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KDM5C and KDM5D mutations have different and opposing consequences in ccRCC cells [RNASeq_double_KO]

GSE284610 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2025/01/21 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 27 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
27 samples: 9 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.
Summary (written by the submitters)
KDM5C is commonly mutated in ccRCC tumours in men but rarely in women. Introducing KDM5C mutation into two male and two female KDM5C wild type ccRCC cell lines caused different phenotypes and nonoverlapping transcriptional consequences, indicative of context-dependent functions of KDM5C. We identify that loss of the Y chromosome, harbouring the KDM5C homologue KDM5D, occurs in most male KDM5C mutant ccRCCs.
Read the full summary ↓
Mutation of KDM5D in male 786-O cells prevented xenograft tumour formation and this phenotype was rescued by co-mutation of KDM5C. This unexpected antagonistic relationship between KDM5C and KDM5D is consistent with the co-occurrence of KDM5C mutation and loss of the Y chromosome in ccRCC. Transcriptional analyses showed that KDM5C and KDM5D regulate the expression of both overlapping as well as distinct sets of genes. Consistent with the tumour growth phenotype, KDM5D mutation induced the upregulation of putative tumour suppressor genes and downregulation of putative pro-proliferative genes. These transcriptional effects were also reversed by co-mutation of KDM5C. While KDM5C and KDM5D bind to at least some overlapping genomic sites, we identify that gene expression changes induced by KDM5C or KDM5D mutation are apparently unrelated to the direct functions of these proteins at the relevant gene promoters or enhancers. Our findings identify similarities and differences in KDM5C and KDM5D functions, challenging the idea that KDM5D in male cells functions equivalently to the second KDM5C allele in female cells, and implicate an interplay between KDM5C mutation and Y chromosome loss in ccRCC development in men.
This dataset
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.

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 GSE284610_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1199916 and SRA study SRP552287. Searching any of these in the dataset finder brings you back here.

Study design
9 conditions, mostly in triplicate
786-O_sgCtrl ×3 786-O_sgKDM5C_4 ×3 786-O_sgKDM5C_5 ×3 786-O_sgKDM5D_2 ×3 786-O_sgKDM5D_4 ×3 786-O_sgKDM5C_4_sgKDM5D_2 ×3 786-O_sgKDM5C_4_sgKDM5D_4 ×3 786-O_sgKDM5C_5_sgKDM5D_2 ×3 +1 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 27 sample titles; they account for 27 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
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