice versa. Mechanistically, PIK3R3 suppresses tumor growth by restraining PI3K/AKT activity. Taken together, we propose a new mechanism by which VHL regulates m6A through modulation of METTL3-METTL14 protein complex formation, thereby promoting PIK3R3 mRNA stability and protein level that is critical for regulating ccRCC tumorigenesis.
Published in
Von Hippel Lindau tumor suppressor controls m6A-dependent gene expression in renal tumorigenesis
Zhang C, Yu M, Hepperla AJ et al. · The Journal of clinical investigation 2024 · PMID 38618952 · doi:10.1172/JCI175703
This dataset
Open GSE239892 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 GSE239892_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 PRJNA1001349 and SRA study SRP453039. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38618952) ↗
Study design
6 conditions, mostly in triplicate
HKC_sgCtrl_MeRIP ×3 HKC_sgVHL_sg1_MeRIP ×3 HKC_sgVHL_sg2_MeRIP ×3 HKC_sgCtrl_RNA ×3 HKC_sgVHL_sg1_RNA ×3 HKC_sgVHL_sg2_RNA ×3 HKC_sgCtrl_MeRIP_input ×1 HKC_sgVHL_sg1_MeRIP_input ×1 +1 more

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 21 sample titles; they account for 18 of them. 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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