← BioTransfer GEO Dataset Finder
GEO series

The E3 ligase RBCK1 reduces the sensitivity of ccRCC to sunitinib through the ANKRD35-MITD1-ANXA1 axis

GSE214635 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/10/02 Platform GPL24676
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)
Topic
Kidney cancerThis series is part of our curated briefing on it.
Samples
18 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.
Summary (written by the submitters)
Despite the promise of targeted tyrosine kinase inhibitors (TKIs), such as sunitinib, in the extension of survival time in patients with clear cell renal cell carcinoma (ccRCC) progression or metastasis, the patients eventually succumb to inevitable drug resistance. Protein degradation executed by the ubiquitin-dependent proteasome system played an important role in determining the sensitivity of ccRCC to sunitinib.
Read the full summary ↓
Here, we applied the bioinformatic analysis to identify that E3 ligase RBCK1 was elevated in the sunitinib-resistant renal cancer cell lines or patient specimens. The subsequent in vitro or in vivo studies demonstrated that RBCK1 contributed to decreasing the sensitivity of ccRCC to sunitinib. Then, we showed that inhibition of RBCK1 activated the AKT and MAPK signaling pathways, which might be one of the main reasons why RBCK1 induces sunitinib resistance in ccRCC cells. Mechanistically, our results indicated that RBCK1 promotes the degradation of ANKRD35 and that ANKRD35 destabilizes MITD1 by binding with SUMO2 in ccRCC cells. In addition, we showed that the RBCK1-ANKRD35-MITD1-ANXA1 axis regulates the phosphorylation of AKT and ERK and contributes to the dysregulation of sunitinib in ccRCC cells. Therefore, we identified a novel mechanism for regulating the sensitivity of sunitinib in ccRCC. Therefore, we elucidated a novel mechanism by which RBCK1 regulates sunitinib sensitivity in ccRCC.
This dataset
Open GSE214635 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 GSE214635_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 PRJNA886429 and SRA study SRP400698. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
786-O cells, shcontrol ×3 786-O cells, shRBCK1 ×3 786-O cells,sicontrol_for_siANKRD35 ×3 786-O cells, siANKRD35 ×3 786-O cells,sicontrol_for_siMITD1 ×3 786-O cells,siMITD1 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 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
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.